Future Internet Architectures must support the rapid growth of traffic generated by mobile endpoints in a manner that is scalable and ensures low latency. We present a quantitative evaluation of three distinct approaches towards handling endpoint mobility: name-based forwarding, indirection and a global name service (GNS). Using a range of parameterized mobility distributions and real ISP topologies, we describe representative instantiations of each approach and evaluate their performance using four key metrics: update cost and update propagation cost in the control plane; and forwarding traffic cost and time-to-connect (TTC) in the data plane. (1) We show that by leveraging the fact that realistic endpoint mobility distributions show a high probability of being at a small subset of visited locations, name-based forwarding strategies can provide up to 60% improvement in control costs over simple best-port forwarding. (2) We show that the TTC in these name-based forwarding strategies is comparable to the TTC in the GNS. (3) Finally we show that a GNS-based approach offers the most suitable balance of total (combined data and control) cost to TTC across all approaches, all endpoint mobility distributions, and all ISP topologies considered.

In-network content caching has been deployed in both the Internet and cellular networks to reduce content-access delay. We investigate the problem of developing optimal joint routing and caching policies in a network supporting in-network caching with the goal of minimizing expected content-access delay. Here, needed content can either be accessed directly from a back-end server (where content resides permanently) or be obtained from one of multiple in-network caches. To access content, users must thus decide whether to route their requests to a cache or to the back-end server. In addition, caches must decide which content to cache. We investigate two variants of the problem, where the paths to the back-end server can be considered as either congestion-sensitive or congestion-insensitive, reflecting whether or not the delay experienced by a request sent to the back-end server depends on the request load, respectively. We show that the problem of optimal joint caching and routing is NP-complete in both cases. We prove that under the congestion-insensitive delay model, the problem can be solved optimally in polynomial time if each piece of content is requested by only one user, or when there are at most two caches in the network. We also identify the structural property of the user-cache graph that makes the problem NP-complete. For the congestion-sensitive delay model, we prove that the problem remains NP-complete even if there is only one cache in the network and each content is requested by only one user. We show that approximate solutions can be found for both cases within a $(1-1/e)$ factor from the optimal, and demonstrate a greedy solution that is numerically shown to be within 1% of optimal for small problem sizes. Through trace-driven simulations, we evaluate the performance of our greedy solutions to joint caching and routing, which show up to 50% reduction in average delay over the solution of optimized routing to least recently used caches.

The majority of Internet traffic is now dominated by streamed video content. As video quality continues to increase, the strain that streaming traffic places on the network infrastructure also increases. Caching content closer to users, e.g., using Content Distribution Networks, is a common solution to reduce the load on the network. A simple approach to selecting what to put in regional caches is to put the videos that are most popular globally across the entire customer base. However, this approach ignores distinct regional taste. In this paper we explore the question of how a video content provider could go about determining whether or not they should use a cache filling policy based solely upon global popularity or take into account regional tastes as well. We propose a model that captures the overlap between inter-regional and intra-regional preferences. We focus on movie content and derive a synthetic model that captures “taste” using matrix factorization, similarly to the method used in recommender systems. Our model enables us to widely explore the parameter space, and derive a set of metrics providers can use to determine whether populating caches according to regional of global tastes provides better cache performance.

Network traffic for sharing contents is significantly increasing. The cache network is a desirable architecture to reduce traffic and to improve reliability of contents retrieval. “Breadcrumbs” is one of the promising techniques to find cached contents in a distributed manner. Thanks to Breadcrumbs, users can retrieve a content without managing where the cache exists. This demo shows a contents sharing application among mobile users in the Breadcrumbs-enabled cache network.

We investigate the problem of optimal request routing and content caching in a heterogeneous network supporting in-network content caching with the goal of minimizing average content access delay. Here, content can either be accessed directly from a back-end server (where content resides permanently) or be obtained from one of multiple in-network caches. To access a piece of content, a user must decide whether to route its request to a cache or to the back-end server. Additionally, caches must decide which content to cache. We investigate the problem complexity of two problem formulations, where the direct path to the back-end server is modeled as i) a congestion-sensitive or ii) a congestion-insensitive path, reflecting whether or not the delay of the uncached path to the back-end server depends on the user request load, respectively. We show that the problem is NP-complete in both cases. We prove that under the congestion-insensitive model the problem can be solved optimally in polynomial time if each piece of content is requested by only one user, or when there are at most two caches in the network. We also identify a structural property of the user-cache graph that potentially makes the problem NP-complete. For the congestion-sensitive model, we prove that the problem remains NP-complete even if there is only one cache in the network and each content is requested by only one user. We show that approximate solutions can be found for both models within a (1 - 1/e) factor of the optimal solution, and demonstrate a greedy algorithm that is found to be within 1% of optimal for small problem sizes. Through trace-driven simulations we evaluate the performance of our greedy algorithms, which show up to a 50% reduction in average delay over solutions based on LRU content caching.

Physical human mobility has played an important role in the design and operation of mobile networks. Physical mobility, however, differs from user identity (name) mobility in both traditional mobility management protocols such as Mobile-IP and in new architectures, such as XIA and MobilityFirst, that support identity mobility and location independence as first class objects. A multi-homed stationary user or a stationary user shifting among multiple devices attached to different networks will persistently keep his/her identity but will change access networks and the IP address to which his/her identity is associated. We perform a measurement study of such user transitioning among networks from a network-level point of view, characterizing the sequence of networks to which a user is attached and discuss insights and implications drawn from these measurements. We characterize network transitioning in terms of network residency time, degree of multi-homing, transition rates and more. We find that users typically spend time attached to a small number of access networks, and that a surprisingly large number of users access two networks contemporaneously. We develop and validate a parsimonious Markov chain model of canonical user transitioning among networks that can be used to provision network services and to analyze mobility protocols.

The Internet recently passed an historic inflection point, with the number of broadband mobile devices surpassing the number of wired PCs and servers connected to the Internet. Mobility now profoundly affects the architecture, services and applications in both the wireless and wired domains. In this "bottom up" talk, we begin by discussing several specific mobility-related challenges and recent results in areas including mobility measurement (including privacy considerations) and modeling, and context-sensitive services. We then take a broader look at current and future challenges, and conclude by discussing several NSF investments in programs and projects in area of mobile networking.

A variety of forwarding strategies have been developed for multi-hop wireless networks, considering the broadcast nature of the wireless medium and the presence of fading channels that result in time-varying and unreliable transmission quality. One such strategy is opportunistic forwarding, which exploits relay diversity by opportunistically selecting an overhearing relay as a forwarder. Prior work has studied the performance of opportunistic forwarding for the simplified scenario of uncorrelated wireless channels. In this paper, we consider a more realistic scenario of temporally correlated wireless channels; the wireless channel is modeled as a Rayleigh fading channel and its temporal correlation as a modified Bessel function of the first kind and zeroth order. We use these models to develop a simple Markovian model to analyze the performance of opportunistic forwarding for correlated wireless channels for the case of linear networks. We then demonstrate via numerical evaluation the diminishing performance of opportunistic forwarding with increasing channel correlation.

Managing the Quality-of-Experience (QoE) of video streaming for wireless clients is becoming increasingly important due to the rapid growth of video traffic on wireless networks. The inherent variability of the wireless channel as well as the Variable Bit Rate (VBR) of the compressed video streams make QoE management a challenging problem. In this paper, we investigate scheduling algorithms to transmit multiple video streams from a base station to mobile clients. We present an epoch-by-epoch framework to fairly allocate wireless transmission slots to streaming videos. In each epoch, our scheme reduces the vulnerability to stalling by allocating slots to videos in a way that maximizes the minimum “playout lead” across all videos. We show that the problem of allocating slots fairly is NP-complete even for a constant number of videos. We then present a fast lead-aware greedy scheduling algorithm. Our greedy algorithm is optimal when the channel quality of a user remains unchanged within an epoch. Our experimental results, based on public MPEG-4 video traces and wireless channel traces that we collected from a WiMAX test-bed, show that the lead-aware greedy approach results in a fair distribution of stalls across the clients when compared to other algorithms, while still maintaining similar or fewer average number of stalls per client.

While wireless ad hoc networks have a wide range of applications in environment monitoring, military operations, and disaster recovery, etc, the full potential of such networks is inherently hindered by their diminishing capacity as the network size scales up. Content caching has been previously proposed to improve the availability of contents in a network and thus helps to alleviate the load on content custodians, reduce access latency, and improve the network capacity. This paper studies the scaling laws of the capacity of cache-enabled content distribution wireless ad hoc networks. We consider two basic content access schemes, namely, the Nearest Caching Node scheme where a request is satisfied by the nearest node to the requestor that has the content in its cache, and the Transparent Enroute Caching scheme where a content request is routed towards the content custodian and is satisfied by an intermediate node (or custodian) along the path that has the content in its cache. We first establish the capacity of content distribution wireless ad hoc networks without content caching as a baseline for investigating the benefit of caching. We then obtain the scaling laws of the capacity for the above two content access schemes with content caching. Based on the results we further explore their design and performance implications. Our results show that the capacity exhibits distinct scaling behaviors under different scaling regimes of the network parameters. Under certain conditions increasing the cache size of the nodes can effectively improve the capacity while under other conditions the improvement can be negligible. The characterizations of the capacity allows us to identify the bottleneck of the content access capacity for given network scenarios and choose effective approaches to improve the capacity.

Network management logs from a campus 802.11 network of nearly 4,500 ARUBA access points at the University of Massachusetts Amherst are presented. The processing steps to transform the logs from a series of individual network events, into user session trajectories are described and preliminary results are shown based on the user mobility characteristics. We plan to release a differentially private set of user trajectories for use by the research community which we hope can provide valuable insights into user mobility characterization.

This paper presents a quantitative methodology and results comparing different approaches for {\it location-independent} communication. Our approach is empirical and is based on real Internet topologies, routing tables from real routers, and a measured workload of the mobility of devices and content across network addresses today. We measure the extent of network mobility exhibited by mobile devices with a home-brewn Android app deployed on hundreds of smartphones, and measure the network mobility of Internet content from distributed vantage points. We combine this measured data with our quantitative methodology to analyze the different cost-benefit tradeoffs struck by location-independent network architectures with respect to routing update cost, path stretch, and forwarding table size. We find that more than 20% of users change over 10 IP addresses a day, suggesting that mobility is the norm rather than the exception, so intrinsic and efficient network support for mobility is critical. We also find that with purely name-based routing approaches, each event involving the mobility of a device or popular content may result in an update at up to 14% of Internet routers; but, the fraction of impacted routers is much smaller for the long tail of unpopular content. These results suggest that recent proposals for pure name-based networking are suitable for highly aggregateable content that does not move frequently but may need to be augmented with addressing-assisted approaches to handle device mobility.

Over the past few years Content-Centric Networking, a networking architecture in which host-to-content communication protocols are introduced, has been gaining much attention. A central component of such an architecture is a large-scale interconnected caching system. To date, the way these Cache Networks operate and perform is still poorly understood. Following the work of Cruz on queueing networks, in this paper we develop a network calculus for bounding flows in LRU cache networks of arbitrary topology. We analyze the tightness of these bounds as a function of several system parameters. Also, we derive from it several analytical results regarding these systems: the uniformizing impact of LRU on the request stream, and the significance of cache and routing diversity on performance.

Over the past few years Content-Centric Networking, a networking model in which host-to-content communication protocols are introduced, has been gaining much attention. A central component of such an architecture is a large-scale interconnected caching system. To date, the way these Cache Networks operate and perform is still poorly understood. In this work, we demonstrate that certain cache networks are non-ergodic in that their steady-state characterization depends on the initial state of the system. We then establish several important properties of cache networks, in the form of three independently-sufficient conditions for a cache network to comprise a single ergodic component. Each property targets a different aspect of the system - topology, admission control and cache replacement policies. Perhaps most importantly we demonstrate that cache replacement can be grouped into equivalence classes, such that the ergodicity (or lack-thereof) of one policy implies the same property holds for all policies in the class.

Thousands of cases each year of child exploitation on P2P file sharing networks lead from an IP address to a home. A first step upon execution of a search warrant is to determine if the home's open Wi-Fi or the closed wired Ethernet was used for trafficking; in the latter case, a resident user is more likely to be the responsible party. We propose methods that use remotely measured traffic to disambiguate wired and wireless residential medium access. Our practical techniques work across the Internet by estimating the perflow distribution of inter-arrival times for different home access network types. We observe that the change of inter-arrival time distribution is subject to several residentialfactors, including differences between OS network stacks, and cable network mechanisms. We propose a model to explain the observed patterns of inter-arrival times, and we study the ability of supervised learning classifiers to differentiate between wired and wireless access based on these remote traffic measurements.

In this paper, we investigate the problem of determining the routing that minimizes the maximum/average delivery time or the maximum/average delivery delay for a set of packets in a deterministic Delay Tolerant Network, i.e. in a network for which all the nodes' transmission opportunities are known in advance. While the general problem with multiple sources and multiple destinations is NP-hard, we present a polynomial time algorithm that can efficiently compute the optimal routing in the case of a single destination or of a single packet that needs to be routed to multiple destinations.

Distributed generation (DG) uses many small on-site energy harvesting deployments at individual buildings to generate electricity. DG has the potential to make generation more efficient by reducing transmission and distribution losses, carbon emissions, and demand peaks. However, since renewables are intermittent and uncontrollable, buildings must still rely, in part, on the electric grid for power. While DG deployments today use net metering to offset costs and balance local supply and demand, scaling net metering for intermittent renewables to a large fraction of buildings is challenging. In this paper, we explore an alternative approach that combines market-based electricity pricing models with on-site renewables and modest energy storage (in the form of batteries) to incentivize DG. We propose a system architecture and optimization algorithm, called GreenCharge, to efficiently manage the renewable energy and storage to reduce a building's electric bill. To determine when to charge and discharge the battery each day, the algorithm leverages prediction models for forecasting both future energy demand and future energy harvesting. We evaluate GreenCharge in simulation using a collection of real-world data sets, and compare with an oracle that has perfect knowledge of future energy demand/harvesting and a system that only leverages a battery to lower costs (without any renewables). We show that GreenCharge's savings for a typical home today are near 20%, which are greater than the savings from using only net metering.

In this paper, we investigate the benefits of applying a form of network coding known as random linear coding (RLC) to unicast applications in disruption-tolerant networks (DTNs). Under RLC, nodes store and forward random linear combinations of packets as they encounter each other. For the case of a single group of packets originating from the same source and destined for the same destination, we prove a lower bound on the probability that the RLC scheme achieves the minimum time to deliver the group of packets. Although RLC significantly reduces group delivery delays, it fares worse in terms of average packet delivery delay and network transmissions. When replication control is employed, RLC schemes reduce group delivery delays without increasing the number of transmissions. In general, the benefits achieved by RLC are more significant under stringent resource (bandwidth and buffer) constraints, limited signaling, highly dynamic networks, and when applied to packets in the same flow. For more practical settings with multiple continuous flows in the network, we show the importance of deploying RLC schemes with a carefully tuned replication control in order to achieve reduction in average delay, which is observed to be as large as 20% when buffer space is constrained.

In recent years, much work has been devoted to developing protocols and architectures for supporting the growing trend of data-oriented services. One drawback of many of these proposals is the need to upgrade or replace all the routers in order for the new systems to work. Among the few systems that allow for gradual deployment is the recently-proposed Breadcrumbs technique for distributed coordination among caches in a cache network. Breadcrumbs uses information collected locally at each cache during past downloads to support in-network guiding of current requests to desired content. Specifically, during content download a series of short-term pointers, called breadcrumbs, is set up along the download path. Future requests for this content are initially routed towards the server which holds (a copy of) this content. However, if this route leads the request to a Breadcrumbs-supporting router, this router re-directs the request in the direction of the latest downloaded, using the aforementioned pointers. Thus, content requests are initially forwarded by a location ID (e.g., IP address), but encountering a breadcrumb entry can cause a shift over to content-based routing. This property enables the Breadcrumbs system to be deployed gradually, since it only enhances the existing location-based routing mechanism (i.e. IP-based routing). In this paper we evaluate the performance of a network where Breadcrumbs is only partially deployed. Our simulation results show Breadcrumbs performs poorly when sparsely deployed. However, if an overlay of Breadcrumbs-supporting routers is setup, system performance is greatly improved. We believe that the reduced load on servers achieved with even a limited deployment of Breadcrumbs-supporting routers, combined with the flexibility of being able to deploy the system gradually, should motivate further investigation and eventual deployment of Breadcrumbs.

Although wireless networks have become ubiquitous, surprisingly few models of user-level mobility have been developed and validated against traces of measured user behavior. In this paper, we develop and validate a simple mixed queueing network model of user mobility among access points in a campus network. We identify two classes of users, an open and a closed class, corresponding to mobile users that visit the network for a short time before departure, and users that are always resident in the network during the observation period. Using CRAWDAD traces of user-access-point affiliation over time, we compare model-predicted performance with the performance actually observed in the traces, and find that such a mixed queueing model can indeed be used to accurately predict a number of performance measures of interest.

Managing the Quality-of-Experience (QoE) of video streaming for wireless clients is becoming increasingly important due to the rapid growth of video traffic on wireless networks. The inherent variability of the wireless channel as well as the Variable Bit Rate (VBR) of the compressed video streams make QoE management a challenging problem. Prior work has studied this problem in the context of transmitting a single video stream. In this paper, we investigate multiplexing schemes to transmit multiple video streams from a base station to mobile clients that use number of playout stalls as a performance metric. In this context, we present an epoch-by-epoch framework to fairly allocate wireless transmission slots to streaming videos. In each epoch our scheme essentially reduces the vulnerability to stalling by allocating slots to videos in a way that maximizes the minimum `playout lead' across all videos. Next, we show that the problem of allocating slots fairly is NP-complete even for a constant number of videos. We then present a fast lead-aware greedy algorithm for the problem. Our choice of greedy algorithm is motivated by the fact that this algorithm is optimal when the channel quality of a user remains unchanged within an epoch (but different users may experience different channel quality). Moreover, our experimental results based on public MPEG-4 video traces and wireless channel traces that we collected from a WiMAX test-bed show that the lead-aware greedy approach performs a fair distribution of stalls across the clients when compared to other algorithms, while still maintaining similar or lower average number of stalls per client.

A wide range of wireless channel models have been developed to model variations in received signal strength. In contrast to prior work, which has focused primarily on channel modeling on a short, per- packet timescale (millisecond), we develop and validate a finite-state Markov chain model that captures variations due to shadowing, which occur at coarser time scales. The Markov chain is constructed by partitioning the entire range of shadowing into a finite number of intervals. We determine the Markov chain transition matrix in two ways: (i) via an abstract modeling approach in which shadowing effects are modeled as a log-normally distributed random variable affecting the received power, and the transition probabilities are derived as functions of the variance and autocorrelation function of shadowing; (ii) via an empirical approach, in which the transition matrix is calculated by directly measuring the changes in signal strengths collected in a 802.16e (WiMAX) network. We validate the abstract model by comparing its steady state and transient performance predictions with those computed using the empirically derived transition matrix and those observed in the actual traces themselves.

In this paper, we propose a classification scheme that differentiates Ethernet and WLAN TCP flows based on measurements collected passively at the edge of a network. This scheme computes two quantities, the fraction of wireless TCP flows and the degree of belief that a TCP flow traverses a WLAN inside the network, using an iterative Bayesian inference algorithm that we developed. We prove that this iterative Bayesian inference algorithm converges to the unique maximum likelihood estimate (MLE) of these two quantities. Furthermore, it has the advantage that it can handle any general K-classification problem given the marginal distributions of these classes. Numerical and experimental evaluations demonstrate that our classification scheme obtains accurate results. We apply this scheme to two sets of traces collected from two campus networks: one set collected from UMass in mid 2005 and the other collected from UConn in late 2010. Our technique infers that 4%-7% and 52%-55% of incoming TCP flows traverse an IEEE 802.11 wireless link in these two networks, respectively.

Structural change and uncertainty are fundamental properties of an ad hoc network, making it difficult to develop communication strategies, i.e., network-level approaches to transport data from sender to receiver. At a basic level, change and uncertainty affect how long any state maintained by a communication strategy remains useful, and so influence the trade-offs made to collect that state. In this paper, we introduce a framework for organizing the decision space for deciding when a communication strategy should maintain state, and what type of state should be maintained, in an ad hoc network. The framework is based on our observation that three network properties (connectivity, unpredictability, and resource contention) determine when state is useful. Using the framework, we make three contributions. First, we illustrate the framework by showing an instantiation in terms of specific measures that can be used to describe a network setting. Second, we validate the framework by showing it correctly and consistently organizes the decision space for different communication strategies. Finally, we demonstrate the analytic power of the framework by using it to (1) uncover surprising aspects of well-known traces, and (2) identify the need for, and value of, a new strategy for network communication.

In this paper, we propose a model-based approach that uses periodic end-end probes to identify whether a “dominant congested link” exists along an end-end path. Informally, a dominant congested link refers to a link that incurs the most losses and significant queuing delays along the path. We begin by providing a formal yet intuitive definition of dominant congested link and present two simple hypothesis tests to identify whether such a link exists. We then present a novel model-based approach for dominant congested link identification that is based on interpreting probe loss as an unobserved (virtual) delay. We develop parameter inference algorithms for hidden Markov model (HMM) and Markov model with a hidden dimension (MMHD) to infer this virtual delay. Our validation using ns simulation and Internet experiments demonstrate that this approach can correctly identify a dominant congested link with only a small amount of probe data. We further provide an upper bound on the maximum queuing delay of the dominant congested link once we identify that such a link exists.

Many systems employ caches to improve performance. While isolated caches have been studied in-depth, multi-cache systems are not well understood, especially in networks with arbitrary topologies. In order to gain insight into and manage these systems, a low-complexity algorithm for approximating their behavior is required. We propose a new algorithm, termed a-Net, that approximates the behavior of multi-cache networks by leveraging existing approximation algorithms for isolated LRU caches. We demonstrate the utility of a-Net using both per- cache and network-wide performance measures. We also perform factor analysis of the approximation error to identify system parameters that determine the precision of a-Net.

In a number of network scenarios (including military settings), mobile nodes are clustered into groups, with nodes within the same group exhibiting significant correlation in their movements. Mobility models for such networks should reflect this group structure. In this paper, we consider the problem of identifying the number of groups, and the membership of mobile nodes within groups, from a trace of mobile nodes. We present two clustering algorithms to determine the number of groups and their identities: k-means chain and spectral clustering. Different from traditional k-means clustering, k-means chain identifies the number of groups in a dynamic graph, using a chaining process to keep track of group trajectories over the entire trace. The second approach uses spectral clustering, which uses similarities between node pairs to cluster nodes into groups. We show that the number of groups and node membership can be accurately extracted from traces, particularly when the number of groups is small.

For several years, web caching has been used to meet the ever-increasing Web access loads. A fundamental capability of all such systems is that of inter-cache coordination, which can be divided into two main types: explicit and implicit coordination. While the former allows for greater control over resource allocation, the latter does not suffer from the additional communication overhead needed for coordination. In this paper, we consider a network in which each router has a local cache that caches files passing through it. By additionally storing minimal information regarding caching history, we develop a simple content caching, location, and routing systems that adopts an implicit, transparent, and best-effort approach towards caching. Though only best effort, the policy outperforms classic policies that allow explicit coordination between caches.

Recent measurement studies have analyzed WLAN performance by means of wireless sniffers that passively capture transmitted frames. Also, for relatively large (enterprise) WLAN scenarios, previous work has investigated multi-sniffer deployments with devices placed far apart in order to capture all traffic in the network (even frames transmitted simultaneously by different nodes at non-interfering locations). However, for both these single- and multi-sniffer scenarios, little attention has been given to the fidelity of an individual device, i.e., the ability of a given sniffer to capture all frames that could have been captured by a more faithful device. We assess this fidelity (a term we make precise in this paper) by running controlled experiments inside an anechoic chamber and analyzing the similarities and differences between the trace file from the device under study and those of additional "shadow" devices placed in its close proximity. Our results show that fidelity varies significantly across sniffers, both quantitatively and qualitatively, and that performance may also depend on the nature of the experiment under study and on slight changes of the sniffer position.

This paper provides a novel characterization of fairness concepts in network resource allocation problems from the viewpoint of information theory. The fundamental idea adopted in this paper is to characterize the utility functions used in optimization problems, which motivate fairness concepts, based on a trade-off between user and system satisfaction. Here, user satisfaction is evaluated using information divergence measures that were originally used in information theory to evaluate the difference between two probability distributions. In this paper, information divergence measures are applied to evaluate the difference between the implemented resource allocation and a requested resource allocation. The requested resource allocation is assumed to be ideal in some sense from the user's point of view. Also, system satisfaction is evaluated based on the efficiency of the implemented resource utilization, which is defined as the total amount of resources allocated to each user. The results discussed in this paper indicate that the well-known fairness concept called weighted alpha-proportional fairness can be characterized using the alpha-divergence measure, which is a general class of information divergence measures, as an equilibrium of the trade-off described above. In the process of obtaining these results, we also obtained a new utility function that has a parameter to control the trade-off. This new function is then applied to typical examples to solve resource allocation problems in simple network models such as those for two-link networks and wireless LANs.

Sensor networks are prone to congestion due to bursty and high-bandwidth data traffic, combined with wireless links and many-to-one data routing to a sink. Delayed and dropped packets then degrade the performance of the sensing application. In this paper, we investigate the value of separate handling of sensor control and data traffic, during times of congestion, in a closed-loop sensor network. We first show that prioritizing sensor control traffic over data traffic decreases the round-trip control-loop delay, and consequently increases the quantity and quality of the data collected by the sensor network. We then ground our analysis in a closed-loop meteorological sensor network, focusing on a storm-tracking application running over a network of X-band radars. Our application measures reflectivity (a measure of the number of scatterers in a unit volume of atmosphere known as a voxel) and tracks storms (i.e., regions of high reflectivity) using a Kalman filter. Considering data quantity, we show that prioritizing sensor control traffic increases the number of voxels, V, that can be scanned given a constant number of reflectivity samples, Nc, obtained per voxel. Here, utility increases linearly with the number of scanned voxels. Considering data quality, we show that prioritizing sensor control traffic increases the number of reflectivity samples, N, that can be obtained per voxel given a constant number of voxels, Vc, to scan. Here, since sensing accuracy improves only as a function of radicN, the gain in accuracy for the reflectivity estimate per voxel as N increases is relatively small except when prioritizing sensor control increases N significantly (such as when sensor control packets suffer severe delays). Because accuracy also degrades as a function of radicN, however, and because prioritizing sensor control traffic reduces the number of control packets dropped, data degradation is mitigated. Considering the performance of the tracking application, we then show that during times of severe congestion, not prioritizing sensor control can actually lead to tracking errors accumulating over time.

In this paper, we propose two online algorithms to detect 802.11 traffic from packet-header data collected passively at a monitoring point. These algorithms have a number of applications in real-time wireless LAN management, for instance, in detecting unauthorized access points and detecting/predicting performance degradations. Both algorithms use sequential hypothesis tests and exploit fundamental properties of the 802.11 CSMA/CA MAC protocol and the half-duplex nature of wireless channels. They differ in that one requires training sets, while the other does not. We have built a system for online wireless traffic detection using these algorithms and deployed it at a university gateway router. Extensive experiments have demonstrated the effectiveness of our approach: the algorithm that requires training provides rapid detection and is extremely accurate (the detection is mostly within 10 seconds, with very low false-positive and false-negative ratios), the algorithm that does not require training detects 60 percent to 76 percent of the wireless hosts without any false positives, and both algorithms are lightweight, with computation and storage overhead well within the capability of commodity equipment.

Distributed networks of short-range radars offer the potential to observe winds and rainfall at high spatial resolution in volumes of the troposphere that are unobserved by today's longrange weather radars. One class of potential distributed radar network designs includes Off-the-Grid (OTG) weather radar networks. These are short-range radar nodes designed to be deployed as part of an ad-hoc network and to limit their reliance on existing infrastructure. Independence of the wired infrastructure (power or communications) would allow OTG networks to be deployed in specific regions where sensing needs are greatest, such as mountain valleys prone to flash-flooding, geographic regions where the infrastructure is susceptible to failure, and underdeveloped regions lacking urban infrastructure. This paper will present an OTG network testbed being deployed in Western Massachusetts to support experimentation with OTG nodes. This testbed will focus on the energy performance of the OTG network and the virtualization of the radar sensor.

IP1 is a prototype CASA radar sensor network located in southwestern Oklahoma whose goal is to detect severe weather in the lower part of the atmosphere. At the center of this system's control loop is its Meteorological Command and Control (MC&C). In this paper, we presented the overall control architecture for the IP1 network and highlight new features that have recently been added to the MC&C. We also present an analysis of the MC&C performance based on measurement data from a 5-day operation period. In addition, we introduce a distributed version of the MC&C.

The capacity gain of network coding has been extensively studied in wired and wireless networks. Recently, it has been shown that network coding improves network reliability by reducing the number of packet retransmissions in lossy networks. However, the extent of the reliability benefit of network coding is not known. This paper quantifies the reliability gain of network coding for reliable multicasting in wireless networks, where network coding is most promising. We define the expected number of transmissions per packet as the performance metric for reliability and derive analytical expressions characterizing the performance of network coding. We also analyze the performance of reliability mechanisms based on rateless codes and automatic repeat request (ARQ), and compare them with network coding. We first study network coding performance in an access point model, where an access point broadcasts packets to a group of K receivers over lossy wireless channels. We show that the expected number of transmissions using ARQ, compared to network coding, scales as ominus (log K) as the number of receivers becomes large. We then use the access point model as a building block to study reliable multicast in a tree topology. In addition to scaling results, we derive expressions for the expected number of transmissions for finite multicast groups as well. Our results show that network coding significantly reduces the number of retransmissions in lossy networks compared to an ARQ scheme. However, rateless coding achieves asymptotic performance results similar to that of network coding.

In many wired and wireless networks, nodes process input traffic to satisfy a network constraint (e.g., a capacity constraint) and to increase the utility of data in the output flows given these constraints. In this paper we focus on the special case in which data processing is applied to satisfy capacity constraints. This occurs when the sum of the rate of the input traffic at a node exceeds the sum of the capacity of its output links, or in a more general case, when the sum of the input rates is larger than any cut capacity in the network. In this case, nodes process data to decrease the output flow rate. This decrease from input rate to output rate distorts the transmitted data, which we characterize by a distortion metric. We show that the distortion cost of distributively processing input traffic in a network can be written as the sum of the distortion at individual nodes.. We present a distributed algorithm for a data-gathering network with many sources and a data sink that routes traffic and performs in-network data processing to minimize the distortion cost. In this algorithm, each node determines its routing table based on gradient information from neighboring nodes.

This research is motivated by large-scale pervasive sensing applications. We examine the benefits and costs of caching data for such applications. We propose and evaluate several approaches to querying for, and then caching data in a sensor field data server. We show that for some application requirements (i.e., when delay drives data quality), policies that emulate cache hits by computing and returning approximate values for sensor data yield a simultaneous quality improvement and cost savings. This win-win is because when system delay is sufficiently important, the benefit to both query cost and data quality achieved by using approximate values outweighs the negative impact on quality due to the approximation. In contrast, when data accuracy drives quality, a linear trade-off between query cost and data quality emerges. We also identify caching and lookup policies for which the sensor field query rate is bounded when servicing an arbitrary workload of user queries. This upper bound is achieved by having multiple user queries share the cost of a single sensor field query. Finally, we demonstrate that our results are robust to the manner in which the environment being monitored changes using models for two different sensing systems.

Many sensor network studies assume that the energy cost for sensing is negligible compared with the cost of communications or computing. Opportunities exist to deploy sensor networks utilizing active sensors with a high energy cost such as radar. For a node utilizing radar as its primary sensor, the actual sensing procedure is the main power consumer. In the worst case almost 50% of the power is consumed by the sensing procedure, while only 3% is used for communication, the remainder is consumed by the computing platform. In this paper we examine a wireless sensor network composed of short range radars used to monitor rainfall. These short-range radar nodes are designed to be deployed as part of an ad-hoc network and to limit their reliance on existing infrastructure. We refer to these networks as "off-the-grid" (OTG) weather radar networks. Independence of the wired infrastructure (power or communications) allows OTG networks to be deployed in specific regions where sensing needs are greatest, such as mountain valleys prone to flash-flooding, geographic regions where the infrastructure is susceptible to failure, and underdeveloped regions lacking urban infrastructure. We present a simulation based investigation of such an OTG sensor network. We focus on power management and energy harvesting for the network. We use these simulations to demonstrate how geographic location, battery capacity, optimization of power consumption, and node density have an impact on the performance and operational lifetime of such a sensor network. In addition to these simulations, we present the design and implementation of an OTG prototype sensor node. Experiences and data gained from the operation of this node are used as input parameters for the simulations.

Many sensing systems remotely monitor/measure an environment at several sites, and then report these observations to a central site. We propose and investigate several practical algorithms for joint routing and compression of data files as they are forward from remote nodes to a central site, with the goal of minimizing the communication cost incurred. Our algorithms are practical in that they do not assume that nodes have a priori information about the correlation structure (and resulting compression gains) of the individual measurements at a given sensor or among multiple sensors. Instead, this correlation structure is learned as pieces of the files are routed and jointly compressed on their way to the sink, and routes are adaptively changed as the nodes learn more about the correlation structure of the data.

TCP is widely used in commercial multimedia streaming systems, with recent measurement studies indicating that a significant fraction of Internet streaming media is currently delivered over HTTP/TCP. These observations motivate us to develop analytic performance models to systematically investigate the performance of TCP for both live and stored-media streaming. We validate our models via ns simulations and experiments conducted over the Internet. Our models provide guidelines indicating the circumstances under which TCP streaming leads to satisfactory performance, showing, for example, that TCP generally provides good streaming performance when the achievable TCP throughput is roughly twice the media bitrate, with only a few seconds of startup delay.

Distributed networks of short-range radars offer the potential to observe winds and rainfall at high spatial resolution in volumes of the troposphere that are unobserved by today's long-range weather radars. One class of potential distributed radar network designs includes Off-the-Grid (OTG) weather radar networks. These are short-range radar nodes designed to be deployed as part of an ad-hoc network and to limit their reliance on existing infrastructure. Independence of the wired infrastructure (power or communications) would allow OTG networks to be deployed in specific regions where sensing needs are greatest, such as mountain valleys prone to flash-flooding, geographic regions where the infrastructure is susceptible to failure, and underdeveloped regions lacking urban infrastructure. This paper will present a system model and simulation framework for the design of OTG networks. The model estimates the energy requirements of the three major system functions, sensing, communicating and computing, as well as power generated from the solar panel. The simulation will be used to develop an energy cost function to be used in control decisions.

Rogue (unauthorized) wireless access points pose serious security threats to local networks. In this paper, we propose two online algorithms to detect rogue access points using sequential hypothesis tests applied to packet-header data collected passively at a monitoring point. One algorithm requires training sets, while the other does not. Both algorithms extend our earlier TCP ACK-pair technique to differentiate wired and wireless LAN TCP traffic, and exploit the fundamental properties of the 802.11 CSMA/CA MAC protocol and the half duplex nature of wireless channels. Our algorithms make prompt decisions as TCP ACK-pairs are observed, and only incur minimum computation and storage overhead. We have built a system for online rogue-access-point detection using these algorithms and deployed it at a university gateway router. Extensive experiments in various scenarios have demonstrated the excellent performance of our approach: the algorithm that requires training provides rapid detection and is extremely accurate (the detection is mostly within 10 seconds, with very low false positive and false negative ratios); the algorithm that does not require training detects 60%-76% of the wireless hosts without any false positives; both algorithms are light-weight (with computation and storage overhead well within the capability of commodity equipment).

We study traces taken from UMass DieselNet, a Disruption-Tolerant Network consisting of WiFi nodes attached to buses. As buses travel their routes, they encounter other buses and in some cases are able to establish pair-wise connections and transfer data between them. We analyze the bus-to-bus contact traces to characterize the contact process between buses and its impact on DTN routing performance. We find that the all-bus-pairs aggregated inter-contact times show no discernible pattern. However, the inter-contact times aggregated at a route level exhibit periodic behavior.Based on analysis of the deterministic inter-meeting times for bus pairs running on route pairs, and consideration of the variability in bus movement and the random failures to establish connections, we construct generative route-level models that capture the above behavior. Through trace-driven simulations of epidemic routing, we find that the epidemic performance predicted by traces generated with this finer-grained route-level model is much closer to the actual performance that would be realized in the operational system than traces generated using the coarse-grained all-bus-pairs aggregated model. This suggests the importance in choosing the rightlevel of model granularity when modelingmobility-related measures such as inter-contact times in DTNs.

We address the problem of adaptive sensor control in dynamic resource-constrained sensor networks. We focus on a meteorological sensing network comprising radars that can perform sector scanning rather than always scanning 360 degrees. We compare three sector scanning strategies. The sit-and-spin strategy always scans 360 degrees. The limited lookahead strategy additionally uses the expected environmental state K decision epochs in the future, as predicted from Kalman filters, in its decision-making. The full lookahead strategy uses all expected future states by casting the problem as a Markov decision process and using reinforcement learning to estimate the optimal scan strategy. We show that the main benefits of using a lookahead strategy are when there are multiple meteorological phenomena in the environment, and when the maximum radius of any phenomenon is sufficiently smaller than the radius of the radars. We also show that there is a trade-off between the average quality with which a phenomenon is scanned and the number of decision epochs before which a phenomenon is rescanned.

We propose Push-to-Peer, a peer-to-peer system to cooperatively stream video. The main departure from previous work is that content is proactively pushed to peers, and persistently stored before the actual peer-to-peer transfers. The initial content placement increases content availability and improves the use of peer uplink bandwidth. Our specific contributions are: (i) content placement and associated pull policies that allow the optimal use of uplink bandwidth; (ii) performance analysis of such policies in controlled environments such as DSL networks under ISP control; (iii) a distributed load balancing strategy for selection of serving peers.

In many energy-rechargeable wireless sensor networks, sensor nodes must both sense data from the environment, and cooperatively forward sensed data to data sinks. Both data sensing and data forwarding (including data transmission and reception) consume energy at sensor nodes. We present a distributed algorithm for optimal joint allocation of energy between sensing and communication at each node to maximize overall system utility (i.e., the aggregate amount of information received at the data sinks). We consider this problem in the context of wireless sensor networks with directional, non-steerable antennas. We first formulate a joint data-sensing and data-routing optimization problem with both per-node energy-expenditure constraints, and traditional flow routing/conservation constraints. We then simplify this problem by converting it to an equivalent routing problem, and present a distributed gradient-based algorithm that iteratively adjusts the per-node amount of energy allocated between sensing and communication to reach the system-wide optimum. We prove that our algorithm converges to the maximum system utility. We quantitatively demonstrate the energy balance achieved by this algorithm in a network of small, energy-constrained X-band radars, connected via point- to-point 802.11 links with non-steerable directional antennas.

Abstract — Verifying the accuracy of a passive measurementsbased inference technique under all possible network scenarios is a difficult challenge- the measurement point has limited observability of events along the path, and monitored paths can exhibit a wide range of network properties (packet loss, reordering, end-end delay, route changes). In this paper, we propose and apply formal verification techniques to exhaustively verify the correctness of an inference technique. We apply this approach to the problem of inferring packet retransmissions and reorderings from passively observed packets at a single measurement point. We define classification rules for this inference problem and, through a combination of model-checking and formal reasoning, uncover all possible events in the network for which the rules produce incorrect inferences. Our work is novel in its use of formal verification tools for evaluating inference techniques in network measurements. I.

2706-2717

2443-2454

2824-2835

In the publish/subscribe paradigm, information is disseminated from publishers to subscribers that are interested in receiving the information. In practice, information dissemination is often restricted by policy constraints due to concerns such as security or confidentiality agreement. Meanwhile, to avoid overwhelming subscribers by the vast amount of primitive information, primitive pieces of information can be combined at so-called brokers in the network, a process called composition. Information composition provides subscribers the desirable ability to express interests in an efficiently selective way. In this paper, we formulate the min-cost event distribution problem in pub/sub systems with policy constraints and information composition. Our goal is to minimize the total cost of event transmission while satisfying policy constraints and enabling information composition. This optimization problem is shown to be NP-complete. Our simulation study shows that our heuristics work efficiently, especially in a policy-constrained system. We also find that by increasing the number of broker nodes in a pub/sub system, we are able to reduce the total cost of event delivery.

In this paper, we consider the problem of finding an "efficient" and "robust" set of routes in the face of changing/uncertain traffic. The changes/uncertainty in exogenous traffic is characterized by multiple traffic matrices. Our goal is to find a set of routes that result in good average case performance over the set of traffic matrices, while avoiding bad worst case performance for any single traffic matrix. With multiple traffic matrices, previous work aims solely to optimize the average case performance Chun Zhang, et al., (2005), or the worst case performance David Applegate, et al., (2003). For a given set of traffic matrices, different sets of routes offer a different tradeoff between the average case and the worst case performance. In this paper, we quantify the performance of a routing configuration at both network level and link level. We propose a simple metric-a weighted sum of the average case and the worst case performance-to control the tradeoff between these two considerations. Despite of its simple form, this metric is very effective. We prove that optimizing routing using this metric has desirable properties, such as the average case performance being a decreasing, convex and differentiable function to the worst case performance. By extending previous work Chun Zhang, et al., (2005) Bernard Fortz, et al., (2002), we derive methods to find the optimal routes with respect to the proposed metric for two classes of intra-domain routing protocols: MPLS and OSPF/IS-IS. We evaluate our approach with data collected from an operational tier-I ISP. For MPLS, we find that there exists significant tradeoff (e.g., 15%-23% difference) between optimizing solely on the average case performance and solely on the worst case performance. Our approach can identify solutions that can dramatically improve the worst case performance (13%-15%) while only slightly sacrificing the average case performance (2.2%-3%), in comparison to that by optimizing solely on the average case performance. For OSPF/IS-IS, we still find a significant difference between the two optimization objectives, however, a fine-grained tradeoff is difficult to achieve due to the limited control that OSPF/IS-IS provide.

2058-2061

Trust negotiation is a process that establishes mutual trust by the exchange of digital credentials and/or guiding policies among entities who may have no pre-existing knowledge about each other. Motivated by the desire to disclose as little sensitive information as possible in practice, this paper investigates the problem of minimizing the "cost" of the credentials exchanged by a trust-negotiation protocol. A credential or a policy is assigned a weighted cost, referred to as its sensitivity cost. We formalize an optimization problem, namely the minimum sensitivity cost problem, whose objective is to minimize the total sensitivity costs of the credentials and policies disclosed during trust negotiation. We study the complexity of the minimal sensitivity cost problem and propose algorithms to solve the problem efficiently, for the cases that policies are cost-sensitive and cost-insensitive. A simple finite state machine model of trust-negotiation protocols is presented to model various trust-negotiation protocols, and to provide a quantitative evaluation of the number of exchange rounds needed to achieve a successful negotiation, and the probability of achieving a successful negotiation under various credential disclosure strategies.

There is increasing interest in concurrent passive monitoring of IP flows at multiple locations within an IP network. The common objective of such a distributed monitoring system is to sample packets belonging to a large fraction of IP flows in a cost-effective manner by carefully placing monitors and controlling their sampling rates. In this paper, we consider the problem of where to place monitors within the network and how to control their sampling. To address the tradeoff between monitoring cost and monitoring coverage, we consider minimum cost and maximum coverage problems under various budget constraints. We show that all of the defined problems are NP-hard. We propose greedy heuristics, and show that the heuristics provide solutions quite close to the optimal solutions through experiments using synthetic and real network topologies. In addition, our experiments show that a small number of monitors is often enough to monitor most of the traffic in an entire IP network.

The current best-effort Internet cannot readily provide the service guarantees that VoIP applications often require. Path switching can potentially address this problem without requiring new network mechanisms, simply by leveraging the robustness to performance variations available from connectivity options such as multi-homing and overlays. In this paper, we evaluate the effectiveness and benefits of path switching in improving the quality of VoIP applications, and demonstrate its feasibility through the design and implementation of a prototype gateway. We argue for an application-driven path switching system that accounts for both network path characteristics and application-specific factors (e.g., codec algorithms, playout buffering schemes). We also develop an application path quality estimator based on the ITU-T E-model for voice quality assessment, and an application-driven path switching algorithm that dynamically adapts the time scales over which path switching decisions are made to maximize voice quality. Through network emulation and experiments over a wide-area multi-homed test bed, we show that, with sufficient path diversity, path switching can yield meaningful improvements in voice quality. Hence by exploiting the inherent path diversity of the Internet, application-driven path switching is a viable option in providing quality-of-service to applications.

We consider the problem of neighbor discovery in static wireless ad hoc networks with directional antennas. We propose several probabilistic algorithms in which nodes perform random, independent transmissions to discover their one-hop neighbors. Our neighbor discovery algorithms are classified into two groups, viz. Direct-Discovery Algorithms in which nodes discover their neighbors only upon receiving a transmission from their neighbors and Gossip-based algorithms in which nodes gossip about their neighbors' location information to enable faster discovery. We first consider the operation of these algorithms in a slotted, synchronous system and mathematically derive their optimal parameter settings. We show how to extend these algorithms for an asynchronous system and describe their optimal design. Analysis and simulation of the algorithms show that nodes discover their neighbors much faster using gossip-based algorithms than using direct-discovery algorithms. Furthermore, the performance of gossip-based algorithms is insensitive to an increase in node density. The efficiency of a neighbor discovery algorithm also depends on the choice of antenna beamwidth. We discuss in detail how the choice of beamwidth impacts the performance of the discovery process and provide insights into how nodes can configure their beamwidths.

Ethernet, wireless LAN, ADSL, cable modem and dialup are common access networks, but have dramatically different characteristics. Fast and accurate classification of access network type can improve protocol or application performance significantly. In this paper, we propose a simple and efficient end-end scheme to classify the type of an access network into three categories: Ethernet, wireless LAN and low-bandwidth connection. Our scheme is based on the intrinsic characteristics of the various access networks and utilizes the median and entropy of packet pair inter-arrival times. Extensive experiments show that our scheme obtains accurate classification results in a very short time (10 to 100 seconds).

Routing optimization is used to find a set of routes that minimizes cost (delay, utilization). Previous work has addressed this problem for the case of a known, static end-to-end traffic matrix. In the Internet, it is difficult to accurately estimate a traffic matrix, and the constantly changing nature of Internet traffic makes it costly to maintain optimal routing by responding to traffic changes. Thus, it is of interest to maintain a set of routes that are "good" for a number of different possible traffic scenarios. In this paper, we explore ways to find an optimal set of routes with multiple traffic matrices to minimize expected cost. We focus on two general approaches, source-destination routing and destination routing. In the case of source-destination routing, we extend existing methods with a single traffic matrix to solve the optimization problem with multiple traffic matrices: we extend the convex optimization solution methods for a single traffic matrix to the multiple traffic matrix case; we also extend the gradient-based solution methods for a single traffic matrix to the multiple traffic matrix case. However, the multiple traffic matrix case requires many more control variables. In the case of destination routing, we encounter many more differences from the single traffic matrix case. The loop-free property, which is valid for the single traffic matrix case, is no longer valid for the multiple traffic matrix case, and it is difficult to extend existing methods for a single traffic matrix to solve the optimization problem with multiple traffic matrices. We show that it is NP-complete even to determine the feasibility of multiple traffic matrices. We thus propose and evaluate a heuristic algorithm for this case.

When properly constructed, a modular multimedia system can satisfy a client's request in multiple ways by using different sequences of modules and by reusing existing streams within the system. Such flexibility in a multimedia server or proxy can provide a rich set of services to clients while efficiently utilizing system resources by choosing the best way to schedule (i.e. allocate resources for) new clients. However, it is difficult to optimally schedule clients in an online fashion as the problem is NP-complete. In this paper, we provide an efficient online algorithm to schedule client requests using a modular multimedia platform.

197-206

185-196

In this paper, we compare two basic approaches towards providing peer-to-peer file-sharing (or more generally, information search) in mobile ad-hoc networks (MANET). The flooding approach broadcasts a query (e.g., to locate a node holding a given file) to all network nodes. The index-server approach adds additional servers (known as index servers) that cache directory information about which nodes have which files. With index servers, a node wishing to locate a file first queries its local index server, which then queries other index servers, as needed. The use of index servers presents the possibility of locating a file index quickly in an index server cache, but requires additional overhead to maintain cache consistency. We compare the performance of the flooding approach to two index-server caching approaches: consistent caching and local caching. We quantify the reduction in search overhead using the index-server scheme rather than flooding in MANET, and study how the optimal number of index servers varies according to network size, query rate, and index generation rate. We compare the flooding scheme and the consistent caching and local caching schemes, for two types of queries: history queries and latest queries. Numerical results show how one can choose between the alternatives of consistent caching and local caching depending on network size, index generation rate and query rate.

This work explores the feasibility of improving the performance of end-to-end data transfers between different sites through path switching. Our study is focused on both the logic that controls path switching decisions and the configurations required to achieve sufficient path diversity. Specifically, we investigate two common approaches offering path diversity multi-homing and overlay networks - and investigate their characteristics in the context of a representative wide-area testbed. We explore the end-to-end delay and loss characteristics of different paths and find that substantial improvements can potentially be achieved by path switching, especially in lowering end-to-end losses. Based on this assessment, we develop a simple path-switching mechanism capable of realizing those performance improvements. Our experimental study demonstrates that substantial performance improvements are indeed achievable using this approach.

Leader election is a very important problem, not only in wired networks, but in mobile, ad hoc networks as well. Existing solutions to leader election do not handle frequent topology changes and dynamic nature of mobile networks. We present a leader election algorithm that is highly adaptive to arbitrary (possibly concurrent) topological changes and is therefore well-suited for use in mobile ad hoc networks. The algorithm is based on finding an extrema and uses diffusing computations for this purpose. We show, using linear-time temporal logic, that the algorithm is "weakly" self-stabilizing and terminating. We also simulate the algorithm in a mobile ad hoc setting. Through our simulation study, we elaborate on several important issues that can significantly impact performance of such a protocol for mobile ad hoc networks such as choice of signaling, broadcast nature of wireless medium etc. Our simulation study shows that our algorithm is quite effective in that each node has a leader approximately 97-99% of the time in a variety of operating conditions.

TCP is widely used in commercial media streaming systems, with recent measurement studies indicating that a significant fraction of Internet streaming media is currently delivered over HTTP/TCP. These observations motivate us to develop analytic performance models to systematically investigate the performance of TCP for both live and stored media streaming. We validate our models via ns simulations and experiments conducted over the Internet. Our models provide guidelines indicating the circumstances under which TCP streaming leads to satisfactory performance, showing, for example, that TCP generally provides good streaming performance when the achievable TCP throughput is roughly twice the media bitrate, with only a few seconds of startup delay.

We present the design, implementation, and performance evaluation of AMPS --- a flexible, scalable proxy testbed that supports a wide and extensible set of next-generation proxy streaming services. AMPS employs a modular architecture and is built on top of a commodity Linux system. We study the performance of AMPS proxy using a server-proxy-client configuration in a switched-Gigabit LAN environment. We identify the CPU to be the system bottleneck. Through profiling study, we further identify the kernel network protocol processing and the Network Reception Module inside the proxy to be the most CPU-intensive components. We also quantify the maximum achievable throughput for two of the principal components of the proxy - the control plane and data plane, and characterize the end-to-end performance along the server-to-proxy-to-client path. We discuss lessons learned and the various optimizations made in the course of our study to improve system performance.

No abstract available.

TCP is widely used in commercial media streaming systems, with recent measurement studies indicating that a significant fraction of Internet streaming media is currently delivered over HTTP/TCP. These observations motivate us to develop analytic performance models to systematically investigate the performance of TCP for both live and stored media streaming. We validate our models via ns simulations and experiments conducted over the Internet. Our models provide guidelines indicating the circumstances under which TCP streaming leads to satisfactory performance, showing, for example, that TCP generally provides good streaming performance when the achievable TCP throughput is roughly twice the media bitrate, with only a few seconds of startup delay.

Providing on-demand video streaming service over the Internet is a challenging task. In this paper, we propose DirectStream, a directory based peer-to-peer video streaming service that efficiently and cost-effectively provides video on-demand service with VCR operation support. We analytically and experimentally examine the system performance, and show that the proposed scheme can significantly reduce the workload posed on the server, and that it scales extremely well as the popularity of the video increases even if participating clients behave non-cooperatively. We propose a QoS parent selection algorithm to construct the appropriate peer-to-peer networks, and discuss how to provide continuous playback in the face of clients' early departures. Our study suggests that peer-to-peer networking is a promising technique to address scalability in on-demand streaming service.

The publish/subscribe (pub/sub) paradigm provides content-oriented data dissemination in which communication channels are established between content publishers and content subscribers based on a matching of subscribers interest in the published content provided - a process we refer to as "matchmaking". Once an interest match has been made, content forwarding state can be installed at intermediate nodes (e.g., active routers, application-level relay nodes) on the path between a content provider and an interested subscriber. In dynamic pub/sub applications, where published content and subscriber interest change frequently the signaling overhead needed to perform matchmaking can be a significant overhead. We first formalize the matchmaking process as an optimization problem, with the goal of minimizing the amount of matchmaking signaling messages. We consider this problem for both shared and per-source multicast data (content) distribution topologies. We characterize the fundamental complexity of the problem, and then describe several efficient solution approaches. The insights gained through our analysis are then embodied in a novel active matchmaker signaling protocol (AMSP). AMSP dynamically adapts to applications' changing publication and subscription requests through a link-marking approach. We simulate AMSP and two existing broadcast-based approaches for conducting matchmaking, and find that AMSP significantly reduces signaling overhead.

In this paper, we propose a model-based approach that uses periodic end-end probes to identify whether a "dominant congested link" exists along an end-end path. Informally, a dominant congested link refers to a link that incurs the most losses and significant queuing delays along the path. We begin by providing a formal yet intuitive definition of dominant congested link and present two simple hypothesis tests to identify whether such a link exists. We then present and examine several novel model-based approaches for identifying a dominant congested link that are based on interpreting probe loss as an unobserved (virtual) delay. We develop parameter inference algorithms for Hidden Markov Model (HMM) and Markov model with a hidden dimension to infer this virtual delay. Our validation using ns simulation and live Internet experiments demonstrate that this approach can correctly identify a dominant congested link with only a small amount of probe data. We further estimate the maximum queuing delay of the dominant congested link, once we identify that a dominant congested link exists.

Peer-peer networking has recently emerged as a new paradigm for building distributed networked applications. We develop simple mathematical models to explore and illustrate fundamental performance issues of peer-peer file sharing systems. The modeling framework introduced and the corresponding solution methods are flexible enough to accommodate different characteristics of such systems. Through the specification of model parameters, we apply our framework to three different peer-peer architectures: centralized indexing, distributed indexing with flooded queries, and distributed indexing with hashing directed queries. Using our model, we investigate the effects of system scaling, freeloaders, file popularity and availability on system performance. In particular, we observe that a system with distributed indexing and flooded queries cannot exploit the full capacity of peer-peer systems. We further show that peer-peer file sharing systems can tolerate a significant number of freeloaders without suffering much performance degradation. In many cases, freeloaders can benefit from the available spare capacity of peer-peer systems and increase overall system throughput. Our work shows that simple models coupled with efficient solution methods can be used to understand and answer questions related to the performance of peer-peer file sharing systems.

We present a measurement study and classification methodology for out-of-sequence packets in TCP connections observed within the Sprint IP backbone. Such out-of-sequence packets can result from many causes including loss, looping, reordering, or duplication in the network. It is important to quantify and understand the causes of such out-of-sequence packets since they are one indication of the "health" of an end-end TCP connection. Our first contribution is methodological. Because we measure out-of-sequence packets at a single point in the backbone (rather than by sending and measuring end-end probe traffic at the sender or receiver), a new methodology is required to infer the causes of a connection's out-of-sequence packets based only on measurements taken in the "middle" of the connection. We thus describe techniques that classify the causes of observed out-of-sequence behavior based only on the previously- and subsequently-observed packets within a connection and knowledge of how TCP behaves. We show that using these simple techniques, it is possible to classify almost all out-of-sequence packets in our traces and that we can quantify the uncertainty in our classification. Our second contribution is the characterization of the out-of-sequence behavior itself. We analyze numerous several-hour packet-level traces from a set of OC-3 and OC-12 links for several million connections generated in nearly 4,300 unique ASs. Our measurements show a relatively consistent amount of out-of-sequence packets of approximately 5%. We find that few out-of-sequence packets result from pathological problems such as routing loops or in network duplication/reordering.

One of the key infrastructure components in all telecommunication networks, ranging from the telephone network, to VC-oriented data networks, to the Internet, is its signaling system. Two broad approaches towards signaling can be identified: so-called hard-state and soft-state approaches. Despite the fundamental importance of signaling, our understanding of these approaches - their pros and cons and the circumstances in which they might best be employed - is mostly anecdotal (and occasionally religious). In this paper, we compare and contrast a variety of signaling approaches ranging from a "pure" soft state, to soft-state approaches augmented with explicit state removal and/or reliable signaling, to a "pure" hard state approach. We develop an analytic model that allows us to quantify state inconsistency in single- and multiple-hop signaling scenarios, and the "cost" (both in terms of signaling overhead, and application-specific costs resulting from state inconsistency) associated with a given signaling approach and its parameters (e.g., state refresh and removal timers). Among the class of soft-state approaches, we find that a soft-state approach coupled with explicit removal substantially improves the degree of state consistency while introducing little additional signaling message overhead. The addition of reliable explicit setup/update/removal allows the soft-state approach to achieve comparable (and sometimes better) consistency than that of the hard-state approach.

Providing video on demand (VoD) service over the Internet in a scalable way is a challenging problem. In this paper, we propose P2Cast - an architecture that uses a peer-to-peer approach to cooperatively stream video using patching techniques, while only relying on unicast connections among peers. We address the following two key technical issues in P2Cast: (1) constructing an application overlay appropriate for streaming; and (2) providing continuous stream playback (without glitches) in the face of disruption from an early departing client. Our simulation experiments show that P2Cast can serve many more clients than traditional client-server unicast service, and that it generally out-performs multicast-based patching if clients can cache more than of a stream's initial portion. We handle disruptions by delaying the start of playback and applying the shifted forwarding technique. A threshold on the length of time during which arriving clients are served in a single session in P2Cast serves as a knob to adjust the balance between the scalability and the clients' viewing quality in P2Cast.

Controlling the rate of bulk data multicast to a large number of receivers is difficult, due to the heterogeneity among the end systems' capabilities and their available network bandwidth. If the data transfer rate is too high, some receivers will lose data, and retransmissions will be required. If the data transfer rate is too slow, an inordinate amount of time will be required to transfer the data. In this paper, we examine an approach toward rate-controlled multicast of bulk data in which the sender uses multiple multicast groups to transmit data at different rates to different subgroups of receivers. We present simple algorithms for determining the transmission rate associated with each multicast channel, based on static resource constraints, e.g., network bandwidth bottlenecks. Transmission rates are chosen so as to minimize the average time needed to transfer data to all receivers. Analysis and simulation are used to show that our policies for rate selection perform well for large and diverse receiver groups and make efficient use of network bandwidth. Moreover, we find that only a small number of multicast groups are needed to reap most of the possible performance benefits.

We compare four different approaches towards modeling frame-level errors in GSM channels. One of these, the Markov-based trace analysis (MTA) model, was developed for the purpose of modeling a GSM channel. The next two, k/sup th/-order Markov models and hidden Markov models (HMMs) have been widely used to model loss in wired networks. All three of these have difficulty modeling empirical GSM frame-level error traces. The MTA model and HMM predict frame error rates substantially different from that measured from the trace, and all three models have difficulty capturing the long term temporal correlation structure. We propose a fourth model, the extended ON/OFF model, which alternates between an ON (error-free) and an OFF (error-filled) state. The state holding times are taken from mixtures of geometric distributions. We show that this model, with mixtures of three or four geometric distributions, captures first order and second order statistics significantly better than the preceding three approaches.

No abstract available.

Many definitions of fairness for multicast networks assume that sessions are single rate, requiring that each multicast session transmits data to all of its receivers at the same rate. These definitions do not account for multirate approaches, such as layering, that permit receiving rates within a session to be chosen independently. We identify four desirable fairness properties for multicast networks, derived from properties that hold within the max-min fair allocations of unicast networks. We extend the definition of multicast max-min fairness to networks that contain multirate sessions, and show that all four fairness properties hold in a multirate max-min fair allocation, but need not hold in a single-rate max-min fair allocation. We then show that multirate max-min fair rate allocations can be achieved via intra-session coordinated joins and leaves of multicast groups. However, in the absence of coordination, the resulting max-min fair rate allocation uses link bandwidth inefficiently, and does not exhibit some of the desirable fairness properties. We evaluate this inefficiency for several layered multirate congestion control schemes, and find that, in a protocol where the sender coordinates joins, this inefficiency has minimal impact on desirable fairness properties. Our results indicate that sender-coordinated layered protocols show promise for achieving desirable fairness properties for allocations in large-scale multicast networks.

Current Internet congestion control protocols operate independently on a per-flow basis. Recent work has demonstrated that cooperative congestion control strategies between flows can improve performance for a variety of applications, ranging from aggregated TCP transmissions to multiple-sender multicast applications. However, in order for this cooperation to be effective, one must first identify the flows that are congested at the same set of resources. We present techniques based on loss or delay observations at end hosts to infer whether or not two flows experiencing congestion are congested at the same network resources. Our novel result is that such detection can be achieved for unicast flows, but the techniques can also be applied to multicast flows. We validate these techniques via queueing analysis, simulation and experimentation within the Internet. In addition, we demonstrate preliminary simulation results that show that the delay-based technique can determine whether two TCP flows are congested at the same set of resources. We also propose metrics that can be used as a measure of the amount of congestion sharing between two flows.

In many large scale data dissemination systems, a large number of information flows must be delivered to a large number of information receivers. However, because of differences in interests among receivers, not all receivers are interested in all of the information flows. Multicasting provides the opportunity to deliver a subset of the information flows to a subset of the receivers. With a limited number of multicast groups available, the channelization problem is to find an optimal mapping of information flows to a fixed number of multicast groups, and a subscription mapping of receivers to multicast groups so as to minimize a function of the total bandwidth consumed and the amount of unwanted information received by receivers. We formally define two versions of the channelization problem and subscription problem (a subcomponent of the channelization problem). We analyze the complexity of each version of the channelization problem and show that they are both NP-complete. We also find that the subscription problem is NP-complete when one flow can be assigned to multiple multicast groups. We also study and compare different approximation algorithms to solve the channelization problem, finding that one particular heuristic, flow-based-merge, finds good solutions over a range of problem configurations.

Network performance evaluation through traditional packet-level simulation is becoming increasingly difficult as today's networks grow in scale along many dimensions. As a consequence, fluid simulation has been proposed to cope with the size and complexity of such systems. This study focuses on analyzing and comparing the relative efficiencies of fluid simulation and packet-level simulation for several network scenarios. We use the "simulation event" rate to measure the computational effort of the simulators and show that this measure is both adequate and accurate. For some scenarios, we derive analytical results for the simulation event rate and identify the major factors that contribute to the simulation event rate. Among these factors, the "ripple effect" is very important since it can significantly increase the fluid simulation event rate. For a tandem queueing system, we identify the boundary condition to establish regions where one simulation paradigm is more efficient than the other. Flow aggregation is considered as a technique to reduce the impact of the "ripple effect" in fluid simulation. We also show that WFQ scheduling discipline can limit the "ripple effect", making fluid simulation particularly well suited for WFQ models. Our results show that tradeoffs between parameters of a network model determines the most efficient simulation approach.

Multimedia streaming applications can consume a significant amount of server and network resources. Periodic broadcast and patching are two approaches that use multicast transmission and client buffering in innovative ways to reduce server and network load, while at the same time allowing asynchronous access to multimedia steams by a large number of clients. Current research in this area has focussed primarily on the algorithmic aspects of these approaches, with evaluation performed via analysis or simulation. In this paper, we describe the design and implementation of a flexible streaming video server and client testbed that implements both periodic broadcast and patching, and explore the issues that arise when implementing these algorithms. We present measurements detailing the overheads associated with the various server components (signaling, transmission schedule computation, data retrieval and transmission), the interactions between the various components of the architecture, and the overall end-to-end performance. We also discuss the importance of an appropriate server video segment caching policy. We conclude with a discussion of the insights gained from our implementation and experimental evaluation.

No abstract available.

Large-scale applications are characterized by a large number of dynamic and often interactive group members. The nature of these applications is such that participants are not interested in all the content transmitted. We examine three currently available techniques to scope delivery of content to interested receivers in IP multicast: filtering, where data is filtered by middleware before being passed to the application; addressing, where data is routed only to those receivers that express their interest; and hybrid approaches. We propose a framework that models large-scale application behavior. We use this framework to evaluate the performance of these applications and related protocols when the network is capable of filtering or addressing. Our results show that the current Internet architecture does not efficiently support large-scale applications because it can not efficiently manage multiple multicast groups. We show that network-level addressing is preferred to filtering and hybrid approaches given that groups are easy to create and manage. We highlight areas of research in the multicast architecture to bring about this change.

Current Internet congestion control protocols operate independently on a per-flow basis. Recent work has demonstrated that cooperative congestion control strategies between flows can improve performance for a variety of applications, ranging from aggregated TCP transmissions to multiple-sender multicast applications. However, in order for this cooperation to be effective, one must first identify the flows that are congested at the same set of resources. In this paper, we present techniques based on loss or delay observations at end-hosts to infer whether or not two flows experiencing congestion are congested at the same network resources. We validate these techniques via queueing analysis, simulation, and experimentation within the Internet.

Wireless networks often employ network-based user agents as proxies for mobile users. In this paper, we consider the fundamental problem of designing migration policies for these user agents. We first introduce a general framework for analyzing user agent migration policies, and then highlight, through analysis and simulation, the numerous parameters and tradeoffs that dictate the design of migration policies. We evaluate these policies in the context of both homogeneous and heterogeneous networks, and in the presence and absence of processing overheads due to migration. Finally, we identify two simple threshold-based policies that deliver very good performance over a wide range of system parameters and configurations. To our knowledge, this is the first paper to propose and evaluate policies for migration of user agents.

Bandwidth smoothing techniques for stored video perform end to end workahead transmission of frames into the client playback buffer, in advance of their display times. Such techniques are very effective in reducing the burstiness of the bandwidth requirements for transmitting compressed, stored video. This paper addresses online bandwidth smoothing for a growing number of streaming video applications such as newscasts, sportscasts, and distance learning, where many clients may be willing to tolerate a playback delay of a few seconds in exchange for a smaller bandwidth requirement. The smoothing can be performed at either the source of the videocast or at special smoothing server(s) (e.g., proxies or gateways) within the network. In contrast to previous work on stored video, the online smoothing server has limited knowledge of frame sizes and access to only a segment of the video at a time. This is either because the feed is live or because it is streaming past the server. We formulate an online smoothing model which incorporates playback delay, client and server buffer sizes, server processing capacity, and frame size prediction techniques. Our model can accommodate an arbitrary arrival process. Using techniques for smoothing stored video at the source as a starting point, we develop an online, window-based smoothing algorithm for delay tolerant applications. Extensive experiments with MPEG-1 and M-JPEG video traces demonstrate that online smoothing significantly reduces the peak rate, coefficient of variation, and effective bandwidth of variable-bit-rate video streams. These reductions can be achieved with modest playback delays of a few seconds to a few tens of seconds and moderate client buffer sizes, and closely approximate the performance of optimal offline smoothing of stored video. In addition, we show that frame size prediction can offer further reduction in resource requirements, though prediction becomes relatively less important for longer playback delays. However, the ability to predict future frame sizes affects the appropriate division of buffer space between the server and client sites. Our experiments show that the optimal buffer allocation shifts to placing more memory at the server as the server has progressively less information about future frame sizes.

We examine an approach for providing reliable, scalable multicast communication, involving the use of multiple multicast channels for reducing receiver processing costs and reducing network bandwidth consumption in a multicast session. In this approach a single multicast channel is used for the original transmission of packets. Retransmissions of packets are done on separate multicast channels, which receivers dynamically join and leave. We first show that protocols using an infinite number of multicast channels incur much less processing overhead at the receivers compared to protocols that use only a single multicast channel. This is due to the fact that receivers do not receive retransmissions of packets they have already received correctly. Next, we derive the number of unwanted redundant packets at a receiver due to using only a finite number of multicast channels, for a specific negative acknowledgment (NAK)-based protocol. We then explore the minimum number of multicast channels required to keep the cost of processing unwanted packets to a sufficiently low value. For an application consisting of a single sender transmitting reliably to many receivers we find that only a small number of multicast channels are required for a wide range of system parameters. In the case of an application where all participants simultaneously act as both senders and receivers a moderate number of multicast channels is needed. Finally, we present two mechanisms for implementing multiple multicast channels, one using multiple IP multicast groups and the other using additional router support for selective packet forwarding. We discuss the impact of both mechanisms on performance in terms of end-host and network resources.

The steady-state performance of a bulk transfer TCP flow (i.e., a flow with a large amount of data to send, such as FTP transfers) may be characterized by the send rate, which is the amount of data sent by the sender in unit time. In this paper we develop a simple analytic characterization of the steady-state send rate as a function of loss rate and round trip time (RTT) for a bulk transfer TCP flow. Unlike the models of Lakshman and Madhow (see IEE/ACM Trans. Networking, vol.5, p.336-50, 1997), Mahdavi and Floyd (1997), Mathis, Semke, Mahdavi and Ott (see Comput. Commun. Rev., vol.27, no.3, 1997) and by by Ott et al., our model captures not only the behavior of the fast retransmit mechanism but also the effect of the time-out mechanism. Our measurements suggest that this latter behavior is important from a modeling perspective, as almost all of our TCP traces contained more time-out events than fast retransmit events. Our measurements demonstrate that our model is able to more accurately predict TCP send rate and is accurate over a wider range of loss rates. We also present a simple extension of our model to compute the throughput of a bulk transfer TCP flow, which is defined as the amount of data received by the receiver in unit time.

An important concern for source-based multicast congestion control algorithms is the loss path multiplicity (LPM) problem that arises because a transmitted packet can be lost on one or more of the many end-to-end paths in a multicast tree. Consequently, if a multicast source's transmission rate is regulated according to loss indications from receivers, the rate may be completely throttled as the number of loss paths increases. In this paper, we analyze a family of additive increase multiplicative decrease congestion control algorithms and show that, unless careful attention is paid to the LPM problem, the average session bandwidth of a multicast session may be reduced drastically as the size of the multicast group increases. This makes it impossible to share bandwidth in a max-min fair manner among unicast and multicast sessions. We show that max-min fairness can be achieved however if every multicast session regulates its rate according to the most congested end-to-end path in its multicast tree. We present an idealized protocol for tracking the most congested path under changing network conditions, and use simulations to illustrate that tracking the most congested path is indeed a promising approach.

In this paper we present methods to evaluate the benefit of using direct ATM connections (shortcuts) between IP nodes in IP over ATM networks, and we identify the combinations of IP and ATM network topologies where ATM shortcut benefits are likely to be high. We model an IP/ATM network with and without ATM shortcuts as two loss networks. We propose a metric for network performance comparison, the network load ratio, that gives the ratio of the number of flows accepted by two networks at the same network blocking probability. We derive an estimator of this metric, the asymptotic load ratio, that has low computational complexity. This estimator forms the basis of a methodology for network performance comparison. We use this method in simulation experiments using random networks. These experiments indicate that in many cases the utilization of an IP/ATM network increases proportionally to the decrease in the average path length when ATM shortcuts are used. We have also found that there is almost no correlation between the increase in network utilization (when using ATM shortcuts) and the IP to ATM node ratio.

This paper reports on the design and the evaluation of transmission control mechanisms specifically designed for multiplayer, distributed (serverless), interactive Internet applications. Distributed synchronization and dead reckoning are the main elements of this transmission control infrastructure. These mechanisms have been implemented in a fully distributed, multiplayer game application, i.e., one in which each entity in a game session computes its own local view of the session. The role of each entity is consequently to periodically send its own state to all other session participants (using RTP/UDP/IP multicast) and to periodically compute its own local view of the global game state using information received from the other participants. A detailed experimental analysis is provided using MBone and LAN experiments. We investigate how the "quality" of the game is influenced by the frequency at which players exchange state information, as well as by network impairments such as packet loss and transmission delay.

We propose and evaluate novel reliable multicast protocols that combine active repair service (a.k.a. local recovery) and parity encoding (a.k.a. forward error correction or FEC) techniques. We show that, compared to other repair service protocols, our protocols require less buffer inside the network, maintain the low bandwidth requirements of previously proposed repair service/FEC combination protocols, and reduce the amount of FEC processing at repair servers, moving more of this processing to the end-hosts. We also examine repair service/FEC combination protocols in an environment where loss rates differ across domains within the network. We find that repair services are more effective than FEC at reducing bandwidth utilization in such environments. Furthermore, adding FEC to a repair services protocol not only reduces buffer requirements at repair servers, but also reduces bandwidth utilization in domains with high loss, or in domains with large populations of receivers.

Understanding and modelling packet loss in the Internet is especially relevant for the design and analysis of delay-sensitive multimedia applications. We present analysis of 128 hours of end-to-end unicast and multicast packet loss measurement. From these we selected 76 hours of stationary traces for further analysis. We consider the dependence as seen in the autocorrelation function of the original loss data as well as the dependence between good run lengths and loss run lengths. The correlation timescale is found to be 1000 ms or less. We evaluate the accuracy of three models of increasing complexity: the Bernoulli model, the 2-state Markov chain model and the k-th order Markov chain model. Out of the 38 trace segments considered, the Bernoulli model was found to be accurate for 7 segments, and the 2-state model was found to be accurate for 10 segments. A Markov chain model of order 2 or greater was found to be necessary to accurately model the rest of the segments. For the case of adaptive applications which track loss, we address two issues of on-line loss estimation: the required memory size and whether to use exponential smoothing or a sliding window average to estimate average loss rate. We find that a large memory size is necessary and that the sliding window average provides a more accurate estimate for the same effective memory size.

169-182

No abstract available.

We study the problem of resource allocation and control for a network node with regulated traffic. Both guaranteed lossless service and statistical service with small loss probability are considered. We investigate the relationship between source characteristics and the buffer/bandwidth tradeoff under both services. Our contributions are the following. For guaranteed lossless service, we find that the optimal resource allocation scheme suggests that sources sharing a network node with finite bandwidth and buffer space divide into groups according to time scales defined by their leaky-bucket parameters. This time-scale separation determines the manner by which the buffer and bandwidth resources at the network node are shared among the sources. For statistical service with a small loss probability, we present a new approach for estimating the loss probability in a shared buffer multiplexer using the "extremal" on-off, periodic sources. Under this approach, the optimal resource allocation for statistical service is achieved by maximizing both the benefits of buffering sharing and bandwidth sharing. The optimal buffer/bandwidth tradeoff is again determined by a time-scale separation.

Controlling the rate of bulk data multicast to a large number of receivers is difficult due to the heterogeneity among the end-systems' capabilities and their available network bandwidth. If the data transfer rate is too high, some receivers will lose data, and retransmissions will be required. If the data transfer rate is too low, an inordinate amount of time will be required to transfer the data. In this paper, we examine an approach towards rate-controlled multicast of bulk data in which the sender uses multiple multicast groups to transmit data at different rates to different sub-groups of receivers. We present simple algorithms for determining the transmission rate associated with each multicast channel, based on static resource constraints, e.g., network bandwidth bottlenecks. Transmission rates are chosen so as to minimize the average time needed to transfer data to all receivers. Analysis and simulation are used to show that our policies for rate selection perform well for large and diverse receiver groups and make efficient use of network bandwidth. Moreover, we find that only a small number of multicast groups are needed to reap most of the possible performance benefits.

Local recovery approaches for reliable multicast have the potential to provide significant performance gains in terms of reduced bandwidth and delay, and higher system throughput. In this paper we examine two local recovery approaches-one server-based, and the other receiver-based, and compare their performance. The server-based approach makes use of specially designated hosts, called repair servers, co-located with routers inside the network. In the receiver-based approach, only the end hosts (sender and receivers) are involved in error recovery. Using analytical models, we first show that the two local recovery approaches yield significantly higher protocol throughput and lower bandwidth usage than an approach that does not use local recovery. Next, we demonstrate that server-based local recovery yields higher protocol throughput and lower bandwidth usage than receiver-based local recovery when the repair servers have processing power slightly higher than that of a receiver and several hundred kilobytes of buffer per multicast session.

Multimedia wireless networks often employ network based user agents as proxies for mobile users. We consider a fundamental question in the design of these networks: should the user agents migrate and if so, what are good user agent migration policies? We first introduce a general framework for analysing user agent migration policies. We then highlight, through analysis and simulation, the numerous parameters and tradeoffs that dictate the design of migration policies. Finally, we identify two simple threshold-based policies that deliver very good performance over a wide range of system parameters and configurations.

In this paper we develop a simple analytic characterization of the steady state throughput, as a function of loss rate and round trip time for a bulk transfer TCP flow, i.e., a flow with an unlimited amount of data to send. Unlike the models in [6, 7, 10], our model captures not only the behavior of TCP's fast retransmit mechanism (which is also considered in [6, 7, 10]) but also the effect of TCP's timeout mechanism on throughput. Our measurements suggest that this latter behavior is important from a modeling perspective, as almost all of our TCP traces contained more time-out events than fast retransmit events. Our measurements demonstrate that our model is able to more accurately predict TCP throughput and is accurate over a wider range of loss rates.

We present algorithms for flow admission control at an earliest deadline first link scheduler when the flows are characterized by piecewise linear traffic envelopes. We show that the algorithms have very low computational complexity and, thus, practical applicability. The complexity can be further decreased by introducing the notion of discretized admission control. Through discretization, the range of positions for the end points of linear segments of the traffic envelopes is restricted to a finite set. Simulation experiments show that discretized admission control can lead to two orders of magnitude decrease in the amount of computation needed to make admission control decisions over that incurred when using exact (nondiscrete) admission control, with the additional benefit that this amount of computation no longer depends on the number of flows. We examine the relative performance degradation (in terms of the number of flows admitted) incurred by the discretization and find that it is small.

Supporting mobility in asynchronous transfer mode (ATM)-based broad-band networks with wireless access links poses many technical challenges. One of the most important of these challenges is the need to reroute ongoing connections to/from mobile users as these users move among base stations. Connection rerouting schemes must exhibit low handoff latency, maintain efficient routes, and limit disruption to continuous media traffic while minimizing reroute updates to the network switches. In this paper we propose, describe an implementation for, and experimentally evaluate the performance of five different connection rerouting schemes. We show that one of these schemes, which operates in two phases, executes very fast reroutes (with a measured latency of 6.5 ms) in a real-time phase and, if necessary, reroutes again in a nonreal-time phase to maintain efficient routing. The scheme also results in negligible disruption to both audio (e.g., a 1-in-100 chance of a single packet loss at CD-quality audio rates of 128 kb/s) and low-bit-rate video (e.g., a 2-in-100 chance of a single packet loss for 1-Mb/s video) traffic during connection rerouting. Based on these results, we conclude that simple handoff schemes coupled with a connection management architecture are sufficient for supporting low-bit-rate continuous media applications over ATM-based wireless networks.

Variable-bit-rate (VBR) compressed video can exhibit significant multiple-time-scale bit-rate variability. In this paper we consider the transmission of stored video from a server to a client across a network, and explore how the client buffer space can be used most effectively toward reducing the variability of the transmitted bit rate. Two basic results are presented. First, we show how to achieve the greatest possible reduction in rate variability when sending stored video to a client with given buffer size. We formally establish the optimality of our approach and illustrate its performance over a set of long MPEG-1 encoded video traces. Second, we evaluate the impact of optimal smoothing on the network resources needed for video transport, under two network service models: deterministic guaranteed service (Chang 1994; Wrege et al. 1996) and renegotiated constant-bit-rate (RCBR) service (Grossglauser et al. 1997). Under both models, the impact of optimal smoothing is dramatic.

We present algorithms for flow admission control at an EDF link scheduler when the flows are characterized by peak rate, average rate and burst size. We show that the algorithms have very low computational complexity and are easily applicable in practice. The complexity can be further decreased by introducing the notion of flex classes. We evaluate the penalty in efficiency that the classes incur to the EDF scheduler. We find that this efficiency degradation can be made arbitrarily small and is acceptable even for a small number of classes.

In this paper we study the problem of resource allocation and control for an ATM node with regulated traffic. Both guaranteed lossless service and statistical service with small loss probability are considered. We investigate the relationship between source characteristics and the buffer/bandwidth trade-off under both services. Our contributions are the following. For guaranteed lossless service, we find that the optimal resource allocation scheme suggests a time scale separation of sources sharing an ATM node with finite bandwidth and buffer space, and the optimal buffer/bandwidth trade-off is determined by the sources' time scale. For statistical service with a small loss probability, we present a new approach for estimating the loss probability in a shared buffer multiplexor with the so called "extremal" on-off periodic sources. Under this approach, the optimal resource allocation for statistical service is achieved by maximizing both the benefits of buffering sharing and bandwidth sharing. The optimal buffer/bandwidth trade-off is again determined by time scale separation.

A growing number of network applications require the use of a reliable multicast protocol to disseminate data from a source to a potentially large number of receivers. This paper presents an analytic performance analysis of the packet delay incurred under three generic sender- and receiver-initiated approaches towards reliable multicast. We focus on the host processing requirements of these protocols and derive expressions for average time between the initial arrival of a packet at a sender and its correct reception at a randomly chosen receiver. Our numerical results indicate that a NAK-based protocol that limits NAK generation by intentionally and randomly delaying NAK packets can achieve substantially higher throughput than the other two protocols examined and can do so without suffering an appreciable higher delay over a range of system parameters.

We examine an approach for providing reliable, scalable multicast communication, using multiple multicast groups for reducing receiver processing costs in a multicast session. In this approach a single multicast group is used for the original transmission of packets. Retransmissions of packets are done to separate multicast groups, which receivers dynamically join or leave. We first show that by using an infinite number of multicast groups, processing overhead at the receivers are substantially reduced. Next, we show that, for a specific negative acknowledgment (NAK)-based protocol, most of this reduction can be obtained by using only a small number of multicast groups for a wide range of system parameters. Finally, we present a local filtering scheme for minimizing join/leave signaling when multiple multicast groups are used.

In this paper we present a performance study of memory reference behavior in network protocol processing, using an Internet-based protocol stack implemented in the x-kernel running in user space on a MIPS R4400-based Silicon Graphics machine. We use the protocols to drive a validated execution-driven architectural simulator of our machine. We characterize the behavior of network protocol processing, deriving statistics such as cache miss rates and percentage of time spent waiting for memory. We also determine how sensitive protocol processing is to the architectural environment, varying factors such as cache size and associativity, and predict performance on future machines.We show that network protocol cache behavior varies widely, with miss rates ranging from 0 to 28 percent, depending on the scenario. We find instruction cache behavior has the greatest effect on protocol latency under most cases, and that cold cache behavior is very different from warm cache behavior. We demonstrate the upper bounds on performance that can be expected by improving memory behavior, and the impact of features such as associativity and larger cache sizes. In particular, we find that TCP is more sensitive to cache behavior than UDP, gaining larger benefits from improved associativity and bigger caches. We predict that network protocols will scale well with CPU speeds in the future.

Sender-initiated reliable multicast protocols based on the use of positive acknowledgments (ACKs) can suffer performance degradation as the number of receivers increases. This degradation is due to the fact that the sender must bear much of the complexity associated with reliable data transfer (e.g., maintaining state information and timers for each of the receivers and responding to receivers' ACKs). A potential solution to this problem is to shift the burden of providing reliable data transfer to the receivers-thus resulting in receiver-initiated multicast error control protocols based on the use of negative acknowledgments (NAKs). We determine the maximum throughputs for generic sender-initiated and receiver-initiated protocols for two classes of applications: (1) one-many applications where one participant sends data to a set of receivers and (2) many-many applications where all participants simultaneously send and receive data to/from each other. We show that a receiver-initiated error control protocol which requires receivers to transmit NAKs point-to-point to the sender provides higher throughput than a sender-initiated counterpart for both classes of applications. We further demonstrate that, in the case of a one many application, replacing point-to-point transfer of NAKs with multicasting of NAKs coupled with a random backoff procedure provides a substantial additional increase in the throughput of a receiver-initiated error control protocol over a sender-initiated protocol. We also find, however, that such a modification leads to a throughput degradation in the case of many-many applications.

Variable bit-rate (VBR) compressed video is known to exhibit significant, multiple-time-scale rate variability. A number of researchers have considered transmitting stored video from server to a client using smoothing algorithms to reduce this rate variability. These algorithms exploit client buffering capabilities and determine a "smooth" rate transmission schedule, while ensuring that a client buffer neither overflows nor underflows. We investigate how video smoothing impacts the statistical multiplexing gains available with such traffic, and we show that a significant amount of statistical multiplexing gains can still be achieved. We then examine the implication of these results on network resource management and call admission control when transmitting smoothed stored video using VBR service with statistical quality-of-service (QoS) guarantees. Specifically, we present a uniform call admission control scheme based on a Chernoff bound method that uses a simple, novel traffic model requiring only a few parameters. This scheme provides an easy and flexible mechanism for supporting multiple VBR service classes with different QoS requirements. We evaluate the efficacy of the call admission control scheme over a set of MPEG-1 coded video tracts.

Techniques for avoiding the high memory overheads found on many modern shared-memory multiprocessors are of increasing importance in the development of high-performance multiprocessor protocol implementations. One such technique is processor-cache affinity scheduling, which can significantly lower packet latency and substantially increase protocol processing throughput. In this paper, we evaluate several aspects of the effectiveness of affinity-based scheduling in multiprocessor network protocol processing, under packet-level and connection-level parallelization approaches. Specifically, we evaluate the performance of the scheduling technique (1) when a large number of streams are concurrently supported, (2) when processing includes copying of uncached packet data, (3) as applied to send-side protocol processing, and (4) in the presence of stream burstiness and source locality, two well-known properties of network traffic. We find that affinity-based scheduling performs well under these conditions, emphasizing its robustness and general effectiveness in multiprocessor network processing. In addition, we explore a technique which improves the caching behavior and available packet-level concurrency under connection-level parallelism, and find performance improves dramatically.

VBR compressed video is known to exhibit significant, multiple-time-scale bit rate variability. In this paper, we consider the transmission of stored video from a server to a client across a high speed network, and explore how the client buffer space can be used most effectively toward reducing the variability of the transmitted bit rate.We present two basic results. First, we present an optimal smoothing algorithm for achieving the greatest possible reduction in rate variability when transmitting stored video to a client with given buffer size. We provide a formal proof of optimality, and demonstrate the performance of the algorithm on a set of long MPEG-1 encoded video traces. Second, we evaluate the impact of optimal smoothing on the network resources needed for video transport, under two network service models: Deterministic Guaranteed service [1, 9] and Renegotiated CBR (RCBR) service [8, 7]. Under both models, we find the impact of optimal smoothing to be dramatic.

Over the next several years the performance demands on globally available information servers are expected to increase dramatically. These servers must be capable of sending and receiving data over hundreds or even thousands of simultaneous connections. In this paper, we show that connection-level parallel protocols (where different connections are processed in parallel) running on a shared-memory multiprocessor can deliver high network bandwidth across a large number of connections.We experimentally evaluate connection-level parallel implementations of both TCP/IP and UDP/IP protocol stacks. We focus on three questions in our performance evaluation: how throughput scales with the number of processors, how throughput changes as the number of connections increases, and how fairly the aggregate bandwidth is distributed across connections. We show how several factors impact performance: the number of processors used, the number of threads in the system, the number of connections assigned to each thread, and the type of protocols in the stack (i.e., TCP versus UDP).Our results show that with careful implementation connection-level parallel protocol stacks scale well with the number of processors, and deliver high throughput which is, for the most part, sustained as the number of connections increases. Maximizing the number of threads in the system yields the best overall throughput. However, the best fairness behavior is achieved by matching the number of threads to the number of processors and scheduling connections assigned to threads in a round-robin manner.

We consider a real time task model where a task receives a "reward" that depends on the amount of service received prior to its deadline. The reward of the task is assumed to be an increasing function of the amount of service that it receives, i.e., the task has the property that it receives increasing reward with increasing service (IRIS). We focus on the problem of online scheduling of a random arrival sequence of IRIS tasks on a single processor with the goal of maximizing the average reward accrued per task and per unit time. We describe and evaluate several policies for this system through simulation and through a comparison with an unachievable upper bound. We observe that the best performance is exhibited by a two level policy where the top level algorithm is responsible for allocating the amount of service to tasks and the bottom level algorithm, using the earliest deadline first (EDF) rule, is responsible for determining the order in which tasks are executed. Furthermore, the performance of this policy approaches the theoretical upper bound in many cases. We also show that the average number of preemptions of a task under this two level policy is very small.

Techniques for avoiding the high memory overheads found on many modern shared-memory multiprocessors are of increasing importance in the development of high-performance multiprocessor protocol implementations. One such technique is processor-cache affinity scheduling, which can significantly lower packet latency and substantially increase protocol processing throughput. We evaluate several aspects of the effectiveness of affinity-based scheduling in multiprocessor network protocol processing, under packet-level and connection-level parallelization approaches. Specifically, we evaluate the performance of the scheduling technique (1) when a large number of streams are concurrently supported, (2) when processing includes copying of uncached packet data, (3) as applied to send-side protocol processing, and (4) in the presence of stream burstiness and source locality, two well-known properties of network traffic. We find that affinity-based scheduling performs well under these conditions, emphasizing its robustness and general effectiveness in multiprocessor network processing. In addition, we explore a technique which improves the caching behavior and available packet-level concurrency under connection-level parallelism, and find performance improves dramatically.

We explore processor-cache affinity scheduling of parallel network protocol processing, in a setting in which protocol processing executes on a shared-memory multiprocessor concurrently with a general workload of non-protocol activity. We find that affinity-based scheduling can significantly reduce the communication delay associated with protocol processing, enabling the host to support a greater number of concurrent streams and to provide higher maximum throughput to individual streams. In addition, we compare the performance of two parallelization alternatives, locking and independent protocol stacks (IPS), with very different caching behaviors. We find that IPS (which maximizes cache affinity) delivers much lower message latency and significantly higher message throughput capacity, yet exhibits less robust response to infra-stream burstiness and limited intra-stream scalability.

We explore processor-cache affinity scheduling of parallel network protocol processing in a setting in which protocol processing executes on a shared-memory multiprocessor concurrently with a general workload of non-protocol activity. We find that affinity scheduling can significantly reduce the communication delay associated with protocol processing, enabling the host to support a greater number of concurrent streams and to provide a higher maximum throughput to individual streams. In addition, we compare implementations of two parallelization approaches (Locking and Independent Protocol Stacks) with very different caching behaviors.

We develop bounds on the individual session backlog and delay distribution under the generalized processor sharing (GPS) scheduling discipline. This work is motivated by, and is an extension of, Parekh and Gallager's (see IEEE/ACM Trans. Networking, vol.1, no.6, p.344-357, 1993, and vol. 2, no.4, p.137-150, 1994) deterministic study of the GPS scheduling discipline with leaky-bucket token controlled sessions. Using the exponentially bounded burstiness (EBB) process model introduced by Yaron and Sidi (see IEEE/ACM Trans. Networking, vol.1, p.372-385, 1993) as a source traffic characterization, we establish results that extend the deterministic study of GPS. For a single GPS server in isolation, we present statistical bounds on the distributions of backlog and delay for each session. In the network setting, we show that networks belonging to a broad class of GPS assignments, the so-called consistent relative session treatment (CRST) GPS assignments, are stable in a stochastic sense. In particular, we establish simple bounds on the distribution of backlog and delay for each session in a rate proportional processor sharing (RPPS) GPS network with arbitrary topology.>

In future BISDN networks, significant burdens will be placed on the processing elements in the network since call routing and admission policies will be more computationally intensive than those in present day networks. Thus, the bottleneck in future networks is likely to shift from the communication links to the processing elements. The delays at these elements are influenced by their processing capacity and factors such as; routing algorithms, propagation delays, admission control functions, and network topology. The goal of this paper is to characterize the behavior of these factors on the call setup time and accepted call throughput. This behavior is examined for three sequential routing schemes and two flooding routing schemes under various network parameters and different forms of admission control. The results of our study indicate that processing capacity and the admission control function can affect the call setup time and accepted call throughput significantly while propagation delay does not affect these performance measures significantly.

The virtual path (VP) concept has been proposed to simplify traffic control and resource management in future B-ISDN. In particular, call setup processing can be significantly reduced when resources are reserved on VPs. However, this advantage is offset by a decrease in statistical multiplexing gains of the networks. The focus of this paper is on how to improve bandwidth efficiency through adaptive routing when capacity is reserved on all VPs. The authors first examine two VP capacity reservation strategies. They then design and evaluate computationally feasible Markov decision process-based routing algorithms and show that the network blocking probability can be significantly reduced by MDP routing.>

Recent interest in supporting packet-audio applications over wide area networks has been fueled by the availability of low-cost, toll-quality workstation audio and the demonstration that limited amounts of interactive audio can be supported by today's Internet. In such applications, received audio packets are buffered, and their playout delayed at the destination host in order to compensate for the variable network delays. The authors investigate the performance of four different algorithms for adaptively adjusting the playout delay of audio packets in an interactive packet-audio terminal application, in the face of such varying network delays. They evaluate the playout algorithms using experimentally-obtained delay measurements of audio traffic between several different Internet sites. Their results indicate that an adaptive algorithm which explicitly adjusts to the sharp, spike-like increases in packet delay which were observed in the traces can achieve a lower rate of lost packets for both a given average playout delay and a given maximum buffer size.>

The authors distinguish between four types of service that may be provided to real-time traffic by packet-switched networks, ranging from "need-blind" and "need-based best-effort" to "guaranteed throughput" and "bounded delay jitter" services. They evaluate a number of scheduling policies that offer need-based, best-effort service. They introduce hop-laxity (HL) scheduling which is based on the time remaining until the packet must reach its destination as well as the number of hops separating it from the destination. HL scheduling is evaluated through simulation and has been implemented within a BSD-based kernel and tested on the DARTnet network. The results indicate that HL scheduling tends to equalize delays between calls with large and small number of hops as compared to a FIFO discipline, reducing the 99.9% percentile of delay and the fraction of late packets. They compare HL scheduling to the FIFO+ discipline suggested by Clark et al., (see SIGCOMM Symposium on Communications Architectures and Protocols, p.14-26, 1992, and Computer Communication Review, vol.22, no.4) and find that their delay properties are similar. Other disciplines, such as minimum laxity or transit priority, may actually do more harm than good.>

Providing smooth playback capabilities for video servers, which must support potentially thousands of on-demand users, has been an area of active research. From a user's perspective, VCR functions of fast-forward and rewind (FF/Rew), are desirable features in video-on-demand. But FF/Rew at n times the regular playback rate requires n times the regular playback bandwidth from architectural components of the video server. Thus, guaranteeing sufficient bandwidth to enable users to perform FF/Rew reduces the number of supportable users by a factor of n. In this paper we propose an alternative, effective FF/Rew service, which provides FF/Rew capabilities with an associated statistical quality-of-service (QoS) guarantee. This service provides immediate access to full-resolution FF/Rew bandwidth with high probability. When bandwidth is not available, service is either delayed or provided immediately but with a loss in resolution. In addition, we specify several QoS metrics to characterize the delay or loss experienced by a FF/Rew request. We show that using effective FF/Rew with statistical guarantees on these QoS metrics results in a significant increase in the number of supportable users, when compared to systems in which FF/Rew bandwidth is statistically reserved for each user. Moreover, a playback-only video server can be extended to provide FF/Rew service by reserving only a small portion of its total bandwidth, which is dynamically shared among FF/Rew requests.

In this paper, we consider the problem of providing statistical guarantees (for example, on the tail distribution of delay) under the Generalized Processor Sharing (GPS) scheduling discipline. This work is motivated by, and is an extension of, Parekh and Gallager's deterministic study of GPS scheduling discipline with leaky-bucket token controlled sessions [PG93a,b, Parekh92]. Using the exponentially bounded burstiness (E.B.B.) process model introduced in [YaSi93a] as a source traffic characterization, we establish results that extend the deterministic study of GPS: for a single GPS server in isolation, we present statistical bounds on the tail distributions of backlog and delay for each session. In the network setting, we show that networks belonging to a broad class of GPS assignments, the so-called Consistent Relative Session Treatment (CRST) GPS assignments, are stable in a stochastic sense. In particular, we establish simple bounds on the tail distribution of backlog and delay for each session in a Rate Proportional Processor Sharing (RPPS) GPS network with arbitrary topology.

Sender-initiated reliable multicast protocols, based on the use of positive acknowledgments (ACKs), lead to an ACK implosion problem at the sender as the number of receivers increases. Briefly, the ACK implosion problem refers to the significant overhead incurred by the sending host due to the processing of ACKs from each receiver. A potential solution to this problem is to shift the burden of providing reliable data transfer to the receivers—thus resulting in a receiver-initiated multicast error control protocol based on the use of negative acknowledgments (NAKs). In this paper we determine the maximum throughputs of the sending and receiving hosts for generic sender-initiated and receiver-initiated protocols. We show that the receiver-initiated error control protocols provide substantially higher throughputs than their sender-initiated counterparts. We further demonstrate that the introduction of random delays prior to generating NAKs coupled with the multicasting of NAKs to all receivers has the potential for an additional substantial increase in the throughput of receiver-initiated error control protocols over sender-initiated protocols.

The dramatically increased bandwidths and processing capabilities of future high-speed networks make possible many distributed real-time applications, such as sensor-based applications and multimedia services. Since these applications will have traffic characteristics and performance requirements that differ dramatically from those of current data-oriented applications, new communication network architectures, and protocols will be required. In this paper we discuss the performance requirements and traffic characteristics of various real-time applications, survey recent developments in the areas of network architecture and protocols for supporting real-time services, and develop frameworks in which these, and future, research efforts can be considered.>

With the addition of new network services, it is anticipated that the processing involved in setting up a call in a circuit-switched network or a session in a packet-switched network will vary greatly for different types of services. In this paper, we address the problem of reducing the call setup time in a circuit-switched network, or equivalently the session setup time in a packet-switched network, through the balancing of load across call processors. With a view to designing algorithms to execute on-line in a system, we formulate a stochastic optimization problem and study the use of stochastic approximation techniques. Given the distributed nature of the problem, we extend previous results obtained for a single node to the case where several nodes operate simultaneously and in an asynchronous manner. Our results include a theoretical study of convergence as well as several simulation results that compare two stochastic approximation techniques.>

A crucial problem facing the designers and deployers of future high-speed networks is providing applications with quality of service (QOS) guarantees. For soft real-time applications, which are delay sensitive but loss tolerant, delay distribution is an important QOS measure of interest. In this paper we study (through simulation) the end-to-end delay distribution seen by individual sessions under simple first-come first-served (FCFS) multiplexing in a network model with two significant features: (1) all traffic is connection-oriented, (2) cross traffic along routes is representative of that seen by calls in a moderately sized wide area network (i.e., less than 100 switches). We compare these delay distributions with the worst case point-valued analytic delay bounds predicted by three different techniques for providing such bounds (two of which require a more sophisticated link-level scheduling policy). We also consider the per-hop delay distributions seen as a session progresses deeper into the network and determine the sensitivity of these delay distributions to the manner in which the interfering traffic is modeled. Finally, we use our delay distribution results to examine the tradeoff between the QOS requested by a call, the manner in which the QOS guarantee is provided, and the number of calls that are admitted at the requested QOS.

In this paper we consider the problem of on-line scheduling of real-time tasks which receive a that depends on the amount of service received. In our model, tasks have associated deadlines at which they must depart the system. The task computations are such that the longer they are able to execute before their deadline, the greater the value of their computations, i.e., the tasks have the property that they receive increasing reward with increasing service (IRIS). We focus on the problem of scheduling IRIS tasks in a system in which tasks arrive randomly over time, with the goal of maximizing the average reward accrued per task and per unit time. We describe and evaluate a two-level policy for this system. A top-level algorithm executes each time a task arrives and determines the amount of service to allocate to each task in the absence of future arrivals. A lower-level algorithm, an earliest deadline first (EDF) policy in our case, is responsible for the actual selection of tasks to execute. This two-level policy is evaluated through a combination of analysis and simulation, We observe that it provides nearly optimal performance when the variance in the interarrival times and/or laxities is low and that the performance is more sensitive to changes in the arrival process than the deadline distribution.

The authors examine the effects of call processing delay, propagation delay, the admission control function due to quality of service (QOS) requirements, and routing algorithms on the call setup time in future B-ISDN networks. Three routing schemes from circuit-switched networks and two parallel versions of these routing schemes are investigated under various network parameters and different forms of admission control. Analytic models for different routing algorithms are developed and were validated by simulation results. The results of the study indicate that call processing delay associated with the admission control function affects the network performance significantly while propagation delay does not affect the performance significantly.>

Future high-speed networks are expected to support a wide variety of services such as voice and video, and to provide a guaranteed quality-of-service (QOS). The authors examine the issues of computing and guaranteeing QOS. Traditionally, the computation of user-oriented performance criteria such as the average delay has been carried out via steady-state analysis of queuing theoretic models of communication networks. It is shown that the steady-state computations are often not sufficient for QOS purposes in future high-speed networks. The authors provide mechanisms for computing and guaranteeing QOS criteria and consider the issue of approximate QOS criteria. It is argued that, for certain envisaged applications, traditional QOS criteria are not appropriate. A QOS criterion for such applications is proposed.>

We present a technique for computing upper bounds on the distribution of individual per-session performance measures such as delay and buffer occupancy for networks in which sessions may be routed over several “hops.” Our approach is based on first stochastically bounding the distribution of the number of packets (or cells) which can be generated by each traffic source over various lengths of time and then “pushing” these bounds (which are then shown to hold over new time interval lengths at various network queues) through the network on a per-session basis. Session performance bounds can then be computed once the stochastic bounds on the arrival process have been characterized for each session at all network nodes. A numerical example is presented and the resulting distributional bounds compared with simulation as well as with a point-valued worst-case performance bound.

In a distributed system an algorithm used to select a distinguished node or leader in the system is known as a leader election algorithm. Leader election algorithms are examined that attempt to locate the leader at a good node (from a performance standpoint) in the system. In the preference-based approaches examined, each node in the system uses locally available information to vote for the various candidates (potential leaders) on the basis of the performance level it would realize under each of them. The preference-based leader election algorithms proposed and examined are simple, and are shown to perform almost as well as a traditional optimization-based approach to leader election.>

A novel packet switch architecture is proposed based on a channel grouped virtual circuit (CG-VC) scheme for high-speed communication networks. The case is considered in which there are several parallel channels between two switching nodes. The CG-VC scheme allows a packet to select an available channel in such a way as to avoid congested channels using a simple, hardware-based, self-routing mechanism. As a result, the architecture provides efficient channel use and low switching delay. The performance of the proposed switch is evaluated by simulation. The results show the proposed switch significantly improves channel utilization and switching delay compared with conventional single-channel allocation transmission policies.>

The stochastic properties of time-out loss periods are characterized for infinite queues, that is, uninterrupted intervals during which the virtual wait is at or above some fixed threshold. Analytic expressions and numerical techniques presented are for computing both time-based measures such as the distribution of periods during which all arriving packets are lost due to excessive delay as well as packet-based measures such as the distribution of the number of consecutively lost packets and the number of successful packets between such periods of loss. Both continuous and discrete-time systems are examined. It is shown that the assumption of random packet loss severely underestimates the number of consecutively lost packets.>

The authors address the problem of reducing the call setup time in a circuit-switched network, or, equivalently, the session setup time in a packet-switched network, through the balancing of load across call processors. A stochastic optimization problem is formulated, and the use of stochastic approximation techniques is studied. Given the distributed nature of the problem, previous results obtained for a single node are extended to the case where several nodes operate simultaneously and in an asynchronous manner. A theoretical study of convergence as well as several simulation results that compare two stochastic approximation techniques are presented.>

Three different approximation techniques are examined. The performance models studied differ primarily in the manner in which the superposition of the voice sources (i.e., the arrival process) is modeled. The first approach models the superimposed voice sources as a renewal process, and performance calculations are based only on the first two moments of the renewal process. The second approach is based on modeling the superimposed voice sources as a Markov modulated Poisson process (MMPP). The choice of parameters for the MMPP attempts to capture aspects of the arrival process in a more intuitive manner than previously proposed approaches for determining the MMPP parameters and is shown to compute loss more accurately. Finally, a fluid flow approximation for computing packet loss is evaluated. For all three approaches, a unifying example, the case of multiplexing voice sources over a T1-rate link is considered. The main conclusion is that both the MMPP model and the fluid flow approximation can provide accurate loss predictions for parameter ranges of practical interest.>

The three performance models studied differ primarily in the manner in which the superposition of the voice sources (i.e. the arrival process) is modeled. The first approach models the superimposed voice sources as a renewal process. The second approach is based on modeling the superimposed voice sources as a Markov modulated Poisson process (MMPP). The choice of parameters for the MMPP captures aspects of the long-term correlation in the arrival process in a more intuitive manner and computes loss more accurately than previous approaches for computing the MMPP parameters. A fluid flow approximation for the superposition is evaluated on the basis of the technique of D. Anick et al. (1982). For all three approaches, the case of multiplexing voice sources over a T1-rate link is considered. Both the new MMPP model and the fluid flow approximation can provide accurate loss predictions for parameter ranges of practical interest. The modeling of buffer overflow for general arrival processes is addressed, and modeling approaches for analyzing finite-buffer multiplexers with general arrival and service processes in a network environment are outlined.>

An investigation is conducted of the possibility of locally controlling short-term congestion for loss-tolerant but delay-sensitive traffic (such as packet voice) through selective discarding of packets based on the virtual work found by a packet on arrival to a queue (local deadlines). By analysis and simulation of a multistage virtual circuit, it is shown that this approach can cut voice-tolerable loss rates in half for high loads. It is also shown that the simple case of using the same local deadline throughout the network performs nearly as well as taking reduced interior traffic into consideration and optimizing loss performance over a set of heterogeneous local deadlines. As an example, the issue of establishing control parameters at call-setup time is also considered.>

The operation of stack splitting random-access protocols in multiaccess networks in which individual stations may receive asymmetric feedback from the channel (i.e. different stations may observe different, possibly erroneous, outcomes on the channel) is examined. Several possible modifications to the basic stack algorithm are proposed for such environments, and the performances of the various alternatives are reviewed. An approximate Markov chain model is developed to analytically study the time delay versus throughput performance of the various alternatives, and the analytic results are validated through simulation. Representative performance results are given for the alternative stack algorithms. It is found that those algorithms which tend to treat the receipt of corrupted feedback by a station as a collision show superior performance for throughput values greater than approximately 0.2, whereas, at low throughput values, there is relatively little difference between the performances of the various approaches studied. It was noted during the simulation studies that, with an error rate of up to 5%, the algorithms remained stable up to an arrival rate of approximately 0.3 or higher.>

The performance of several policies for scheduling real-time and non-real-time messages in a statistical multiplexer is examined. The performance metric for the real-time traffic is the percentage of messages not transmitted within their deadlines; the performance metric for the non-real-time traffic is the average delay. The scheduling policies are: (1) first-come first-served (FCFS); (2) head of the line priority, in which real-time packets are given priority; (3) minimum-laxity threshold (MLT) policy; and (4) queue-length threshold (QLT) policy. Under the MLT policy, priority is given to the real-time traffic when the minimum laxity is below some threshold. The QLT policy gives priority to the non-real-time traffic whenever the number of queued non-real-time packets is above some threshold. Results show that the FCFS policy causes relatively high losses for the real-time traffic while providing relatively low message delays for the non-real-time traffic; the converse holds true for the strict priority discipline. Both the MLT and QLT disciplines allow the designer to explicitly trade off the performance realized by each traffic class by using an appropriately chosen value for the threshold parameter. Little difference is observed in the performance tradeoffs available, so it is concluded that the QLT policy is more practical, as it is simpler to implement.>

Decentralized algorithms are examined for optimally distributing a divisible resource in a distributed computer system. To study this problem in a specific context, the problem of optimal file allocation is considered. In this case, the optimization criteria include both the communication cost and average processing delay associated with a file access. The algorithms examined have their origins in the field of mathematical economics. They are shown to have several attractive properties, including their simplicity and distributed nature, the computation of feasible and increasingly better resource allocations as the result of each iteration, and, in the case of file allocation, rapid convergence. Conditions are formally derived under which the algorithms are guaranteed to coverage, and their convergence behavior is additionally examined through simulation.>

A novel class of action probability update algorithms for learning automata that use the relative reward strengths of responses from the environment is examined. Specifically, update algorithms for S-model automata in which 'recent' environmental responses for each of the actions retained are used. A convergence result is proven and the behavior of these automat is studied by simulation. A major result is that the performance of these algorithms is superior, in several respects, to that of the well-known SL/sub R-1/ update algorithm. Additional results are presented on the variability of performance, the cost of learning and, in the case of static environments, modifications that result in improved convergence.>

An examination is made of the performance of two different approaches for handling the loss and/or corruption of messages as they are transmitted between two end users in a high-speed network. In the link-by-link approach, two adjacent nodes in an end-to-end path locally detect and recover from message loss or corruption along their joining link. In the end-to-end approach, recovery is done solely on the basis of a single end-to-end protocol. The authors develop analytic performance models for comparing the performance of these two approaches; these analytic models are validated by simulation. The models explicitly consider the effects of channel errors, propagation delays of messages and their acknowledgments, both separate and shared VC buffer pools, finite buffer capacities, buffering of unacknowledged messages, and timeout mechanisms. It is found that for the range of network parameters of practical interest, an end-to-end approach toward error control is superior to a link-by-link approach, while requiring fewer network resources.>

A hybrid protocol is proposed for high bandwidth rings in which the roundtrip propagation delay is much larger than the packet transmission time. Features of random-access protocols and conflict-free protocols such as token passing are combined to achieve superior performance. The scheme permits simultaneous use of the channel by many packets, is fair to all stations, and is completely distributed. Performance results show that the system remains stable for throughputs up to a maximum of 1 and that the delay characteristics are better than those of related access protocols. The protocol additionally provides for reservation of bandwidth on demand and bounded delays for real-time applications.>

The authors examine the performance of two different approaches for handling the loss and/or corruption of messages as they are transmitted between two end users in a high-speed network. In the link-by-link approach, two adjacent nodes in an end-to-end path locally detect and recover from message loss or corruption along their joining link. In the end-to-end approach, recovery is done solely on the basis of a single end-to-end protocol. The authors develop analytic performance models, validated with simulation, for comparing the performance of these two approaches. The authors find that for the range of network parameters of practical interest, an end-to-end approach towards error control is superior to a link-by-link approach, even under assumptions that would overly favor the link-by-link approach, while at the same time requiring fewer network resources (e.g. buffers, computation time) than the link-by-link approach. The performance differences arise primarily from the increased buffer requirements of the link-by-link approach.>

Computer-aided design, analysis, and simulation techniques for communication networks are surveyed. The focus is on analytic and simulation techniques that are either amendable to, or require, implementation on a computer. Issues relating to the implementation of these techniques on a computer as well as their embodiment in software tools are addressed. Past and present work in these areas is surveyed, the application of these techniques to network performance modeling and analysis is discussed, and promising directions for future research are indicated.>

The authors examine the use of a group random-access protocol based on time windows for supporting time-constrained communication applications in a multiple-access network. First they formulate a policy for controlling protocol operation to minimize the percentage of messages with waiting times greater than some given bound. A semi-Markov decision model is then developed for protocol operation, and three of the four optimal control elements of this policy are determined. Although the semiMarkov decision model can also be used to obtain performance results, the procedure is to computationally expensive to be of practical use. Thus, an alternate performance model based on a queuing system with impatient customers is developed. Protocol performance under the optimal elements of the control policy shows significant improvements over cases in which the protocol is not controlled in this manner. Simulation results are presented to corroborate the analytic results.>

in soft real-time distributed computer stems, a job submitted at a node in the network must complete execution within a specified time constraint, otherwise it is considered lost. When a single node occasionally experiences an overload of jobs, it may still be possible to execute some of the otherwise lost jobs by invoking a load sharingnode algorithm to distribute the local overload to other system nodes. We examine several relatively simple approaches to load sharing and show that these simple real-time load sharing algorithms may often perform as well as their more complex counterparts. Approximate analytic performance models are developed and validated through simulation. The performance results suggest that, over a relatively wide range of system parameters, the performance of these simple approaches is substantially better than the case of no load sharing and often close to that of a theoretically optimum algorithm.

Queueing networks are a powerful abstraction for modeling systems involving contention for resources, e.g., manufacturing lines and computer systems. Queueing networks are especially effective in modeling computer communication systems. Most papers concerning queueing models of communication describe analytic solution of queueing models. This paper describes simulation models based on "extended" queueing networks. The primary advantage of using a queueing network representation for simulation of a computer communication system is the high level of description, in comparison with conventional simulation programming languages. For queueing network models to be used effectively for simulation of contention systems, appropriate software is needed. The research queueing package (RESQ) is a general purpose tool for modeling contention for resources and associated system characteristics. RESQ facilitates i) appropriate abstraction of system characteristics through its definitions of extended queueing networks, ii) efficient and convenient definition and revision of models through its integrated interactive and batch model definition interface, and iii) effective experimentation with simulation models through facilities for parameterized sets of experiments, interactive running of simulations and statistical analysis of simulation results. With a tool such as RESQ, an analyst can produce results in days instead of weeks, and so an analyst can answer questions which otherwise would be left unanswered.

For many time-constrained communication applications, such as packetized voice, a critical performance measure is the percentage of messages which are transmitted within a given amount of time after their arrival at a sending station. We examine the use of a group random access protocol based on time windows for achieving time-constrained communication in a multiple access environment. First, we formulate a policy for controlling protocol operation in order to minimize the percentage of messages with waiting times greater than some given bound. A semi-Markov decision model is then developed for protocol operation and three of the four optimal control elements of this policy are then determined.