Smartphones are the central component of our modern, connected life. We carry them from the moment we wake up till the time we go to bed. Continuous technology innovation has created ever more sophisticated phones. Their small size belies a complexity that is largely unknown to the user -- making it almost impossible to discover and use these expanded capabilities. Designers are forced to make tradeoffs between adding more capabilities and burying the functionality in menu hierarchies. Users are frustrated when forced to accept either of these choices. This is the fundamental limitation of modern touch based interfaces to smartphones.

In this paper, we propose a simple, distributed, but highly efficient fairness-enforcing incentive mechanism for cooperative computing. The proposed mechanism, called triangle chaining (T-Chain), enforces reciprocity to avoid the exploitable aspects of the schemes that allow free-riding. In T-Chain, symmetric key cryptography provides the basis for a lightweight, almost-fair exchange protocol, which is coupled with a pay-it-forward mechanism. This combination increases the opportunity for multi-lateral exchanges and further maximizes the resource utilization of participants, each of whom is assumed to operate solely for his or her own benefit. T-Chain also provides barrier-free entry to newcomers with flexible resource allocation, allowing them to immediately benefit, and, therefore, is suitable for dynamic environments with high churn (i.e., turnover). T-Chain is distributed and simple to implement, as no trusted third party is required to monitor or enforce the scheme, nor is there any reliance on reputation information or tokens.

The problem of overbuffering in the current Internet (termed as bufferbloat) has drawn the attention of the research community in recent years. Cellular networks keep large buffers at base stations to smooth out the bursty data traffic over the time-varying channels and are hence apt to bufferbloat. However, despite their growing importance due to the boom of smart phones, we still lack a comprehensive study of bufferbloat in cellular networks and its impact on TCP performance. In this paper, we conducted extensive measurement of the 3G/4G networks of the four major U.S. carriers and the largest carrier in Korea. We revealed the severity of bufferbloat in current cellular networks and discovered some ad-hoc tricks adopted by smart phone vendors, which mitigate the impact of bufferbloat but result in performance degradation under various practical scenarios. To address the problem, we propose dynamic receiver window adjustment (DRWA) that requires slight TCP modification only in smart phones, thus guarantees quick deployment via over-the-air updates. Our extensive real-world tests confirm that DRWA reduces the latency of TCP flows by 25-49 percent and increase TCP throughput by up to 51 percent in certain scenarios. It is further verified that DRWA has significant effect on the latency of Voice-over-IP traffic and on the traffic going through TCP split scenarios with performance enhancing proxy.

We present ACMI, an FM-based indoor localization system that does not require proactive site profiling. ACMI constructs the fingerprint database based on pure estimation of indoor received signal strength (RSS) distribution, where only the signals transmitted from commercial FM radio stations are used. Based on extensive field measurement study, we established our own signal propagation model that harnesses FM radio characteristics and open information of FM transmission towers in combination with the floor-plan of a building. Output of the model is an RSS fingerprint database. Using the fingerprint database as a knowledge base, ACMI refines a positioning result via the two-step process; parameter calibration and path matching, during its runtime. Without site profiling, our evaluation indicates that ACMI in seven campus locations and three downtown buildings using eight distinguished FM stations finds positions with only about 6 and 10 meters of errors on average, respectively.

In this paper, we propose a simple, distributed, but highly efficient fairness-enforcing incentive mechanism for cooperative computing. The proposed incentive scheme, called Triangle Chaining (T-Chain), enforces reciprocity to minimize the exploitable aspects of other schemes that allow free-riding. In T-Chain, symmetric key cryptography provides the basis for a lightweight, almost-fair exchange protocol, which is coupled with a pay-it-forward mechanism. This combination increases the opportunity for multi-lateral exchanges and further maximizes the resource utilization of participants, each of whom is assumed to operate solely for his or her own benefit. T-Chain also provides barrier-free entry to newcomers with flexible resource allocation, providing them with immediate benefits, and therefore is suitable for dynamic environments with high churn (i.e., Turnover). TChain is distributed and simple to implement, as no trusted third party is required to monitor or enforce the scheme, nor is there any reliance on reputation information or tokens.

In this paper, we propose a practical interaction interface for a local set of devices to connect to each other without requiring a lot of effort from their users. We find that highly time-correlated Wi-Fi signal measures experience less variation in their received signal strength (RSS), which alleviates the impediment of the RSS-based solution. We also notice that each room observes significantly discrete signal signature even when they are adjacent to each other. We leverage these observations and rely on the RSS measure to detect and unobtrusively pair devices in the same space. To achieve our goal, we devise a new similarity metric for RSS comparison and propose a means of selecting the cluster threshold. We implement a prototype named Flock for Android devices. By relying on our client-server system architecture, mobile users can interface with others in a few seconds without having to search-and-select nearby devices.

In this paper, a joint optimization of link scheduling, routing and replication for delay-tolerant networks (DTNs) has been studied. The optimization problems for resource allocation in DTNs are typically solved using dynamic programming which requires knowledge of future events such as meeting schedules and durations. This paper defines a new notion of approximation to the optimality for DTNs, called snapshot approximation where nodes are not clairvoyant, i.e., not looking ahead into future events, and thus decisions are made using only contemporarily available knowledges. Unfortunately, the snapshot approximation still requires solving an NP-hard problem of maximum weighted independent set (MWIS) and a global knowledge of who currently owns a copy and what their delivery probabilities are. This paper proposes an algorithm, Max-Contribution (MC) that approximates MWIS problem with a greedy method and its distributed online approximation algorithm, Distributed Max-Contribution (DMC) that performs scheduling, routing and replication based only on locally and contemporarily available information. Through extensive simulations based on real GPS traces tracking over 4,000 taxies and 500 taxies for about 30 days and 25 days in two different large cities, DMC is verified to perform closely to MC and outperform existing heuristically engineered resource allocation algorithms for DTNs.

Smart devices such as smartphones and tablets are becoming more powerful and versatile enough to replace conventional personal computers. Despite the rapid evolution in their capabilities, controlling peripherals such as network printers directly from smart devices is still in the primitive stage due to the lack of dedicated drivers. We propose and prototype a cloud-powered, driver-less printing system called CloudBridge for ubiquitous printing support from off the shelf smart devices. The CloudBridge service, which runs on a smart device, operates as a communication bridge connecting a network printer and a cloud server. By using cloud's ability to translate the operation commands into a language that the printer can understand, it is possible for a smart device to control the printer without having dedicated drivers. CloudBridge achieves the true meaning of ubiquitous mobile printing: it does not require any prerequisite settings. Compared to most widely used mobile printing solutions, the operation time is reasonable, compensating for the time and effort required for setting up the solution. CloudBridge is further optimized to improve the quality of experience, such as response time and energy consumption of the smart device, by adopting an adaptive compression method.

A variety of mathematical tools have been developed for predicting the spreading patterns in a number of varied environments including infectious diseases, computer viruses, and urgent messages broadcast to mobile agents (e.g., humans, vehicles, and mobile devices). These tools have mainly focused on estimating the average time for the spread to reach a fraction (e.g., α) of the agents, i.e., the so-called average completion time E(Tα). We claim that providing probabilistic guarantee on the time for the spread Tαrather than only its average gives a much better understanding of the spread, and hence could be used to design improved methods to prevent epidemics or devise accelerated methods for distributing data. To demonstrate the benefits, we introduce a new metric Gα,βthat denotes the time required to guarantee α completion with probability β, and develop a new framework to characterize the distribution of Tαfor various spread parameters such as number of seeds, level of contact rates, and heterogeneity in contact rates. We apply our technique to an experimental mobility trace of taxies in Shanghai and show that our framework enables us to allocate resources (i.e., to control spread parameters) for acceleration of spread in a far more efficient way than the state-of-the-art.

Spectrum sensing, the task of discovering spectrum usage at a given location, is a fundamental problem in dynamic spectrum access networks. While sensing in narrow spectrum bands is well studied in previous work, wideband spectrum sensing is challenging since a wideband radio is generally too expensive and power consuming for mobile devices. Sequential scan, on the other hand, can be very slow if the wide spectrum band contains many narrow channels. In this paper, we propose an analog-filter based spectrum sensing technique, which is much faster than sequential scan and much cheaper than using a wideband radio. The key insight is that, if the sum of energy on a contiguous band is low, we can conclude that all channels in this band are clear with just one measurement. Based on this insight, we design an intelligent search algorithm to minimize the number of total measurements. We prove that the algorithm has the same asymptotic complexity as compressed sensing while our design is much simpler and easily implementable in the real hardware. We show the availability of our technique using hardware devices that include analog filters and analog energy detectors. Our extensive evaluation using real TV “white space” signals shows the effectiveness of our technique.

We present ACMI, an FM-based indoor localization that does not require proactive site profiling. ACMI constructs the fingerprint database based on the pure estimation of indoor RSS distribution, where the signals transmitted from commercial FM radio stations are used. For this, ACMI makes use of our signal model harnessing public transmission information of FM stations in a combination with a floorplan of a building. Using the fingerprint database as the knowledge base, ACMI actively performs multi-level online signal matching to infer the current location of a mobile user. ACMI achieves good indoor localization accuracy even without site profiling efforts. We evaluate ACMI with extensive indoor experiments in 7 different locations with over 1,100 indoor spots. The results show that ACMI achieves up to 89% room identification and accuracy of 6m localization error on average using 8 FM broadcast signals.

Delay-capacity tradeoffs for mobile networks have been analyzed through a number of research works. However, Lévy mobility known to closely capture human movement patterns has not been adopted in such work. Understanding the delay-capacity tradeoff for a network with Lévy mobility can provide important insights into understanding the performance of real mobile networks governed by human mobility. This paper analytically derives an important point in the delay-capacity tradeoff for Lévy mobility, known as the critical delay. The critical delay is the minimum delay required to achieve greater throughput than what conventional static networks can possibly achieve (i.e., O(1/√n) per node in a network with n nodes). The Lévy mobility includes Lévy flight and Lévy walk whose step-size distributions parametrized by α ∈ (0,2] are both heavy-tailed while their times taken for the same step size are different. Our proposed technique involves: 1) analyzing the joint spatio-temporal probability density function of a time-varying location of a node for Lévy flight, and 2) characterizing an embedded Markov process in Lévy walk, which is a semi-Markov process. The results indicate that in Lévy walk, there is a phase transition such that for α ∈ (0,1), the critical delay is always Θ(n[1/2]), and for α ∈ [1,2] it is Θ(n[(α)/2]). In contrast, Lévy flight has the critical delay Θ(n[(α)/2]) for α ∈ (0,2].

This paper presents a quantitative study on the performance of 3G mobile data offloading through WiFi networks. We recruited 97 iPhone users from metropolitan areas and collected statistics on their WiFi connectivity during a two-and-a-half-week period in February 2010. Our trace-driven simulation using the acquired whole-day traces indicates that WiFi already offloads about 65% of the total mobile data traffic and saves 55% of battery power without using any delayed transmission. If data transfers can be delayed with some deadline until users enter a WiFi zone, substantial gains can be achieved only when the deadline is fairly larger than tens of minutes. With 100-s delays, the achievable gain is less than only 2%-3%, whereas with 1 h or longer deadlines, traffic and energy saving gains increase beyond 29% and 20%, respectively. These results are in contrast to the substantial gain (20%-33%) reported by the existing work even for 100-s delayed transmission using traces taken from transit buses or war-driving. In addition, a distribution model-based simulator and a theoretical framework that enable analytical studies of the average performance of offloading are proposed. These tools are useful for network providers to obtain a rough estimate on the average performance of offloading for a given WiFi deployment condition.

Locality-aware P2P file sharing systems have drawn the attention of the research community as a promising technique to alleviate the tussle between P2P traffic and ISPs. However, existing locality-based schemes mainly focus on how to distinguish whether a peer is local or not and pay less attention to how to utilize the locality information. Typically, they simply bias the peer selection towards local peers in the hope that it will reduce cross-ISP traffic. In this paper, we argue that such coarse-grained control is inadequate and propose a fine-grained mechanism called Swarm-over-Swarm (SOS). Through explicit coordination on piece selection among local peers, SOS is much more effective in reducing redundant cross-ISP traffic than existing schemes. We implement SOS in both NS-2 and a real BitTorrent client and demonstrate the effectiveness of our solution via both simulations and Internet experiments.

WiFi-based wireless LANs (WLANs) are widely used for Internet access. They were designed such that an Access Points (AP) serves few associated clients with symmetric uplink/downlink traffic patterns. Usage of WiFi hotspots in locations such as airports and large conventions frequently experience poor performance in terms of downlink goodput and responsiveness. We study the various factors responsible for this performance degradation. We analyse and emulate a large conference network environment on our testbed with 45 nodes. We find that presence of asymmetry between the uplink/downlink traffic results in backlogged packets at WiFi Access Point's (AP's) transmission queue and subsequent packet losses. This traffic asymmetry results in maximum performance loss for such an environment along with degradation due to rate diversity, fairness and TCP behaviour. We propose our solution WiFox, which (1) adaptively prioritizes AP's channel access over competing STAs avoiding traffic asymmetry (2) provides a fairness framework alleviating the problem of performance loss due to rate-diversity/fairness and (3) avoids degradation due to TCP behaviour. We demonstrate that WiFox not only improves downlink goodput by 400-700 % but also reduces request's average response time by 30-40 %.

The problem of overbuffering in the current Internet (termed as bufferbloat) has drawn the attention of the research community in recent years. Cellular networks keep large buffers at base stations to smooth out the bursty data traffic over the time-varying channels and are hence apt to bufferbloat. However, despite their growing importance due to the boom of smart phones, we still lack a comprehensive study of bufferbloat in cellular networks and its impact on TCP performance. In this paper, we conducted extensive measurement of the 3G/4G networks of the four major U.S. carriers and the largest carrier in Korea. We revealed the severity of bufferbloat in current cellular networks and discovered some ad-hoc tricks adopted by smart phone vendors to mitigate its impact. Our experiments show that, due to their static nature, these ad-hoc solutions may result in performance degradation under various scenarios. Hence, a dynamic scheme which requires only receiver-side modification and can be easily deployed via over-the-air (OTA) updates is proposed. According to our extensive real-world tests, our proposal may reduce the latency experienced by TCP flows by 25% ~ 49% and increase TCP throughput by up to 51% in certain scenarios.

In the literature, one of the key assumptions in characterizing the scaling laws for wireless mobile networks, is to assume that nodes do not communicate while being mobile. In other words, contact opportunities are not considered during the mobility process itself. However, we find that this assumption leads to an inflated estimate of the delay, even in an order sense. To address this issue, a new framework that allows nodes to communicate while being mobile is proposed in this paper. Under this framework, it is shown that delays to obtain various levels of throughput for i.i.d. mobility model are overestimated and a new tighter delay-capacity tradeoff is suggested. Also, the framework is used to analytically derive the delay-capacity tradeoff of Lévy flight model for various levels of throughput, where Lévy flight is a random walk of a power-law flight distribution with an exponent α ∈ (0, 2]. It is known as a mobility model which closely captures human movement patterns. The tradeoffs from the proposed framework between the delay (D̅) and per-node throughput (λ) indicate that D̅ = O(√(max(1,nλ3))) holds for i.i.d. mobility and D̅ = O(√(min(n1+αλ,n2))) holds for Lévy flight.

There is a lack of method to communicate wirelessly without underlying networking infrastructure. We adopt the concept of camera-LCD communication and proposed this VisualComm system, a channel to communicate wirelessly through transmission and reception of a QR-code stream. VisualComm implements a series of techniques to overcome big challenges of frame missing, perspective distortion and viewing angle issue. In this demo, we show our VisualComm system can achieve real-time wireless file transfer with a reasonable bandwidth (of hundreds of Kbps) and good robustness.

Many empirical studies of human walks have reported that there exist fundamental statistical features commonly appearing in mobility traces taken in various mobility settings. These include: 1) heavy-tail flight and pause-time distributions; 2) heterogeneously bounded mobility areas of individuals; and 3) truncated power-law intercontact times. This paper reports two additional such features: a) The destinations of people (or we say waypoints) are dispersed in a self-similar manner; and b) people are more likely to choose a destination closer to its current waypoint. These features are known to be influential to the performance of human-assisted mobility networks. The main contribution of this paper is to present a mobility model called Self-similar Least-Action Walk (SLAW) that can produce synthetic mobility traces containing all the five statistical features in various mobility settings including user-created virtual ones for which no empirical information is available. Creating synthetic traces for virtual environments is important for the performance evaluation of mobile networks as network designers test their networks in many diverse network settings. A performance study of mobile routing protocols on top of synthetic traces created by SLAW shows that SLAW brings out the unique performance features of various routing protocols.

This paper analytically derives the delay-capacity tradeoffs for Lévy mobility: Lévy walks and Lévy flights. Lévy mobility is a random walk with a power-law flight distribution. α is the power-law slope of the distribution and 01/2) and for 1 ≤ α ≤ 2, is Θ(nα/2). In contrast, Lévy flight has critical delay Θ(nα/2) for 0 <; α ≤ 2.

A practical protocol jointly considering PHY and MAC for MIMO based concurrent transmissions in wireless ad hoc networks, called Contrabass, is presented. Concurrent transmissions refer to simultaneous transmissions by multiple nodes over the same carrier frequency within the same interference range. Contrabass is the first-to-date open-loop based concurrent transmission protocol which implements simultaneous channel training for concurrently transmitting links without any control message exchange. Its MAC protocol is designed for each active transmitter to independently decide to transmit with near optimal transmission probability. Contrabass maximizes the number of successful concurrent transmissions, thus achieving very high aggregate throughput, low delays and scalability even under dynamic environments. The design choices of Contrabass are deliberately made to enable practical implementation which is demonstrated through GNURadio implementation and experimentation.

We report that human walk patterns contain statistically similar features observed in Levy walks. These features include heavy-tail flight and pause-time distributions and the super-diffusive nature of mobility. Human walks are not random walks, but it is surprising that the patterns of human walks and Levy walks contain some statistical similarity. Our study is based on 226 daily GPS traces collected from 101 volunteers in five different outdoor sites. The heavy-tail flight distribution of human mobility induces the super-diffusivity of travel, but up to 30 min to 1 h due to the boundary effect of people's daily movement, which is caused by the tendency of people to move within a predefined (also confined) area of daily activities. These tendencies are not captured in common mobility models such as random way point (RWP). To evaluate the impact of these tendencies on the performance of mobile networks, we construct a simple truncated Levy walk mobility (TLW) model that emulates the statistical features observed in our analysis and under which we measure the performance of routing protocols in delay-tolerant networks (DTNs) and mobile ad hoc networks (MANETs). The results indicate the following. Higher diffusivity induces shorter intercontact times in DTN and shorter path durations with higher success probability in MANET. The diffusivity of TLW is in between those of RWP and Brownian motion (BM). Therefore, the routing performance under RWP as commonly used in mobile network studies and tends to be overestimated for DTNs and underestimated for MANETs compared to the performance under TLW.

This paper presents a quantitative study on the performance of 3G mobile data offloading through WiFi networks. We recruited about 100 iPhone users from metropolitan areas and collected statistics on their WiFi connectivity during about a two and half week period in February 2010. Our trace-driven simulation using the acquired traces indicates that WiFi already offloads about 65% of the total mobile data traffic and saves 55% of battery power without using any delayed transmission. If data transfers can be delayed with some deadline until users enter a WiFi zone, substantial gains can be achieved only when the deadline is fairly larger than tens of minutes. With 100 second delays, the achievable gain is less than only 2--3%. But with 1 hour or longer deadline, traffic and energy saving gains increase beyond 29% and 20%, respectively. These results are in stark contrast to the substantial gain (20 to 33%) reported by the existing work even for 100 second delayed transmission using traces taken from transit buses or war-driving. The major performance difference comes from traces: while bus and war-driving traces contain much shorter connection and inter-connection times, our traces reflects the daily mobility patterns of average users more accurately.

This paper identifies the possibility of using electronic compasses and accelerometers in mobile phones, as a simple and scalable method of localization without war-driving. The idea is not fundamentally different from ship or air navigation systems, known for centuries. Nonetheless, directly applying the idea to human-scale environments is non-trivial. Noisy phone sensors and complicated human movements present practical research challenges. We cope with these challenges by recording a person's walking patterns, and matching it against possible path signatures generated from a local electronic map. Electronic maps enable greater coverage, while eliminating the reliance on WiFi infrastructure and expensive war-driving. Measurements on Nokia phones and evaluation with real users confirm the anticipated benefits. Results show a location accuracy of less than 11m in regions where today's localization services are unsatisfactory or unavailable.

This is by far the first paper considering joint optimization of link scheduling, routing and replication for disruption-tolerant networks (DTNs). The optimization problems for resource allocation in DTNs are typically solved using dynamic programming which requires knowledge of future events such as meeting schedules and durations. This paper defines a new notion of optimality for DTNs, called snapshot optimality where nodes are not clairvoyant, i.e., cannot look ahead into future events, and thus decisions are made using only contemporarily available knowledge. Unfortunately, the optimal solution for snapshot optimality still requires solving an NP-hard problem of maximum weight independent set and a global knowledge of who currently owns a copy and what their delivery probabilities are. This paper presents a new efficient approximation algorithm, called Distributed Max-Contribution (DMC) that performs greedy scheduling, routing and replication based only on locally and contemporarily available information. Through a simulation study based on real GPS traces tracking over 4000 taxies for about 30 days in a large city, DMC outperforms existing heuristically engineered resource allocation algorithms for DTNs.

The movement of people is by-products of spatial and temporal correlations. People go to a place at a certain time with a purpose and they meet because they are in the same place at the same time. Extracting and representing the statistical features of spatio-temporal correlations inherent in human mobility is the goal of this paper. Most of the existing human mobility models focus on representing only the spatial features of human mobility (e.g., where and how they visit) and devote less attention to representing the temporal features (when they visit). This paper shows through GPS experiments simultaneously tracking the movement of about 200 students in two university campuses that many existing models cannot capture the temporal features and their correlations with the spatial features, and proposes a new mobility model called spatio-temporal mobility model (STEP) that aims to remedy this deficiency. The paper reports a work-in-progress for evaluating the performance of STEP and the other mobility models in representing inherent spatio-temporal features of human mobility such as the inter-contact times and diffusion speeds which are captured in the GPS experiments.

This is a quantitative study on the performance of 3G mobile data offloading through WiFi networks. We recruited about 100 iPhone users from a metropolitan area and collected statistics on their WiFi connectivity during about a two and half week period in February 2010. We find that a user is in WiFi coverage for 70% of the time on average and the distributions of WiFi connection and disconnection times have a strong heavy-tail tendency with means around 2 hours and 40 minutes, respectively. Using the acquired traces, we run trace-driven simulation to measure offloading efficiency under diverse conditions e.g. traffic types, deadlines and WiFi deployment scenarios. The results indicate that if users can tolerate a two hour delay in data transfer (e.g, video and image up-loads), the network can offload 70% of the total 3G data traffic on average. We also develop a theoretical framework that permits an analytical study of the average performance of offloading. This tool is useful for network providers to obtain a rough estimate on the average performance of offloading for a given inputWiFi deployment condition.

Simulating human mobility is important in mobile networks because many mobile devices are either attached to or controlled by humans and it is very hard to deploy real mobile networks whose size is controllably scalable for performance evaluation. Lately various measurement studies of human walk traces have discovered several significant statistical patterns of human mobility. Namely these include truncated power-law distributions of flights, pause-times and inter-contact times, fractal way-points, and heterogeneously defined areas of individual mobility. Unfortunately, none of existing mobility models effectively captures all of these features. This paper presents a new mobility model called SLAW (self-similar least action walk) that can produce synthetic walk traces containing all these features. This is by far the first such model. Our performance study using using SLAW generated traces indicates that SLAW is effective in representing social contexts present among people sharing common interests or those in a single community such as university campus, companies and theme parks. The social contexts are typically common gathering places where most people visit during their daily lives such as student unions, dormitory, street malls and restaurants. SLAW expresses the mobility patterns involving these contexts by fractal way points and heavy-tail flights on top of the way points. We verify through simulation that SLAW brings out the unique performance features of various mobile network routing protocols.

Congestion control in wireless multi-hop networks is challenging and complicated because of two reasons. First, interference is ubiquitous and causes loss in the shared medium. Second, wireless multihop networks are characterized by the use of diverse and dynamically changing routing paths. Traditional end point based congestion control protocols are ineffective in such a setting resulting in unfairness and starvation. This paper adapts the optimal theoretical work of Tassiulas and Ephremedes on cross-layer optimization of wireless networks involving congestion control, routing and scheduling, for practical solutions to congestion control in multi-hop wireless networks. This work is the first that implements in real off-shelf radios, a differential backlog based MAC scheduling and router-assisted backpressure congestion control for multi-hop wireless networks. Our adaptation, called DiffQ, is implemented between transport and IP and supports legacy TCP and UDP applications. In a network of 46 IEEE 802.11 wireless nodes, we demonstrate that DiffQ far outperforms many previously proposed "practical" solutions for congestion control.

In P2P file sharing systems, free-riders who use others' resources without sharing their own cause system-wide performance degradation. Existing techniques to counter free-riders are either complex (and thus not widely deployed), or easy to bypass (and therefore not effective). This paper proposes a simple yet highly effective free-rider prevention scheme using (t, n) threshold secret sharing. A peer must upload encrypted file pieces to obtain the subkeys necessary to decrypt a file which has been downloaded, i.e., subkeys are swapped for file pieces. No centralized monitoring or control is required. This scheme is called “treat-before-trick” (TBeT). TBeT penalizes free-riding with increased file completion times (time to download file and necessary subkeys). TBeT counters known free-riding strategies, incentivizes peers to donate more upload bandwidth, and increases the overall system capacity for compliant peers. TBeT has been implemented as an extension to BitTorrent, and results of experimental evaluation are presented.

This paper presents a distributed implementation of RAND, a randomized time slot scheduling algorithm, called DRAND. DRAND runs in O(\delta ) time and message complexity where \delta is the maximum size of a two-hop neighborhood in a wireless network while message complexity remains O(\delta ), assuming that message delays can be bounded by an unknown constant. DRAND is the first fully distributed version of RAND. The algorithm is suitable for a wireless network where most nodes do not move, such as wireless mesh networks and wireless sensor networks. We implement the algorithm in TinyOS and demonstrate its performance in a real testbed of Mica2 nodes. The algorithm does not require any time synchronization and is shown to be effective in adapting to local topology changes without incurring global overhead in the scheduling. Because of these features, it can also be used even for other scheduling problems such as frequency or code scheduling (for FDMA or CDMA) or local identifier assignment for wireless networks where time synchronization is not enforced. We further evaluate the effect of the time-varying nature of wireless links on the conflict-free property of DRAND-assigned time slots. This experiment is conducted on a 55-node testbed consisting of the more recent MicaZ sensor nodes.

Multicast is an efficient means of transmitting the same content to multiple receivers while minimizing network resource usage. Applications that can benefit from multicast such as multimedia streaming and download, are now being deployed over 3G wireless data networks. Existing multicast schemes transmit data at a fixed rate that can accommodate the farthest located users in a cell. However, users belonging to the same multicast group can have widely different channel conditions. Thus existing schemes are too conservative by limiting the throughput of users close to the base station. We propose two proportional fair multicast scheduling algorithms that can adapt to dynamic channel states in cellular data networks that use time division multiplexing: inter-group proportional fairness (IPF) and multicast proportional fairness (MPF). These scheduling algorithms take into account (1) reported data rate requests from users which dynamically change to match their link states to the base station, and (2) the average received throughput of each user inside its cell. This information is used by the base station to select an appropriate data rate for each group. We prove that IPF and MPF achieve proportional fairness among groups and among all users inside a cell respectively. Through extensive packet-level simulations, we demonstrate that these algorithms achieve good balance between throughput and fairness among users and groups.

Existing wireless MACs are known to have fairness and QoS problems1. In response, the wireless community have come up with numerous ldquopoint solutionsrdquo, with one-to-one comparison of their solution with existing MACs for the specific fairness model they target. However, with some tradeoff of flexibility and efficiency, many of these MACs can be made relatively free of a a specific fairness model. This decoupling of the MAC from the fairness model is desirable because it allows objective testing of the MAC under different fairness models and also allows independent evolution of fairness policies and research into medium access issues. However, there is no cross-model evaluation of such MACs especially in the context of real multihop wireless testbeds. In this paper we address this issue by testing three MACs - 802.11e, EY-NPMA and DWOP, (which represent different ways of enabling fairness in the MAC) across a number of fairness and QoS models - temporal/rate and proportional fairness, and EDF and static priority scheduling. In the process we also extend EY-NPMA significantly (which we call Siren) for multihop wireless environments. We perform these comparisons on a 30 node multihop wireless sensor testbed comprising of MicaZ devices equipped with the CC2420 radio.

We report that human walks performed in outdoor settings of tens of kilometers resemble a truncated form of Levy walks commonly observed in animals such as monkeys, birds and jackals. Our study is based on about one thousand hours of GPS traces involving 44 volunteers in various outdoor settings including two different college campuses, a metropolitan area, a theme park and a state fair. This paper shows that many statistical features of human walks follow truncated power-law, showing evidence of scale-freedom and do not conform to the central limit theorem. These traits are similar to those of Levy walks. It is conjectured that the truncation, which makes the mobility deviate from pure Levy walks, comes from geographical constraints including walk boundary, physical obstructions and traffic. None of commonly used mobility models for mobile networks captures these properties. Based on these findings, we construct a simple Levy walk mobility model which is versatile enough in emulating diverse statistical patterns of human walks observed in our traces. The model is also used to recreate similar power-law inter-contact time distributions observed in previous human mobility studies. Our network simulation indicates that the Levy walk features are important in characterizing the performance of mobile network routing performance.

In this paper, we introduce a search engine, Dgoogle, designed for large scale P2P systems. Dgoogle is purely text- based, does not organize documents based on pre-defined keywords or based on their semantics. It is simple to implement and can tolerate variations in the wording of text queries. Compared to existing proposals, such as Inverted Indices, Dgoogle does not stress network bandwidth and offers an order of magnitude of savings in storage overhead and in the response time to user queries. Furthermore, Dgoogle's performance is not affected by long queries or by processing popular query words. Simulation results validate the efficacy of our proposal.

In this demo, we showcase DiffQ - a congestion control protocol inspired by theoretical cross-layer optimization approaches. DiffQ can support congestion control for network flows that use either single-path or opportunistic multi-path routing. Our demo will focus on the performance in single-path routing environments, where contemporary end-point congestion control algorithms like TCP face severe unfairness or even starvation. This is primarily due to the interaction of such protocols with MAC layer unfairness. We demonstrate micro (5 flows) as well as macro-evaluations (60 flows) of such cases. Our demo is conducted on WiSeNet - a 70-node wireless mesh test-bed hosted in the computer science building at NCSU. Distributed over a 100,000 sq ft building, this is one of the largest test-bed installations both in terms of number of nodes and coverage area, hence an ideal testing ground for such scenarios. Experimental results like throughput, MAC-layer statistics, delay, routing path flaps and network buffer overflows are recorded and displayed in real-time and enable a bird's eye-view of the entire network status and allow us to point out various phenomenon as they happen.

Limited resources and time-varying nature of wireless ad hoc networks demand optimized use of resources across layers. Cross-layer optimization (CLO) for wireless networks, an approach that coordinates protocol behaviors at different layers with a goal to maximize a utility function, has received considerable attention lately. However, most existing work remains as theory and no practical CLO based on utility optimization exists today. The main difficulties in implementing theoretical CLO designs arise often from impractical assumptions about the characteristics of the wireless medium and also from computational and communication overhead of proposed solutions to achieve or approximate the optimality. In contrast, many existing practical approaches for CLO (not necessarily utility optimization) are rather ad hoc in nature and developed mostly based on intuitions. Thus, a clear gap between theory and practice in CLO exists. This paper addresses this dichotomy to close the gap by taking an optimal solution from utility-based CLO and applying practical approximation to enable a practical implementation in a wireless mesh network where nodes are statically positioned in an ad hoc fashion. We focus on the utility of maximizing throughput. We identify the impractical or computationally-intensive components of a theoretically-derived optimal throughput-maximizing solution and then propose, in most cases, practical approximation with O(1) complexity for MAC, scheduling, routing and congestion control. The result is a practical CLO solution that approximates the theoretically-derived optimal solution, but achieves much improved performance over existing practical CLO implementations.

Window growth function for congestion control is a strong determinant of protocol behaviors, especially its second and higher-order behaviors associated with the distribution of transmission rates, its variances, and protocol stability. This paper presents a new stochastic tool, called convex ordering, that provides an ordering of any convex function of transmission rates of two protocols and valuable insights into high order behaviors of protocols. As the ordering determined by this tool is consistent with any convex function of rates, it can be applied to any unknown metric for protocol performance that consists of some high-order moments of transmission rates, as well as those already known such as rate variance. Using the tool, it is analyzed that a protocol with a growth function that starts off with a concave function and then switches to a convex function (e.g., an odd order function such as x3and x5) around the maximum window size in the previous loss epoch, gives the smallest rate variation under a variety of network conditions. Among existing protocols, BIC and CUBIC have this window growth function. Experimental and simulation results confirm the analytical findings.

Multicast is an efficient means of transmitting the same content to multiple receivers while minimizing network resource usage. Applications that can benefit from multicast such as multimedia streaming and download, are now being deployed over 3G wireless data networks. Existing multicast schemes transmit data at a fixed rate that can accommodate the farthest located users in a cell. However, users belonging to the same multicast group can have widely different channel conditions. Thus existing schemes are too conservative by limiting the throughput of users close to the base station. We propose two proportional fair multicast scheduling algorithms that can adapt to dynamic channel states in cellular data networks that use time division multiplexing: Inter-group Proportional Fairness (IPF) and multicast proportional fairness (MPF). These scheduling algorithms take into account (1) reported data rate requests from users which dynamically change to match their link states to the base station, and (2) the average received throughput of each user inside its cell. This information is used by the base station to select an appropriate data rate for each group. We prove that IPF and MPF achieve proportional fairness among groups and among all users in a group inside a cell respectively. Through extensive packet-level simulations, we demonstrate that these algorithms achieve good balance between throughput and fairness among users and groups.

This work was supported by the Ministry of Information and Communication, Korea, under the grant for BrOMA-ITRC program supervised by IITA.

This paper presents a distributed implementation of RAND, a randomized time slot scheduling algorithm, called DRAND. DRAND runs in O(δ) time and message complexity where δ is the maximum size of a two-hop neighborhood in a wire-less network while message complexity remains O(δ), assuming that message delays can be bounded by an unknown constant.DRAND is the first fully distributed version of RAND. The algorithm is suitable for a wireless network where most nodes do not move,such as wireless mesh networks and wireless sensor networks.We implement the algorithm in TinyOS and demonstrate its performance in a real testbed of Mica2 nodes. The algorithm does not require any time synchronization and is shown to be effective in adapting to local topology changes without incurring global overhead in the scheduling.Because of these features, it can also be used even for other scheduling problems such as frequency or code scheduling (for FDMA or CDMA) or local identifier assignment for wireless networks where time synchronization is not enforced.

Session initiation protocol (SIP) provides call establishment functions for VoIP. These functions are highly CPU-intensive and hence need to be distributed over multiple servers in order to support the peak workload. Existing approaches to this problem are unfortunately not scalable or fault-tolerant, incurring high maintenance overheads or introducing a single point of failure. This paper presents a proof-of-concept design and analysis of a scalable, robust architecture for SIP infrastructures using a content addressable network (CAN) model, called CASIP (CAN-based SIP). The performance study of CASIP using real implementation of a SIP stack and NS-2 shows that the proposed system distributes the SIP processing (both update and lookup) load over multiple nodes very effectively without incurring much routing and maintenance overhead.

This paper presents the design, implementation and performance evaluation of a hybrid MAC protocol, called Z-MAC, for wireless sensor networks that combines the strengths of TDMA and CSMA while offsetting their weaknesses. Like CSMA, Z-MAC achieves high channel utilization and low-latency under low contention and like TDMA, achieves high channel utilization under high contention and reduces collision among two-hop neighbors at a low cost. A distinctive feature of Z-MAC is that its performance is robust to synchronization errors, slot assignment failures and time-varying channel conditions; in the worst case, its performance always falls back to that of CSMA. Z-MAC is implemented in TinyOS.

We study limitations of an equation-based congestion control protocol, called TFRC (TCP Friendly Rate Control). It examines how the three main factors that determine TFRC throughput, namely, the TCP friendly equation, loss event rate estimation and delay estimation, can influence the long-term throughput imbalance between TFRC and TCP. Especially, we show that different sending rates of competing flows cause these flows to experience different loss event rates. There are several fundamental reasons why TFRC and TCP flows have different average sending rates, from the first place. Earlier work shows that the convexity of the TCP friendly equation used in TFRC causes the sending rate difference. We report two additional reasons in this paper: (1) the convexity of 1/x where x is a loss event period and (2) different RTO (retransmission timeout period) estimations of TCP and TFRC. These factors can be the reasons for TCP and TFRC to experience initially different sending rates. But we find that the loss event rate difference due to the differing sending rates greatly amplifies the initial throughput difference; in some extreme cases, TFRC uses around 20 times more, or sometimes 10 times less, bandwidth than TCP.

High-speed networks with large delays present a unique environment where TCP may have a problem utilizing the full bandwidth. Several congestion control proposals have been suggested to remedy this problem. The existing protocols consider mainly two properties: TCP friendliness and bandwidth scalability. That is, a protocol should not take away too much bandwidth from standard TCP flows while utilizing the full bandwidth of high-speed networks. This work presents another important constraint, namely, RTT (round trip time) unfairness where competing flows with different RTTs may consume vastly unfair bandwidth shares. Existing schemes have a severe RTT unfairness problem because the congestion window increase rate gets larger as the window grows ironically the very reason that makes them more scalable. RTT unfairness for high-speed networks occurs distinctly with drop tail routers for flows with large congestion windows where packet loss can be highly synchronized. After identifying the RTT unfairness problem of existing protocols, This work presents a new congestion control scheme that alleviates RTT unfairness while supporting TCP friendliness and bandwidth scalability. The proposed congestion control algorithm uses two window size control policies called additive increase and binary search increase. When the congestion window is large, additive increase with a large increment ensures square RTT unfairness as well as good scalability. Under small congestion windows, binary search increase supports TCP friendliness. The simulation results confirm these properties of the protocol.

The session problem is an abstraction of fundamental synchronization problems in distributed systems. It has previously been used as a test case to demonstrate the differences in the time needed to solve problems in several timing models. The goal of this paper is to compare the computational power of a family of partially synchronous models by studying the time needed to solve the session problem. Four timing parameters are considered: the maximum and minimum process step times and message delays. Timing models are obtained by considering independently whether each parameter is known (i.e., is hard-wired into the processes' code) or unknown, giving rise to four shared memory models and 16 message passing models. The models are compared based on the time complexity, measured in real time, of the session problem. This paper presents a modular proof technique for obtaining asymptotically tight bounds on the time complexity of the session problem for the four shared memory models and the 16 message passing models. Timing information known in each particular model can be exploited by algorithms to count sessions in different ways. This paper reports five different counting algorithms. The matching lower bound for each model suggests that they are the optimal ways to count sessions. Based on these bounds, a lattice among unknown parameter models is constructed, which confirms the common belief that as more timing information is known in a model, the model behaves more like a synchronous system.

The set of TCP congestion control algorithms associated with TCP-Reno (e.g., slow-start and congestion avoidance) have been crucial to ensuring the stability of the Internet. Algorithms such as TCP-NewReno (which has been deployed) and TCP-Vegas (which has not been deployed) represent incrementally deployable enhancements to TCP as they have been shown to improve a TCP connection's throughput without degrading performance to competing flows. Our research focuses on delay-based congestion avoidance algorithms (DCA), like TCP-Vegas, which attempt to utilize the congestion information contained in packet round-trip time (RTT) samples. Through measurement and simulation, we show evidence suggesting that a single deployment of DCA (i.e., a TCP connection enhanced with a DCA algorithm) is not a viable enhancement to TCP over high-speed paths. We define several performance metrics that quantify the level of correlation between packet loss and RTT. Based on our measurement analysis, we find that, although there is useful congestion information contained within RTT samples, the level of correlation between an increase in RTT and packet loss is not strong enough to allow a TCP-sender to improve throughput reliably. While DCA is able to reduce the packet loss rate experienced by a connection, in its attempts to avoid packet loss, the algorithm reacts unnecessarily to RTT variation that is not associated with packet loss. The result is degraded throughput as compared to a similar flow that does not support DCA.

This paper presents a closed-loop (demand-driven) approach towards VoD services, called multicast with caching (Mcache). Servers use multicast to reduce bandwidth usage by serving multiple requests using a single data stream. However, this requires clients to delay receiving the movie until the multicast starts. Using regional cache servers, Mcache removes initial playout delays at the clients, because the clients can receive the prefix of a requested clip from regional caches while waiting for the multicast to start. In addition, the multicast containing the later portion of the movie can wait until the prefix is played out. While this use of caches has been proposed before, the novelty of our scheme lies in that the requests coming after the multicast starts can still be batched together to be served by multicast patches without any playout delays. The use of patches has been proposed to be used either with unicast or with playout delays. Mcache effectively hires the idea of a multicast patch with caches to provide a truly adaptive VoD service whose bandwidth usage is up to par with the best known open-loop schemes under high request rates while using only minimal bandwidth under low request rates. In addition, efficient use of multicast and caches removes the need for a priori knowledge of client request rates and client disk storage requirements which some of the existing schemes assume. This makes Mcache ideal for the current heterogeneous Internet environments where those parameters are hard to predict.

A closed-loop (demand-driven) approach toward video-on-demand services, called multicast cache (Mcache), is discussed. Servers use multicast to reduce their bandwidth usage by allowing multiple requests to be served with a single data stream. However, this requires clients to delay receiving the movie until the multicast starts. Using regional cache servers deployed over many strategic locations, Mcache can remove the initial playout delays of clients in multicast-based video streaming. While requests are batched together for a multicast, clients can receive the prefix of a requested movie clip from caches located in their own regions. The multicast containing the later portion of the movie can wait until the prefix is played out. While this use of regional caches has been proposed previously, the novelty of our scheme lies in that the requests coming after the multicast starts can still be batched together to be served by multicast patches without any playout delays. The use of patches was proposed before, but they are used either with unicast or with playout delays. Mcache effectively hires the idea of a multicast patch with caches to provide a truly adaptive video-on demand service whose bandwidth usage is up to par with the best known open-loop schemes under high request rates while using only minimal bandwidth under low request rates. In addition, efficient use of multicast and caches removes the need for a priori knowledge of client disk storage requirements which some of the existing schemes assume. This makes Mcache ideal for the current heterogeneous Internet environments where those parameters are hard to predict. We further propose the Segmented Mcache (SMcache) scheme which is a generalized and improved version of Mcache where the clip is partitioned into several segments in order to preserve the advantages of the original Mcache scheme with nearly the same server bandwidth requirement as the open loop schemes under high request rates.

Many scalable reliable multicast protocols use the local repair scheme where certain receivers retransmit packets by other receivers. Such schemes need a mechanism, called message stability, to ensure reliable delivery to all members of a multicast group and to delete those packets received by all members from the buffers of the local repairers. We propose a new protocol for message stability based on random gossiping. The protocol offers scalabilty and fault-tolerance by limiting each of its message transmissions only to a constant number of randomly chosen group members, hence eliminating message implosion and single point failure through the diffusion of responsibility. Both statistical analysis and simulation study indicate that our gossip-style message stability protocol can be highly effective for large-scale reliable multicast.

The round trip network delay times between pairs of nodes in a multicast session is a key parameter; it is used in suppressing the implosion of request and repair packets, in detecting congestion, etc. This paper presents a protocol to estimate the delays between every pair of nodes in a multicast group. While existing protocols use O(n) multicast messages with O(n) size each (total of O(n/sup 2/) bits), our protocol requires O(n) multicasts with only O(1) size each (total of O(n) bits); here, n is the session size. It does not require clocks to be synchronized, or any knowledge of network topology and the session size. We incorporate our protocol into the SRM (scalable reliable multicast) protocol (Rhee et al., 1999) and show by our simulations that, (i) our delay estimation protocol is reasonably accurate, (ii) it is just as effective as existing delay estimation protocols in suppressing repair and request traffic in SRM, and (iii) it has significantly lower overhead than the existing delay estimation protocols. Furthermore, our protocol can be extended to run within a hierarchically structured multicast protocol such as RMTP (reliable multicast transport protocol) (Paul et al., 1996). Here the goal is to estimate round trip delays from a sender to each receiver. Our protocol ensures that only the immediate children of the sender send feedback messages directly to the sender, thereby avoiding feedback implosion. Our delay estimation protocols therefore significantly enhance the scalability of unstructured multicast protocols such as SRM, as well as tree-structured multicast protocols such as RMTP.

We study the problem of localizing repair packets when packets are lost during multicasts. When repair packets are multicast, a highly lossy receiver may swamp the entire multicast "group" with duplicate repair packets thereby wasting bandwidth; thus, the protocols need repair locality. We present a multicast layering scheme where the sender proactively distributes FEC repair packets among multiple multicast groups. Each receiver can selectively tune in to a subset of these multicast groups to obtain packets close in number to what it needs. We develop an efficient algorithm that dynamically determines the optimal distribution of FEC repair packets to a given (small constant) number of multicast groups. The running time of this algorithm is independent of the number of receivers in the multicast session, and is hence highly scalable. However, the optimal algorithm requires the knowledge of the FEC repair requirements of all the receivers in the multicast group, and hence is subject to the implosion problem. To handle the implosion problem, we develop an heuristic algorithm that achieves repair locality very similar to that of the optimal algorithm, but does not require as much global knowledge. Our multicast layering scheme can be integrated into known reliable multicast protocols to make them more scalable. For concreteness, we focus on: (i) singly scoped SRM, (ii) hierarchically scoped SRM, and (iii) a tree-based reliable multicasting protocol RMTP, and present combined protocols incorporating our solutions into each of them. Simulation experiments show that our solutions can substantially enhance the scalability of these reliable multicast protocols.

The current Internet is not reliable; packet loss rates are frequently high, and varying over time. Transmitting high-quality interactive video over the Internet is challenging because the quality of compressed video is very susceptible to packet losses. Loss of packets belonging to a video frame manifests itself not only in the reduced quality of that frame but also in the propagation of that distortion to successive frames. This error propagation problem is inherent in many motion-based video codecs due to the interdependence of encoded video frames. This paper presents a dynamic loss recovery scheme, called RESCU, to address the error propagation problem. In this new scheme, picture coding patterns are dynamically adapted to current network conditions in order to maximize the effectiveness of hybrid transport level recovery (employing both forward error correction and retransmission) in reducing error propagation. Since RESCU does not introduce any playout delay at the receiver, it is suitable for interactive video communication. An experimental study based on actual Internet transmission traces representing various network conditions shows that dynamic hybrid RESCU exhibits better error resilience and incurs much less bit overhead than existing error recovery techniques such as NEWPRED and Intra-H.261.

Our research focuses on end-to-end congestion avoidance algorithms that use round trip time (RTT) fluctuations as an indicator of the level of network congestion. The algorithms are referred to as delay-based congestion avoidance or DCA. Due to the economics associated with deploying change within an existing network, we are interested in an incrementally deployable enhancement to the TCP/Reno protocol. For instance, TCP/Vegas, a DCA algorithm, has been proposed as an incremental enhancement. Requiring relatively minor modifications to a TCP sender, TCP/Vegas has been shown to increase end-to-end TCP throughput primarily by avoiding packet loss. We study DCA in today's best effort Internet where IP switches are subject to thousands of TCP flows resulting in congestion with time scales that span orders of magnitude. Our results suggest that RTT-based congestion avoidance may not be reliably incrementally deployed in this environment. Through extensive measurement and simulation, we find that when TCP/DCA (i.e., a TCP/Reno sender that is extended with DCA) is deployed over a high speed Internet path, the flow generally experiences degraded throughput compared to an unmodified TCP/Reno flow. We show (1) that the congestion information contained in RTT samples is not sufficient to predict packet loss reliably and (2) that the congestion avoidance in response to delay increase has minimal impact on the congestion level over the path when the total DCA traffic at the bottleneck consumes less than 10% of the bottleneck bandwidth.

Real-time interactive video transmission in the current Internet has mediocre quality because of high packet loss rates. Loss of packets in a video frame manifests itself not only in the reduced quality of that frame but also in the propagation of that distortion to successive frames. This error propagation problem is inherent in any motion compensation-based video codec. In this paper, we present a new error recovery scheme, called recovery from error spread using continuous updates (RESCU), that effectively alleviates error propagation in the transmission of interactive video. The main benefit of the RESCU scheme is that it allows more time for transport-level recovery such as retransmission and forward error correction to succeed while effectively masking out delays in recovering lost packets without introducing any playout delays, thus making it suitable for interactive video communication. Through simulation and real Internet experiments, we study the effectiveness and limitations of our proposed techniques and compare their performance to that of existing video error recovery techniques including H.263+ (NEWPRED). The study indicates that RESCU is effective in alleviating the error spread problem and can sustain much better video quality with less bit overhead than existing video error recovery techniques under various network environments.

This paper reports two efficient quadtree-based algorithms for variable-size block matching (VSBM) motion estimation. The schemes allow the dimensions of blocks to adapt to local activity within the image, and the total number of blocks in any frame can be varied while still accurately representing true motion. This permits adaptive bit allocation between the representation of displacement and residual data, and also the variation of the overall bit-rate on a frame-by-frame basis. The first algorithm computes the optimal selection of variable-sized blocks to provide the best-achievable prediction error under the fixed number of blocks for a quadtree-based VSBM technique. The algorithm employs an efficient dynamic programming technique utilizing the special structure of a quadtree. Although this algorithm is computationally intensive, it does provide a yardstick by which the performance of other more practical VSBM techniques can be measured. The second algorithm adopts a heuristic way to select variable-sized square blocks. It relies more on local motion information than on global error optimization. Experiments suggest that the effective use of local information contributes to minimizing the overall error. The result is a more computationally efficient VSBM technique than the optimal algorithm, but with a comparable prediction error.

We present MTCT, a congestion control scheme for large-scale reliable multicast. Congestion control for reliable multicast is important because of its wide applications in multimedia and collaborative computing, yet nontrivial, because of the potentially large number of receivers involved. Many schemes have been proposed to handle the recovery of lost packets in a scalable manner; but there is little work on the design and implementation of congestion control schemes for reliable multicast. We propose new techniques that can effectively handle instances of congestion occurring simultaneously at various parts of a multicast tree. Our protocol incorporates several novel features: (1) hierarchical congestion status reports that distribute the load of processing feedback from all receivers across the multicast group, (2) the relative time delay (RTD) concept which overcomes the difficulty of estimating round-trip times in tree-based multicast environments, (3) window-based control that prevents the sender from transmitting faster than packets leave the bottleneck link an the multicast path through which the sender's traffic flows, (4) a retransmission window that regulates the flow of repair packets to prevent local recovery from causing congestion, and (5) a selective acknowledgment scheme that prevents independent (i.e., non-congestion-related) packet loss from reducing the sender's transmission rate. We have implemented MTCP both on UDP in SunOS 5.6 and on the simulator ns, and we have conducted extensive Internet experiments and simulation to test the scalability and inter-fairness properties of the protocol. The encouraging results we have obtained support our confidence that TCP-like congestion control for large-scale reliable multicast is within our grasp.

Maestro is a middleware support tool for distributed multimedia and collaborative computing applications. These applications share a common need for managing multiple subgroups while providing possibly different quality-of-service guarantees for each of these groups. Maestro's functionality maps well into these requirements, and can significantly shorten the development time of such applications. In this paper, we report on Maestro, and demonstrate its utility in implementing several multimedia and collaborative computing applications. In particular, we provide a detailed description of the implementation of IMUX, a pseudo X-server (proxy) for collaborative computing applications that is based on Maestro. Copyright © 1999 John Wiley & Sons, Ltd.

Application sharing is an important aspect of collaborative computing. One mechanism for sharing applications is a multiplexor, a tool that broadcasts input/output messages from a single client to multiple displays. We describe the design and implementation of a multiplexor for X windows that supports a heterogeneous environment and works effectively across both local and wide area networks. This X-multiplexor is composed of two distinct components, the Collaborative Computing Frameworks X-Multiplexor (CCFX) which acts as a pseudo server for the client, and the Collaborative Computing Session Manager (CCSM) which renders the client images and supplies the user interface to the system. In effect, CCSM acts as a distributed window manager, ensuring that all participants have the same view of the shared clients. This two headed approach offers significant gains in flexibility and resource usage. CCFX and CCSM can communicate using any reliable transport protocol. This can result in significant reduction of bandwidth, decreased latency, and avoids some TCP/IP communication required by the X protocol. In addition, this architecture facilitates the creation of a virtual X environment. Using this virtual environment, instead of an actual X server's environment, and then translating the virtual properties to a specific server's properties, allows for more robust support of heterogeneous systems.

CCF (Collaborative Computing Frameworks) is a suite of software systems, communications protocols, and tools that enable collaborative, computer-based cooperative work. CCF constructs a virtual work environment on multiple computer systems connected over the Internet, to form a Collaboratory. In this setting, participants interact with each other, simultaneously access and operate computer applications, refer to global data repositories or archives, collectively create and manipulate documents or other artifacts, perform computational transformations, and conduct a number of other activities via telepresence. Research issues addressed in this project include problem solving environments and methodologies for laboratory and instrument-based scientific disciplines, and computer science issues in heterogeneous distributed systems. New approaches are being investigated and developed for fast multiway communication, robust geographically distributed data management methodologies, high-performance computational transforms inlined within collaboration sessions, and related auxiliary issues such as active documents, security, archival storage, and experiment management and control. In this paper, we discuss the design philosophy and systems rationale behind CCF, describe the major subsystems of the collaborative computing environment, and discuss the salient features of the system.

A new retransmission-based error control technique is presented that does not incur any additional latency in frame playout times, and hence are suitable for interactive applications. It takes advantage of the motion prediction loop employed in most motion compensation-based codecs. By correcting errors in a reference frame caused by earlier packet loss, it prevents error propagation. The technique rearranges the temporal dependency of frames so that a displayed frame is referenced for the decoding of its succeeding dependent frames much later than its display time. Thus, the delay in repairing lost packets can be effectively masked out. The developed technique is combined with layered video coding to maintain consistently good video quality even under heavy packet loss. Through the results of extensive Internet experiments, the paper shows that layered coding can be very effective when combined with the retransmission-based error control technique for low-bit rate transmission over best effort networks where no network-level mechanism exists for protecting high priority data from packet loss.

The Collaborative Computing Transport Layer (CCTL) is a communication substrate consisting of a suite of multiparty protocols, providing varying service qualities among process groups. CCTL explicitly supports distributed collaborative and multimedia applications. CCTL is based on a two-level group hierarchy. Logical interconnections among entities, called channels, define an efficient and light-weight group mechanism. Channels support a variety of service qualities such as reliability and message ordering. Related channels can also be combined to form sessions, heavy-weight groups which provide a default atomic multicast service. CCTL supports membership protocols tailored to the quality of service offered by a channel, including a relaxed form of virtual synchrony. In this paper, we present three membership protocols and compare and relate our implementations to alternatives. Our two-level architecture allows simple and efficient implementation of the membership protocols.

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The paper presents a FIFO queue based, scalable spin lock (FSSL) that: (1) uses only one atomic swap operation; (2) is scalable as it requires a constant amount of communication; (3) runs without a coherent cache support; and (4) provides a timing guarantee suitable for real time applications. The algorithm is optimal in the number of atomic operations required to solve the scalable mutual exclusion problem in NUMA architectures, improving on T. Craig's (1993) spin lock that uses four atomic swap operations. The FSSL algorithm minimizes the number of atomic operations by replacing them with non atomic read and write operations, and takes good advantage of recent multiprocessors where non atomic memory operations are much more optimized than atomic operations. The algorithm runs correctly in various weakly consistent memories, providing a potentially significant speedup over algorithms with more atomic operations.

This paper concerns resource allocation in distributed message passing systems, i.e., the scheduling of accesses to system resources shared among many concurrent processes. Three different kinds of resource allocation problems with varying degrees of generality are considered: the dining philosophers problem, the drinking philosophers problem and the dynamic resource allocation problem. We present an efficient modular resource allocation algorithm that uses any arbitrary resource allocation algorithm as a subroutine. It improves the performance of the subroutine by letting each process wait only for its currently conflicting processes, and therefore, allows more concurrency. For appropriate choices of the subroutine, we obtain the fastest known resource allocation algorithms in terms of the worst case response time. Simulation studies were conducted which also indicate that our algorithms perform faster and require a smaller number of messages than other previously known algorithms on average, especially when resource contention among processes is high and the average time that a process remains in the critical region is large.

A distributed protocol is proposed for the synchronization of real-time tasks that have variable resource requirements. The protocol is simple to implement and is intended for large-scale distributed or parallel systems in which processes communicate by message passing. Critical sections, even when nested, may be executed on any processor. Thus, given an adequate number of processors, the execution of critical sections can be completely distributed. More significantly, since the protocol enables the distributed allocation of critical sections, the benefits of various allocations can be analyzed and the system optimized to provide minimal blocking. This has important application in global optimization techniques for allocating large numbers of hard real-time tasks in multiprocessor systems.

No abstract available.

The session problem is an abstraction of synchronization problems in distributed systems. It has been used as a test-case to demonstrate the differences in the time needed to solve problems in various timing models, for both shared memory (SM) systems [2] and message-passing (MP) systems [4]. In this paper, the session problem continues to be used to compare timing models quantitatively. The session problem is studied in two new timing models, the periodic and sporadic. Both SM and MP systems are considered. In the periodic model, each process takes steps at a constant unknown rate; different processes can have different rates. In the sporadic model, there exists a lower bound but no upper bound one step time, and message delay is bounded. We show upper and lower bounds on the time complexity of the session problem for these models. In addition, upper and lower bounds on running time are presented for the semi-synchronous SM model, closing an open problem from [4]. Our results suggest a hierarchy of various timing models in terms of time complexity for the session problem.