Network slicing allows leveraging virtualization techniques for the creation of multiple, logically-isolated network instances over a shared infrastructure. In general, it is composed of a set of unique network functions with a specific physical capacity request. In order to improve network and service robustness, ETSI has introduced the concept of Network Function Set where network functions are replicated and deployed in different physical nodes. In this paper, we integrate this concept of the network function set to implement load-balancing and efficient resource distribution in 5G networks by leveraging on an existing network slice design formulation without the network function set. This helps relieve the burden on the nodes and links and prevent QoS degradation, in particular during failures. We describe how the baseline approach is impacted for the placement of network functions. We then show that our approach improves load balancing and latency with respect to the baseline solution.

In the domain of IoT security management, we consider attack vulnerabilities and how to identify those so as to prevent attacks from spreading. More specifically, inspired by this problem for Smart Home Internet of Things (SHIoT), we take a complex network framework in which an IoT system attack graph can be cast. We then address the problem of assessing the worst vulnerability, that is the one that has the potential to cause maximum damage, in the SHIoT. Due to the non-additive nature of an attack path’s attack probability, we show how the problem can be modeled so that a shortest path-based algorithm approach can be used to determine the worst vulnerability. We then illustrate an approach to iteratively fortify the environment to reduce impact from vulnerability. Finally, we show an approach to use Common Vulnerability Scoring System (CVSS) to determine attack probabilities on arcs in the attack graph and present analysis on representative attack graphs for small to large attack graphs.

Drone-assisted 5G and beyond 5G wireless communication networking capabilities require strong consideration of constrained transmission power, user equipment receiver sensitivity, coverage area, and severe mmWave path loss. We present a Non-terrestrial downlink wireless communication system using a Cyclic Postfixed Windowed Orthogonal Frequency Division Multiplexing (CPW-OFDM) signal format. We demonstrate the impact of combining a Tukey windowing technique with Clipping and Filtering techniques for simultaneous reduction of both Out of Band (OOB) energy and Peak to Average Power Ratio (PAPR). Block Diagonalization (BD) channel precoding provides Multiuser Interference (MUI) reduction, while (3,2) - Single Parity Check (SPC), Repeat and Accumulate (RA) channel coding, and Zero Forcing (ZF) signal detection schemes improve Bit Error Rate (BER). Numerical results confirm that the proposed Non-terrestrial downlink CPW-OFDM system is suitable for multiuser signaling on mmWave frequencies.

While anecdotally it is believed that Wi-Fi signal strength impacts the application performance, there is little work to quantity this connection. In this work, we explored a data-driven approach to model the relationship between Wi-Fi signal strength and the application performance in an indoor wireless environment. We discuss challenges in measurement in a noisy indoor Wi-Fi environment. Our experience and lessons learned are shared for the broader audience. While it was not possible to find definitive empirical models, our study shows that a trend in relationship can still be obtained. We conclude with lessons learned from this work.

In this work, we present the first Cyclic prefix (CP)-less Multiple-Input Multiple-Output (MIMO) OFDM System. It is based on incorporating DFT spreading, signal discrimination with Walsh-Hadamard coding, and PAPR reduction with Tukey (tapered cosine) time-domain windowing techniques. This combination of mechanisms provides an effective combination of benefits related to Bit Error Rate (BER), Peak-to-Average Power Ratio (PAPR), Complementary Cumulative Distribution Function (CCDF) of PAPR, and Out-of-Band (OOB) spectral power. Our simulation study shows that the proposed scheme achieves Out-of-Band (OOB) spectral power attenuation of 142 dB with PAPR of 8.56 dB and BER of 10-4under a scenario of Eb/N0= 15 dB with a 16-QAM modulation.

Dynamic adaptive streaming over HTTP (DASH) is widely used for video streaming on mobile devices. Ensuring a good quality of experience (QoE) for mobile video streaming is essential, as it severely impacts both the network and content providers’ revenue. Thus, a good rate adaptation algorithm at the client end that provides high QoE is critically important. Recently, a segment size-aware rate adaptation (SARA) algorithm was proposed for DASH clients. However, its performance on mobile clients has not been investigated so far. The main contributions of this article are twofold: (1) We discuss SARA’s implementation for mobile clients to improve the QoE in mobile video streaming, one that accurately predicts the download time for the next segment and makes an informed bitrate selection, and (2) we developed a new parametric QoE model to compute a cumulative score that helps in fair comparison of different adaptation algorithms. Based on our subjective and objective evaluation, we observed that SARA for mobile clients outperforms others by 17% on average, in terms of the Mean Opinion Score, while achieving, on average, a 76% improvement in terms of the interruption ratio. The score obtained from our new parametric QoE model also demonstrates that the SARA algorithm for mobile clients gives a better QoE among all the algorithms.

In this paper, we propose a framework to leverage electrical microgrids and cellular networks to support post-disaster communications for the public, government and critical infrastructure operation. The framework involves both policy and technical components. The proposed approach is an integration of electrical microgrids to provide power together with self con-figuring wireless mesh communication networks and local edge computing infrastructure to support critical communications and smart infrastructure services/applications in a specific geographic area. Hence, geographic zones which are resilient safe havens are created in a city. We outline the basic components of our approach and discuss open challenges to realizing the vision.

The traditional IP network has its inherent limitations that could cause application runs in a non-optimized manner. The common methods to improve applications' performance requires a great effort from both network administrators and application designers. In this work, we propose a Software- Defined Network (SDN) approach in an Application-Aware Network (AAN) platform. We first present an architecture for our approach and then show how this architecture can be applied to two real-world applications: Hadoop MapReduce (M/R) framework and MPEG-DASH. Our approach provides both underlying network functions and application-level forwarding logic for MapReduce and video streaming. Based on our experiments, we observed that our AAN platform for Hadoop MapReduce job optimization offers a significant improvement compared to a static, traditional IP network environment by reducing job run time by 16% to 300% for various MapReduce benchmark jobs. As for MPEG-DASH based video streaming, we can increase user perceived video bitrate by 100%.

Allocation of resources in data centers (DCs) needs to be done in a dynamic fashion for cloud enterprise customers who require virtualized reservation-oriented services on demand. Due to the spatial diversity of data centers, the cost of using different DCs also varies. In this paper, we propose an allocation scheme to balance the load among these DCs with different cost to minimize the total provisioning cost in a dynamic environment while ensuring that the service level agreements (SLAs) are met. Compared to a benchmark scheme (where all requests are first sent to the cheapest data center), our scheme can decrease the proportional utilization from 24% (for heavy load) to 30% (for normal load) and achieve a significant balance in the cost incurred by individual DCs. Our scheme can also achieve 7.5% reduction in total provisioning cost under certain service level agreement (SLA) in exchange of low increment in blocking. Finally, we tested our heuristic on 5 DCs to show that our allocation scheme follows the weighted cost proportionally.

Geo-distributed Data Centers (DCs) are increasingly common in order to provide scalability for increasing compute demands of modern applications. When multiple geo-distributed DCs serve user requests, it is important to determine which DC and server to select to fulfill the demand at minimum cost, given that enough resources are available in terms of e.g., CPU and bandwidth. This is a complex task since every DC has different operational costs due to e.g. energy, carbon emission, and bandwidth costs. In this paper, we develop a novel mathematical optimization model that guides the decision maker which DC to select, which server to use, and which DC gateway and network path to use to route the user demand in order to satisfy the time varying compute, bandwidth, and latency demands. Our model is based on the concept of virtual networks, which have different requirements in terms of e.g. latency, and we model the queuing delay as a function of the traffic load. Our extensive numerical evaluation, which is based on real-world DC locations, their resource provision costs, and typical demand patterns, shows how operational costs increase with the traffic load, and we analyze the impact of different latency bounds on the performance of different virtual networks.

The push from online video content providers to replace traditional broadcast television comes with the added expectation of comparable Quality of Experience (QoE) of video streaming. In-network caching, combined with prefetching, can be useful to improve DASH video delivery latency. In this paper, we propose an Adaptation Aware Hybrid Client-Cache (AAHCC) framework, a cache pre-fetching scheme that prefetch bitrate using an adaptation algorithm based on throughput measurements from the client and the forecasted throughput at the cache. For evaluation, we ran the experiments in a network with and without background traffic on GENI distributed testbed. Our results show that AAHCC by predicting the correct bitrate for the next segment reduces the number of unused pre-fetches and improve the byte-hit rate compare to a basic client-driven pre-fetch scheme.

Ethernet is the main choice of connectivity in data centers operating in clouds. The Ethernet standards body (IEEE 802.3) has generated Ethernet specifications with increasing transmission rates since its inception. As a result, it is observed that data centers with groups of physical hosts having heterogeneous bandwidths. In this paper, we present an energy-aware virtual machine's scheduling method, taking into account this heterogeneity while aiming at energy efficiency. This method consists of two algorithms: one to determine to which physical hosts virtual machines should be allocated, and the other for the provision of bandwidth on physical hosts to virtual machines. Our study shows that, regarding energy savings for the studied scenarios, the presented method is comparable to other energy-aware methods in data centers with groups of machines with homogeneous settings, surpassing them in groups of machines with heterogeneous configurations, bringing improvements especially to data centers with heterogeneous bandwidths' networks or to where restrictive SLAs are used for the provision of bandwidth to virtual machines.

It is a challenging task for network administrators to properly monitor and manage an institution's incoming and outgoing network traffic patterns. While NetFlow is useful to gather flow-level data, its feature is limited to traditional flow-level information such as the source IP address, destination IP address, source port number, destination port number, and the protocol type. Thus, if we are to understand geographic dynamics of any flow connected to hosts at an institution from the outside world, it is not currently possible with NetFlow. To address the geo-location information of such flows, we developed the tool, GoLCoNDa, for use by campus network administrators. This tool allows the correlation of IP addresses with the geo-location information to visualize the geo-location of incoming and outgoing flows. Our tool handles millions of records quickly.

Future Smart Cities require new ways to manage services that benefit the end users. An important issue is how to connect homes in a community and create an alert management system in Smart Cities with coordination among different entities. In this paper, we present an architectural vision of a software defined home alert management system for Smart Cities. This alert management system would make the residents aware of any incidents in the neighborhood such as fire. In this work, we use the features of software defined networking to design a manageable and flexible smart home for a smart community to provide services such as smart alarm systems.

In a virtual network environment, a substrate network provider allocates computing and networking resources for service providers who request virtual networks to be created for particular services, and it also has the capability to provide resilient virtual network management with redundant resources, such as dynamic virtual network restoration from failures. In this papers, we consider the situation where the substrate network provider desires to have standby virtual routers ready to serve virtual networks under node failures. Such a failure can affect one or more virtual routers in multiple virtual networks. The goal of this paper is to make the optimal selection of standby virtual routers so that virtual networks can be dynamically reconfigured back to their original topologies right after the failures. We present an optimization formulation and a heuristic for this problem. By considering a number of factors, we present numerical studies to show how the optimal selection was affected by those factors, and the proposed heuristic's performance was close to the optimization model when there were sufficient standby virtual routers for each virtual network and the substrate nodes have the capability to support multiple standby virtual routers to be in service concurrently.

Many critical e-commerce and financial services are deployed on geo-distributed data centers for scalability and availability. Recent market surveys show that failure of a data center is inevitable resulting in a huge financial loss. Fault-tolerance in distributed data centers is typically handled by provisioning spare capacity to mask failure at a site. We argue that the operating cost and data replication cost (for data availability) must be considered in spare capacity provisioning along with minimizing the number of servers. Since the operating cost and client demand vary across space and time, we propose cost-aware capacity provisioning to minimize the total cost of ownership (TCO) for fault-tolerant data centers. We formulate the problem of spare capacity provisioning in fault-tolerant distributed data centers using mixed integer linear programming (MILP), with an objective of minimizing the TCO. The model accounts for heterogeneous client demand, data replication strategies (single and multiple site), variation in electricity price and carbon tax, and delay constraints while computing the spare capacity. Solving the MILP using real-world data, we observed a saving in the TCO to the tune of 35% compared to a model that minimizes the total number of servers and 43% compared to the model that minimizes the average response time. We demonstrate that our model is beneficial when the cost of electricity, carbon tax, and bandwidth vary significantly across the locations, which seems to be the problem for most of the operators.

The MapReduce (M/R) framework used in Hadoop has become the de facto standard for big data analytics. However, the lack of network-awareness of the default M/R resource manager in a traditional IP network can cause unbalanced job scheduling and network bottlenecks; such factors can eventually lead to an increase in the Hadoop M/R job completion time. In this paper, we propose a software-defined network (SDN) approach in an application-aware network (AAN) platform that provides both underlying networks functions as well M/R particular forwarding logics. We measure the resources' usage for M/R workloads using the HiBench benchmark suite to identify the traffic pattern. We then demonstrate that by using our AAN-SDN framework, which uses an adaptive traffic engineering mechanism, the job completion time can be noticeably improved.

Despite tremendous software quality assurance efforts made by network vendors, chastising software bugs is a difficult problem especially, for the network systems in operation. Recent trends towards softwarization and opensourcing of network functions, protocols, controls, and applications tend to cause more software bug problems and pose many critical challenges to handle them. Although many traditional redundancy recovery mechanisms are adopted to the softwarized systems, software bugs cannot be resolved with them due to unexpected failure behavior. Furthermore, they are often bounded by common mode failure and common dependencies (CMFD). In this paper, we propose an online software bug detection, debugging, and isolation (BuDDI) middlebox architecture for software-defined network controllers. The BuDDI architecture consists of a shadow-controller based online debugging facility and a CMFD mitigation module in support of a seamless heterogeneous controller failover. Our proof-of-concept implementation of BuDDI is on the top of OpenVirtex by using Ryu and Pox controllers and verifies that the heterogeneous controller switchover does not cause any additional performance overhead.

Instantaneous low delay on-demand video streaming with a very low start up and channel switching delay is highly desirable for users. The dominant over-the-top (OTT) solutions like DASH, which is based on HTTP and/or WebSocket, suffer from a slow start of the underlying TCP transport while the typical coding structure of the DASH content introduces additional delays. In this work, we address these issues with a new low delay transport based on a WebRTC data channel along with a new content side packetization scheme based on a new QoE metric driven DASH sub-representation to facilitate a fast start, with an agile and fine granular rate adaptation. Simulations on both NS-3 and the GENI testbed demonstrate the effectiveness of this approach. This can serve as a basis for a further peer assisted low delay over-the-top (OTT) solution for an instantaneous live video streaming solution.

Dynamic Adaptive Streaming over HTTP (DASH) enables the video player to adapt the bitrate of the video while streaming to ensure playback without interruptions even with varying throughput. A DASH server hosts multiple representations of the same video, each of which is broken down into small segments of fixed playback duration. The video bitrate adaptation is purely driven by the player at the endhost. Typically, the player employs an Adaptive Bitrate (ABR) algorithm, that determines the most appropriate representation for the next segment to be downloaded, based on the current network conditions and user preferences. The aim of an ABR algorithm is to dynamically manage the Quality of Experience (QoE) of the user during the playback. ABR algorithms manage the QoE by maximizing the bitrate while at the same time trying to minimize the other QoE metrics: playback start time, duration and number of buffering events, and the number of bitrate switching events. Typically, the ABR algorithms manage the QoE by using the measured network throughput and buffer occupancy to adapt the playback bitrate. However, due to the video encoding schemes employed, the sizes of the individual segments may vary significantly. For low bandwidth networks, fluctuation in the segment sizes results in inaccurate estimation the expected segment fetch times, thereby resulting in inaccurate estimation of the optimum bitrate. In this paper we demonstrate how the Segment-Aware Rate Adaptation (SARA) algorithm, that considers the measured throughput, buffer occupancy, and the variation in segment sizes helps in better management of the users' QoE in a DASH system. By comparing with a typical throughput-based and buffer-based adaptation algorithm under varying network conditions, we demonstrate that SARA manages the QoE better, especially in a low bandwidth network. We also developed AStream, an open-source Python-based emulated DASH-video player that was used to evaluate three different ABR algorithms and measure the QoE metrics with each of them.

Fault-tolerance in a virtualized networking environment (VNE) requires additional efforts to provide the survivability against failures on either virtual networks (VNs) or the underlying substrate network. In this dissertation, we design a software-defined resilient VNE using a hybrid scheme of protection and restoration, where for each VN, a set of redundant virtual routers (VRs) are reserved as shared standby virtual routers (S-VRs), and any S-VR can be activated to replace a failed VR in the existed VN dynamically after the failure is identified. We first introduce a dynamic reconfiguration scheme (DRS) for node failures in a VNE, and then propose a Mixed-Integer Linear Programming (MILP) model with dual goals to optimally select S-VRs to restore all VNs while load balancing, and a heuristic algorithm based on the model is also presented. By considering a number of factors, the results showed that the proposed heuristics performance was close to the optimization model when there were sufficient standby virtual routers for each virtual network and the substrate nodes had the capability to support multiple standby virtual routers to be in service simultaneously. Finally, we present a prototyping design and implementation on the realistic virtual network testbeds (i.e., GpENI and GENI).

Hadoop has become the de facto standard for Big Data analytics, especially for workloads that use the MapReduce (M/R) framework. However, the lack of network awareness of the default MapReduce resource manager in Hadoop can cause unbalanced job scheduling, network bottleneck, and eventually increase the Hadoop run time if Hadoop nodes are clustered in several geographically distributed locations. In this paper, we present an application-aware network approach using software-defined networking (SDN) for distributed Hadoop clusters. We develop the SDN applications for this environment that consider network topology discovery, traffic monitoring, and flow rerouting in addition to loop avoidance mechanisms.

MPEG DASH is a client driven, pull based, adaptive streaming technology that allows for quality and bandwidth trade offs at streaming times. This is especially useful for mobile and Over The Top (OTT) video streaming applications, as throughput variations are inevitable. However, when multiple DASH clients are sharing a common wireless bottleneck with under-provisioned resources, e.g., multiple devices sharing the same home cable connection, or multiple UEs sharing the radio resource served by the same base station, simple adaptation within the same traffic session is not enough and may lead to sub-optimal solutions. In this work, we introduce new Quality of Experience (QoE) metrics for DASH sub-representations, and propose a marginal utility maximization-based resource pricing scheme to coordinate multiple video traffic sharing the bottleneck resource. The solution is based on the DASH SAND (Server And Network assisted DASH) messaging framework. Simulation results demonstrate the QoE multiplexing gains from this solution, and the pricing control scheme is adopted in SAND messages.

In this paper, we address the network virtualization problem of embedding a unique shortest path-based IP topology using lightpaths in a wavelength-routed network. We present an integer linear programming formulation and propose a 2-phase heuristic approach to solve this problem. We extend the model and the heuristic by addressing survivability in an integrated cross-layer framework, where the objective is to allocate a lightpath topology that remains connected in the event of any single physical link failure while providing the IP network with unique shortest paths for all node-pairs. We consider a number of measures to show effectiveness of our approach and to discuss the impact on normal and survivable topology design, in terms of the number of transreceivers deployed.

In multilayer networks, protection can be accomplished in any of the layers. However, which layer to protect most remains an important problem. In this paper, we consider a three-layer with IP/MPLS-over-OTN-over-DWDM in which we consider an optimization modeling framework incorporating modularization of its capacity for protection in any layer. Our resulting study, conducted on two topologies, shows that the cost ratio of different layers is an important factor in answering this question, as well as the actual modular values of the capacity used. Furthermore, we found that the cost providing protection in the OTN layer is highly influenced by the network connectivity.

HTTP-based video streaming services have been dominating the global IP traffic over the last few years. Caching of video content reduces the load on the content servers. In the case of Dynamic Adaptive Streaming over HTTP (DASH), for every video the server needs to host multiple representations of the same video file. These individual representations are further broken down into smaller segments. Hence, for each video the server needs to host thousands of segments out of which, the client downloads a subset of the segments. Also, depending on the network conditions, the adaptation scheme used at the client-end might request a different set of video segments (varying in bitrate) for the same video. The caching of DASH videos presents unique challenges. In order to optimize the cache hits and minimize the misses for DASH video streaming services we propose an Adaptation Aware Cache (AAC) framework to determine the segments that are to be prefetched and retained in the cache. In the current scheme, we use bandwidth estimates at the cache server and the knowledge of the rate adaptation scheme used by the client to estimate the next segment requests, thus improving the prefetching at the cache.

Network Virtualization promotes the development of new architectures and protocols by enabling the creation of multiple virtual networks on top of the same physical substrate. One of its main advantages is the use of isolation to limit the scope of attacks – that is, avoiding traffic from one virtual network to interfere with the others. However, virtual networks are still vulnerable to disruptions on the underlying network. Particularly, high capacity physical links constitute good targets since they may be important for a large number of virtual networks. Previous work protects virtual networks by setting aside backup resources. Although effective, this kind of solution tends to be expensive, as backup resources increase the cost to infrastructure providers and usually remain idle. This paper presents ORE (opportunistic resilience embedding), a novel embedding approach for protecting virtual links against substrate network disruptions. ORE’s design is two-fold: while a proactive strategy embeds each virtual link into multiple substrate paths in order to mitigate the initial impact of a disruption, a reactive one attempts to recover any capacity affected by an underlying disruption. Both strategies are modeled as optimization problems . Additionally, since the embedding problem is NP -Hard, ORE uses a simulated annealing-based meta-heuristic to solve it efficiently. Numerical results show that ORE can provide resilience to disruptions at a lower cost.

With the increasing frequency of natural disasters and intentional attacks that challenge communication networks, vulnerability to cascading, and regional‐correlated challenges is escalating. Given the high complexity and large traffic load of communication networks, these correlated challenges cause substantial damage to reliable network communication. In this work, we extend the GeoDivRP routing protocol to consider delay‐skew requirement when using multiple geographically diverse paths for telecommunication networks under area‐based challenges. We present a flow‐diverse minimum‐cost routing multicommodity flow problem. Furthermore, we present a nonlinear delay‐skew optimization problem to balance between delay and traffic skew on paths. We investigate the tradeoff between the delay and skew in choosing multiple geodiverse paths. We implement GeoDivRP in ns‐3 to use the optimized paths given by the two optimization solutions and demonstrate their effectiveness compared to open shortest path first Equal‐Cost Multi‐Path routing in terms of overall link utilization. It guarantees the delay‐skew constraint provided by the upper layer while satisfies the traffic demand imposed by multiple routing commodities in the telecommunication networks. © 2015 Wiley Periodicals, Inc. NETWORKS, Vol. 66(4), 335–346 2015

The increasing adoption of server virtualization has recently favored three key technology advances in data-center networking: the emergence at the hypervisor software level of virtual bridging functions between virtual machines and the physical network; the possibility to dynamically migrate virtual machines across virtualization servers in the data-center network (DCN); a more efficient exploitation of the large path diversity by means of multipath forwarding protocols. In this paper, we investigate the impact of these novel features in DCN optimization by providing a comprehensive mathematical formulation and a repeated matching heuristic for its resolution. We show, in particular, how virtual bridging and multipath forwarding impact common DCN optimization goals, traffic engineering (TE) and energy efficiency (EE), and assess their utility in the various cases of four different DCN topologies. We show that virtual bridging brings a high performance gain when TE is the primary goal and should be deactivated when EE becomes important. Moreover, we show that multipath forwarding can bring relevant gains only when EE is the primary goal and virtual bridging is not enabled.

We seek to understand proportional fairness in equilibrium in the presence of both applications with multiple flows (MFAs) and traditional applications with single flows (SFAs). Proportional fairness is shown to be applicable to TCP variants such as TCP Reno, TCP Vegas, and FAST TCP. We consider the competing scenario where an SFA with proportionally fair sharing TCP is competing with an MFA that invokes a number of parallel flows, also with proportional fair sharing TCP. We present analytical results for a linear network, and show the extent of the quantitative gain of an MFA can over an SFA regardless of whether it is connecting the far end of a linear network or just the adjacent nodes.

Multipath routing gives traffic demands an opportunity to use multiple paths through a network. In a single-demand situation, its benefits are easy to see. In a multi-commodity case, when potentially all node-pairs (demands) generate traffic, they compete for the same network resources. In this work, we consider multipath routing in communication networks in a multi-commodity setting from a traffic engineering perspective. Based on a result from linear programming, we show that at an optimal solution, the number of demands that can have multiple paths with nonzero flows is of the order of the number of network links for three commonly used traffic engineering objectives. We introduce a multipath measure (MPM) and show that under certain traffic conditions and topological structures, the MPM is zero or close to zero, i.e., Multipath routing provides little or limited gain compared to single-path routing. For the all-pair traffic case, multipath routing is observed to be advantageous for small networks. When the number of nodes is about 25 or higher and all node pairs have traffic, this advantage drops as the number of nodes in a network increases. For the fat-tree data center topology, the benefit of multipath routing also drops as the number of pods increases. Our findings are somewhat against a common belief (expressed by the term "load sharing") that multipath routing is significantly better in effective distribution of traffic over the network resources.

The resource allocation problem has been a very hot topic since the migration from CDMA to OFDMA modulation schemes has taken place for the wireless communication systems. The scheduling problem has transformed into a rather more complex one due to the increased number of resource elements at hand. There have been numerous proposed scheduling algorithms with various analytical approaches to enhance the efficiency, QoS, fairness, or throughput of the systems that employ OFDMA. We propose an original multi-user downlink scheduling scheme for LTE where the problem is formulated as an optimization problem with minimum throughput limitations for the users.We introduce a time-window parameter to exploit the slow varying channel conditions if there are any. Specifically, this is accomplished by means of defining the minimum throughput limitation over a larger period of time than the scheduling time for users with relative slow varying channel conditions. The suggested algorithm is called the Two-Stage Time windowed Scheduling (TSTwS) and it achieves up to 30% higher average total downlink throughput than the equivalent model without the time-window approach.

Software-Defined Networking (SDN) is a new approach to manage the whole network flexibly by decoupling the control plane and the forwarding plane. While forwarding elements can be managed by a unified control, complexity arisen from the network size and scalability regarding the increase of the control traffic are notable problems. To deal with events of network reconfiguration that occur asynchronously and change frequently with intervals shorter than hours, a controller has to continue to asynchronously update the configuration of the whole network. However, it is hard to maintain the consistency of the configuration of the whole network because it needs to manage a huge amount of network information and to deal with user requests that occur asynchronously. In this paper, we propose a database oriented management for asynchronous reconfiguration to achieve the consistency of configuration in SDN. We design a structure of the database to store network information and two functional components. Finally, we adopt our management system to an OpenFlow-based network, and validate that our system can manage and control an OpenFlow network via the database.

A campus network provides a number of services to its stakeholders. Due to the complexity of having many services, it is often difficult to pinpoint an issue quickly. The currently available tools for monitoring a campus network are often designed for a specific piece of the network. On the other hand, systems administrators running a campus network with data centers and supporting a number of internal and external applications face several challenges with the current set of tools for monitoring and management. To fill this void, we propose the I-CaN-MaMa (Integrated Campus Network Monitoring and Management) framework. Our approach takes an integrated view that was developed in consultations with issues faced by systems administrators. We present the key components in this framework and through a brief study, we show the utility of our approach.

An important goal of data center providers is to minimize their operational cost, which reflected through the wear-and-tear cost and the energy consumption cost. In this paper, we present optimization formulations to minimize the cost of ownership in terms of server energy consumption and serverwear-and-tear cost under three different data center server setups (homogeneous, heterogeneous, and hybrid hetero–homogeneous clusters) for dynamic temporal workloads. Our studies show that the homogeneous model takes significantly less computational time than the heterogeneous model (by an order of magnitude). To compute optimal configurations in near real time for large-scale data centers, we propose two modes for using our models: aggregation by maximum (preserves workload deadline) and aggregation by mean (relaxes workload deadline). In addition, we propose two aggregation methods for use in each of the two modes: static (periodic) aggregation and dynamic (aperiodic)aggregation. We found that in the aggregation by maximum mode, dynamic aggregation resulted in cost savings of up to approximately 18% over the static aggregation. In the aggregation by mean mode, dynamic aggregation saved up to approximately a 50% workload rearrangement compared with the static aggregationby mean mode.

In this paper, we consider bandwidth-intensive services for customers that want virtual networks (VN) in a data center environment. In particular, we consider this problem in a temporal context where bandwidth-intensive requests from each VN may arrive randomly at a review point, which may last for a certain duration. Thus, at each review point, the data center network provider must optimally allocate resources for the demand requests. For this problem, we present a mixed-integer programming (MIP) problem formulation where any request from a VN customer may be assigned to any virtual machine so that network resource availability is optimized. We present an overbooking strategy that may be employed to allow for some demands not met in the first try. For comparison, we also consider a base case where the allocation is pinned to a specific destination. Through our study, we show the comparative gains of different schemes.

With Cloud Computing technology occupying the majority of future Internet research and development work, research on deploying and extending existing capabilities onto a newly emerging infrastructure becomes more significant. For example, extending the virtual network provisioning capability onto a Geo-distributed programmable layer-2 networking environment (G-PLaNE) is a novel attempt and is different from in a single domain system. In this paper, we aim to illustrate how to construct the virtual networking environment upon our self-designed resource provisioning system consisting of multiple clusters through G-PLaNE. Experimenters and researchers are able to develop and explore their own mechanisms in our platform. Furthermore, a concrete example named Secure and Resilient Virtual Trust Routing (SeRViTR) is given to illustrate how this can be constructed over G-PLaNE.

A secure network is considered to be an important goal of the Future Internet; one way this can be embodied is by having flexible and robust routing functionalities with intrinsic security mechanisms. It is also desirable to provide user-centric or service-centric routing capabilities to achieve service-oriented traffic controls as well as trust and policy management for security. Based on these potential needs, a flexible, scalable, and robust routing framework that enables fine-grained flow control under fixed or dynamic policies called the Virtual Trusted Routing and Provisioning Domain (VTRouPD)[11] has been recently proposed. In this paper, we present a framework called the Secure and Resilient Virtual Trust Routing (SeRViTR) framework, which is a proof-of-concept model of VTRouPD at the implementation level. SeRViTR has particular entities that are designed for policy management and trust management between different VTRouPDs to enable a secure Internet. We define the roles of each entity within the SeRViTR framework as well as the messages exchanged between them. We also discuss how policy management and trust negotiation can be achieved. Moreover, we present validation on the functional implementation of several SeRViTR components to illustrate how to create virtual domains and change of trust levels between virtual domains.

Multilayer network design has received significant attention in current literature. Despite this, the explicit modeling of IP/MPLS over OTN over DWDM in which the OTN layer is specifically considered has not been addressed before. This architecture has been identified as promising that bridges integration and interaction between the IP and optical layers. In this paper, we present an integrated capacity optimization model for network planning of such multilayer networks that consider the OTN layer as a distinct layer with its unique technological sublayer constraints. We develop a heuristic algorithm to solve this model for large networks. Finally, we provide a detailed numeric study that considers various cost parameter values of each layer in the network. We analyze the impact of each layer's cost parameter values on neighboring layers and overall network cost.

Great Plains Environment for Network Innovation (GpENI) is an international testbed for future Internet research. A key component of GpENI is programmable network virtualization (GpENI-VINI). The scope of this paper is to present the framework, implementation and integration experience with network virtualization in GpENI. In particular, this is described through our experience of implementing and integrating the XORP (eXtensible Open Router Platform) routing platform into GpENI-VINI. Preliminary results on measurements and validation are presented.

As online service providers utilize cloud computing to host their services, they are challenged by evaluating the quality of experience and designing redirection strategies in this complicated environment. We propose a hierarchical modeling approach that can easily combine all components of this environment. Identifying interactions among the components is the key to construct such models. In this particular environment, we first construct four sub-models: an outbound bandwidth model, a cloud computing availability model, a latency model and a cloud computing response time model. Then we use a redirection strategy graph to glue them together. We also introduce an all-in-one barometer to ease the evaluation. The numeric results show that our model serves as a very useful analytical tool for online service providers to evaluate cloud computing providers and design redirection strategies.

Secure virtualization is the enabling technique to protect both network providers and user services. Particularly, secure routing in the virtualized service domains is one of the key research areas that has not been explored in literature. In this paper, we present a new secure routing framework to address both network-centric and user-centric networking service models for the future Internet. We aim to provide a flexible network routing framework that has the capability to route traffic with different service requirements and constraints. In other words, it could be highly desirable that two types of network traffic should be isolated either physically or logically and trustworthy services should be avoided to share the bandwidth with normal traffic that may be prone to security attacks. To achieve this capability, we present how to establish a virtual trust routing framework to handle both network-centric routing and user-centric routing simultaneously by using attribute-based cryptography that can provide information-level protection for virtual routing domain isolation. Our performance evaluation on prioritized services through virtual routing domains and cryptography performance analysis demonstrates the viability of the proposed solution.

PhoneFactor is a two-factor authentication service that combines the knowledge-based authenticator with an object-based authenticator in which the object-based authenticator has advantages of hardware token-based systems without requiring the administration overhead of distribution of special hardware to every user in advance. For transaction scalability of this service, we propose a Distributed Real-Time Transaction Memory Cache (DReaM-Cache) approach. In this paper, we present the basic architecture and present reliability models for different data centers and node reliability factors, and show how reliability can be accomplished.

The IP Multimedia Subsystem (IMS) is a generic open-systems architecture offering converged multimedia services over IP. A function in the signaling plane of an IMS network is the interrogating Call/Session Control Function (I-CSCF) choosing the serving CSCF (S-CSCF) for a request. In this paper, we investigate distributed S-CSCF selection by considering four schemes: uniform random allocation, round robin, shortest expected delay, and least response time with network feedback. Through our study, we found that the shortest expected delay gives the best performance when the message size is one. However, when the message size of a request is higher, the shortest expected delay and the round robin scheme perform similarly in most cases while they are both better than uniform random allocation and least response time with network feedback schemes.

Agent-based virtual private networks architecture (ABVA) refers to the environment where a third-party provider runs and administers remote access virtual private network (VPN) service for organizations that do not want to maintain their own in-house VPN servers. In this paper, we consider the problem of optimally connecting users of an organization to VPN server locations in an ABVA environment so that request denial probability and latency are balanced. A user request needs a certain bandwidth between the user and the VPN server. The VPN server may deny requests when the bandwidth is insufficient (capacity limitation). At the same time, the latency perceived by a user from its current location to a VPN server is an important consideration. We present a number of schemes regarding how VPN servers are to be selected and the number of servers to be tried so that request denial probability is minimized without unduly affecting latency. These schemes are studied on a number of different topologies. For our study, we consider Poisson and non-Poisson arrival of requests under both finite and infinite population models to understand the impact on the entire system. We found that the arrival processes have a significant and consistent impact on the request denial probability and the impact on the latency is dependent on the traffic load in the infinite model. In the finite model, arrival processes have an inconsistent impact to the request denial probability. As to the latency in the finite model, arrivals that have a squared co-efficient of variation less than one is consistently largest, followed by the Poisson case, then the case that the squared co-efficient of variation is more than one. Finally, a strength of this work is the comparison of infinite and finite models; we found that a mismatch between the infinite and the finite model is dependent both on the number of users in the system and the load.

In this work, we consider the performance benefits of distribution reservation control schemes in partially-connected wavelength-routed all-optical WDM networks. In particular, we propose a new distributed reservation control scheme designed to work for general topology wavelength-routed WDM networks. In this new scheme, capacity reservation is invoked by always using the first shortest path if the direct route does not exist between all node (demand) pairs. Through our study, we show that our proposed scheme in the presence of distributed adaptive routing is much more fair on pairwise blocking than the conventional reservation method in general topology wavelength-routed WDM networks, especially in the presence of wavelength converters and overload situations.

PhoneFactortrade is a token-less two-factor authentication service for user remote logons. This allows users of an organization to be authenticated through an automated phone call to the user's phone before access is allowed. In this paper, we present the service management architecture of PhoneFactor that depends on both the Internet and the public switched telephone network (PSTN), and we identify two key quality of service parameters, the system response time and call blocking probability, where the latter can impact the former. Furthermore, through traffic analysis of the measurement data from the deployed PhoneFactor service, we found that the inter-arrival time of requests follows the generalized Pareto distribution while the system response time and the call duration (for the authentication part through the phone call) follow the log-normal distribution. Given these distributions, we then present system capacity design methodologies by comparing them to known results for systems that are analytically derivable.

Summary form only given, as follows. The complete presentation was not made available for publication as part of the conference proceedings. Routing in the Internet in its simplest form plays the role of carrying information between two end devices. Due to the structure of the Internet being federated, many components need to play together to make routing between two end devices work, and more importantly, make it work efficiently; in this regard, management plays a critical role in a federated environment. In addition, the federated environment leads to peering and tiering arrangements, and so on. In this tutorial, I'll present an overview of Internet routing, along with several critical management components such as intra/inter-domain traffic engineering, IP prefix management, and policy management. The main focus is on routing management, rather than routing itself. However, the basics of Internet routing architecture will be discussed at the beginning so that the audience get the most out of this tutorial.

Agent-based virtual private networks architecture (ABVA) refers to the environment where a third-party provider runs and administers remote access VPN service for organizations that do not want to maintain their own in-house VPN servers. This environment presents interesting management challenges for an ABVA provider. In this paper, we consider the problem of connecting users of an organization to an optimal VPN server location so that request denial probability and latency are balanced. Because of the bandwidth requirement of a user to be met when connected to a server, this system has the appearance of a standard loss system. However, due to latency perceived by a user from its current location to a VPN server and to allow for servers to be located in a distributed fashion, this environment is not a pure loss system. By considering a finite population, this environment can be approximately represented using the Engset model; however, this does not address the latency issue either. We present a number of strategies regarding which VPN server is to be selected and the number of attempts to be tried so that request denial probability is minimized without unduly affecting latency. Through computational results, we show that the clustering with directional hunting (CDH) strategy provides the best result. However, in the heterogeneous case of users with differing data rates ("traffic classes"), request denial observed by each class is different leading to unfair treatment. We have proposed a reserved capacity based add-on feature with CDH, which allows service classes with different data rates to be treated fairly.

In this paper, we address the issue of forecasting for periodically measured nonstationary traffic based on statistical time series modeling. Often with time-series-based applications, minimum-mean-square error-based forecasting is sought that minimizes the square of the positive, as well as the negative, deviations of the forecast from the unknown true value. However, such a forecast function is not directly applicable for applications such as predictive bandwidth provisioning in which the negative deviations (underforecast) have more impact on the system performance than the positive deviation (overforecast). For instance, an underforecast may potentially result in an insufficient allocation of bandwidth leading to short-term data loss. To facilitate a differential treatment between the under- and the over-forecast, we introduce a generalized forecast cost function that is defined by allowing a different penalty associated with the under and the overforecast. We invoke mild assumptions on the first-order characteristics of such penalty functions to ensure the existence and uniqueness of the optimal forecast value in the domain of interest. The sufficient condition on the forecast distribution is that all the orders of the moments are well defined. We provide several possible classes of penalty functions to illustrate the generic nature of the cost function and its applicability from a dynamic bandwidth provisioning perspective. A real network traffic example using several classes of penalty functions is presented to demonstrate the effectiveness of our approach.

Understanding outage and failure characteristics of a network is important to assess the availability of the network, determine failure source for trouble-shooting, and identify weak areas for network availability improvement. However, there has been virtually no failure measurement and analysis on access networks. In this paper, we carry out an in-depth outage and failure analysis of a university campus network using a rich set of both node outage and link failure data. We investigate the aspects of spatial and temporal localities of failures and outages, the relation of link failure and node outage, and the impact of the hierarchical and redundant network design on outage. We find most of link failure events are not caused by node failures; frequent link up-down events may not lead to the corresponding node's outage; for access layer switches that connect to end hosts, their link up-down events exhibit periodic patterns.

Existing pairwise key establishment schemes for large-scale sensor networks are vulnerable to various passive or active attacks. We classify attacks as selective node capture attacks, node fabrication attacks, and insider attacks. In order to improve the security robustness of random key predistribution and pairwise key establishment schemes against these attacks, we propose a five-phase pairwise key predistribution and pairwise key establishment approach by using area partitioning and multigroup key predistribution. Our security performance studies show that our proposed approach is resilient to selective node capture and node fabrication attacks, and restricts the consequence of any insider attack to a minimal level.

Abstract — In current network routing domains, routing information exchange usually lacks protection based on confidentiality. This makes network routing vulnerable to a variety of security attacks. In this paper, we present a framework to provide confidentiality for a link state routing protocol. This framework involves creation of a trust structure among routers as well as key management. Routing information is encrypted so that it can be accessed only by authorized routers. We present an implementation framework for our approach by extending Open Shortest Path First (OSPF), a commonly deployed link-state routing protocol. Based on our performance assessment, we have found that the additional cost in implementing our scheme has fairly moderate impact on the overall performance. I.

The integration of lightpath topology design and IP/MPLS traffic engineering provides greater flexibility for next generation networks. In this paper, we consider the integrated design problem of configuration of lightpath topology and optimal routing of IP/MPLS tunnels on this lightpath topology for time- varying traffic. A mixed integer linear programming model is proposed to design an optimal configuration of lightpath topology, which takes time-dependent traffic demand as an input to the model for IP/MPLS traffic engineering. We consider two variants of the problem: in the first variant, re-routing of IP/MPLS tunnels is not allowed from one-time period to another while reconfiguration rerouting is allowed in the second variation. We also consider various traffic engineering objectives and study their impact on different performance measures. In particular, we propose a composite objective function to combine the benefits of various objectives. Through computational results, we quantify the benefit of the configurable option over the static option.

Sensor networks are composed of a large number of low power sensor devices. For secure communication among sensors, secret keys must be established between them. The establishment of secret keys after deployment of sensors requires wireless communication. Because of the energy constraints, an efficient key establishment scheme cannot be designed without considering the power consumption factor in wireless communication. In order to reduce the communication overhead, we propose a source routing based pairwise key establishment protocol for large-scale sensor networks. We then use a probability model proposed in [D. Huang et al., (2004)] to analyze the communication overhead, and security strength of the scheme.

The double authentication (DA) scheme presented in D. Huang et al., (2003) is designed to provide security against impersonation attack to link state routing protocol at a lower computational cost as compared to the existing schemes, such as, digital signature scheme S. Murphy et al. (1997). In this paper, we present a key distribution scheme that can be used for generating and distributing keys to provide DA. This scheme leads to a storage complexity for each router that varies linearly with the number of routers in the network in the worst case (fully connected network with n nodes). Moreover, for router with four or less average number of links, the storage complexity falls below log/sub 2/n. This scheme also increases the security robustness of DA as the subverted routers can collude only if they are neighbors.

An important traffic engineering problem for OSPF networks is the determination of optimal link weights. Certainly, this depends on the traffic engineering objective. Regardless, often a variety of performance measures may be of interest to a network provider due to their impact on the network. In this paper, we consider different objectives and discuss how they impact the determination of the link weights and different performance measures. In particular, we propose a composite objective function; furthermore, we present a Lagrangian relaxation-based dual approach to determine the link weight system. We then consider different performance measures and discuss the effectiveness of different objectives through computational studies of a variety of network topologies. We find that our proposed composite objective function with Lagrangian relaxation-based dual approach is very effective in meeting different performance measures and is computationally very fast.

We propose an adaptive bandwidth provisioning mechanism based on packet-level measurements (done at discrete time intervals) without any assumption on the statistical property of the traffic. Our approach consists of two stages: traffic forecasting, followed by bandwidth estimation. For the first stage, we have developed a probability-hop forecasting algorithm (based on ARIMA model) to forecast traffic based on online traffic measurements in a temporal management information base framework. For the second stage, we present several bandwidth provisioning schemes that allocate or deallocate bandwidth depending on the traffic forecast generated by our forecasting algorithm. We have introduced an utility function (along with other measures) to evaluate the overall effectiveness of our bandwidth provisioning framework. Through the use of real-world data, we have found that our approach works well for highly fluctuating data

We propose a novel secure group keying scheme using hash chain for many-to-many secure group communication. This scheme requires a key predistribution center to generate multiple hash chains and allocates exactly one hash value from each chain to a group member. A group member can use its allocated hash values (secrets) to generate group and subgroup keys. Key distribution can be offline or online via the key distribution protocol. Once keys are distributed, this scheme enables a group member to communicate with any possible subgroups without the help of the key distribution center, and without having to leave the overall group, thus avoiding any setup delay. Our scheme is suitable for applications where the population of a system is stable, group size is moderate, subgroup formation is frequent, and the application is delay sensitive. Through analysis, we present effectiveness of our approach.

In this paper, we present an authentication scheme to prevent impersonation attack in link state routing protocol. The existing authentication schemes are either simple to compute but vulnerable to attacks of too robust against attacks but has exponential computation cost. We introduce a double authentication (DA) scheme which provides authentication to the routing information data carried by link state routing packets. In this scheme every router needs to sign the routing data twice with two different keys using a group keying scheme, which is based on one-way hash function. Based on our performance assessment, we found that this scheme is simpler to implement, computationally efficient and provides the degree of robustness desired with less communication overhead but has higher memory requirement.

In this paper, we attempt to improve the performance in congested parts (CP) of an asymmetric network using network controls and routing mechanisms. Typically, an asymmetric network is characterized by non-uniform link capacities or uneven traffic load or both. In such a network, certain service classes can experience poor performance in parts of the network, even when the average performance is very close to the expected performance level. We studied a network derived from an actual service provider network with asymmetric concentration of traffic. We have developed two metrics in order to capture the congested part behavior in a network. In order to understand the generality of our conclusions, we used three variations of our network and show that controls like service class based multi-link dynamic capacity reservation (SMDCR) with a properly chosen reservation factor, significantly reduce variability in the performance over all parts of the network.

IPSec provides two types of security algorithms, symmetric encryption algorithms (e.g. data encryption standard DES) for encryption, and one-way hash functions (e.g., message digest MD5 and secured hash algorithm SHA1) for authentication. This paper presents performance analysis and comparisons between these algorithms in terms of time complexity and space complexity. Parameters considered are processing power and input size. The analysis results revealed that HMAC-MD5 can be sufficient for the authentication purposes rather than using the more complicated HMAC-SHA1 algorithm. In encryption applications, authentication should be combined with DES.

In this paper, we attempt to understand the benefits of MPLS traffic engineering through a case study. Specifically, we do a comparative study of MPLS traffic engineering in the presence of dynamic constraint-based routing compared to destination-based routing. For this case study, we use a model derived from an actual service provider network. Different control schemes that can be deployable for MPLS traffic engineering are also considered. This case study shows that services can indeed obtain benefits from constraint-based routing and traffic engineering controls.

In the public switched telephone network (PSTN), 911 (emergency) services are handled by a dedicated, point-to-point analog network infrastructure. In contrast, 911 in IP telephony is constrained by IP's flat addressing scheme and dynamic IP address assignment, best-effort service model and inherent dynamicity in network topology connectivity. To serve crucial E911 needs of accurate assistance dispatch with callback facility in IP telephony, the existing model from analog telephony is not applicable. We investigate ways of resolving location information of an IP telephony 911 caller and propose a novel approach to convey geographic location information parameters of connected hosts by extending the DHCP protocol. The case scenario of voice over IP (VoIP) in local area networks (LAN) is used as the basis for our approach and specifically, University of Missouri Kansas City's (UMKC) VoIP network has been considered for possible deployment of this approach.

Network layer phenomena (such as route fluctuations and link failure) occur due to a variety of reasons. While TCP performance and the routing protocol dynamics have been independently studied, their inter-relation has received little attention. We study the interaction between TCP and routing in the presence of link state routing over a number of network topologies. Our observation is that routing changes can cause additional effects such as inevitable false retransmission and data compression in TCP (beyond effects observed in the absence of routing).

We consider an interconnected network environment where one network can act as a 'provider' or 'service' network to the 'user' network or a collection of 'user' networks. In such an environment, a major failure in a provider network can affect the user networks. Very often, failure management is addressed in each individual network domain independently. We present an overview of a loosely-coupled network management framework through the development of a multi-layered network manager of managers concept for correlated management, for failure cases that can not be addressed by each component network individually.

We consider dynamic QoS routing in an integrated-services environment where some of the offered traffic streams are dynamic. While there has been work on routing performance in the presence of purely stationary traffic, the presence of dynamic traffic has received very little attention. We consider three routing schemes: dynamic random routing (DRR), maximum available capacity routing with periodic update and crankback (MACRPC) and maximum available capacity routing with instant computations (MACRIC). Based on simulation, we have found that while DRR performs and adapts better than MACRPC in the case of no trunk reservation, it is other way around when there is moderately high trunk reservation (even for less frequent routing updates). Further, we found that dynamics of a traffic class can result in dynamic flow blocking behavior even on stationary traffic, especially at a low or no trunk reservation level.

We address a multiservice, multirate loss network environment with dynamic routing. In this setting, we consider multiple traffic load periods (multihour) during the day, and by observing network dynamics, we present a network dimensioning model that consists of two steps: a bandwidth estimation step, followed by a multicommodity flow model for multiple services and traffic loads. For network operations, we discuss a probabilistic admission control policy and three multiservice routing schemes. We have used a ten-node network with multiple asymmetric traffic data sets (partially extracted from an actual network) for our study. It was found that the capacity obtained using the analytic network dimensioning model provides a good estimate of network capacity required for meeting the grade-of-service goal for each service type in each traffic load period; this observation is based on a simulated network environment that uses the proposed admission control and the dynamic routing schemes. Our observation suggests that it may not be not necessary for the dimensioning model to explicitly incorporate an admission control policy, but admission control is needed for network operation to provide desirable grade-of-service.

We present a comparative analysis of bandwidth access control schemes under nonstationary traffic conditions for heterogeneous circuit-mode traffic offered to a B-ISDN network link. A unified model for analysing the behavior of several bandwidth access control schemes is developed using a Markov process model with acceptance functions. Numerical techniques are used to solve the associated Chapman-Kolmogorov equations and determine the nonstationary behavior. Performance results are given for several common bandwidth access control schemes, namely: complete sharing, complete partitioning, partial sharing, classical trunk reservation, and the probabilistic reservation policy. It is shown that the use of the average arrival rate to estimate the average connection blocking rate may be an underestimate for a system with a time varying arrival process. Also, it is found that a nonstationarity in one traffic class arrival process can impact other stationary traffic classes and the degree of variability depends on the particular access control scheme.

Presents a unified model to compute various performance measures when Poissonian and non-Poissonian (renewal) multi-slot traffic streams are offered to a digital link in a (double) loss system. the authors represent the non-Poissonian arrival process by a matrix-exponential distribution, requiring only that the inter-arrival distribution has a rational Laplace transform. Several distributions are considered as the non-Poissonian traffic. The resulting model uses matrix algebraic techniques only, thus not requiring any complex and/or tedious transform techniques. The authors also incorporate various control policies in their modeling framework using acceptance functions. Through computational studies, they conclude that the second and the third moments of the non-Poissonian traffic have significant impact on various performance measures.>

The virtual path (VP) concept has been gaining attention in terms of effective deployment of asynchronous transfer mode (ATM) networks in recent years. In a recent paper, we outlined a framework and models for network design and management of dynamically reconfigurable ATM networks based on the virtual path concept from a network planning and management perspective. Our approach has been based on statistical multiplexing of traffic within a traffic class by using a virtual path for the class and deterministic multiplexing of different virtual paths, and on providing dynamic bandwidth and reconfigurability through virtual path concept depending on traffic load during the course of the day. In this paper, we discuss in detail, a multi-hour, multi-traffic class network (capacity) design model for providing specified quality-of-service in such dynamically reconfigurable networks. This is done based on the observation that statistical multiplexing of virtual circuits for a traffic class in a virtual path, and the deterministic multiplexing of different virtual paths leads to decoupling of the network dimensioning problem into the bandwidth estimation problem and the combined virtual path routing and capacity design problem. We discuss how bandwidth estimation can be done, then how the design problem can be solved by a decomposition algorithm by looking at the dual problem and using subgradient optimization. We provide computational results for realistic network traffic data to show the effectiveness of our approach. We show for the test problems considered, our approach does between 6% to 20% better than a local shortest-path heuristic. We also show that considering network dynamism through variation of traffic during the course of a day by doing dynamic bandwidth and virtual path reconfiguration can save between 10% and 14% in network design costs compared to a static network based on maximum busy hour traffic.

Addresses the problem of network survivability by presenting a unified approach where the wide-area circuit-switched teletraffic network and the underlying transmission facility network are considered simultaneously. The author assumes the backbone circuit-switched teletraffic network to be nonhierarchical with dynamic call routing capabilities. The transmission facility network is considered to be sparse (as is observed for emerging fiber optic networks) and is assumed to be two-arc connected. The approach addresses the network survivability objective by considering two grade-of-service parameters: one for the traffic network under normal operating condition and the other for affected part of the network under a network failure. The author presents unified mathematical models and develops heuristic algorithms. The author then presents computational results to demonstrate the effectiveness of the unified approach.>

The authors present traffic restoration design algorithms to attain a robust network for any facility link or node failure. Some of these algorithms were implemented on network models to compute the cost for doing traffic restoration for different traffic restoration level objectives. From their simulation studies, the authors found that with efficient use of trunk group diversity and at a reasonable incremental cost, one can obtain a robust network to respond to a major facility link or a node failure and still meet the network objectives. A similar approach based on the algorithms presented in this work has been proposed for design of the worldwide intelligent network.>