A.A. Abouzeid Publications

In this paper an information-theoretic formulation is used for characterizing the minimum overhead of maintaining link state information across a mobile ad hoc network. The minimum overhead problem is formulated a rate-distortion problem. Lower bounds are derived for the minimum overhead incurred by maintaining link state information when link state routing protocols are designed with guaranteed delivery ratio for data packets. The deficit caused by the this overhead on the overall transport capacity of a mobile network is characterized. Further a threshold value is derived for the delivery error ratio, and it is shown that no link state routing protocol can achieve a delivery error ratio smaller than this threshold.

We consider the scenario of distributed data aggregation in wireless sensor networks, where each sensor can obtain and estimate the information of the whole sensing field through local data exchange and aggregation. The intrinsic trade-off between energy and delay in aggregation operations imposes a crucial question on nodes to decide optimal instants for forwarding their samples. The samples could be composed of the information from their own sensor readings or an aggregation of information with other samples forwarded from neighboring nodes. By considering the randomness of the sample arrival instants and the uncertainty of the availability of the multiaccess communication channel due to the asynchronous nature of information exchange among neighboring nodes, we propose a decision process model to analyze this problem and determine the optimal decision policies at nodes with local information. We show that, once the statistics of the sample arrival and the availability of the channel satisfy certain conditions, there exist optimal control-limit type policies which are easy to implement in practice. In the case that the required conditions are not satisfied, we provide two learning algorithms to solve a finite-state approximation model of the decision problem. Simulations on a practical distributed data aggregation scenario demonstrate the effectiveness of the developed policies, which can also achieve a desired energy-delay tradeoff.

Overheads incurred by routing protocols diminish the capacity available for relaying useful data over a mobile wireless ad hoc network. Discovering and understanding the lower bounds on the amount of protocol overhead incurred for routing data packets is important for development of efficient routing protocols, and for understanding the actual (effective) capacity available for network users. In this paper we use an information-theoretic approach for characterizing the minimum routing overheads of geographic routing in a mobile network. We formulate the minimum overhead problem as a rate-distortion problem. The formulation may be applied to networks with arbitrary traffic arrival and location service schemes. We evaluate lower bounds on the minimum overheads incurred for maintaining the location of destination nodes and consistent neighborhood information in terms of node mobility and packet arrival process. We also characterize the deficit caused by the routing overheads in the overall transport capacity of a mobile network.

The per-node throughput capacity of hybrid radio frequency and free space optics (RF/FSO) networks is studied and the benefit of using this hybrid network architecture over the pure RF wireless networks is evaluated. The hybrid RF/FSO network consists of an RF ad hoc network of n nodes, m of them (so called super nodes) are equipped with an additional FSO transceiver. Every RF and FSO transceiver is able to transmit at a maximum data rate of W₁ and W₂ bits/sec, respectively. All the super node are connected by the FSO links and thus can form a stand-alone FSO network. With a minimum transmit power objective, an upper bound on the per node capacity of √(1/n log n) + c₂W₂ √(m log m)/n is derived. In order to prove that this upper bound is achievable, we design a hybrid routing scheme in which the data traffic is divided into two classes and use different routing strategies: a portion of data will be forwarded with the (partial) support of super nodes in a hierarchical routing fashion, and the rest will be purely routed through RF links in a multi-hop fashion. By properly balancing the load between these two classes of traffic, it is shown that this upper bound is tight when the maximum data rate ratio of FSO and RF transceivers, W₂/W₁, grows slower than √n. Under such circumstances, the capacity improvement with the support of FSO nodes, as compared with the results for RF wireless networks in [1], is evaluated. A significant capacity gain will be achieved if W₂/W₁m log m = Ω(n). The results characterize the number of super nodes and/or the FSO data rate necessary in order to cause a non-trivial increase in the per-node throughput.

Mobile sensors cover more area over a fixed period of time than do the same number of stationary sensors. However, the quality of coverage (QoC) achieved by mobile sensors depends on the velocity, mobility pattern, number of mobile sensors deployed, and the dynamics of the phenomenon being sensed. The gains attained by mobile sensors over static sensors and the optimal motion strategies for mobile sensors are not well understood. In this paper, we consider the following event capture problem: the events of interest arrive at certain points in the sensor field and disappear according to known arrival and departure time distributions. An event is said to be captured if it is sensed by one of the mobile sensors before it fades away. We analyze how the QoC scales with velocity, path, and number of mobile sensors. We characterize cases where the deployment of mobile sensors has no advantage over static sensors, and find the optimal velocity pattern that a mobile sensor should adopt. We also present algorithms for two motion planning problems: 1) for a single sensor, what is the sensor trajectory and the <i>minimum speed </i>required to satisfy a bound on the event loss probability and 2) for sensors with fixed speed, what is the <i>minimum number of sensors </i>required to satisfy a bound on the event loss probability. When the robots are restricted to move along a line or a closed curve, our algorithms return the optimal velocity for the minimum velocity problem. For the minimum sensor problem, the number of sensors used is within a factor of 2 of the optimal solution. For the case where the events occur at arbitrary points on a plane, we present heuristic algorithms for the aforementioned motion planning problems and bound their performance with respect to the optimal.

MAC protocols for wireless sensor networks employ periodic switching to low energy sleep state in order to enhance network lifetime. During the sleep state, the sensors do not perform energy consuming operations such as receiving and transmitting packets. During the normal state, CSMA based multi-access mechanism is the MAC protocol of choice in distributed, unsynchronized sensor networks. The energy conserving mechanism has a two-fold effect on delay in the network. On one hand it increases delay since many a times the intended receiver may be in sleep state and the transmitter has to delay the transmission to allow the receiver to wake up. On the other hand, since the sensors do not transmit in sleep state, the contention for channel is reduced which tends to improve delay. In this paper we present a queuing theoretic analysis of delay and capacity in sensor networks with uncoordinated sleep mechanism and characterize the energy-delay-capacity tradeoffs. We consider several sleep states which consume different levels of energy. We model sensor networks as queuing networks and evaluate closed form expressions for average packet delay and maximum achievable pernode throughput in terms of network parameters and sleep schedule. Comparisons with the performance of networks that do not employ any energy conserving mechanisms show that any of the energy conserving sleep states in the networks considered in this paper leads to considerable degradation in delay and capacity of the network.

Routing in communication networks involves the indirection from a persistent name (or ID) to a locator and delivering packets based upon the locator. In a large-scale, highly dynamic network, the ID-to-locator mappings are both large in number, and change often. Traditional routing protocols require high overhead to keep these indirections up-to-date. In this paper, we propose Weak State Routing (WSR), a routing mechanism for large-scale highly dynamic networks. WSR's novelty is that it uses random directional walks biased occasionally by weak indirection state information in intermediate nodes. The indirection state information is weak, i.e. interpreted not as absolute truth, but as probabilistic hints. Nodes only have partial information about the region a destination node is likely to be. This method allows us to aggregate information about a number of remote locations in a geographic region. In other words, the state information maps a set-of-IDs to a geographical region. The intermediate nodes receiving the random walk use a method similar to longest-prefix-match in order to prioritize their mappings to decide how to bias and forward the random walk. WSR can also be viewed as an unstructured distributed hashing technique. WSR displays good rare-object recall with scalability properties similar to structured DHTs, albeit with more tolerance to dynamism and without constraining the degree distribution of the underlying network. Through simulations, we show that WSR offers a high packet delivery ratio, more than 98The control packet overhead incurred in the network scales as O(N) for N-node networks. The number of mappings stored in the network appears to scale as Θ(N^3/2). We compare WSR with Dynamic Source Routing (DSR) and geographic forwarding (GPSR) combined with Grid Location Service (GLS). Our results indicate that WSR delivers more packets with less overhead at the cost of increased path length.

In this paper we analyze the average end-to-end delay and maximum achievable per-node throughput in random access multihop wireless ad hoc networks with stationary nodes. We present an analytical model that takes into account the number of nodes, the random packet arrival process, the extent of locality of traffic, and the back off and collision avoidance mechanisms of random access MAC. We model random access multihop wireless networks as open G/G/1 queuing networks and use the diffusion approximation in order to evaluate closed form expressions for the average end-to-end delay. The mean service time of nodes is evaluated and used to obtain the maximum achievable per-node throughput. The analytical results obtained here from the queuing network analysis are discussed with regard to similarities and differences from the well established information-theoretic results on throughput and delay scaling laws in ad hoc networks. We also investigate the extent of deviation of delay and throughput in a real world network from the analytical results presented in this paper. We conduct extensive simulations in order to verify the analytical results and also compare them against NS-2 simulations

In this paper we develop a model for random walk-based search mechanisms in unstructured P2P networks. This model is used to obtain analytical expressions for the performance metrics of random walk search in terms of the popularity of the resource being searched for and the random walk parameters. We propose an equation-based adaptive search mechanism that uses an estimate of the popularity of a resource in order to choose the parameters of random walk such that a targeted performance level is achieved by the search. We also propose a low-overhead method for maintaining an estimate of popularity that utilizes feedback (or lack there-off) obtained from previous searches. Simulation results show that the performance of the equation-based adaptive search is significantly better than the non-adaptive random walk and other straight-forward adaptive mechanisms

We present an information theoretic analysis of the minimum routing overhead incurred for reliable routing of packets using location-based routing. We formulate the minimum routing overhead problem as a rate-distortion problem and derive a lower bound on the minimum routing overhead incurred. We also characterize the deficit in transport capacity caused by the routing overheads. It is observed that for high mobility and packet arrival rates, the routing overheads may consume the entire capacity of a network.

In this paper we focus on characterizing the average end-to-end delay and maximum achievable per-node throughput in random access multihop wireless ad hoc networks with stationary nodes. We present an analytical model that takes into account the number of nodes, the random packet arrival process, the extent of locality of traffic, and the back off and collision avoidance mechanisms of random access MAC. We model random access multihop wireless networks as open G/G/1 queuing networks and use diffusion approximation to evaluate closed form expressions for the average end-to-end delay. The mean service time of nodes is derived and used to obtain the maximum achievable per-node throughput. The analytical results obtained here from the queuing network analysis are discussed with regard to similarities and differences from the well established information-theoretic results on throughput and delay scaling laws in ad hoc networks. We also investigate the extent of deviation of delay and achievable throughput in a real world network from the analytical results presented in this paper. We perform extensive simulations and verify that the analytical results closely match the results obtained from simulations.

Wireless mesh networks (WMNs) are emerging as a popular means of providing connectivity to communities in both affluent and poor parts of the world. The presence of backbone mesh routers and the use of multiple channels and interfaces allow mesh networks to have better capacity than infrastructure-less multihop ad hoc networks. In this paper we characterize the average delay and capacity in WMNs that utilize random medium access (MAC).We model residential area WMNs as open G/G/1 queuing networks. The analytical model takes into account the density of the mesh clients and mesh routers, the random packet arrival process, the degree of locality of traffic and the collision avoidance mechanism of random access MAC. The diffusion approximation method is used to obtain closed form expressions for (a) end-to-end packet delay and (b) maximum achievable per-node throughput. The analytical results describe how the performance of WMNs scales with the number of mesh routers and clients. The results obtained from simulations agree closely with the analytical results. For the asymptotic case (as the network size grows indefinitely), we discuss how the results obtained using the proposed queuing network framework compare against previous well known results on asymptotic capacity of infrastructure-less ad hoc networks.

In this paper, we study a novel “coverage by directional sensors” problem with tunable orientations on a set of discrete targets. We propose a Maximum Coverage with Minimum Sensors (MCMS) problem in which coverage in terms of the number of targets to be covered is maximized whereas the number of sensors to be activated is minimized. We present its exact Integer Linear Programming (ILP) formulation and an approximate (but computationally efficient) centralized greedy algorithm (CGA) solution. These centralized solutions are used as baselines for comparison. Then we provide a distributed greedy algorithm (DGA) solution. By incorporating a measure of the sensors residual energy into DGA, we further develop a Sensing Neighborhood Cooperative Sleeping (SNCS) protocol which performs adaptive scheduling on a larger time scale. Finally we evaluate the proposed solutions and protocol in terms of providing coverage and maximizing network lifetime through extensive simulations.

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Link reversal routing (LRR) is a local, distributed, and low-overhead technique used to maintain loop free routes in mobile wireless ad hoc networks. We explore the problem of load balancing the packet traffic in the network when using the LRR created routes. We study a fundamental LRR algorithm and identify usual situations which cause the load to be unbalanced. We propose three modifications to the LRR algorithm such that the load is distributed in a more uniform manner. The modifications preserve all the desirable qualities of LRR algorithms such as loop free routes, local response to topology change, low overhead and are completely distributed in nature. We perform simulations in order to evaluate the performance of the proposed modifications for both single-path and multi-path scenarios. The simulation results show that the modifications enable LRR to provide a much improved load balancing and ensure higher network lifetime.

In this paper we focus on characterizing the average end-to-end delay and maximum achievable per-node throughput in random access multihop wireless ad hoc networks with stationary nodes. We present an analytical model that takes into account the number of nodes, the random packet arrival process, the extent of locality of traffic, and the back off and collision avoidance mechanisms of random access MAC. We model random access multihop wireless networks as open G/G/1 queuing networks and use diffusion approximation to evaluate closed form expressions for the average end-to-end delay. The mean service time of nodes is derived and used to obtain the maximum achievable per-node throughput. The analytical results obtained here from the queuing network analysis are discussed with regard to similarities and differences from the well established information-theoretic results on throughput and delay scaling laws in ad hoc networks. We also investigate the extent of deviation of delay and achievable throughput in a real world network from the analytical results presented in this paper. We perform extensive simulations and verify that the analytical results closely match the results obtained from simulations

In order to adapt to the time-varying nature of wireless channels, various channel-adaptive schemes have been proposed to exploit inherent spatial diversity in wireless ad hoc networks where there are usually alternate forwarding nodes available at a given forwarding node. However, existing schemes along this line are designed based on heuristics, implying room for performance enhancement. Thereby, to seek a theoretical foundation for improving spatial diversity gain, we formulate the selection of the next-hop relay as a sequential decision problem and derive a general 'optimal stopping relaying (OSR)' framework for designing such spatial-diversity schemes. As a particular example, assuming Rayleigh fading channels, we implement an OSR strategy to optimize information efficiency (IE) in a protocol stack consisting of greedy perimeter stateless routing (GPSR) and IEEE 802.11 MAC protocols. We present an analysis of the algorithm for a single node. In addition, we perform extensive simulations (using QualNet) to evaluate the end-to-end performance of the proposed forwarding strategy. The results demonstrate the superiority of OSR over other existing schemes

In this paper, we propose an 'in-network' diversity combining scheme for image transport over wireless sensor networks. We consider a wireless sensor network with both wireless link impairments and node failures. We analyze two performance metrics of the proposed image transport scheme: energy consumption and received image quality distortion. Our analysis models key aspects of the network including forward error correction, path diversity, and the multi-hop nature of ad-hoc networks. The channel model used is a two-state Markov model describing errors on the bit level. We also use a two-state Markov model of node transitions between an 'on' and 'off' state. Reed-Solomon coding is used for forward error correction. Theoretical and simulation results show the robustness improvement. This work also helps in understanding the tradeoffs between image quality distortion and energy consumption as a function of various network parameters such as the number of hops between the source and the destination, the average channel error rate, and the average node failure rate. [All rights reserved Elsevier]

We study a novel 'coverage by directional sensors' problem with tunable orientations on a set of discrete targets. We propose a maximum coverage with minimum sensors (MCMS) problem in which coverage in terms of the number of targets to be covered is maximized whereas the number of sensors to be activated is minimized. We present its exact integer linear programming (ILP) formulation and an approximate (but computationally efficient) centralized greedy algorithm (CGA) solution. These centralized solutions are used as baselines for comparison. Then we provide a distributed greedy algorithm (DGA) solution. By incorporating a measure of the sensors residual energy into DGA, we further develop a sensing neighborhood cooperative sleeping (SNCS) protocol which performs adaptive scheduling on a larger time scale. Finally, we evaluate the properties of the proposed solutions and protocols in terms of providing coverage and maximizing network lifetime through extensive simulations. Moreover, for the case of circular coverage, we compare against the best known existing coverage algorithm

In this paper we focus on characterizing the average end-to-end delay and maximum achievable per-node throughput in random access multihop wireless ad hoc networks with stationary nodes. We present an analytical model that takes into account the number of nodes, the random packet arrival process, the extent of locality of traffic, and the back off and collision avoidance mechanisms of random access MAC. We model random access multihop wireless networks as open G/G/1 queuing networks and use the diffusion approximation in order to evaluate closed form expressions for the average end-to-end delay. The mean service time of nodes is evaluated and used to obtain the maximum achievable per-node throughput. The analytical results obtained here from the queuing network analysis are discussed with regard to similarities and differences from the well established information-theoretic results on throughput and delay scaling laws in ad hoc networks. We perform extensive simulations and verify that the analytical results closely match the results obtained from simulations.

Mobile sensors cover more area over a period of time than the same number of stationary sensors. However, the quality of coverage achieved by mobile sensors depends on the velocity, mobility pattern, number of mobile sensors deployed and the dynamics of the phenomenon being sensed. The gains attained by mobile sensors over static sensors and the optimal motion strategies for mobile sensors are not well understood. In this paper we consider the problem of event capture using mobile sensors. The events of interest arrive at certain points in the sensor field and fade away according to arrival and departure time distributions. An event is said to be captured if it is sensed by one of the mobile sensors before it fades away. For this scenario we analyze how the quality of coverage scales with the velocity, path and number of mobile sensors. We characterize the cases where the deployment of mobile sensors has no advantage over static sensors and find the optimal velocity pattern that a mobile sensor should adopt. We also present algorithms for two motion planning problems: (i) for a single sensor, what is the minimum speed and sensor trajectory required to satisfy a bound on event loss probability and (ii) for sensors with fixed speed, what is the minimum number of sensors required to satisfy a bound on event loss probability. When events occur only along a line or a closed curve our algorithms return optimal velocity for the minimum velocity problem. For the minimum sensor problem, the number of sensors used is within a factor two of the optimal solution. For the case where the events occur at arbitrary points on a plane we present heuristic algorithms for the above motion planning problems and bound their performance with respect to the optimal. The results of this paper have wide range of applications in areas like surveillance, wildlife monitoring, hybrid sensor networks and under-water sensor networks.

In this paper we develop a model for random walk search mechanism in unstructured P2P networks. Using the model we obtain analytical expressions for the performance metrics of random walk search in terms of the popularity of the resource being searched for and the parameters of random walk. We propose an equation based adaptive search mechanism that uses estimate of popularity of a resource in order to choose the parameters of random walk such that a targeted performance level is achieved by the search. We also propose a low-overhead method for maintaining an estimate of popularity that utilizes feedback (or lack there-off) obtained from previous searches. Simulation results show that the performance of equation based adaptive search is significantly better than the non-adaptive random walk.

In this paper, we propose an 'in-network' diversity combining scheme for image transport in wireless sensor networks. We consider a wireless sensor network with both wireless link impairments and node failures. We investigate two performance metrics of the proposed image transport scheme: energy consumption and received image quality distortion. Simulation results show that the proposed image transport scheme improves the robustness to network errors at the expense of low energy overhead. This improvement is more noticeable in case of high node failure probability and long distance between the source and the destination. Our work also helps in understanding the tradeoffs between image quality distortion and energy consumption with different network parameters such as the number of hops between the source and the destination, the average channel error rate, and the average node failure rate.

Efficient compression and transmission of images in a resource-constrained multihop wireless network is considered. Distributed image compression is proposed as a means to overcome the computation and/or energy limitation of individual nodes by sharing the processing of tasks. It has the additional benefit of extending the overall lifetime of the network by distributing the computational load among otherwise idle processors. Two design alternatives for energy efficient distributed image compression are proposed and investigated with respect to energy consumption and image quality. Simulation results show that the proposed scheme prolongs the system lifetime at a normalized total energy consumption comparable to the centralized image compression. [All rights reserved Elsevier]

In this paper, information theoretic techniques are used to derive analytic expressions for the minimum expected length of control messages exchanged by proactive routing in a two-level hierarchical ad hoc network. Several entropy measures are introduced and used to bound the memory size necessary for the storage of the routing tables. The entropy rates of the topology sequences are used to bound the communication routing overhead-both the interior routing overhead within a cluster and the exterior routing overhead across clusters. A scalability analysis of the routing overheads with regard to the number of nodes and the cluster size is provided under three different network scaling modes. Finally, practical design issues are studied by providing the optimal cluster sizes that asymptotically minimize (i) the memory requirement for each cluster head; (ii) the total control message routing overhead

This paper presents a mathematical and simulative framework for quantifying the overhead of reactive routing protocols, such as dynamic source routing and ad hoc on-demand distance vector, in wireless variable topology (ad hoc) networks. A model of the routing-layer traffic, in terms of the statistical description of the distance between a source and a destination, is presented. The model is used to study the effect of the traffic on the routing overhead. Two network models are analyzed; a Manhattan grid model for the case of regular node placement, and a Poisson model for the case of random node placement. We focus on situations where the nodes are stationary but unreliable. For each network model, expressions of various components of the routing overhead are derived as a function of the traffic pattern. Results are compared against ns-2 simulations, which corroborate the essential characteristics of the analytical results. One of the key insights that can be drawn from the mathematical results of this paper is that it is possible to design infinitely scalable reactive routing protocols for variable topology networks by judicious engineering of the traffic patterns to satisfy the conditions presented in this paper

The problem of energy efficient image transmission over a resource constrained multi-hop wireless network is considered. Two methods of data exchange in distributed wavelet transform are proposed and investigated with respect to energy consumption and image quality. An energy-balancing distributed JPEG2000 image compression scheme which uses a combination of tiling of images and load balancing by nodes rotation is proposed. Simulation results show that the proposed scheme prolongs the system lifetime by up to 4 times and has a normalized total energy consumption comparable to centralized image compression

We consider transmitting images in a multihop wireless network with the minimal total power consumption while satisfying an end-to-end image quality constraint. Contrary to popular belief, we show that maximum compression before transmission does not always provide minimal energy consumption, especially in the case of dense sensor networks with complex signal processing algorithms. We formulate the minimal energy transmission problem as an optimization problem and present a heuristic algorithm for it. The proposed algorithm selects the optimal image compression parameters to minimize total energy dissipation given the network conditions and image quality constraints. Simulation results show up to 80% reduction in the total power consumption achieved by using the proposed adaptive algorithm compared to nonadaptive algorithms

While several cluster based routing algorithms have been proposed for ad hoc networks, there is a lack of formal mathematical analysis of these algorithms. Specifically, there is no published investigation of the relation between routing overhead on one hand and route request pattern (traffic) on the other. This paper provides a mathematical framework for quantifying the overhead of a cluster-based routing protocol. We explicitly model the application-level traffic in terms of the statistical description of the number of hops between a source and a destination. The network topology is modelled by a regular two-dimensional grid of unreliable nodes, and expressions for various components of the routing overhead are derived. The results show that clustering does not change the traffic requirement for infinite scalability compared to flat protocols, but reduces the overhead by a factor of O(1/M) where M is the cluster size. The analytic results are validated against simulations of random network topologies running a well known (D-hop max-min) clustering algorithm

This paper focuses on Bluetooth, a promising new wireless technology, developed mainly as a cable replacement. We argue that, in practice, Bluetooth devices will have different power capabilities, classifying them as either high-power or low-power nodes. We propose a deterministic, distributed algorithm that accounts for the physical properties of devices, connecting nodes into a scatternet of small diameter. The proposed protocol results in a high effective throughput and allows components to arrive and leave arbitrarily, dynamically updating the cluster formation. Performance is evaluated through extensive ns-2 simulations.

In this paper, we define the routing overhead as the amount of information needed to describe the changes in a network topology. We derive a universal lower bound on the routing overhead in a mobile ad-hoc network. We also consider a prediction-based routing protocol that attempts to minimize the routing overhead by predicting the changes in the network topology from the previous mobility pattern of the nodes.We apply our approach to a mobile ad-hoc network that employs a dynamic clustering algorithm, and derive the optimal cluster size that minimizes the routing overhead, with and without mobility prediction. We believe that this work is a fundamental and essential step towards the rigorous modeling, design and performance comparisons of protocols for ad-hoc wireless networks by providing a universal reference performance curve against which the overhead of different routing protocols can be compared.

In coding theory, a channel coding algorithm is good if it achieves the Shannon capacity [1]. Similarly, we seek to derive a universal curve against which we can measure how good (or bad) a variable topology routing protocol (e.g. for ad-hoc networks) performs, in comparison with a theoretical minimum routing overhead, which is the amount of information needed to describe the changes in a dynamic network topology.

An analytical model of TCP (Transport Control Protocol) over an end-to-end path with random abrupt round-trip time (RTT) changes is presented. Modeling the RTT as a stochastic process, we analytically quantify and compare between the degree of degradation of the steady-state average throughput and window size due to spurious retransmissions for the different versions of TCP (Reno/NewReno versus Tahoe). The modeling methodology in this paper is used for evaluating different design alternatives for TCP for highly dynamic networks

A link model-driven approach toward transmission control protocol (TCP) performance over a wireless link is presented. TCP packet loss behavior is derived from an underlying two-state continuous time Markov model. The approach presented here is (to our knowledge) the first that simultaneously considers (1) variability of the round-trip delay due to buffer queueing; (2) independent and nonindependent (bursty) link errors; (3) TCP packet loss due to both buffer overflow and channel errors; and (4) the two modes of TCP packet loss detection (duplicate acknowledgments and timeouts). The analytical results are validated against simulations using the ns-2 simulator for a wide range of parameters; slow and fast fading links; small and large link bandwidth-delay products. For channels with memory, an empirical rule is presented for categorizing the impact of channel dynamics (fading rate) on TCP performance

This paper presents a new mathematical and simulative framework for quantifying the overhead of a broad class of reactive routing protocols, such as DSR and AODV, in wireless variable topology (ad-hoc) networks. We focus on situations where the nodes are stationary but unreliable, as is common in the case of sensor networks. We explicitly model the application-level traffic in terms of the statistical description of the number of hops between a source and a destination. The sensor network is modelled by an unreliable regular Manhattan (i.e. degree four) grid, and expressions for various components of the routing overhead are derived. Results are compared against ns-2 simulations for regular and random topologies, which corroborate the essential characteristics of the analytical results. One of the key insights that can be drawn from the mathematical results of this paper is that it is possible to design infinitely scalable reactive routing protocols for variable topology networks by judicious engineering of the traffic patterns to satisfy the conditions presented in this paper.

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This paper focuses on Bluetooth, a promising new wireless technology, developed mainly as a cable replacement. We argue that, in practice, Bluetooth devices will have different power capabilities, classifying them as either high-power or low-power nodes. We propose a deterministic, distributed algorithm that accounts for the physical properties of devices, connecting nodes into a scatternet of small diameter. The proposed protocol results in a high effective throughput and allows components to arrive and leave arbitrarily, dynamically updating the cluster formation. Performance is evaluated through extensive ns-2 simulations.

An analytical framework for modeling a network of random early detection (RED) queues with mixed traffic types (e.g. TCP and UDP) is developed. Expressions for the steady-state goodput for each flow and the average queuing delay at each queue are derived. The framework is extended to include a class of RED queues that provides differentiated services for flows with multiple classes. Finally, the analysis is validated against ns simulations for a variety of RED network configurations where it is shown that the analytical results match with those of the simulations within a mean error of 5%. Several new analytical results are obtained; TCP throughput formula for a RED queue; TCP timeout formula for a RED queue and the fairness index for RED and tail drop

This paper provides a preliminary investigation of the effect of abrupt round-trip variations on the performance of different versions of TCP. It is shown that end-to-end goodput of a bulk TCP transfer can be severely limited by variations in RTT primarily due to the non-adaptiveness of TCP's timeout estimation and fast recovery thresholds. The paper proposes a model for evaluating the performance of TCP in environments with abrupt RTT changes and random packet loss and outlines possible future TCP improvements

An analytical framework for multiple TCP flows sharing a bottleneck link under the Random Early Detection (RED) regime is developed. Closed form expressions for the steady state throughput and average queueing delay are derived and verified by simulations; these show that RED significantly improves the inherent TCP bias against links with higher round-trip delays as compared to Tail Drop, contrary to prevailing belief. Further, we derive closed form bounds on the minimum average queuing delay achievable through a RED gateway with no deterministic packet drop.

An analytical framework for modeling the performance of a single TCP session in the presence of random packet loss is presented. A Markovian approach is developed that allows us to study both memoryless channels (IID packet loss) and channels with memory (correlated packet loss) modeled by a two-state continuous-time Gilbert model. The analytical results are validated against results using the ns simulator. It is shown that the model predicts throughput for LAN/WAN (low and high bandwidth-delay products) with good accuracy. Further, throughput for the IID loss model is found to be relatively insensitive to the probability density function (PDF) of the loss inter-arrival process. For channels with memory, we present an empirically validated rule of thumb to categorize the channel transition frequency

An analytical framework for modeling the performance of a single TCP session in the presence of random packet loss is presented that is based on a semi-Markov model for the window size evolution. The model predicts the throughput for LAN/WAN (low and high bandwidth-delay products) with good accuracy, as compared against simulation results with the ns simulator. Generally, higher speed channels are found be more vulnerable to random loss than slower channels, especially for moderate to high loss rates