Results 1  10
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11
Crosslayer analysis of the endtoend delay distribution in wireless sensor networks
 in Proc. IEEE RTSS
, 2009
"... Abstract—Emerging applications of wireless sensor networks (WSNs) require realtime qualityofservice (QoS) guarantees to be provided by the network. Due to the nondeterministic impacts of the wireless channel and queuing mechanisms, probabilistic analysis of QoS is essential. One important metric ..."
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Cited by 17 (2 self)
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Abstract—Emerging applications of wireless sensor networks (WSNs) require realtime qualityofservice (QoS) guarantees to be provided by the network. Due to the nondeterministic impacts of the wireless channel and queuing mechanisms, probabilistic analysis of QoS is essential. One important metric of QoS in WSNs is the probability distribution of the endtoend delay. Compared to other widely used delay performance metrics such as the mean delay, delay variance, and worstcase delay, the delay distribution can be used to obtain the probability to meet a specific deadline for QoSbased communication in WSNs. To investigate the endtoend delay distribution, in this paper, a comprehensive crosslayer analysis framework, which employs a stochastic queueing model in realistic channel environments, is developed. This framework is generic and can be parameterized for a wide variety of MAC protocols and routing protocols. Case studies with the CSMA/CA MAC protocol and an anycast protocol are conducted to illustrate how the developed framework can analytically predict the distribution of the endtoend delay. Extensive testbed experiments and simulations are performed to validate the accuracy of the framework for both deterministic and random deployments. Moreover, the effects of various network parameters on the distribution of endtoend delay are investigated through the developed framework. To the best of our knowledge, this is the first work that provides a generic, probabilistic crosslayer analysis of endtoend delay in WSNs. Index Terms — Delay distribution, quality of service (QoS), realtime systems, wireless sensor networks. I.
Nonasymptotic throughput and delay distributions in multihop wireless networks
 In Allerton Conference on Communications, Control and Computing
, 2010
"... Abstract—The class of GuptaKumar results give the asymptotic throughput in multihop wireless networks but cannot predict the throughput behavior in networks of typical size. This paper addresses the nonasymptotic analysis of the multihop wireless communication problem and provides, for the firs ..."
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Cited by 8 (4 self)
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Abstract—The class of GuptaKumar results give the asymptotic throughput in multihop wireless networks but cannot predict the throughput behavior in networks of typical size. This paper addresses the nonasymptotic analysis of the multihop wireless communication problem and provides, for the first time, closedform results on multihop throughput and delay distributions. The results are nonasymptotic in that they hold for any number of nodes and also fully account for transient regimes, i.e., finite time scales, delays, as well as bursty arrivals. Their accuracy is supported by the recovery of classical singlehop results, and also by simulations from empirical data sets with realistic mobility settings. Moreover, for a specific network scenario and a fixed pair of nodes, the results confirm GuptaKumar’s Ω
On the catalyzing effect of randomness on the perflow throughput in wireless networks. Technical report. Available from http://net.tlabs.tuberlin.de/∼florin/lib/randnet.pdf and also from arXiv.org
, 2013
"... Abstract—This paper investigates the throughput capacity of a flow crossing a multihop wireless network, whose geometry is characterized by general randomness laws including Uniform, Poisson, HeavyTailed distributions for both the nodes ’ densities and the number of hops. The key contribution is t ..."
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Cited by 2 (2 self)
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Abstract—This paper investigates the throughput capacity of a flow crossing a multihop wireless network, whose geometry is characterized by general randomness laws including Uniform, Poisson, HeavyTailed distributions for both the nodes ’ densities and the number of hops. The key contribution is to demonstrate how the perflow throughput depends on the distribution of 1) the number of nodes Nj inside hops ’ interference sets, 2) the number of hops K, and 3) the degree of spatial correlations. The randomness in both Nj ’s and K is advantageous, i.e., it can yield larger scalings (as large as Θ(n)) than in nonrandom settings. An interesting consequence is that the perflow capacity can exhibit the opposite behavior to the network capacity, which was shown to suffer from a logarithmic decrease in the presence of randomness. In turn, spatial correlations along the endtoend path are detrimental by a logarithmic term. I.
Combining Analytical and Simulation Approaches for Estimating EndtoEnd Delay in Multihop Wireless Networks
, 2012
"... Abstract—In this work, we present an empirical support of an analytical approach which employs a frequency domain analysis for estimating endtoend delay in multihop networks. The proposed analytical results of the endtoend delay distribution are validated through simulation and compared with qu ..."
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Cited by 1 (0 self)
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Abstract—In this work, we present an empirical support of an analytical approach which employs a frequency domain analysis for estimating endtoend delay in multihop networks. The proposed analytical results of the endtoend delay distribution are validated through simulation and compared with queueing based analysis by defining two concrete scenarios. Our results demonstrate that an analytical prediction schema is insufficient to provide an adequate estimation of the endtoend delay distribution function, but it requires to be combined with a simulation method for detailed links and nodes latencies distribution. Index Terms—communication Reliability, endtoend delay, latency, estimation, queueing delay.
A LowComplexity Congestion Control and Scheduling Algorithm for Multihop Wireless Networks with OrderOptimal PerFlow Delay
, 2012
"... Abstract—Quantifying the endtoend delay performance in multihop wireless networks is a wellknown challenging problem. In this paper, we propose a new joint congestion control and scheduling algorithm for multihop wireless networks with fixedroute flows operated under a general interference model ..."
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Abstract—Quantifying the endtoend delay performance in multihop wireless networks is a wellknown challenging problem. In this paper, we propose a new joint congestion control and scheduling algorithm for multihop wireless networks with fixedroute flows operated under a general interference model with interference degree K. Our proposed algorithm not only achieves a provable throughput guarantee (which is close to at least 1=K of the system capacity region), but also leads to explicit upper bounds on the endtoend delay of every flow. Our endtoend delay and throughputbounds are in simple and closed forms, and they explicitly quantify the tradeoff between throughput and delay of every flow. Further, the perflow endtoend delay bound increases linearly with the number of hops that the flow passes through, which is orderoptimal with respect to the number of hops. Unlike traditional solutions based on the back
Analysis of Wireless MultiHop Broadcasting: Optimal and Approximate Solutions and Applications
, 2015
"... ii In this work, we design and analyze transmission range assignments for broadcasting in wireless multihop networks. Moreover, we study different features of wireless networks. We consider network scenarios in which the exact location of the nodes is known and others where the nodes location is k ..."
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ii In this work, we design and analyze transmission range assignments for broadcasting in wireless multihop networks. Moreover, we study different features of wireless networks. We consider network scenarios in which the exact location of the nodes is known and others where the nodes location is known probabilistically. For the former, we propose optimal and nearoptimal algorithms to solve the MinimumEnergy Broadcasting problem for linear (onedimensional) networks. We further extend our solutions to encompass cross networks, in which the nodes are located on two perpendicular lines. The proposed algorithms have polynomialtime complexity, and are shown to perform better than previously known algorithms (for some cases, they are the first polynomialtime solutions). For probabilistic networks, we propose a transmission range assignment such that for a given average total consumed power, the linear network is connected with high probability. We then analyze some features of these networks, including derivation
Photonic Network Communications manuscript No. (will be inserted by the editor) A Simple Analytical ThroughputDelay Model for Clustered FiWi Networks
, 2014
"... Abstract A FiberWireless (FiWi) network integrates a passive optical network (PON) with wireless mesh networks (WMNs) to provide high speed backhaul via the PON while offering the flexibility and mobility of a WMN. Generally, increasing the size of a WMN leads to higher wireless interference and lo ..."
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Abstract A FiberWireless (FiWi) network integrates a passive optical network (PON) with wireless mesh networks (WMNs) to provide high speed backhaul via the PON while offering the flexibility and mobility of a WMN. Generally, increasing the size of a WMN leads to higher wireless interference and longer packet delays. We examine the partitioning of a large WMN into several smaller WMN clusters, whereby each cluster is served by an Optical Network Unit (ONU) of the PON. Existing WMN throughputdelay analysis techniques considering the mean load of the nodes at a given hop distance from a gateway (ONU) are unsuitable for the heterogeneous nodal traffic loads arising from clustering. We introduce a simple analytical queuing model that considers the individual node loads to accurately characterize the throughputdelay performance of a clustered FiWi network. We verify the accuracy of the model through extensive simulations. We employ the model to examine the impact of the number of clusters on the network throughputdelay performance. We find that with sufficient PON bandwidth, clustering substantially improves the FiWi network throughputdelay performance.
1 Approximation Algorithms for Throughput Maximization in Wireless Networks with Delay Constraints
"... Abstract—We study the problem of throughput maximization in multihop wireless networks with endtoend delay constraints for each session. This problem has received much attention starting with the work of Grossglauser and Tse (2002), and it has been shown that there is a significant tradeoff betw ..."
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Abstract—We study the problem of throughput maximization in multihop wireless networks with endtoend delay constraints for each session. This problem has received much attention starting with the work of Grossglauser and Tse (2002), and it has been shown that there is a significant tradeoff between the endtoend delays and the total achievable rate. We develop algorithms to compute such tradeoffs with provable performance guarantees for arbitrary instances, with general interference models. Given a target delaybound ∆(c) for each session c, our algorithm gives a stable flow vector with a total throughput within a factor of O () log∆m of the maximum, so that the loglog∆m persession (endtoend) delay is O ( ( log∆m loglog∆m ∆(c))2) , where ∆m = maxc{∆(c)}; note that these bounds depend only on the delays, and not on the network size, and this is the first such result, to our knowledge.