2016
DOI: 10.1145/2812811
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Distributed Algorithms for End-to-End Packet Scheduling in Wireless Ad Hoc Networks

Abstract: Packet scheduling is a particular challenge in wireless networks due to interference from nearby transmissions. A distance-2 interference model serves as a useful abstraction here, and we study packet routing and scheduling under this model of interference. The main focus of our work is the development of fully distributed (decentralized) protocols. We present polylogarithmic/constant factor approximation algorithms for various families of disk graphs (which capture the geometric nature of wireless-signal prop… Show more

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Cited by 8 publications
(11 citation statements)
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“…Under the protocol model, graph-based scheduling algorithms employing implicit or explicit coloring strategies are widely used, e.g., [73,74]. In [75,76], greedy-type heuristic algorithms are developed for the MTSP.…”
Section: Solutionsmentioning
confidence: 99%
“…Under the protocol model, graph-based scheduling algorithms employing implicit or explicit coloring strategies are widely used, e.g., [73,74]. In [75,76], greedy-type heuristic algorithms are developed for the MTSP.…”
Section: Solutionsmentioning
confidence: 99%
“…in packet scheduling (Kumar et al [2004]), channel assignment (Kodialam and Nandagopal [2005]) or link scheduling (Gandham et al [2005]). Many wireless and ad hoc networks are modeled by Unit Disk Graphs (UDGs), where nodes are embedded in the plane and two nodes are adjacent if and only if their Euclidean distance is at most one.…”
Section: Introductionmentioning
confidence: 99%
“…We notice that most solution methods proposed so far focus on polynomial time algorithms that achieve provably good performance in the worst case. Unfortunately these methods are not suitable for practical implementations; in fact they are centralized and/or require solving complex combinatorial optimization problems [5,15,16]. Since sensors have limited computational power and are unable to perform sophisticated coordination activities, sophisticated algorithms that require solving complex combinatorial optimization problems are impractical for implementations and have mainly theoretical interest.…”
Section: Introductionmentioning
confidence: 99%
“…A relevant parameter that has been considered in the literature is ∆, the maximum degree of a node in the network [3,15,16]. We assume that all nodes know ∆ (or an upper bound on it); we observe that such an information can be easily obtained once the routing tree has been constructed.…”
Section: Introductionmentioning
confidence: 99%
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