2017
DOI: 10.1049/iet-com.2015.1170
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Efficient coding for unicast flows in opportunistic wireless networks

Abstract: In this paper we consider the scenario of multiple unicast flows intersecting a common router in an opportunistic wireless network. Instead of forwarding packets in each of the flows independently, the router can perform inter-session network coding and transmit codewords to improve the network throughput. Unlike coding for multicast data flow for which an optimal code can be constructed in polynomial time, coding for unicast data flows is a more complicated coding problem and has been shown to be an NP-hard p… Show more

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Cited by 3 publications
(3 citation statements)
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“…Many researchers used the DCAR idea to design different routing schemes for a more complex wireless network. However, choosing when, where, and which packets to encode in wireless networks is an NP-hard problem [28]. Moreover, PCC may cause partial network congestion in a more complex wireless network, in which the decoding nodes are also the coding nodes or the decoding nodes are too close to the coding nodes.…”
Section: Related Workmentioning
confidence: 99%
“…Many researchers used the DCAR idea to design different routing schemes for a more complex wireless network. However, choosing when, where, and which packets to encode in wireless networks is an NP-hard problem [28]. Moreover, PCC may cause partial network congestion in a more complex wireless network, in which the decoding nodes are also the coding nodes or the decoding nodes are too close to the coding nodes.…”
Section: Related Workmentioning
confidence: 99%
“…Awais et. al [10] proposed an algorithm to piggyback a message which is sparsely connected to cycles of length k on the given graph G.…”
Section: Introductionmentioning
confidence: 99%
“…Similarly, The (k, k)th entry of the matrix A n gives the number of cycles of length n, which pass through x k . These properties of adjacency matrix were used in [10] to give an algorithm to piggyback a message which is sparsely connected to cycles of length n on the given side-information graph G.…”
Section: Introductionmentioning
confidence: 99%