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Multiple-path source routing protocols allow a data source node to distribute the total traffic among available paths. In this article, we consider the problem of jamming-aware source routing in which the source node performs traffic allocation based on empirical jamming statistics at individual network nodes. We formulate this traffic allocation as a lossy network flow optimization problem using portfolio selection theory from financial statistics. We show that in multi-source networks, this centralized optimization problem can be solved using a distributed algorithm based on decomposition in network utility maximization (NUM). We demonstrate the network’s ability to estimate the impact of jamming and incorporate these estimates into the traffic allocation problem. Finally, we simulate the achievable throughput using our proposed traffic allocation method in several scenarios.
Dr. M. Karunakar Reddy. 2012. \u201cPortfolio Selection in Multipath Routing for Traffic Allocation\u201d. Global Journal of Computer Science and Technology - E: Network, Web & Security GJCST-E Volume 12 (GJCST Volume 12 Issue E14): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
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Total Score: 107
Country: India
Subject: Global Journal of Computer Science and Technology - E: Network, Web & Security
Authors: Dr. M. Karunakar Reddy, S. Nageswara Rao (PhD/Dr. count: 1)
View Count (all-time): 253
Total Views (Real + Logic): 10087
Total Downloads (simulated): 2642
Publish Date: 2012 10, Sat
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Multiple-path source routing protocols allow a data source node to distribute the total traffic among available paths. In this article, we consider the problem of jamming-aware source routing in which the source node performs traffic allocation based on empirical jamming statistics at individual network nodes. We formulate this traffic allocation as a lossy network flow optimization problem using portfolio selection theory from financial statistics. We show that in multi-source networks, this centralized optimization problem can be solved using a distributed algorithm based on decomposition in network utility maximization (NUM). We demonstrate the network’s ability to estimate the impact of jamming and incorporate these estimates into the traffic allocation problem. Finally, we simulate the achievable throughput using our proposed traffic allocation method in several scenarios.
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