International Journal of Advanced Computing and Communication Systems

Jamming-Aware Traffic Allocation for Multiple-Path routing using reinforcement Learning Algorithm

Saradha S and Sangeetha Priya M, Sri Eshwar College of Engineering, Coimbatore, TamilNadu, India.

International Journal of Advanced Computing and Communication Systems

ISSN (Online) : 2347 - 9299

ISSN (Print) : 2347 - 9280

Received On :

Revised On :

Accepted On :

Published On :

Volume 03, Issue 01

Page No : 022-025

Abstract

Multiple-path source routing protocols allow a data source node to distribute the total traffic among available paths .Thisrate/power control. First, we perform an in-depth measurement- based experimental study on our indoor test-bed to quantify the paper proposes technique for the network odes to estimate and characterize the impact of jamming and for a source node to incorporate these estimates into its traffic allocation. And we have shown that in multi-source networks, this unified optimization problem can be solved using a distributed impact of jamming when employing rate and/or power control. With rate control, a spreader can increase or lower its broadcast rate depending on the experiential packet delivery ratio (PDR) at the receiver. Designing ARES, a novel anti-jamming system. The above algorithm based on decomposition in network utility maximization. We express this traffic allo ation as a lossy network flow optimization problem using ortfolio selection theory from financial statistics which allow individual network nodes to locally characterize the jamming impact and aggregate this information for the source nodes. We prove that the use of portfolio selection theory allows the data sources to balance the expected data throughput with the uncertainty in achievable traffic rates.

Keywords

Traffic Allocation, Multi-Source Networks, Power Control, Connectivity, packet delivery ratio.

Cite this Article

Saradha S and Sangeetha Priya M, ”Jamming-Aware Traffic Allocation for Multiple-Path routing using reinforcement Learning Algorithm, ”International Journal of Advanced Computing and Communication Systems,pp. 022-025, March, 2016.

Copyright

© 2016 Saradha S and Sangeetha Priya M. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.