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A Tracking Assisted Relaying Scheme for Decentralized Wireless Networks

Authors:
Baohua Shao
Mark Leeson

Keywords: Store-Carry and Forward; Decentralized Wireless Networks; Kalman Filter

Abstract:
We present a computationally simple approach for mobile node motion recognition and prediction in decentralized wireless networks. The ability to observe and analyze movement data and infer targeted mobile subscriber motion strategies offers performance gains in Delay Tolerant Networks (DTNs). The method here offers new mechanisms for the Store-Carry and Forward Relaying Scheme to create opportunities for the system to increase its overall performance. The motion data are processed by the Kalman Filter (KF) algorithm, which may be viewed as a series of prediction, tracking and smoothing calculations of the movement of mobile subscribers. The outcomes illustrate that the algorithm performs well on prediction and tracking the motion of mobile users. A Java based routing protocol implementation of the KF algorithm offers a delivery probability of at least 0.7 and a mean hop count of between 2.1 and 3.7 for small and large networks, respectively. For modest node densities, between 60% and 80% of the messages will be delivered but after a substantial delay. Thus, the approach described will be of benefit in data collection as part of the Internet of Things and small sensor networks.

Pages: 1 to 6

Copyright: Copyright (c) IARIA, 2017

Publication date: November 12, 2017

Published in: conference

ISSN: 2326-9383

ISBN: 978-1-61208-602-6

Location: Barcelona, Spain

Dates: from November 12, 2017 to November 16, 2017