Paper Info
Title
Traffic Prediction-Based Fast Rerouting Algorithm For Wireless Multimedia Sensor Networks
Abstract
Rerouting has become an important challenge to Wireless Multimedia Sensor Networks (WMSNs) due to the constraints on energy, bandwidth, and computational capabilities of sensor nodes and frequent node and link failures. In this paper, we propose a traffic prediction-based fast rerouting algorithm for use between the cluster heads and a sink node in WMSNs (TPFR). The proposed algorithm uses the autoregressive moving average (ARMA) model to predict a cluster head's network traffic. When the predicted value is greater than the predefined network traffic threshold, both adaptive retransmission trigger (ART) that contributes to switch to a better alternate path in time and trigger efficient retransmission behaviors are enabled. Performance comparison of TPFR with ant-based multi-QoS routing (AntSensNet) and power efficient multimedia routing (PEMuR) shows that they: (a) maximize the overall network lifespan by load balancing and not draining energy from some specific nodes, (b) provide high quality of service delivery for multimedia streams by switching to a better path towards a sink node in time, (c) reduce useless data retransmissions when node failures or link breaks occur, and (d) maintain lower routing overhead.
Year
DOI
Venue
2013
10.1155/2013/176293
INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS
Field
DocType
Volume
Autoregressive–moving-average model,Computer science,Retransmission,Load balancing (computing),Wireless multimedia sensor networks,Quality of service,Algorithm,Computer network,Real-time computing,Bandwidth (signal processing),Traffic prediction,Sink (computing)
Journal
2013
Issue
ISSN
Citations 
null
1550-1477
4
PageRank 
References 
Authors
0.42
12
3
Name
Order
Citations
PageRank
Zhiyuan Li11380155.70
Jun-lei Bi2103.58
Siguang Chen36312.91