Title :
Experience Based Sink Placement in Mobile Wireless Sensor Network
Author :
Banerjee, Subhra ; Bhunia, Suman Sankar ; Mukherjee, Nandini
Author_Institution :
Alumnus Software Ltd., Kolkata, India
Abstract :
In some applications of wireless sensor networks (WSN), sensor nodes are mobile while the sinks are static. In such dynamic environment, situations may arise where many sensor nodes are forwarding data through the same sink node resulting in sink overloading. One of the obvious effects of sink overloading is packet loss. It also indirectly affects the network lifetime in loss-sensitive WSN applications. Therefore, proper placement of sinks in such dynamic environment has a great impact on the performance of WSN applications. Multiple sink placement may not also work in some situations as node density may not be uniform. This paper introduces a sink placement scheme that aims at gathering experiences about sensor node density in region at different times and based on these observations, the scheme proposes candidate sink locations in order to reduce sink overloading. Next, based upon current sensor node density pattern, sinks at these locations are scheduled to active mode, while sinks at remaining candidate locations are scheduled to sleep mode. The second phase is repeated periodically. The scheme is implemented in a simulation environment and compared with another well-known strategy, namely Geographic Sink Placement (GSP). It has been observed that the proposed scheme exhibits better performance with respect to sink overloading and packet loss in comparison with GSP.
Keywords :
mobile radio; telecommunication scheduling; wireless sensor networks; loss-sensitive WSN scheduling applications; mobile wireless sensor network node density; packet loss; sink overloading; sink placement scheme; Clustering algorithms; Medical services; Mobile communication; Mobile computing; Packet loss; Wireless sensor networks; Dynamic Wireless Sensor Networks; Experience Gathering; Mobile Sensor Nodes; Multiple Sink Placement; Node Density;
Conference_Titel :
Cluster, Cloud and Grid Computing (CCGrid), 2015 15th IEEE/ACM International Symposium on
Conference_Location :
Shenzhen
DOI :
10.1109/CCGrid.2015.57