Using Multiple Path-Constraint Mobile Sinks for Energy Efficient Data Collection in Wireless Sensor Networks
Data collection is a fundamental task of WSN. It aims to collect sensor readings in a sensory field through sinks for analysis and processing. Research has shown that sinks deplete most of the battery power for collecting the data than processing it. Non-uniform energy consumption causes degraded network performance and shortens network lifetime. Recently, sink mobility with limited path has been exploited to reduce and balance the energy expenditure among sensors. This paper addresses this issue and proposes a new data collection scheme, which enhances the Maximum Amount Shortest Path (MASP) for multiple mobile sinks. This scheme increases network throughput and streamlining the energy consumption by optimizing the assignment of sensor nodes to subsinks and subsinks to mobile sinks, using Genetic Algorithm.