Abstract
Improving network lifetime is the fundamental challenge of wireless sensor networks. One possible solution consists in making use of mobile sinks. Sink mobility along a constrained path can improve the energy efficiency in wireless sensor networks. However, due to the path constraint, a mobile sink with constant speed has limited communication time to collect data from the sensor nodes deployed randomly. This poses significant challenges in jointly improving the amount of data collected and reducing the energy consumption. This paper proposes a data collection scheme, called the Maximum Amount Shortest Path (MASP), to address this issue that increases network throughput as well as conserves energy by optimizing the assignment of sensor nodes.MASP is formulated as an integer linear programming problem and then solved with the help of improved ant colony optimization. The residual energy of each node is calculated and the optimal path is selected by considering the shortest path, residual energy, channel noise, and delay. This approach is validated through simulation experiments using NS2
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