In order to overcome the energy hole problem in some wireless sensor networks (WSNs), lifetime optimization algorithm with mobile sink nodes for wireless sensor networks (LOA MSN) is proposed. In LOA MSN, hybrid positioning algorithm of satellite positioning and RSSI positioning is proposed to save energy. Based on location information, movement path constraints, flow constraint, energy consumption constraint, link transmission constraint, and other constraints are analyzed. Network optimization model is established and decomposed into movement path selection model and lifetime optimization model with known grid movement paths. Finally, the two models are solved by distributed method. Sink nodes gather data of sensor nodes along the calculated paths. Sensor nodes select father nodes and transmit data to corresponding sink node according to local information. Simulation results show that LOA MSN makes full use of node energy to prolong network lifetime. LOA MSN with multiple sink nodes also reduces node energy consumption and data gathering latency. Under certain conditions, it outperforms MCP, subgradient algorithm, EASR, and GRAND. [12] divides network into several grids, and proposes a gridbased clustering algorithm. Reference [13] proposes range constrained clustering (RCC). RCC divides nodes into several clusters. Sink node stays at the cluster centers to gather data. The Concorde TSP solver is used to calculate the shortest movement path of sink node through some cluster centers. References [11] [12] [13] determine the locations of mobile sink node. However, they do not consider the data gathering when sink node is moving. Whether the algorithms can obtain optimal solution still needs theoretical analysis. Reference [14] proposes energy-aware sink relocation (EASR) algorithm for mobile sinks. EASR uses maximum capacity path (MCP) protocol for routing, starts to move when two relocation conditions are met, and finds the next moving location which has the greatest weight value. But compared with network lifetime, the relocation conditions are met after a long time. The protocol is not good at prolonging network lifetime. Therefore, lifetime optimization algorithm with mobile sink nodes for wireless sensor networks based on location information (LOA MSN) is proposed. In LOA MSN, energysaving positioning algorithm of nodes is proposed and the monitoring area is divided into several grids of the same size. Sink node can move into each grid center to gather data. The movement path constraints, flow constraint, energy consumption constraint, link transmission constraint, and other constraints are analyzed. The network optimization model is established. Then, the network optimization model is decomposed into movement path selection model and network lifetime optimization model with known movement paths. The movement path selection model is solved in sink nodes by distributed clustering method and graph theory method. Mobile gathering and static gathering are considered and the network lifetime optimization model is approximately solved by distributed graph theory method. Compared with MCP, subgradient algorithm, EASR and GRAND (for grid random scheme), LOA MSN uses the node energy as much as possible to prolong the network lifetime. The remaining parts of paper are organized as follows. In Section 2, the energy-saving positioning algorithm of nodes is proposed. In Section 3, the algorithm assumption and lifetime optimization model with mobile sink nodes are proposed. In Section 4, the distributed solution of model is proposed. In Section 5, the simulation results are presented. In Section 6, the paper is concluded.
In REF , authors proposed a Lifetime Optimization Algorithm with Mobile Sink Nodes for WSNs based on location information (LOA MSN).
Lifetime Optimization Algorithm with Mobile Sink Nodes for Wireless Sensor Networks Based on Location Information
International Journal of Distributed Sensor Networks
Computer Science