A Data Gathering Algorithm Based on Mobile Agent and Emergent Event-Driven in Cluster-Based WSN
In order to improve energy efficiency and decrease network delay in wireless sensor network applied to emergent event monitoring, a new data gathering algorithm based on mobile agent and event-driven is proposed for cluster-based wireless sensor network. The process of dynamically clustering the sensor nodes is based on the event severity degree, by which the scale and lifetime of clusters are determined. And a multi-hop virtual cluster is formed between the base station and the cluster heads in which the base station is regarded as its cluster head. The order of nodes visited along the route by mobile agent has a significant impact on the algorithm efficiency and the lifetime for wireless sensor network. In this paper, the next hop in route planning for mobile agents is determined by the residual energy, the path loss and the stimulated intensity. The mobile agents can gather information by traversing all member nodes. The theory analysis and simulation results show that mobile-agent-based model has a better performance in energy consumption and network delay compared to C/S model. And mobile agent is more suitable for wireless sensor network than C/S model in data aggregation. Furthermore, DGMA will provide a more network applied to a large scale emergent event monitoring.