A Task Scheduling Strategy in Heterogeneous Multi-sinks Wireless Sensor Networks
Using multiple sinks in a wireless sensor network can signiﬁcantly decrease the amount of energy spent on communication, so it has been paid much attention in recent years. In this paper, we introduce a new divisible load scheduling strategy to solve the problem how to complete the tasks within the possibly shortest time in multi-sinks wireless sensor network. In this strategy, the tasks are distributed to wireless sensor network based on the processing and communication capacity of each sensors by multiple sinks. After received the sub-tasks, the intra-cluster sensors perform its tasks simultaneously, and send its results to cluster head sequentially. By removing communications interference between each sensor, reduced makespan and improved network resource utilization achieved. Cluster heads send fused data to sinks sequentially after fused the data got from intra-cluster sensors, which could overlap the task-performing and communication phase much better. A unique scheduling strategy that allows one to obtain closed form solutions for the optimal finish time and load allocation for each node in heterogeneous clustered networks is presented. And solutions for an optimal allocation of fractions of task to sensors in the network are also obtained via bi-level programming. Finally, simulation results indicate this strategy reasonably distributes tasks to each node in multi-sinks wireless sensor networks, and effectively reduces the time-consuming of task completion. Compared to the traditional single-sink structure, makespan is reduced by 20%, and the energy-consuming of sensors is more balanced.