[Show abstract][Hide abstract] ABSTRACT: Task allocation and scheduling is an important typical problem in the area of high performance computing. Unfortunately, the existing traditional solutions to this problem in high performance computing cannot be directly implemented in wireless sensor networks (WSNs) due to the limitations of WSNs such as resource availability and shared communication medium. In this paper, a dynamic task scheduling strategy with the application of the game theory in WSNs is presented. First, an effective parallel alliance generating algorithm is proposed to process the multi-tasks environment. A task allocation algorithm based on the game theory is used to enhance the performance of the network. A novel resource conflict eliminating algorithm is also developed to eliminate the conflicting issues. Finally, the simulation results confirm and reassure the effectiveness of our proposed scheme as we compare with that of the other schema's available in the public domain.
No preview · Article · Nov 2014 · New Mathematics and Natural Computation
[Show abstract][Hide abstract] ABSTRACT: In this paper, as physical resources of sensor nodes are limited, such as storage and computing power, frequent faults and reconfiguration caused by failure nodes may occur. We propose a multi-agent-based adaptive task allocation algorithm in wireless sensor network (WSNs). The algorithm applies multi-agent theory and technology to the adaptive task allocation in WSNs to recover the network with the minimum cost. Simulation experiment demonstrates that unexecuted tasks of unavailable nodes can effectively migrate to other health nodes in WSNs by the algorithm, and the experiment results show that the algorithm can save more energy and help to improve the performance of the whole network.
[Show abstract][Hide abstract] ABSTRACT: In distributed sensor networks, which have limited resources, such as energy and storage, and work in a dynamic environment, the networks should effectively allocate some real-time tasks on those limited resources. Additionally, we should do our best to maximize the lifetime of wireless sensor networks (WSNs) and the accuracy of the results. Due to most of previous works focusing on static task allocation for WSNs and only a few works having paid attention to dynamic resource allocation for sensor networks, this paper present an effectively adaptive task allocation (EATA) in WSNs which applied dynamic alliance. Instead of being aid of manual adjustment, each node can autonomously adjust its parameters and state by means of EATA according to tracking the change of environment, such as energy depletion. By comparing with static task allocation, experiment results show that our scheme can save a great deal of energy and prolong the lifetime of the network.