Abstract
To a wireless sensor network, cooperation among multiple sensors is necessary when it executes applications that consist of several computationally intensive tasks. Most previous works in this field concentrated on energy savings as well as load balancing. However, these schemes merely considered the situations where only one type of resource is required which drastically constrains their practical applications. To alleviate this limitation, in this article, we investigate the issue of complex application allocation, where various distinctive types of resources are demanded. We propose a heuristic-based algorithm for distributing complex applications in clustered wireless sensor networks. The algorithm is partitioned into two phases, in the inter-cluster allocation stage, tasks of the application are allocated to various clusters with the purpose of minimizing energy consumption, and in the intra-cluster allocation stage, the task is distributed to appropriate sensor nodes with the consideration of both energy cost and workload balancing. In so doing, the energy dissipation can be reduced and balanced, and the lifetime of the system is extended. Simulations are conducted to evaluate the performance of the proposed algorithm, and the results demonstrate that the proposed algorithm is superior in terms of energy consumption, load balancing, and efficiency of task allocation.
Highlights
In the last decade, with the development in technology of micro-electronics, digital electronics design, as well as advances in low-power wireless communication and network technique, a new type of network, wireless sensor network (WSN), has emerged.[1]
Since no similar works have been proposed so far, we develop an intuitive method as well as modify an existing method to solve the problem, namely, greedy-based distribution method and binary PSObased method, and compare our approach with these two methods
All the sensor nodes are partitioned into several groups according to their resource type, in each group, a sensor node is determined by using BPSO algorithm with the consideration of both the energy consumption and load balancing
Summary
With the development in technology of micro-electronics, digital electronics design, as well as advances in low-power wireless communication and network technique, a new type of network, wireless sensor network (WSN), has emerged.[1] In general, a WSN is composed of a large number of sensor nodes which are endowed with detection, computation, and communication capabilities. The emergence of WSN has greatly extended the application areas over traditional sensors. By grouping numerous sensors into a connected network, the end-users can obtain much more accurate data of a target that is in a remote and/. WSNs have been widely used in many applications such as object. International Journal of Distributed Sensor Networks detection and tracking,[2] privacy and security protection,[3] natural disaster rescue,[4] health care,[5] and so on
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