Hierarchical Clustering-Task Scheduling Policy in Cluster-Based Wireless Sensor Networks
| Autor: | Peyman Neamatollahi, Saeid Abrishami, Mohammad Moghaddam, Mahmoud Naghibzadeh, O. Younis |
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| Rok vydání: | 2018 |
| Předmět: |
Job shop scheduling
business.industry Computer science Distributed computing 020206 networking & telecommunications 02 engineering and technology Energy consumption Load balancing (computing) Computer Science Applications Scheduling (computing) Hierarchical clustering Load management Key distribution in wireless sensor networks Control and Systems Engineering 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Electrical and Electronic Engineering Cluster analysis business Wireless sensor network Information Systems Computer network |
| Zdroj: | IEEE Transactions on Industrial Informatics. 14:1876-1886 |
| ISSN: | 1941-0050 1551-3203 |
| DOI: | 10.1109/tii.2017.2757606 |
| Popis: | Organizing sensor nodes into a clustered architecture is an effective method for load balancing and prolonging the network lifetime. However, a serious drawback of the clustering approach is the imposed energy overhead caused by the “global” clustering operations in every round of the global round-based policy (GRBP). To mitigate this problem, this paper proposes a hierarchical clustering-task scheduling policy (HCSP), which triggers node-driven clustering as opposed to GRBP's time-driven clustering. Based on HCSP, each cluster is reconfigured only once at each local super round. Therefore, the cluster reconfiguration frequency varies on-demand and may differ from one cluster to another throughout the network lifetime. However, in order to refresh the entire network structure, global clustering is performed at the end of every global hyper round. Accordingly, HCSP aims to achieve a more flexible, energy-efficient, and scalable clustering-task scheduling than that of GRBP. This policy mitigates the clustering overhead, which is the worst disadvantage of clustering approaches. Energy consumption calculations and extensive simulations show the effectiveness of HCSP in saving energy and in prolonging the network lifetime. |
| Databáze: | OpenAIRE |
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