Name
Abstract | ||
|---|---|---|
Recently, the big data emerged as a hot topic because of the tremendous growth of the information and communication technology. One of the highly anticipated key contributors of the big data in the future networks is the distributed wireless sensor networks (WSNs). Although the data generated by an individual sensor may not appear to be significant, the overall data generated across numerous sensors in the densely distributed WSNs can produce a significant portion of the big data. Energy-efficient big data gathering in the densely distributed sensor networks is, therefore, a challenging research area. One of the most effective solutions to address this challenge is to utilize the sink node's mobility to facilitate the data gathering. While this technique can reduce energy consumption of the sensor nodes, the use of mobile sink presents additional challenges such as determining the sink node's trajectory and cluster formation prior to data collection. In this paper, we propose a new mobile sink routing and data gathering method through network clustering based on modified expectation-maximization technique. In addition, we derive an optimal number of clusters to minimize the energy consumption. The effectiveness of our proposal is verified through numerical results. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/TETC.2014.2318177 | Emerging Topics in Computing, IEEE Transactions |
Keywords | Field | DocType |
Big Data,energy conservation,expectation-maximisation algorithm,mobility management (mobile radio),wireless sensor networks,WSN,data gathering method,densely distributed sensor networks,distributed wireless sensor networks,energy consumption,energy-efficient big data gathering,expectation-maximization technique,information and communication technology,mobile sink routing,network clustering,sensor nodes,sink node mobility,Big data,clustering,data gathering,energy efficiency,optimization,wireless sensor networks (WSNs) | Key distribution in wireless sensor networks,Computer science,Efficient energy use,Computer network,Cluster analysis,Group method of data handling,Energy consumption,Big data,Wireless sensor network,Mobile telephony,Distributed computing | Journal |
Volume | Issue | ISSN |
2 | 3 | 2168-6750 |
Citations | PageRank | References |
21 | 1.00 | 19 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daisuke Takaishi | 1 | 56 | 3.49 |
| Hiroki Nishiyama | 2 | 1285 | 92.61 |
| Nei Kato | 3 | 3982 | 263.66 |
| ryu miura | 4 | 243 | 43.36 |