Adaptive Data Collection in Sparse Underwater Sensor Networks Using Mobile Elements

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• 作者：M. J. Jalaja (18)
  Lillykutty Jacob (18)
  
• 关键词：Underwater Wireless Sensor Network ; Delay Tolerant Network ; Mobile sink ; Polling ; Dynamic optimization ; Scheduling Preference Index
• 刊名：Lecture Notes in Computer Science
• 出版年：2015
• 出版时间：2015
• 年：2015
• 卷：8629
• 期：1
• 页码：57-65
• 全文大小：419 KB
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  16. Takagi, H.: Queueing Analysis of Polling Models: An Update. Stochastic Analysis of Computer and Communication Systems, pp. 267鈥?18. Elsevier Science Publishers B.V., Amsterdam/North Holland (1990)
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• 作者单位：M. J. Jalaja (18)
  Lillykutty Jacob (18)
  
  18. Department of Electronics and Communication Engineering, National Institute of Technology Calicut, Kozhikode, India
  
• 丛书名：Ad-hoc Networks and Wireless
• ISBN：978-3-662-46338-3
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

Underwater Wireless Sensor Network (UWSN) is a group of sensors and underwater vehicles, networked via acoustic links to perform collaborative tasks. Due to hostile environment, resource constraints and the peculiarities of the underlying physical layer technology, UWSNs tend to be sparse or partitioned, and energy-efficient data collection in a sparse UWSN is a challenging problem. We consider mobility-assisted routing as a technique for enabling connectivity and improving the energy efficiency of sparse UWSN, considering it as a Delay/Disruption Tolerant Network (DTN) or Intermittently Connected Network (ICN). The DTN framework shows superior performance in terms of energy efficiency and packet delivery ratio, at the cost of increased message latency. We investigate the effectiveness of a polling model to analyze the delay performance and propose a dynamic optimization technique to minimize latency adaptively, thereby supporting delay-sensitive applications also. The effectiveness of the proposed technique in modelling the dynamically changing environment and minimizing the data collection latency is validated using NS-2 based simulation.