Contiguous link scheduling for data aggregation in wireless sensor networks

Junchao Ma, Wei Lou, Xiang Yang Li

Research output: Journal article publicationJournal articleAcademic researchpeer-review

46 Citations (Scopus)


Wireless sensor networks (WSNs) consist of a large number of battery-powered wireless sensor nodes, and one key issue in WSNs is to reduce the energy consumption while maintaining the normal functions of WSNs. Data aggregation, as a typical operation in data gathering applications, can cause a lot of energy wastage since sensor nodes, when not receiving data, may keep in the listen state during the data collection process. To save this energy wastage, sleep scheduling algorithms can be used to turn the nodes to the sleep state when their radios are not in use and wake them up when necessary. In this paper, we identify the contiguous link scheduling problem in WSNs, in which each node is assigned consecutive time slots so that the node can wake up only once in a scheduling period to fulfil its data collection task. The objective of the problem is to find an interference-free link scheduling with the minimum number of time slots used. In virtue of the contiguous link scheduling, the energy consumption caused by nodes' state transitions can be reduced. We prove the contiguous link scheduling problem in WSNs to be NP-complete, and then present efficient centralized and distributed algorithms with theoretical performance bounds in both homogeneous and heterogeneous networks. We also conduct simulation experiments that corroborate the theoretical results and demonstrate the efficiency of our proposed algorithms.
Original languageEnglish
Article number6678513
Pages (from-to)1691-1701
Number of pages11
JournalIEEE Transactions on Parallel and Distributed Systems
Issue number7
Publication statusPublished - 1 Jan 2014


  • contiguous link scheduling
  • data aggregation
  • Energy efficient algorithms
  • sleep scheduling
  • wireless sensor networks

ASJC Scopus subject areas

  • Signal Processing
  • Hardware and Architecture
  • Computational Theory and Mathematics


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