Power-aware communication in body area networks

Hassan Ghasemzadeh, Roozbeh Jafari

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Monitoring human movements using wireless sensory devices promises to revolutionize the delivery of health care services. Such platforms use inertial information of their subjects for motion analysis. Potentially, each action or disease can be discovered by collaborative processing of sensor data from multiple locations on the body. This functionality is provided by a body area network (BAN), which consists of several wireless sensor nodes positioned on different parts of the body. In spite of the revolutionary potential of this platform, power requirements and wearability have limited the commercialization of these systems. This chapter presents energy-efficient communication models for BAN applications using buffers to limit communication to higher-rate short bursts, decreasing power usage and simplifying the communication. Transmission at higher rates and in short bursts will create opportunities to reduce the energy per bit for communication, hence decreasing the overall energy consumption. This energy minimization is achieved via proper buffer allocation in this chapter. The buffer allocation problem is formulated as an optimization problem that reduces transmissions among sensor nodes. Both an integer linear programming (ILP) solution and a fast greedy heuristic algorithm are discussed to solve this power optimization problem. It is shown that despite the decreased transmission efficiency, the greedy algorithm can be adopted for fast allocation of buffers in real time. Performance of both the near-optimal and greedy solutions is compared against an unbuffered system using experimental analysis. It is demonstrated that ILP and greedy solutions can reduce the amount of transmissions by an average factor of 70% and 41%, respectively.

Original languageEnglish (US)
Title of host publicationAmbient Assisted Living
PublisherCRC Press
Pages203-224
Number of pages22
ISBN (Electronic)9781439869857
ISBN (Print)9781439869840
DOIs
StatePublished - Jan 1 2015
Externally publishedYes

Keywords

  • Buffer allocation
  • Collaborative signal processing
  • Power optimization

ASJC Scopus subject areas

  • General Medicine
  • General Health Professions
  • General Biochemistry, Genetics and Molecular Biology

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