Compression/transmission power allocation in multimedia wireless sensor networks

Ming Yang, Lei Chen, Weiqiang Xiong

Research output: Contribution to conferencePaperpeer-review

9 Scopus citations

Abstract

Wireless Sensor Networks (WSN) have been widely deployed in monitoring and surveillance in recent years, and have dramatically changed the related methodologies and technologies. Despite WSN's popularity, the sensor nodes in WSN have very limited computing resources and power supply, and thus the maximization of network life has become a very critical issue. In the newly-emerging Wireless Multimedia Sensor Network (WMSN), the high volume of sensed video data needs to be compressed before transmission. Different video coding schemes have been developed and applied to wireless multimedia sensor networks, and there exists a tradeoff between the power consumption of data compression and that of data transmission. Video compression will reduce the amount of data that needs to be transmitted and in turn the amount of power consumed for data transmission; however, too much video compression will consume excessive power which outweighs the power savings on data transmission. Thus, how to reach an optimized balance between compression and transmission and maximize network life becomes a challenging research issue. In this paper, we propose mathematical models which describe power consumptions of data compression and transmission of sensor nodes in hexagon-shaped clusters. Under the proposed model, we have achieved the optimized data compression ratio which minimizes the overall power consumption of the whole cluster.

Original languageEnglish
Pages1103-1107
Number of pages5
DOIs
StatePublished - 2014
Event2014 International Conference on Computing, Networking and Communications, ICNC 2014 - Honolulu, HI, United States
Duration: Feb 3 2014Feb 6 2014

Conference

Conference2014 International Conference on Computing, Networking and Communications, ICNC 2014
Country/TerritoryUnited States
CityHonolulu, HI
Period02/3/1402/6/14

Keywords

  • Cluster
  • Compression
  • Multimedia
  • Power
  • Sensor
  • Transmission
  • Wireless

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