Performance analysis of data management in sensor data storage via stochastic petri nets

Rongfei Zeng*, Chuang Lin, Yixin Jiang, Xiaowen CHU, Fangqin Liu

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

5 Citations (Scopus)


Recently, sensor data storage has gained increasing popularity for reliable access to data through redundancy spread over unreliable nodes in wireless sensor networks. In storage-centric sensor networks, several schemes have been proposed to optimize the performance of data management in terms of data availability, repair bandwidth, etc. However, few works have been undertaken to study the performance of these data management schemes from a comprehensive point of view. In this paper, we adopt a concise graphic model, i.e., Stochastic Petri Nets (SPNs), to analyze the performance of three representative data management schemes. From the steady state probability matrix of the SPNs models, we can easily get the average energy consumption, repair bandwidth, reliability and data availability. Based on numerical results, we provide guidelines for designing sensor data storage systems. The results also demonstrate that our proposed models are suitable for analyzing data management schemes in sensor data storage.

Original languageEnglish
Title of host publication2010 IEEE Global Telecommunications Conference, GLOBECOM 2010
Publication statusPublished - 2010
Event53rd IEEE Global Communications Conference, GLOBECOM 2010 - Miami, FL, United States
Duration: 6 Dec 201010 Dec 2010

Publication series

NameGLOBECOM - IEEE Global Telecommunications Conference


Conference53rd IEEE Global Communications Conference, GLOBECOM 2010
Country/TerritoryUnited States
CityMiami, FL

Scopus Subject Areas

  • Electrical and Electronic Engineering

User-Defined Keywords

  • Data management
  • Performance evaluation
  • Sensor data storage
  • Stochastic petri nets


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