Loading...

Resource Management in Query-Driven Wireless Sensor Networks

Bahrami, Somaieh | 2011

368 Viewed
  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 42069 (19)
  4. University: Sharif University of Technology
  5. Department: Computer Engineering
  6. Advisor(s): Movaghar Rahimabadi, Ali
  7. Abstract:
  8. Wireless sensor network is composed of a large number of sensor nodes which are densely deployed to monitor the environment and collect information from physical events. There are different modelsfor sending collected data to users; one of them is query-driven models, in which according to user interest and via declarative queries collected data is delivered. Wireless sensor networks are energy constrained; regarding this issue, it is necessary to have an energy efficient design. Data aggregation or in network processing is one existing solution to reduce energy consumption. Data correlation or redundancy is also can be used with this method to save energy even more. In this thesis, an algorithm to manage limited energy of sensor network is proposed which is a clustering approach based on data correlation and exploits data aggregation when collecting data. Proposed algorithm includes five phases: 1) query dissemination and cluster forming, 2) cluster head election, 3) collecting results, 4) cluster adjustment, and 5) cluster merging. The goal incluster head election phase is to select optimized nodes as cluster heads based on remaining energy of sensor nodes, magnitude value of data, and the number of sensor nodes neighbors. In collecting query results phase, only cluster heads send their data to the base station, and exploits data aggregation. The aim in cluster adjustment phase is to solve the inconsistency by reducing data correlation as time passes, and in cluster merging phase is prevented from forming clusters with one member. The performance of proposed algorithm has been evaluated with NS2 simulator and the results show a significant reduction in energy consumption comparing to existing algorithms.
  9. Keywords:
  10. Wireless Sensor Network ; Clustering ; Data Aggregation ; Resources Management ; Data Correlation ; Query

 Digital Object List

 Bookmark

No TOC