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In-Network Data Aggregation for Ad Hoc Clustered Cognitive Radio Wireless Sensor Network.

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This study optimizes clustered cognitive radio wireless sensor networks (CRSN) by analyzing spectrum sensing (SS) and in-network data aggregation (IDA). Results show IDA extends network lifespan and reduces collision rates and latency.

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Wireless Communications

Background:

  • Cognitive radio wireless sensor networks (CRSN) enable secondary users to access channels opportunistically.
  • Cluster heads (CHs) in CRSN perform spectrum sensing (SS), data gathering, and transmission to a base station.
  • Increasing clusters impacts energy consumption for SS and data transmission.

Purpose of the Study:

  • Investigate the impact of in-network data aggregation (IDA) on CRSN performance.
  • Determine the optimal number of clusters to extend network lifespan.
  • Analyze energy consumption, collision rates, and network latency.

Main Methods:

  • Theoretical derivation of collision rates and network latency.
  • Analysis of energy consumption for SS and data transmission in a clustered CRSN.
  • Optimization study for cluster number considering SS requirements and IDA effects.

Main Results:

  • In-network data aggregation (IDA) effectively extends CRSN network lifespan.
  • IDA significantly minimizes both primary/secondary transmission collision rates.
  • IDA contributes to reducing overall network latency.

Conclusions:

  • The proposed approach balances SS requirements and IDA benefits for enhanced CRSN performance.
  • Optimizing cluster numbers is crucial for maximizing network lifespan and efficiency.
  • IDA is a key technique for improving CRSN reliability and performance.