iSleep: thermal entropy aware intelligent sleep scheduling algorithm for wireless sensor network

The optimal operation of Wireless Sensor Network (WSN) requires a sustainable topology. A dead node may result in a breach of end-to-end connectivity in the network. The thermal sensitivity of any sensor affects the lifetime of the node. Every sensor node has a typical operating temperature zone. Be...

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Bibliographic Details
Published in:Microsystem technologies : sensors, actuators, systems integration actuators, systems integration, 2020-07, Vol.26 (7), p.2305-2323
Main Authors: Banerjee, Partha Sarathi, Mandal, Satyendra Nath, De, Debashis, Maiti, Biswajit
Format: Article
Language:English
Subjects:
Algorithms
Anisotropy
Connectivity
Electronics and Microelectronics
Energy efficiency
Engineering
Entropy
Flow distribution
Heat
Instrumentation
Mechanical Engineering
Nanotechnology
Nodes
Operating temperature
Scheduling
Sensors
Sleep
Sun
Technical Paper
Temperature
Temperature distribution
Topology
Wireless sensor networks
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Summary:The optimal operation of Wireless Sensor Network (WSN) requires a sustainable topology. A dead node may result in a breach of end-to-end connectivity in the network. The thermal sensitivity of any sensor affects the lifetime of the node. Every sensor node has a typical operating temperature zone. Beyond the operating temperature threshold, the system reduces the performances and consequently forms a disconnected network. Network entropy represents the evaluation of the anisotropy of the temperature distribution profile of the system that measures the network stability. In this work, an intelligent sleep scheduling algorithm ‘ i Sleep’ is proposed based on available neighboring nodes, associated network entropy, and traffic flow pattern. i Sleep enables the sensor nodes to auto-control the sleep state of the nodes and maintain network connectivity for a longer amount of time. The proposed algorithm is tested for numerous representative networks on MATLAB 2016a and the Cooja simulator on Instant Contiki-2.7 with two energy models of Tmote Sky and Zolertia Z1. It is found that the proposed algorithm outperforms the existing scheduling algorithms in terms of the lifetime of a network for both the energy models.
ISSN:0946-7076
1432-1858
DOI:10.1007/s00542-019-04706-7