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A Technique for Scalable and Energy Efficient Context Monitoring Framework

Avinash Palave, Dr. Shiv K Sahu, Amit Sinhal


The context monitoring imposes heavy workloads on mobile devices and sensor nodes with limited computing and battery power. In this paper present SeeMon, a scalable and energy efficient context monitoring framework for sensor-rich, resource-limited mobile environment running on a personal mobile device, SeeMon effectively performs context monitoring approach. This paper support Mobile Privacy of user details. This system have capability to contain set of sensor’s to search all mobile users in nearest places. The system has proposed a novel context monitoring approach that provides efficient processing and sensor control mechanisms .It improves efficient processing and battery consumption power. It covers unlimited area. This paper implementing ESS algorithm for calculating Essential Sensor Set.I also employ Greedy algorithm to reduce the energy cost as much as possible while simplifying the computation. For this purpose, the Greedy algorithm selects the most cost-effective sensor until all false-state CMQs are covered. By using these two algorithms we can solve ESS calculation problem and also reduce energy cost.


Context Monitoring Query , Minimum Cost False Query Covering Sensor Election, Essential Sensor Set, T-QSET, FQSET, U- QSET, SEEMON

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