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Development of Trustworthy Self-Adaptive Framework for Wireless Sensor Networks
Wireless sensor networks (WSN) deployed for outdoor monitoring face many problems due to harsh external environment. Transmission loss is one such problem under weather extremities, which may induce erroneous decisions or a complete data loss. We have developed a self-adaptive trustworthy framework, which utilizes self-awareness of the environment and trustworthiness of the sensor to select alternate transmission channel with increased powers suiting to the current environmental conditions. Each sensor channel is partitioned with varying transmission powers to boost the received signal strength and thereby ensuring an improved data delivery. We have selected temperature and wind velocity as the environmental parameters to monitor, as their combined extremities produce unfavorable conditions for wireless transmission at 2.4 GHz. The framework have ensured the trust of the communicating sensor by checking its re-transmission history and battery performance, as these parameters increased the power consumption, which is directly proportional to the battery lifespan and quality of data delivery. Our framework has devised the possible impacts due to the combined effects of the selected weather extremities into four categories as no-loss, sub minimal loss, minimal loss and medium loss to partition the channel accordingly with 0%, 4%, 6% and 10% increased transmission powers. Our experiments on sensors tested under two sets of environmental data show an average of 5% improvement in data delivery after redesigning the data transmission channel; however, with 2% increase in battery consumption due to the gusty environments.