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In this paper, a novel framework for enabling machine-to-machine (M2M) communications between machine type devices (MTDs) having heterogeneous message types and under stringent resource constraints is proposed. In particular, an M2M communication system is considered in which two types of messages must seamlessly coexist: periodic, delay tolerant messages, such as meter readings, and critical, real-time...
Machine-type devices (MTDs) will lie at the heart of the Internet of things (IoT) system. A key challenge in such a system is sharing network resources between small MTDs, which have limited memory and computational capabilities. In this paper, a novel learning with finite memory framework is proposed to enable MTDs to effectively learn about each others message state, so as to properly adapt their...
For a seamless deployment of the Internet of Things (IoT), there is a need for self-organizing solutions to overcome key IoT challenges that include data processing, resource management, coexistence with existing wireless networks, and improved IoT-wide event detection. One of the most promising solutions to address these challenges is via the use of innovative learning frameworks that will enable...
One important application of wireless sensor networks (WSNs) is intruder detection for protection of a region of interest, and k-barrier coverage is a good way to achieve the necessary level of security using WSNs. One of the biggest problems with WSNs is their limited lifetime, which is directly related to the deployment and maintenance costs, and many approaches have been proposed to improve network...
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