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Traffic Adaptive Hybrid MAC with QoS Driven Energy Efficiency for WSNs Through Joint Dynamic Scheduling Mode | IEEE Conference Publication | IEEE Xplore

Traffic Adaptive Hybrid MAC with QoS Driven Energy Efficiency for WSNs Through Joint Dynamic Scheduling Mode


Abstract:

This paper proposes a joint TDMA and CSMA-based traffic Adaptive Intelligent Hybrid Medium Access Control protocol (AI-HMAC) for low-power duty cycle Wireless Sensor Netw...Show More

Abstract:

This paper proposes a joint TDMA and CSMA-based traffic Adaptive Intelligent Hybrid Medium Access Control protocol (AI-HMAC) for low-power duty cycle Wireless Sensor Networks (WSNs). The objective of AI-HMAC is to modify the link scheduling and leveraging contention windows mechanism of IH-MAC and smooth the coordination among them by avoiding delay and to efficiently achieve energy consumption. Accordingly, AI-HMAC reintroduces the idea to combines the functionalities of CSMA, TDMA, broadcast scheduling and link scheduling in order to improve throughput and energy efficiency of protocol. It can operate under wide range of data traffic and choosing send/receive mechanism technique according to packet rate and loss with extending energy minimization techniques and bringing down energy consumption. Another advantage of AI-HMAC is to regulating initial contention window according flowing traffic asking rate between nodes in order to achieve high channel utilization under high traffic load without any energy compromising and to minimize certain delay probability that may cause with data collision. AI-HMAC doing this task through applying prioritized back-off scheme to make efficient time adaptive for node idle listening period during Back-off process. It adjusts contention for adapting traffic load with suitable duty cycle length in order to increase energy efficiency. And by leveraging and exploiting the concept of parallel transmission to minimize energy consumption during communication. The mathematical analytical expression of our protocol are presented to compute the energy consumption efficiency and the simulation showing how AI-HMAC efficiently manages compare evaluated protocols in terms of network life, energy consumption and latency.
Date of Conference: 27-29 June 2018
Date Added to IEEE Xplore: 23 August 2018
ISBN Information:
Conference Location: Busan, Korea (South)

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