Auto-organization approach with adaptive frame periods for IEEE 802.15.4/zigbee forest fire detection system

Ouni, Sofiane; Ayoub, Zayneb Trabelsi; Kamoun, Farouk

doi:10.1007/s11276-018-01936-x

Cited by 2 publications

(2 citation statements)

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“…The collision probability is related to the waiting contention window of the back-off (W) and the number of neighboring nodes (N) in the same transmission range (in which these nodes can be in interference in their transmissions). Referring to research studies [19,20,22] the probability that a node transmits into a random slot in the contention window is 1/W .Thus, the probability that a node correctly transmits data without interference with another is (1 − 1 N ) N−1 . Therefore, the collision probability is given by formula 5.…”

Section: One-hop Response Time Analysismentioning

confidence: 99%

“…In this respect, a depth tree where the level number equals 5 has been simulated and each node of the tree has an average of 3 children with all leaves are located at the same depth. To calculate the energy consumption of devices we used the parameter values of MiCAz motes (IoT sensor node) summarized by [19]. Below table 2 which provides the values of energy conception that will be used.…”

Section: Simulation Environmentmentioning

confidence: 99%

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An MQTT Brokers Distribution Based on Mist Computing for Real-Time IoT Communications

Hmissi

Ouni

2021

Preprint

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As we consider the number of IoT time-sensitive applications , the transfer of data to a remote data center and server such as Cloud, Fog, and Edge becomes inefficient since the deadline constraint is not satisfied. Thus, ensuring that the IoT time-sensitive applications meet their timing constraints is a challenge. Mist Computing is closer to IoT devices, presenting the lowest communication delay but less computational resource than the Cloud, Fog, and Edge. Seeing several IoT devices use MQTT protocol to access the data due to its lightness and flexibility, we propose an architecture for IoT time-sensitive applications based on MQTT protocol and integrating Mist Computing. We focus on distributing the MQTT brokers over Mist nodes to satisfy the deadline constraints with the consideration of the limited resource of Mist nodes. Hence, we propose an approach for the selection of the appropriate MQTT Mist broker. We have also proposed MQTT communication model that provides the M/M/1 based analysis for delay computing and energy conception. The experiment results show that our proposal is very effective for time-sensitive applications and also maximize the lifetime of IoT systems since it minimizes the cumulative energy of the system. Compared to MQTT Edge broker distribution, our solution provides the lesser delay of communication between IoT devices.

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Section: One-hop Response Time Analysismentioning

confidence: 99%

Section: Simulation Environmentmentioning

confidence: 99%