Abstract
The long-term use of wireless sensors node while guaranteeing a good Quality of Services (QoS) is a major challenge in wireless sensor networks. Most of the relevant solutions which exist are proposed under Mac layer level but they use an optimization technique which requires a regular update of parameters and leads to unnecessary energy consumptiom which reduces the expected liftime and QoS. So in order to adress this issue, we propose in this paper, an adaptive management of wireless sensor node resources to meet application requirements in terms of energy consumption, reliability and delay. To do this, we have used the theory of viability, which is an approach that allows controling the evolution of a system in a set of desirable states. Here we have proposed an enhanced analytical model of sensor node’s energy dynamic, and we control it based on both Mac layer parameters of the IEEE 802.15.4 standard and the packet sampling frequency. The simulation results have shown that the proposed model is more accurate and efficient as a node can send more information without violating energy, reliability and delay constraints.
Highlights
Nowadays, the integration of sensors in our daily life is a reality
Pcf and Pcr are respectively the probability that the packet is rejected due to a communication channel failure and due to the reach of the limit number of attempts allowed for accessing the channel. x is the probability that the channel is busy and y is the probability of failure to transmit a packet, more precisely, it is the probability that a packet, after successfully been emitted on the channel, either lost; m is the maximum number of attempts before declaring a channel access failure and n is the maximum number of attempts allowed after a transmission failure in IEEE 802.15.4 slotted CSMA/CA, λ is the sensor node sensing/sending data frequency
In the previews works [25], we have shown that the following MAC layer parameters: MacMaxCSMABackoffs (m ) which denotes the maximum number of backoff that CSMA/CA algorithm will attempt before declaring a channel access failure and MacMinBE (m0) which represents the minimum number of backoff slots a device should wait before starting a channel access attempt through CSMA/CA
Summary
The integration of sensors in our daily life is a reality They are used as an automatic data acquisition system (physical information: temperature, pressure, brightness, humidity, movement ...) for monitoring the environment in which they are deployed. It is often difficult to recharge or replace batteries of sensor nodes that have been deployed to monitor some areas hostile to human This becomes problematic if the system is used to collect information autonomously and over a long period of time. 427 policy in order to meet the application requirements in terms of both services' lifetime and QoS (reliability, delay, throughput ...) To mitigate this problem, it happens that one uses an additional supplied energy from various sources (Solar, wind, vibration...). After that we analyze and discuss the numerical results that we obtained after several simulations and we conclude and give some future scopes of this work
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