Abstract
Wireless Sensor Networks (WSN) have nodes that are small in size and are powered by small batteries having very limited amount of energy. In most applications of WSN, the nodes in the network remain inactive for long periods of time, and intermittently they become active on sensing any change in the environment. The data sensed by the different nodes are sent to the sink node. In contrast to other infrastructure-based wireless networks, higher throughput, lower latency and per-node fairness in WSN are imperative, but their importance is subdued when compared to energy consumption. In this work, we have regarded the amount of energy consumption in the nodes to be of primary concern, while throughput and latency in the network to be secondary. We have proposed a protocol for energy-efficient adaptive listen for medium access control in WSN. Our protocol adaptively changes the slot-time, which is the time of each slot in the contention window. This correspondingly changes the cycle-time, which is the sum of the listen-time and the sleep-time of the sensors, while keeping the duty-cycle, which is the ratio between the listen-time and the cycle-time, constant. Using simulation experiments, we evaluated the performance of the proposed protocol, compared with the popular Sensor Medium Access Control (SMAC) (Ye et al. IEEE/ACM Trans Netw 12(3):493–506, 39) protocol. The results we obtained show a prominent decrease in the energy consumption at the nodes in the proposed protocol over the existing SMAC protocol, at the cost of decreasing the throughput and increasing the latency in the network. Although such an observation is not perfectly what is ideally desired, given the very limited amount of energy with which the nodes in a WSN operate, we advocate that increasing the energy efficiency of the nodes, thereby increasing the network lifetime in WSN, is a more important concern compared to throughput and latency. Additionally, similar observations relating energy efficiency, network lifetime, throughput and latency exist in many other existing protocols, including the popular SMAC protocol (Ye et al. IEEE/ACM Trans Netw 12(3):493–506, 39).
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Notes
As we use only the Centroid Method, in the interest of brevity, we do not explain the other defuzzification methods in this paper. Interested readers are referred to [31] and [28] for getting an understanding of how the other defuzzification methods work. Although we believe that using the other defuzzification methods will not substantially influence the conclusions that we have drawn from this work, in the future, we plan to empirically investigate it.
In our simulation, we chose to have 10 nodes. Such a setup is aligned with the experimental results reported in most of the existing works as well. The increase in the number of nodes can lead to an increase in the levels of congestion. The number of nodes can be varied by implementing appropriate modifications in the simulation code and transmission range of the nodes. However, sensor nodes have very short transmission range compared to the nodes in other wireless networks and it is typical that only a few nodes that are not too distant from any particular node can exist in its transmission range.
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Acknowledgement
The work of the first author was partly supported by a grant from the Department of Science & Technology, Government of India, Grant No. SR/FTP/ETA-36/08, which the author gratefully acknowledges.
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Misra, S., Mohanta, D. Adaptive listen for energy-efficient medium access control in wireless sensor networks. Multimed Tools Appl 47, 121–145 (2010). https://doi.org/10.1007/s11042-009-0410-9
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DOI: https://doi.org/10.1007/s11042-009-0410-9