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Wireless Sensor Networks

Performance Impact of Wind Speed on MAC Protocols for Underwater Wireless Sensor Networks


Acoustic communication in under water environments is challenging due to high propagation delay and severely limited bandwidth. Furthermore, the quality of the channel is dynamically changing due to wind, rain, temperature and other environmental factors. Efficient medium access control (MAC) protocols are therefore particularly important for acoustic sensor networks (UWSNs) to prevent a significant portion of the scarce bandwidth to be wasted on packet collision. Increased wind speed add surface roughness for underwater communication, which in turn can affect the overall performance of MAC protocols in UWSNs. The contribution of this paper is to investigate the performance of five MAC protocols for UWSNs in terms of packet delivery rate, energy consumption and delay under different wind speeds.

The protocols investigated are: Aloha, Aloha with carrier sense (Aloha-CS), Carrier Sense Multiple Access (CSMA), T-Lohi, and Distance Aware Collision Avoidance Protocol (DACAP). Our simulation studies show that at low wind speeds of 10 m/s, CSMA performs better than other protocols in terms of Packet Delivery Ratio (PDR) while Aloha without acknowledgement has the lowest End-to-End (E2E) delay with a trade-off in packet delivery ratio (PDR). At higher wind speed of 20 m/s to 30 m/s, T-Lohi outperforms the other protocols both in terms of PDR, E2E delay, and energy consumption.

We have undertaken a comparative simulation study of five MAC protocols in the context of underwater acoustic communication investigating how their performance is affected by wind-speed. The simulations show that T-Lohi and CSMA performs better in terms of PDR. Except for Aloha, T-Lohi has the lowest E2E delay. The weakness of Aloha is low PDR, making it less suitable unless the traffic density is low enough to make the collision probability insignificant. The PDR and energy consumption of CSMA is only slightly poorer than T-Lohi, i.e, the simulation results are in the same order of magnitude. In addition CSMA is simpler and easier to deploy. Thus, CSMA could often be a suitable choice. As part of future work, the analysis of these protocols will be extended to a wider set of network topologies and depths , and hence explore the behavior of the protocols in a broader range of environments. In a short term, this paper has given us insight into our immediate deployment context at the Austevoll research station.

wireless communication, distributed sensing, energy efficiency, fault tolerance, data aggregation, real-time monitoring, scalability, sensor nodes, multi-hop routing, coverage optimization, localization, self-organization, adaptive protocols, IoT integration, reliability, latency reduction, heterogeneous sensors, mobility support, cluster-based routing, environmental monitoring

#WirelessSensorNetworks, #IoT, #SmartCities, #SensorNodes, #DataAggregation, #WSN, #EnergyEfficiency, #RoutingProtocols, #RealTimeMonitoring, #DistributedSensing, #EdgeComputing, #NetworkScalability, #ClusterRouting, #SensorDeployment, #AdaptiveProtocols, #EnvironmentalMonitoring, #LatencyReduction, #SmartAgriculture, #IoTIntegration, #FaultToleranc

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