Abstract
The general problem faced in the field of Wireless Multimedia Sensor Networks (WMSNs) is congestion. The most common method in the area of WMSNs to minimize congestion is traffic control. Quality Of Service (QOS) is widely used in WMSNs to guarantee preferential service for critical applications by controlling end-to-end delay, reducing data loss and by providing adequate bandwidth. The present work is on Probabilistic QOS Aware Congestion Control (PQACC) which employs probabilistic method based congestion prediction and priority based data transmission rate adjustment, where inelastic real-time traffic and elastic non-real-time traffic are treated separately. Using the present PQACC approach, average throughput, average source-to-sink delay and average packet loss probability are improved by 9%, 10.33% and 16.03% compared to EWPBRC and achieved 5.97%, 7.05% and 11.69% improvement compared to FEWPBRC. Simulation result reveals that, congestion is effectively predicted, controlled and provides necessary level of QOS in terms of delay, throughput and packet loss, hence making this approach possible in mission critical applications.
Highlights
Recent advances and development in the field of sensors and availability of economical hardware such as mi-How to cite this paper: Mayandi, M. and Pillai, K.V. (2016) Probabilistic Quality Of Service (QOS) Aware Congestion Control in Wireless Multimedia Sensor Networks
The two kinds of data traffic supported by Wireless Multimedia Sensor Networks (WMSNs) are InElastic Real Time (IERT) and Elastic Non Real Time traffic (ENRT)
The protocol Probabilistic QOS Aware Congestion Control (PQACC), for congestion control is developed by considering the requirements of multimedia applications on WMSNs
Summary
How to cite this paper: Mayandi, M. and Pillai, K.V. (2016) Probabilistic QOS Aware Congestion Control in Wireless Multimedia Sensor Networks. (2016) Probabilistic QOS Aware Congestion Control in Wireless Multimedia Sensor Networks. The importance of the traffic generated by these sensors is different; it is needed that preference must be given to packets carrying important data by providing more network resources than other packets to achieve diverse levels of service [2]. The main objective of WMSNs is to develop algorithms that prolong the lifetime of the network and assures to provide QOS necessities insisted by the applications [5]. The present study is based on the following considerations: a probability based congestion prediction; a mixture of three parameters to attain accurate determination of congestion; service discrimination among different kinds of data; an algorithm for rate adjustment based on probability based congestion prediction, priority of the source data and location of source sensors
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