A pre-emptive multiple queue based congestion control for different traffic classes in WSN

Abstract

Abstract-Traffic in wireless sensor networks (WSN) exhibits a many-to-one pattern in which multiple source nodes send sensing data to a single sink node. Since bandwidth, processor and memory are highly constrained in WSN, packet loss is common when a great deal of traffic rushes to sink. The system must provide differentiated service to individual traffic classes. In this paper, a pre-emptive multiple queue based congestion control mechanism is proposed. To detect congestion and to provide QoS for high priority traffic multiple buffers are used. Using this mechanism, high system utilization, reduced packet waiting time, and reduced packet drop probability are achieved. An analytical model is developed to predict the performance of the proposed mechanism by calculating the performance measures including system throughput, drop probability of packets, and mean queue length. By comparing analytical and simulation results the effectiveness and accuracy of the model is demonstrated. Markovian process is used to develop the analytical model and ns-2 for evaluating the performance of the mechanism.

An Enhanced Packet Transmission Framework for Handling Real Time Burst Traffic in Wireless Sensor Networks

“…The exponential shape parameter q, variation coefficient ρ denoting inter-arrival with service times and Hurst exponent H denoting access rate change are essential for efficacy of the model. A pre-emptive multiple queue [20] using congestion removal mechanism for handling high traffic condition is proposed. This technique outperforms the traditional DropTail method in terms of throughput, packet drop and energy consumption.…”

An integrated MAC protocol based on DMAC for emergency priority

“…This protocol focuses on a staggered wakeup scheduling mechanism, which makes the data stream flow to the sink node in a given path. However, this protocol has the following defects: (1) It will lead to serious data accumulation, and even overflow around hot spots; (2) Because the protocol is not a fair data transmission strategy [11], it would cause the data entering the cache of the hot spots earlier keep a more front place in the send queue and the data from the node far from the hot spots in the rear of the send queue [12]; (3) In DMAC, there is competition between the nodes at the same layer, which can result in great difference in data delay between nodes in each layer, loss of data, and poor network reliability [13].…”

Service Strategies in Two-Server Tandem Configurations – Modeling and Investigation

“…Some examples of their application in real systems (two transmitter communication networks with Dynamic Bandwidth Allocation, service facility with front and back room operations) can be found in [ 28], [1] respectively. The behavior of various systems, including communication and computer systems, as well as production and manufacturing procedures, can be represented and analyzed through queuing network models to evaluate their performance [11,12,13], [29,30]. System performance analysis usually includes the queue length distribution and various performance indicators such as response time, throughput and utilization [2], [6,7], [10].…”