Adaptive QoS routing for significant events in wireless sensor networks

Author(s):  
Erol Gelenbe ◽  
Edith C.-H. Ngai
2011 ◽  
Vol 31 (2) ◽  
pp. 298-300
Author(s):  
Wei-ren SHI ◽  
Ming-meng YAN ◽  
He HUANG

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Hind Alwan ◽  
Anjali Agarwal

With the growing demand for quality-of-service (QoS) aware routing protocol in wireless networks, QoS-based routing has emerged as an interesting research topic. Quality of service guarantee in wireless sensor networks (WSNs) is difficult and more challenging due to the fact that the available resources of sensors and the various applications running over these networks have different constraints in their nature and requirements. In this paper, we present a heuristic neighbor selection mechanism in WSNs that uses the geographic routing mechanism combined with the QoS requirements to provide multiobjective QoS routing (MQoSR) for different application requirements. The problem of providing QoS routing is formulated as link, and path-based metrics. The link-based metrics are partitioned in terms of reliability, delay, distance to sink, and energy, and the path-based metrics are presented in terms of end-to-end delay, reliability of data transmission, and network lifetime. The simulation results demonstrate that MQoSR protocol is able to achieve the delay requirements, and due to optimum path selection process, the achieved data delivery ratio is always above the required one. MQoSR protocol outperforms the existing model in the literature remarkably in terms of reliable data transmission, time data delivery, and routing overhead and underlines the importance of energy-efficient solution to enhance network lifetime.


2014 ◽  
Vol 672-674 ◽  
pp. 2033-2036
Author(s):  
Li Fen Li

This paper presents a new cross-layer QoS routing algorithm for wireless sensor networks. Basing on the principle of cross-layer design, the algorithm adopts delay, nodes’ load and link quality as QoS metrics. The QoS routing metrics are regarded as heuristics correction factors in ant colony algorithm (ACA). The ants are divided into a number of different populations. Through the interaction of pheromone between multi populations, the routing algorithm searches for the feasible paths in parallel and updates the pheromone in time. To overcome the slow convergence of ant colony algorithm, membership cloud model (MCL) is used to control the randomness of the ants. The simulation results demonstrate that the routing algorithm can guarantee the real time, reliability and robustness of wireless sensor networks. It can also achieve the network load balancing.


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