Link Quality and Energy-Aware Metric-Based Routing Strategy in WSNS

Author(s):  
Vijayabaskar ◽  
T. Kumanan
Author(s):  
Linfeng Yuan ◽  
Zongkai Yang ◽  
Liang Ou ◽  
Wenqing Cheng ◽  
Xu Du

Author(s):  
ARAFAT S.M. QAED ◽  
T. DEVI

Routing Optimization in mobile ad hoc networks is an ever-demanding task. Mobile ad hoc networks are highly dynamic topology natured and hence several routing protocols meet the challenge of link quality, delay and energy conscious routing. This paper proposes a link quality, delay and energy conscious routing approach based on ant colony optimization. Based on the estimated link quality, delay and residual energy of the nearby nodes, Adaptive node stability (ANS) mechanism is mathematically modeled to make the routing strategy. LQDEARP selects the efficient node based on the ANS mechanism and sends the data packets through that node. Simulation results proved that LQDEARP reduces delay and energy consumption and increases packet delivery ratio than that of the AODV and DECRP protocol.


2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Sai Krishna Mothku ◽  
Rashmi Ranjan Rout

In a heterogeneous sensor actor network, packet loss may occur due to bad link quality, overflow of buffer, and low energy levels. Retransmission of the lost packets leads to more energy consumption and delay. Ensuring data reliability and minimum delay requirement while improving energy efficiency are challenging issues in a resource-constrained heterogeneous sensor actor network. In this paper, a fuzzy-based delay and energy-aware intelligent routing mechanism has been proposed to select efficient routes. In the proposed mechanism, routing decisions are taken using a fuzzy logic system by considering network resources, such as residual energy, quality of link, available buffer size, and distance (proximity). In a network, a node with higher residual energy, higher free available buffer, good link quality, and close distance (proximity) gets opportunity to become a next hop node in a routing path. Furthermore, network performance has been analyzed with various network states. Simulation has been carried out using Network Simulator 3 by considering performance metrics, such as delay, number of retransmissions, energy consumption, lifetime, and network stability of the network.


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