Energy efficient multi-metric QoS routing using genetic algorithm in MANET

Abstract

Nodes in Mobile Adhoc NETwork (MANET) are suffered by limited bandwidth and frequent changes in the topology due to node mobility. The nodes participating in the network are powered by limited battery resources and the battery depletion can imply network failure. Although establishing correct and efficient routes is an important design issue in MANET, providing energy efficient routes is a more challenging goal because mobile nodes' operation time is the most critical limiting factor. The problem of network exhausting batteries which partitions the entire network can be prevented by considering the energy consumption in MANET. To support real-time communications which require better QoS, metrics like bandwidth, end-to-end delay and energy consumption has to be considered. It is necessary to consider multiple metrics for selecting an efficient path. This multi-metric QoS routing problem can be solved with optimization techniques. An energy efficient genetic algorithm based unicast routing is proposed to provide energy efficient unicast, multipath route by considering multiple QoS parameters such as end-to-end delay, energy consumption , bandwidth and hop count.

Energy efficient multiconstrained optimization using hybrid ACO and GA in MANET routing

“…The pause time was set to 50 s. The speed was set to 10 m/s. Each simulation result for the proposed energy-efficient ACO GA hybrid metaheuristic (EAGHM) approach was compared to that of an ACO-based algorithm swarm-based hybrid routing protocol (SHRP) [28] and a GA-based algorithm EGHRP [29]. In SHRP, the results were obtained using QualNet.…”

Bat Optimized Link State Routing Protocol for Energy-Aware Mobile Ad-Hoc Networks

“…The CAABO attempts to discover the paths that fulfil the delay requirements and limitations as well as improving the energy usage of the network. Brindha et al [31] propose a new energy-efficient routing protocol by using different Quality of Service (QoS) parameters such as hops count, End-To-End (E2E) delay, and bandwidth. These parameters are managed via the GA algorithm to get an optimal solution.…”

“…The OLSR is proposed by Clausen et al [37] as a proactive routing protocol for ad hoc networks and is built based on the link-state (LS) protocol with reduced signaling packets and control traffic flooding [37]. Accordingly, the OLSR protocol broadcasts messages transmitted in the network by using MPRs, nodes that are specifically designed to broadcast only such messages [31,38]. The mechanisms of the OLSR protocol and MPR selection are shown in Figures 2 and 3 using MPRs, nodes that are specifically designed to broadcast only such messages [31,38].…”

“…Accordingly, the OLSR protocol broadcasts messages transmitted in the network by using MPRs, nodes that are specifically designed to broadcast only such messages [31,38]. The mechanisms of the OLSR protocol and MPR selection are shown in Figures 2 and 3 using MPRs, nodes that are specifically designed to broadcast only such messages [31,38]. The mechanisms of the OLSR protocol and MPR selection are shown in Figures 2 and 3, respectively.…”

“…This phenomenon indicates that various nodes that receive the messages do not transmit them [40]. A using MPRs, nodes that are specifically designed to broadcast only such messages [31,38]. The mechanisms of the OLSR protocol and MPR selection are shown in Figures 2 and 3, respectively.…”