Open AccessEIMO‐ESOLSR: energy efficient and security‐based model for OLSR routing protocol in mobile ad‐hoc network
Author(s) -
Kanagasundaram Hamela,
Kathirvel A.
Publication year - 2019
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2018.5564
Subject(s) - computer network , computer science , optimized link state routing protocol , routing protocol , mobile ad hoc network , energy consumption , link state routing protocol , wireless ad hoc network , network packet , wireless routing protocol , ad hoc wireless distribution service , distributed computing , wireless , telecommunications , engineering , electrical engineering
In numerous areas mobile ad hoc network (MANET) has plenteous mobile nodes that are allowed to communicate independently. In optimised link state routing protocols (OLSR), multi‐point relays (MPR) are unique nodes that are chosen by different nodes to relay their traffic information which may prompt to MPR nodes high energy consumption. However, misbehaving MPR nodes tend to protect their energy by dropping different nodes packets as opposed to sending them. This prompts to huge energy loss and debasement of execution in many existing energy efficient MPR selection plans. In this work, an energy and security aware routing model is introduced for MANET including an enhanced intellects‐masses optimiser (EIMO). At first, by methods of MPR selection the route discovery is advanced. In this approach, parameters, for example, available bandwidth, queue occupancy, and lifetime are considered as willingness nodes and misbehaving probability, power factor and forwarding behavior are considered as Composite Eligibility Index (CEI). Contrasted with other energy models this approach has less energy and secured. The accomplished simulation upshot exhibits that the EIMO‐energy‐efficient and secure optimised link state routing (ESOLSR) outperforms other state of art with respect to the performance metrics like energy consumption, total remaining time, average network lifetime, and a variance of energy.