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Information 2018, 9(1), 23;

Inspired from Ants Colony: Smart Routing Algorithm of Wireless Sensor Network

LRIT, Associated Unit to CNRST (URAC No 29), Faculty of Sciences, Mohammed V University in Rabat, B.P.1014 RP Rabat, Morocco
SIRC/LAGeS-EHTP, Hassania School of Public Labors Km 7 EI Jadida Road, B.P 8108 Casablanca Morocco, Morocco
Author to whom correspondence should be addressed.
Received: 14 December 2017 / Revised: 11 January 2018 / Accepted: 17 January 2018 / Published: 22 January 2018
(This article belongs to the Special Issue Machine to Machine Communications and Internet of Things (IoT))
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In brief, Wireless Sensor Networks (WSNs) are a set of limited power nodes, used for gathering the determined data of an area. Increasing the lifetime is the main challenge to optimize WSNs routing protocols, since the sensors’ energy in most cases is limited. In this respect, this article introduces a novel smart routing algorithm of wireless sensor networks, consisting of stable nodes randomly dispersed, and this approach is inspired from ant colonies. The proposed algorithm takes into consideration the distance between two nodes, the chosen path length and the nodes’ residual energy so as to update the choice probability of the next node among the neighbouring nodes, contrary to several routing algorithms; on the one hand, the nodes are aggregating data of their predecessors and sending to all to their successors; on the other hand, the source is almost always changed in each iteration. Consequently, the energy consumption is balanced between the nodes. Hence, the network lifetime will be increased. Detailed descriptions and a set of simulation using Matlab is provided to measure the network lifetime and the energy consumed by nodes of the proposed approach are presented. The replications’ consequences of simulations prove the success of our future routing algorithm (SRA). View Full-Text
Keywords: energy consumption; ant colony; smart routing algorithm (SRA); residual energy wireless sensor network energy consumption; ant colony; smart routing algorithm (SRA); residual energy wireless sensor network

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Bouarafa, S.; Saadane, R.; Rahmani, M.D. Inspired from Ants Colony: Smart Routing Algorithm of Wireless Sensor Network. Information 2018, 9, 23.

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