Title: Design of smart logistics transportation system using MapReduce intelligent water drops algorithm in Hadoop environment

Authors: R. Sathish Kumar; C. Rani; P. Ganesh Kumar

Addresses: Department of Computer Science and Engineering, Government College of Engineering, Salem-11, India ' Department of Computer Science and Engineering, Government College of Engineering, Salem-11, India ' Department of Information Technology, Anna University Regional Campus, Coimbatore-46, India

Abstract: Designing a smart system for delivering goods to various fair price shops effectively is one of the major goals in the mission of smart city development. In this paper, the smart city environment is treated as a distributed environment for carrying goods across different parts of the city. Hence, the widely used intelligent water drops algorithm is implemented as MapReduce model using Hadoop environment to compute the shortest path for speedy delivery of goods. A front end is designed to carry out interstate and intrastate transportation of items. Distance matrix comprising 50, 100, 150….500 cities is considered for the simulation. From the experiment, it is observed that the intelligent water drops algorithm implemented in MapReduce model meets the objective of delivering materials to the right destination in minimum time. The performance of the proposed MapReduce intelligent water drops algorithm is compared with other popular algorithms like Bellman-Ford algorithm, Thorup algorithm, Gobow algorithm, and Dijkstra's algorithm. It is observed that the proposed MapReduce intelligent water drops algorithm gives a reliable shortest path between any source and destination city with less CPU time than the other algorithms.

Keywords: smart city; transportation system; intelligent water drops algorithm; MapReduce; Hadoop environment.

DOI: 10.1504/IJLSM.2018.094937

International Journal of Logistics Systems and Management, 2018 Vol.31 No.2, pp.249 - 266

Received: 25 Oct 2016
Accepted: 14 Apr 2017

Published online: 27 Sep 2018 *

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