Fault Detection Enabled Optimal Of Vehicle Alert And Routing Problem Using Hybrid KP-OACO Algorithm For Balancing Load In Cloud Computing
M. Kannan1, C. Priya2

1M. Kannan, M.Phil Research Scholar, Department of Computer Science, Vels Institute of Science, Technology and Advanced Studies (VISTAS), Pallavaram, Chennai (Tamil Nadu), India.
2Dr. C. Priya, Associate Professor, Research Supervisor, Department of Information Technology, Vels Institute of Science, Technology and Advanced Studies (VISTAS), Pallavaram, Chennai (Tamil Nadu), India.

Manuscript received on 18 June 2019 | Revised Manuscript received on 25 June 2019 | Manuscript published on 30 June 2019 | PP: 903-909 | Volume-8 Issue-5, June 2019 | Retrieval Number: E7403068519/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Traffic and vehicle routing is one of the nigh natural and common topic. Generally, vehicle routing is a condemnatory circulation. Many cities have considered lots of people. Specimen, Turkey. Generally turkey city has 6 cities with more millions of people, which is the 8th largest city, it has 14,804,116 (2019). In this paper produce the optimized solution for vehicle routing and waking up the people from the traffic. ACO (Ant Colony) is an optimization technique, which was specially made for hard combinatorial problems (NP-Hard), in which ACO (Ant Colony) was first invented by Dorigo. ACO (Ant Colony) is a heuristic tactic that is animated by the activity of the original ant. Many research peoples have already worked on this vehicle routing problem and discuss their results. Even though it has some alleviate like computation time and speed. This paper is re-analyzed and to propose the new hybrid Ant Colony Algorithm (ACA), namely, KP-OACO is to deal with the VARP using some variant of a bio-energy algorithm, scilicet, the Ant System (AS), Ant Colony System (ACS), and Hybrid KP-OACO (KP-Optimized Ant COlony) Algorithm to quest the better optimized result of the VAR problem (VARP). The main sequel of this paper is to attentive the person while he/she is on the vehicle and also find the optimized way from the traffic, through this we can solve the routing problem either the object is heavily loaded or if it is a normal vehicle. From this proposed work the speed will also increase through this algorithm and also we can remit our cost. At this paper KP-OACO algorithm is a proposed and modified algorithm for re-analyzing the VAR (Vehicle Routing and Alert) problem. The goal of the algorithm KP-OACO is to balance the mass. In this proposed work has been simulated using Cloud Analyst. ACO (Ant Colony) helps to analyze the new way from an existential way, to do this we can avoid the traffic.
Keywords: VARP, AS, ACS, Hybrid KP-OACO Algorithm, and Load Balancing.

Scope of the Article: Cloud Computing