Mobile Ad-hoc Network one of the prominent area for the researchers and practitioners in assorted domains including security, routing, addressing and many others. A Mobile Ad-hoc Network (MANET) refers to an autonomous group or cluster of mobile users that communicate over relatively bandwidth constrained wireless links. Mobile ad hoc network refers to the moving node rather than any fixed infrastructure, act as a mobile router. These mobile routers are responsible for the network mobility. The history of mobile network begin after the invention of 802.11 or WiFi they are mostly used for connecting among themselves and for connecting to the internet via any fixed infrastructure. Vehicles like car, buses and trains equipped with router acts as nested Mobile Ad-hoc Network. Vehicles today consists many embedded devices like build in routers, electronic devices like Sensors PDAs build in GPS, providing internet connection to it gives, information and infotainment to the users. These advances in MANET helps the vehicle to communicate with each other, at the time of emergency like accident, or during climatic changes like snow fall, and at the time of road block, this information will be informed to the nearby vehicles. Now days technologies rising to provide efficiency to MANET users like providing enough storage space, as we all know the cloud computing is the next generation computing paradigm many researches are conducting experiments on Mobile Ad-hoc Network to provide the cloud service securely. This paper attempts to propose and implement the security based algorithmic approach in the mobile adhoc networks.

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The area of metaheuristic optimization algorithms has been attracting researchers for many years. These algorithms have built in capability to explore a large region of the solution space, are computationally robust, efficient and can avoid premature convergence. They have been extensively tested and applied on many hard optimization problems where conventional computing techniques perform unsatisfactorily. They are capable of solving general N-dimensional, linear, nonlinear and complex global optimization problems. One of the latest entrants in this field is the Bat algorithm which is based on the echolocation behaviour of bats. It has been proven to have good convergence properties on different benchmark functions and seems promising for dealing with optimization problems. The aim of this paper is to provide a survey of the state of the art on Bat algorithm. A concise effort has been made so that the readers get a rapid insight into some of the applications upon which bat algorithm has been applied till date in specialized fields of science and engineering. Some of the variants of the bat algorithm as reported in the literature have also been discussed.

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