The artificial bee colony (ABC), an optimization technique is based upon the intelligent moving behavior of honey bee swarm was proposed by Karaboga in 2005. This kind of new Meta heuristic is inspired by the clever foraging behavior of honey bee swarm. The criteria presented in the work is for numerical function optimization. The advantage of ABC is that the global search ability in the algorithm is implemented by introducing neighborhood source production mechanism. Rao et al. deals with radial division system network reconfiguration problem. This paper presents a method for deciding the sectionalizing switch to be operated in order to solve the distribution system loss minimization problem. ABC algorithm were used in many …show more content…
Tsai t al. present an interactive artificial bee nest supported passive continuous authentication system. A new population-based search algorithm called the Bees Algorithm (BA) is presented. The algorithm copies the food foraging patterns of swarms of honey bees. In its basic version, the algorithm works a kind of community search along with random search and can be used for both combinatorial optimization and functional optimization. Honey bees have developed the ability to collectively choose between nectar sources by opting for the optimum one: This source provides a maximum ratio of gain compared to costs. According to Johnson and Nieh, honey Bees are social pesky insects where collective decisions are made via feedback periods based on positive and negative signaling. Dependent task scheduling papers and scheduling with artificial bee colony is reviewed and found that no one has focused on artificial bee colony for scheduling …show more content…
This algorithm is extracted from a detailed examination of the behavior that honey bees adopt to find a food source. In bee hives, there is a class of bees called the scout bees which forage for food resources after finding one, offered back to the beehive in promoting this using a dance called waggle dance. The display of this dance, gives the notion of the quality and/or quantity of food and also its distance from the beehive. Forager bees then follow the Scout Bees to the location of food and then get started to reap it. Then they return to the beehive is to do a waggle or tremble or vibration dance to other bees in the beehive giving an idea of how much food is left and hence producing in either more abandonment of the food source. In the same manner, the removed tasks from over loaded server are considered as the honey bees. After submission to the under loaded server. In fact, the duties are the honey bees and the VM are the food sources. Loading of a task to a VM is just like a honey bee foraging a food source (a flower or a patch of flowers). Whenever a VM is full i. e., similar to the honey getting exhausted at a food source, the task will be scheduled to an under loaded VM similar to a foraging bee discovering a new food source. This removed task improves the rest of the tasks about the VM status similar to the waggle dance