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SYSTEM DYNAMIC MULTISERVICE LOAD BALANCING IN

                        CLOUD-BASED MULTIMEDIA        

ABSTRACT

In this paper we study about centralized hierarchical cloud-based multimedia system (CMS).That consisting of a resource manager, cluster heads, and server clusters, in which the resource manager assigns clients that requests for multimedia service tasks to server clusters according to the task characteristics, and then each cluster head distributes the assigned task to the servers within its server cluster. For such a complicated CMS, however, it is are search challenge to design an effective load balancing algorithm that spreads the multimedia service task load on servers with the minimal cost for transmitting multimedia data between server clusters and clients, while the maximal load limit of each server cluster is not violated. Unlike previous work, this paper takes into account a more practical dynamic multiservice scenario in which each server cluster only handles a specific type of multimedia task, and each client requests a different type of multimedia service at a different time. Such a scenario can be modelled as an integer linear programming problem, which is computationally intractable in general. As a consequence, this paper further solves the problem by an efficient genetic algorithm with an immigrant scheme, which has been shown to be suitable for dynamic problems. Simulation results demonstrate that the proposed genetic algorithm can efficiently manage with dynamic multiservice load balancing in CMS.

EXISTING SYSTEM	PROPOSED SYSTEM
EXISTING CONCEPT:- In the existing system the server cluster handles only a specific type of multimedia task, and each client requests a different type of multimedia service at a different time. Such a scenario can be modelled as an integer linear programming problem. The load balancing problem for the CMS is based on all the multimedia service tasks are of the same type, and did not consider the dynamic scenario where load balancing should adapt to the time change. The decentralized technique is only suitable for smaller systems.	PROPOSED CONCEPT:- In the proposed system we implement a centralized CMS and we proposed a genetic algorithm (GA) for the concerned dynamic load balancing problem in CMS. The resource manager of the centralized CMS stores the global service task load information collected from server clusters, and decides the amount of client’s requests assigned to each server cluster so that the load of each server cluster is distributed as balanced as possible in terms of the cost of transmitting multimedia data between server clusters and clients.
EXISTING TECHNIQUE:- Decentralized Framework	PROPOSED TECHNIQUE:- Genetic algorithm, Load balancing algorithm
TECHNIQUE DEFNITION:- The decentralized CMS, each time it receives clients’ requests for multimedia service tasks, the resource manager of the centralized CMS stores the global service task load information collected from server clusters and to client cluster.	TECHNIQUE DEFNITION:- Load balancing algorithm that spreads the multimedia service task load on servers with the minimal cost for transmitting multimedia data between server clusters and clients, while the maximal load limit of each server cluster is not violated.
DRAWBACKS:- Decentralized framework method is suitable for only small collection of system Server cluster can handle only one type  request at a time so that load balancing problem occurs	ADVANTAGES:- The centralized CMS framework is scalable CMS framework is suitable for larger collection of systems Client’s requests assigned to each server cluster so that the load of each server cluster is distributed as balanced.