A REVIEW ON LOAD BALANCING IN CLOUD USING ENHANCED GENETIC ALGORITHM

“Cloud computing” is a term, which involves virtualization, distributed computing, networking, software and net services. A cloud consists of several parts such as shoppers, datacenter and distributed servers. It includes fault tolerance, high availability, scalability, flexibility, reduced overhead for users, reduced cost of possession, on demand services etc. Central to these issues lies the institution of a good load reconciliation algorithmic rule. The load can be CPU load, memory capacity, delay or network load. Load balancing is the method of distributing the load among varied nodes of a distributed system to boost each resource utilization and job interval whereas additionally avoiding a state of affairs wherever a number of the nodes area unit heavily loaded whereas different nodes area unit idle or doing little work. Load balancing ensures that all the processors within the system or each node within the network will require the equal quantity of labor at any instant of your time. This technique will be sender initiated, receiver initiated or symmetric sort (combination of sender initiated and receiver initiated types). Our objective is to develop an effective load reconciliation algorithmic rule mistreatment divisible load programming theorem to maximize or minimize completely different performance parameters (throughput, latency for example) for the clouds of different sizes (virtual topology de-pending on the appliance requirement).