Abstract

In the contemporary realm of operation in the World Wide Web, the cloud applications have to meet the high availability, operations on dynamic loads and must function at a very high quality. Load balancing is a proper technique to achieve above goals to distribute the loads across the server or to the various resources. This distribution optimizes performance, scalability, reliability and resources to be used, hence making the network to be appealing to bigger organizations to adopt it. The advantages because of load balancing are reduced response time, increased throughput and fault tolerance because the network traffic load is spread evenly among different servers thereby avoiding the occurrence of a bottleneck server. Some of these ways include Round Robin, Least Connection, and Weighted Distribution, help in the process by making it possible for systems to horizontally scale up for more traffic. As cloud services becomes popular, it becomes very important to manage the load since some applications or services may be more resource intensive than others. It distributes the incoming requests following the current loads on various servers and consequently, no server is too busy or idle. Also, load balancers provide for fault tolerance in the sense that traffic will be handled by other healthy servers in the occurrence of failures hence the solutions are highly available and reliable. Load balancing algorithms such from the basic rule-dependent to complex reinforcement learning algorithms are very crucial with respect to allocation of resources, energy management, and stability of the system. These algorithms will be increasingly important as cloud environments develop further in the efficiency of delivering services and the managing of resources needed, benefiting both the economy and the environment. INDEX TERMS: Performance, Scalability, Response Times, Latency, Horizontal Scaling, Load Balancing

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