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The static scheduling algorithms are widely used to evaluate the performance of distributed computing system. In such systems, purpose of scheduling algorithm is to allocate tasks to available processor so as to efficiently utilize this processor and to reduce the makespan, total computational cost and various other such factors, with the motive of achieving optimal solution. Scheduling algorithms are classified into two broad categories i.e., static scheduling algorithms and dynamic scheduling algorithms. In this paper we are discussing various static scheduling algorithm and numerous problems in various levels of the homogeneous and heterogeneous distributed systems. Also we are comparing these algorithms on the basis of various factors such as speedup, time complexity, scheduling length ratio, normalized scheduling length and so on.

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Cloud computing is emerging as a new standard model for enabling ubiquitous network access, computing resources, deploying, organizing, and accessing vast distributed computing applications over the network. In cloud computing, Load balancing is one of the main challenges which are required to distribute the workload equally across all the nodes. Load balancing uses services offered by many computer network service provider corporations. Load balancing can be different types like network load, storage capacity, memory capacity and CPU load. Load balancing helps to achieve a high user satisfaction and resource utilization ratio by confirming an efficient and fair allocation of every computing resource. Proper load balancing support in implementing failover, enabling scalability, overprovisioning, and decreases costs associated with document management systems and maximizes the availability of resources. This paper describes a survey of different dynamic load balancing algorithms in the cloud environment with their comparisons on the bases of different load balancing metrics. KeywordsCloud Computing, Load balancing, load balancer, static load balancing, dynamic load balancing algorithm, load balancing metrics.

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