Cloud computing (CC) is fast-growing and frequently adopted in information technology\n(IT) environments due to the benefits it offers. Task scheduling and load balancing are amongst the\nhot topics in the realm of CC. To overcome the shortcomings of the existing task scheduling and load\nbalancing approaches, we propose a novel approach that uses dominant sequence clustering (DSC)\nfor task scheduling and a weighted least connection (WLC) algorithm for load balancing. First, usersâ??\ntasks are clustered using the DSC algorithm, which represents user tasks as graph of one or more\nclusters. After task clustering, each task is ranked using Modified Heterogeneous Earliest Finish\nTime (MHEFT) algorithm. where the highest priority task is scheduled first. Afterwards, virtual\nmachines (VM) are clustered using a mean shift clustering (MSC) algorithm using kernel functions.\nLoad balancing is subsequently performed using a WLC algorithm, which distributes the load based\non server weight and capacity as well as client connectivity to server. A highly weighted or least\nconnected server is selected for task allocation, which in turn increases the response time. Finally,\nwe evaluate the proposed architecture using metrics such as response time, makespan, resource\nutilization, and service reliability.
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