An AHP based Task Scheduling and Optimal Resource Allocation in Cloud Computing

Cloud systems by virtue characterize ultimate resource utilization with ever evolving user requirements facilitating adaptivity. With a scope of enhancing the QoS needs applications, numerous factors are considered for tunning among which Task scheduling promises to grab focus. The Scheduling mechanism ascertains improvement distributing subtasks specific set resources pertaining prevailing Quality models. work emphasizes need effective task and optimizing allocation modelling modified AHP (Analytical Hierarchy Process) driven approach. proposed method guarantees functionality in two phases ranking pipelined Optimized algorithms resulting maximization utilization. former phase is aided improved substantial usage fuzzy clustering followed an enhanced CUCMCA (Chimp Updated Cauchy Mutated Coot Algorithm) algorithm optimal cloud applications. contributed model leveraged performance 32% memory usage, 33.5% execution time, 29% makespan 18% communication cost over pre-existing conventional models considered.