Abstract
The current existing high flexibility, profitability, and potential have made cloud computing extremely popular among the companies. This is used for improving and applying resources in an efficient manner and optimize makespan of the tasks. Scheduling is easy while there are only a few tasks to complete with few resources. Contrastingly, at the time the users forward several demands to the environment of the cloud, there may be a need for optimally selecting and allocating resources for achieving the desired quality of service that makes scheduling challenging. In this work, using intelligent metaheuristic algorithms for processing the requests and tasks of users in energy-aware scheduling made for a deadline is proposed. Genetic Algorithm (GA) the evolutionary algorithm that is inspired by the natural process of selection and the evolution theory. The Invasive Weed Optimization (IWO) was yet another novel stochastic based on the population that was a derivative-free technique of optimization inspired by the growth of the weed plants. The TABU Search (TS) was a generalization technique of local search where the TABU list was used for preventing cycling and further generating the candidates of the neighborhood. A hybrid GA with the TS (GA-TS) with a hybrid IWO with TS (IWO-TS) has been proposed for the energy and deadline aware scheduling. The framework further offers optimization of energy and performance. The primary purpose of this algorithm has been to improve deadline and scheduling in cloud computing along with local as well as global search algorithms. This framework will offer optimization of performance and energy. The reason behind presenting this algorithm was improving both scheduling and deadline in cloud computing using both local and global algorithms and results proved the algorithm to have better results.
Highlights
Cloud computing can be termed as a new paradigm where computing has been delivered as a new service as opposed to being a product with shared resources
For the purpose of cloud computing, at the time a user asks for services, task scheduling becomes important for selection
There is an ability to allocate limited resources for computing large tasks that have a goal of optimization inspiring wider solutions in the domain of cloud computing
Summary
Cloud computing can be termed as a new paradigm where computing has been delivered as a new service as opposed to being a product with shared resources. A major advantage of cloud computing is the reduction of capital expenditure for cloud users and their service providers. Cloud computing may be termed as a model of expanding computation that is based on the technology of virtualization which is in response to the request of users through the network of the internet with dynamic resource allocation. Such virtualization will reduce the cost of maintenance of the organizations and improve their accessibility. At the time users send different demands to the environment of the cloud, there may be a need to choose optimally and allocate resources to the desired quality of users making scheduling challenging [2]
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