Nowadays, cloud computing has come to the attention of big companies due to its high potential and flexibility and profitability. The approach followed in cloud computing services is to pay the costs for requested resources for an agreed period of time. In this system, the resource providers have to offer the best tradeoff between the requested resources and the amount of money users can pay, to be profitable for resource owners, in addition to customer satisfaction. Therefore, due to the massive volume of requests scheduling the users' requests is difficult and creating frameworks for scheduling is necessary. Scheduling algorithms attempt to allocate the tasks to the existing resources by considering the quality of services. In this paper, we review and compare various scheduling methods in the cloud computing environment.

A review of recent methods of task scheduling in cloud computing

Despite the increasing use of cloud computing technology because it offers unique features to serve its customers perfectly, exploiting the full potential is very difficult due to the many problems and challenges. Therefore, scheduling resources are one of these challenges. Researchers are still finding it difficult to determine which of the scheduling algorithms are appropriate and effective and that helps increases the performance of the system to accomplish these tasks. This paper provides a broad and detailed examination of resource scheduling algorithms in the environment of a cloud computing environment and highlights the advantages and disadvantages of some algorithms to help researchers in selecting the best algorithms to schedule a particular workload to get a satisfy a quality of service, guarantee good utilization of the cloud resources also minimizing the make-span.

/pdf/a-cloud-computing-scheduling-and-its-evolutionary-approaches-2s18nbok2s.pdf

A cloud computing scheduling and its evolutionary approaches

With the growth of grid computing, having priorities that vary according to the context and, therefore, in the scheduling algorithms that operate in it, elaborating optimizations that maximize the quality of the resources disposition and minimize the unwanted outgoings is essential. With this, a model is built based on the users confindence level, based on an algorithm that reposition the queues according to this information, helping the precise users at the expense of the non-precise ones. It also seeks, through this, to make users aware in sending more accurate information. The results obtained have a positive return on reducing the waiting time of these more accurate users by up to 93% Resumo. Com o crescimento da computação em grade, possuindo prioridades que variam conforme o contexto e, portanto, nos algoritmos de escalonamento que nela atuam, elaborar otimizações que maximizem a qualidade da disposição dos recursos e minimizem os gastos indesejados é essencial. Com isso, é construı́do um modelo baseado no nı́vel de confiança do usuário, a partir de um algoritmo que reposiciona as filas de acordo com essa informação, ajudando os usuários precisos em detrimento dos não precisos. Busca-se também, através disso, conscientizar os usuários no envio de informações mais acertadas. Os resultados obtidos tem um retorno positivo de redução do tempo de espera desses usuários mais precisos em até 93%

/pdf/buc-beneficiador-de-usuarios-conscientes-em-grades-6n0p6w3m1v.pdf

BUC: Beneficiador de Usuários Conscientes em Grades

Cloud computing is a concept introduced in the information technology era, with the main components being the grid, distributed, and valuable computing. The cloud is being developed continuously and, naturally, comes up with many challenges, one of which is scheduling. A schedule or timeline is a mechanism used to optimize the time for performing a duty or set of duties. A scheduling process is accountable for choosing the best resources for performing a duty. The main goal of a scheduling algorithm is to improve the efficiency and quality of the service while at the same time ensuring the acceptability and effectiveness of the targets. The task scheduling problem is one of the most important NP-hard issues in the cloud domain and, so far, many techniques have been proposed as solutions, including using genetic algorithms (GAs), particle swarm optimization, (PSO), and ant colony optimization (ACO). To address this problem, in this paper, one of the collective intelligence algorithms, called the Salp Swarm Algorithm (SSA), has been expanded, improved, and applied. The performance of the proposed algorithm has been compared with that of GAs, PSO, continuous ACO, and the basic SSA. The results show that our algorithm has generally higher performance than the other algorithms. For example, compared to the basic SSA, the proposed method has an average reduction of approximately 21% in makespan.

pdf/a-schedule-of-duties-in-the-cloud-space-using-a-modified-3wj8emafhb.pdf

A Schedule of Duties in the Cloud Space Using a Modified Salp Swarm Algorithm

Cloud computing is a form of distributed computing which provides various services to the users. Because it of its dynamic and distributed services it has attracted the users and it is a fast growing technology in the field of distributed computing. It is highly scalable and it allows on-demand services. Millions of user are using the cloud environment because of its pay-as-you-go service. The cloud environment must be able to meet the user requirements and provide quality of service with high performance. The performance of cloud computing will be better if an efficient task scheduling algorithm is used for mapping the tasks to the available resources. An efficient scheduling algorithm increases the resource utilization thereby minimizing the execution time and cost. This paper proposes a Mean-Min Task Scheduling algorithm for Cloud environment based on the minimum execution time of the tasks submitted.

/pdf/mean-min-task-scheduling-algorithm-for-cloud-environment-2hi1ka8sqp.pdf

Mean-Min task scheduling algorithm for cloud environment

cloud computing is an emerging technology and serves as next generation platform, which allows the user to pay as they use. It permits access to remote and geographically distributed resources with the help of an important feature in cloud computing called virtualization. Cloud consists of number of virtual machines. In cloud there is need of number of virtual machines (VM) based on the requirement of user and cloud service providers. Scheduling is necessary to manage large number of VM requests. Scheduling is key technology in cloud computing, scheduling of tasks and resource allocation is challenging task in cloud. So we require scheduling algorithm. Primary consideration of scheduling algorithm is to provide proficiency to task and resource scheduling. Main objective of the paper is to give comparative analysis of existing scheduling algorithm in cloud platform where resources have varying cost and computational efficiency. In this paper we have surveyed on different types of scheduling algorithm and tabulated their various parameters, scheduling factors and so on.

Comparative Study of Various Scheduling Algorithms in Cloud Computing

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Comparative Study of Various Scheduling Algorithms in Cloud Computing