A disruptive technology fundamentally transforming the way that computing services are delivered, cloud computing offers information and communication technology users a new dimension of convenience of resources, as services via the Internet. Because cloud provides a finite pool of virtualized on-demand resources, optimally scheduling them has become an essential and rewarding topic, where a trend of using Evolutionary Computation (EC) algorithms is emerging rapidly. Through analyzing the cloud computing architecture, this survey first presents taxonomy at two levels of scheduling cloud resources. It then paints a landscape of the scheduling problem and solutions. According to the taxonomy, a comprehensive survey of state-of-the-art approaches is presented systematically. Looking forward, challenges and potential future research directions are investigated and invited, including real-time scheduling, adaptive dynamic scheduling, large-scale scheduling, multiobjective scheduling, and distributed and parallel scheduling. At the dawn of Industry 4.0, cloud computing scheduling for cyber-physical integration with the presence of big data is also discussed. Research in this area is only in its infancy, but with the rapid fusion of information and data technology, more exciting and agenda-setting topics are likely to emerge on the horizon.

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Cloud Computing Resource Scheduling and a Survey of Its Evolutionary Approaches

https://cyberleninka.org/article/n/468779.pdf

A review of metaheuristic scheduling techniques in cloud computing

Load Balancing is essential for efficient operations indistributed environments. As Cloud Computing is growingrapidly and clients are demanding more services and betterresults, load balancing for the Cloud has become a veryinteresting and important research area. Many algorithms weresuggested to provide efficient mechanisms and algorithms forassigning the client's requests to available Cloud nodes. Theseapproaches aim to enhance the overall performance of the Cloudand provide the user more satisfying and efficient services. Inthis paper, we investigate the different algorithms proposed toresolve the issue of load balancing and task scheduling in CloudComputing. We discuss and compare these algorithms to providean overview of the latest approaches in the field.

A Survey of Load Balancing in Cloud Computing: Challenges and Algorithms

In this paper, we proposed an algorithm for load distribution of workloads among nodes of a cloud by the use of Ant Colony Optimization (ACO). This is a modified approach of ant colony optimization that has been applied from the perspective of cloud or grid network systems with the main aim of load balancing of nodes. This modified algorithm has an edge over the original approach in which each ant build their own individual result set and it is later on built into a complete solution. However, in our approach the ants continuously update a single result set rather than updating their own result set. Further, as we know that a cloud is the collection of many nodes, which can support various types of application that is used by the clients on a basis of pay per use. Therefore, the system, which is incurring a cost for the user should function smoothly and should have algorithms that can continue the proper system functioning even at peak usage hours.

Load Balancing of Nodes in Cloud Using Ant Colony Optimization

Cloud computing is emerging as a new paradigm of large-scale distributed computing. It is a framework for enabling convenient, on-demand network access to a shared pool of computing resources. Load balancing is one of the main challenges in cloud computing which is required to distribute the dynamic workload across multiple nodes to ensure that no single node is overwhelmed. It helps in optimal utilization of resources and hence in enhancing the performance of the system. The goal of load balancing is to minimize the resource consumption which will further reduce energy consumption and carbon emission rate that is the dire need of cloud computing. This determines the need of new metrics, energy consumption and carbon emission for energy-efficient load balancing in cloud computing. This paper discusses the existing load balancing techniques in cloud computing and further compares them based on various parameters like performance, scalability, associated overhead etc. that are considered in different techniques. It further discusses these techniques from energy consumption and carbon emission perspective.

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Cloud Load Balancing Techniques : A Step Towards Green Computing

Although cloud computing is generally recognized as a technology which will has a significant impact on IT in the future. However, Cloud computing is still in its infancy, many crucial problems need to be solved for the realization of the fine scenery which theoretically depicted by cloud computing. Load balancing is one of these problems; it plays a very important role in the realization of Open Cloud Computing Federation. We proposal a load balancing mechanism based on ant colony and complex network theory in open cloud computing federation in this paper, it improves many aspects of the related Ant Colony algorithms which proposed to realize load balancing in distributed system, Furthermore, this mechanism take the characteristic of Complex Network into consideration. Finally, the performance of this mechanism is qualitatively analyzed, and a prototype is developed to enable the quantitative analysis, simulation results manifest the analysis.

Zehua Zhang

Papers

A load balancing mechanism based on ant colony and complex network theory in open cloud computing federation