A Survey on Load Balancing Algorithms for VM Placement in Cloud Computing

The emergence of cloud computing based on virtualization technologies brings huge opportunities to host virtual resource at low cost without the need of owning any infrastructure. Virtualization technologies enable users to acquire, configure and be charged on pay-per-use basis. However, Cloud data centers mostly comprise heterogeneous commodity servers hosting multiple virtual machines (VMs) with potential various specifications and fluctuating resource usages, which may cause imbalanced resource utilization within servers that may lead to performance degradation and service level agreements (SLAs) violations. To achieve efficient scheduling, these challenges should be addressed and solved by using load balancing strategies, which have been proved to be NP-hard problem. From multiple perspectives, this work identifies the challenges and analyzes existing algorithms for allocating VMs to PMs in infrastructure Clouds, especially focuses on load balancing. A detailed classification targeting load balancing algorithms for VM placement in cloud data centers is investigated and the surveyed algorithms are classified according to the classification. The goal of this paper is to provide a comprehensive and comparative understanding of existing literature and aid researchers by providing an insight for potential future enhancements.Comment: 22 Pages, 4 Figures, 4 Tables, in pres

Load Balancing Mechanisms in the Software Defined Networks: A Systematic and Comprehensive Review of the Literature

With the expansion of the network and increasing their users, as well as emerging new technologies, such as cloud computing and big data, managing traditional networks is difficult. Therefore, it is necessary to change the traditional network architecture. Lately, to address this issue, a notion named software-defined network (SDN) has been proposed, which makes network management more conformable. Due to limited network resources and to meet the requirements of quality of service, one of the points that must be considered is load balancing issue that serves to distribute data traffic among multiple resources in order to maximize the efficiency and reliability of network resources. Load balancing is established based on the local information of the network in the conventional network. Hence, it is not very precise. However, SDN controllers have a global view of the network and can produce more optimized load balances. Although load balancing mechanisms are important in the SDN, to the best of our knowledge, there exists no precise and systematic review or survey on investigating these issues. Hence, this paper reviews the load balancing mechanisms which have been used in the SDN systematically based on two categories, deterministic and non-deterministic. Also, this paper represents benefits and some weakness regarded of the selected load balancing algorithms and investigates the metrics of their algorithms. In addition, the important challenges of these algorithms have been reviewed, so better load balancing techniques can be applied by the researchers in the future. © 2018 IEEE

Cloud computing resource scheduling and a survey of its evolutionary approaches

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

Load Balancing and Virtual Machine Allocation in Cloud-based Data Centers

As cloud services see an exponential increase in consumers, the demand for faster processing of data and a reliable delivery of services becomes a pressing concern. This puts a lot of pressure on the cloud-based data centers, where the consumers’ data is stored, processed and serviced. The rising demand for high quality services and the constrained environment, make load balancing within the cloud data centers a vital concern. This project aims to achieve load balancing within the data centers by means of implementing a Virtual Machine allocation policy, based on consensus algorithm technique. The cloud-based data center system, consisting of Virtual Machines has been simulated on CloudSim – a Java based cloud simulator