Load Balancing Algorithms In Cloud Research Articles

A review on load balancing algorithms in cloud computing

Cloud computing is the method for figuring, by means of the web that shares PC assets as opposed to utilizing programming or capacity on a nearby PC. It stores the information and assets in the open condition. So now daily's measure of information stockpiling increment rapidly. load Balancing is the primary issues in Cloud which is required to disseminate the dynamic remaining task at hand over numerous hubs to guarantee that no single hub is overpowered. load Balancing gives appropriate use of assets and upgrading the execution of the framework. The few existing calculations that can give load adjusting and furthermore give better systems through productive employment booking and asset planning methods also. So as to pick up boost the benefit and adjusting calculations, it is important to use assets effectively. This paper talks about a portion of the current load adjusting calculations in distributed computing.

A comparative study of energy and task efficient load balancing algorithms in cloud computing

The future growth of the Internet of Services has fundamentally changed the emergence of cloud computing. Cloud data centres serve multiple tenant demands for cloud applications that discharge vast amounts of electricity, leading to high operating costs and environmental diffusion of carbon dioxide (CO2). To fix this is the need for preservation to enable potential use by building a new structure and measuring the effect in a cloud data centre. Consequently, the use of pruned electricity reduces the cost of processing power. In order to meet energy-efficient data centres in the cloud, adjusting to optimal load balancing processing a good way for energy savings. To minimise the large energy use of cloud data centres herds, this focuses on increasing efficacy by breaking the workload evenly. In this paper, we plan to provide a comprehensive comparative analysis in cloud computing of current load balancing algorithms.

A binary Bird Swarm Optimization based load balancing algorithm for cloud computing environment

Abstract Task scheduling and load balancing are a concern for service providers in the cloud computing environment. The problem of scheduling tasks and balancing loads in a cloud is categorized under an NP-hard problem. Thus, it needs an efficient load scheduling algorithm that not only allocates the tasks onto appropriate VMs but also maintains the trade-off amidst VMs. It should keep an equilibrium among VMs in a way that reduces the makespan while maximizing the utilization of resources and throughput. In response to it, the authors propose a load balancing algorithm inspired by the mimicking behavior of a flock of birds, which is called the Bird Swarm Optimization Load Balancing (BSO-LB) algorithm that considers tasks as birds and VMs as destination food patches. In the considered cloud simulation environment, tasks are assumed to be independent and non-preemptive. To evaluate the efficacy of the proposed algorithm under real workloads, the authors consider a dataset (GoCJ) logged by Goggle in 2018 for the execution of cloudlets. The proposed algorithm aims to enhance the overall system performance by reducing response time and keeping the whole system balanced. The authors have integrated the binary variant of the BSO algorithm with the load balancing method. The proposed technique is analyzed and compared with other existing load balancing algorithms such as MAX-MIN, RASA, Improved PSO, and other scheduling algorithms as FCFS, SJF, and RR. The experimental results show that the proposed method outperforms when being compared with the different algorithms mentioned above. It is noteworthy that the proposed approach illustrates an improvement in resource utilization and reduces the makespan of tasks.

A Load Balancing Algorithm for Infrastructure as a Service Platform (IaaS) Using Bees Algorithm and Queuing Theory

Cloud computing is an emerging computing paradigm in the IT industry and the acceptance of this technology is rising fast with an unprecedented growth of data centre across the world. Recent studies have shown that ensuring load balancing (LB) in different data centre is critical for achieving optimal resource utilisation, maximise throughput, minimum response time and avoid overloading of resource. The traditional techniques of LB are not suitable for the cloud data centre's because of the virtualisation of the physical systems. In a centralised approach, scalability issues are more especially on machines with small amount of memory. On the other hand, a fully distributed approach tends to yield a poor performance on very large number of systems. In this paper, we propose a hybrid agent-based LB algorithm for cloud computing using Bees algorithm and queuing theory for Infrastructure as a Service platform. The proposed algorithm solves the problem of load unbalance and ensures high resource utilisation with minimum response time.

A survey on load balancing algorithms in cloud computing

Cloud computing is a rising technology, which offers various online services like data storage, application and infrastructure on pay per used fashion that provides access in location independent manner. These services offer significant benefits for both consumer and producer. For optimal utilisation of resources, researchers from both academia and industry focus their efforts towards on cloud computing services. To achieve this target, numerous challenges have to be faced, out of which, load balancing is a centric issue in cloud computing environment which requires distribution of work load in a fairly manner across all the nodes. In this paper, a rich collection of algorithms has been surveyed and presented with detailed classification of algorithms based on different metrics such as reaction time, resource utilisation and energy efficiency and so on. Moreover, the merits, demerits, implementation tool and scope of implementation of each algorithm have been presented. The different implementation tools have also been discussed which provides the better idea for simulation platform. This work is intended to enable the readers to decide suitable approach and simulation platform for better load balancing algorithm.

A survey on load balancing algorithms in cloud computing

Cloud computing is a rising technology, which offers various online services like data storage, application and infrastructure on pay per used fashion that provides access in location independent manner. These services offer significant benefits for both consumer and producer. For optimal utilisation of resources, researchers from both academia and industry focus their efforts towards on cloud computing services. To achieve this target, numerous challenges have to be faced, out of which, load balancing is a centric issue in cloud computing environment which requires distribution of work load in a fairly manner across all the nodes. In this paper, a rich collection of algorithms has been surveyed and presented with detailed classification of algorithms based on different metrics such as reaction time, resource utilisation and energy efficiency and so on. Moreover, the merits, demerits, implementation tool and scope of implementation of each algorithm have been presented. The different implementation tools have also been discussed which provides the better idea for simulation platform. This work is intended to enable the readers to decide suitable approach and simulation platform for better load balancing algorithm.

An In-depth Analysis and Study of Load Balancing Techniques in the Cloud Computing Environment

Abstract In the cloud computing paradigm, load balancing is one of the challenges, With Tremendous increase in the users and their demand of different services on the cloud computing platform, fruitful or efficient usage of resources in the cloud environment became a critical concern. Load balancing is playing a vital role in maintaining the rhythm of Cloud computing. The performance metrics of load balancing algorithms in cloud are response time and waiting time. In this paper we mainly focus on two load balancing algorithms in cloud, Min-Min and Max-Min algorithm.

Round Robin with Server Affinity: A VM Load Balancing Algorithm for Cloud Based Infrastructure

Cloud computing is an evolving computing paradigm that has influenced every other entity in the globalized industry, whether it is in the public sector or the private sector. Considering the growing importance of cloud, finding new ways to improve cloud services is an area of concern and research focus. The limitation of the available Virtual Machine Load balancing policies for cloud is that they do not save the state of the previous allocation of a virtual machine to a request from a Userbase and the algorithm requires execution each time a new request for Virtual Machine allocation is received from the Userbase. This problem can be resolved by developing an efficient virtual machine load balancing algorithm for the cloud and by doing a comparative analysis of the proposed algorithm with the existing algorithms. Keywords—Virtual Machine (VM), Server affinity, VM load balancer, CloudAnalyst, Data center, Cloudlet