Load Balancing pada Cloud Computing dengan Sumber Daya Terbatas Menggunakan Penggabungan Algoritma ESCE dan Throttled

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Endang Wahyu Pamungkas ◽  
Divi Galih Prasetyo Putri
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Load Balancing ◽  
High Reliability ◽  
Cloud Service ◽  
The Other ◽  
Limited Resources ◽  
Resource Quality ◽  
Cloud Computing Environment ◽  
Load Balancing Algorithm

Recently cloud computing technology has been implemented by many companies. This technology requires a really high reliability that closely related to hardware specification and management resource quality used. Adequate hardware would make resource allocation easier. On the other hand, resource allocation will be harder if the resources are limited. This is a common condition in a developing cloud service provider. In this paper, a load balancing algorithm to allocate resources in cloud computing environment that has limited resources has been proposed. This algorithm is developed by taking the advantages of the existing algorithms, Equally Spread Current Execution and Throttled. We merge those algorithm without losing the advantages and we try to eliminate the shortcoming of each algorithm. The result shows that this algorithm is able to give a significant improvement in the limited resources environment. In addition, the algorithm also able to compete with the other algorithm in the more adequate resource environment. Based on the consistent results, this algorithm is expected to be more adaptive in different resources environment.

A Proficient Approach for Load Balancing in Cloud Computing-Join Minimum Loaded Queue

2020 ◽  
Vol 11 (1) ◽  
pp. 12-36
Author(s):  
Minakshi Sharma ◽  
Rajneesh Kumar ◽  
Anurag Jain
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Response Time ◽  
Resource Utilization ◽  
Cloud Service ◽  
Cloud Environment ◽  
Cloud Service Provider ◽  
Qos Parameters ◽  
Load Balancing Algorithm

Cloud load balancing is done to persist the services in the cloud environment along with quality of service (QoS) parameters. An efficient load balancing algorithm should be based on better optimization of these QoS parameters which results in efficient scheduling. Most of the load balancing algorithms which exist consider response time or resource utilization constraints but an efficient algorithm must consider both perspectives from the user side and cloud service provider side. This article presents a load balancing strategy that efficiently allocates tasks to virtualized resources to get maximum resource utilization in minimum response time. The proposed approach, join minimum loaded queue (JMLQ), is based on the existing join idle queue (JIQ) model that has been modified by replacing idle servers in the I-queues with servers having one task in execution list. The results of simulation in CloudSim verify that the proposed approach efficiently maximizes resource utilization by reducing the response time in comparison to its other variants.

scholarly journals Resource Allocation in Cloud Computing using Heuristic Load Balancing Algorithm

2020 ◽  
Author(s):  
Anup Shrestha ◽  
Suriayati Chuprat ◽  
Nandini Mukherjee
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Load Balancing ◽  
Completion Time ◽  
Virtual Machines ◽  
It Services ◽  
Computing Environment ◽  
Load Balancing Algorithm ◽  
Better Than

Cloud computing is becoming more popular, unlike conventional computing, due to its added advantages. This is because it offers utility-based services to its subscribers upon their demand. Furthermore, this computing environment provides IT services to its users where they pay for every use. However, the increasing number of tasks requires virtual machines for them to be accomplished quickly. Load balancing a critical concern in cloud computing due to the massive increase in users' numbers. This paper proposes the best heuristic load balancing algorithm that will schedule a strategy for resource allocation that will minimize make span (completion time) in any technology that involves use cloud computing. The proposed algorithm performs better than other load balancing algorithms.

Performance Improvement in Cloud Computing Environment by Load Balancing-A Comprehensive Review

2021 ◽  
Vol 11 (2) ◽  
pp. 1386-1399
Author(s):  
Ramya K.
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Load Balancing ◽  
Cloud Service ◽  
Cloud Environment ◽  
Cloud Computing Environment ◽  
Consumption Cost ◽  
High Level ◽  
Near Future

With the advent of cloud computing, the affinity between business and technology had increased manifold, allowing users to access IT resources at their convenience through the pay-per-use scheme. With such huge demand surging day to day, the cloud environment must cater to the user requirements flawlessly and also should be rewarding to the providers of cloud service. To maintain its high level of efficiency, there are several challenges that the cloud environment should tackle. One amongst those challenges is the balancing of load. It is one of the primary features of cloud computing that focuses on avoiding the overloading of nodes where there may be idle nodes or nodes with lesser load present at the same juncture. By keeping an effective check on the load several the Quality of Service (QoS) parameters including response time, throughput, resource utilization, energy consumption, cost etc., can be improved, adding to better performance of the entire cloud environment. Even distribution of load among datacenters will contribute to optimal energy consumption and keeps a check on carbon emissions. In this paper we have presented a methodical review on literature pertaining to load balancing strategies that had been proposed in the cloud environment. We had made in-depth analyses of available load balancing techniques and had come up with their advantages, limitations along with the challenges to be addressed by researchers for developing efficient load balancing strategies in the near future. We had also suggested prospective insights about the aspects in load balancing that could be applied in the cloud environment.

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

2021 ◽  
Vol 11 (1) ◽  
pp. 146-160
Author(s):  
Kaushik Mishra ◽  
Santosh Kumar Majhi
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Service Providers ◽  
Scheduling Algorithm ◽  
Simulation Environment ◽  
Computing Environment ◽  
Swarm Optimization ◽  
Cloud Computing Environment ◽  
Np Hard Problem ◽  
Load Balancing Algorithm

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.

scholarly journals A Proposed Load Balancing Algorithm Over Cloud Computing (Balanced Throttled)

2021 ◽  
Vol 10 (2) ◽  
pp. 28-33
Author(s):  
Shereen Yousef Mohamed ◽  
◽  
Mohamed Hamed N. Taha ◽  
Hesham N. Elmahdy ◽  
Hany Harb ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Virtual Machine ◽  
Static Load ◽  
Dynamic Load Balancing ◽  
System State ◽  
Computing Environment ◽  
Virtual Machine Migration ◽  
Cloud Computing Environment ◽  
Load Balancing Algorithm

Cloud computing refers to the services and applications that are accessible throughout the world from data centers. All services and applications are available online. Virtual machine migration is an important part of virtualization which is considered as essential part in cloud computing environment. Virtual Machine Migration means transferring a running Virtual Machine with all its applications and the operating system state as it is to target destination machine where it continues to run as if nothing happened. It makes balancing between servers. This improves the performance by redistributing the workload among available servers. There are many algorithms of load balancing classified into two types: static load balancing algorithms and dynamic load balancing algorithms. This paper presents the algorithm (Balanced Throttled Load Balancing Algorithm- BTLB). It compares the results of the BTLB with round robin algorithm, AMLB algorithm and throttled load balancing algorithm. The results of these four algorithms would be presented in this paper. The proposed algorithm shows the improvement in response time (75 µs). Cloud analyst simulator is used to evaluate the results. BTLB was developed and tested using Java.

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