scholarly journals MINIMIZATION OF LOAD BASED RESOURCES IN CLOUD COMPUTING SYSTEMS

2015 ◽  
pp. 72-75
Author(s):  
ZULFIKHAR AHMAD ◽  
ASHIS KU. MISHRA ◽  
BIKASH CHANDRA ROUT
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Distributed System ◽  
Work Load ◽  
Memory Capacity ◽  
Performance Parameters ◽  
Computing Systems ◽  
Divisible Load ◽  
Network Load ◽  
Load Balancing Algorithm

“Cloud computing” is a term, which involves virtualization, distributed computing, networking, software and Web services. Our Objective is to develop an effective load balancing algorithm using Divisible Load Scheduling Theorem to maximize or minimize different performance parameters (throughput, latency for example) for the clouds of different sizes. Central to these issues lays the establishment of an efficient load balancing algorithm. The load can be CPU load, memory capacity, delay or network load. Load balancing is the process of distributing the load among various nodes of a distributed system to improve both resource utilization and job response time while also avoiding a situation where some of the nodes are heavily loaded while other nodes are idle or doing very little work. Load balancing ensures that all processor in the system or every node in the network does approximately the equal amount of work at any instant of time.

scholarly journals Optimized Load Balancing Strategy In Cloud Computing : A Review

2016 ◽  
Vol 15 (4) ◽  
pp. 6681-6685
Author(s):  
Parveen Kaur ◽  
Monika Sachdeva
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Load Balancing ◽  
Response Time ◽  
Resource Utilization ◽  
Distributed System ◽  
Job Scheduling ◽  
Work Load ◽  
Memory Capacity ◽  
Network Load

Now a days every organization is migrating towards  cloud computing as cloud computing is considered being more flexible and scalable as compared to other technologies. The technology simply means to provide the computing resources and services through a network. This paper discusses the existing approaches for scheduling algorithms that can maintain the load balancing and provides better improved strategies through efficient job scheduling and modified resource allocation techniques. The load can be CPU load, memory capacity, delay or network load. Load balancing is the process of distributing the load among various nodes of a distributed system to improve both resource utilization and job response time while also avoiding a situation where some of the nodes are heavily loaded while other nodes are idle or doing very little work. Load balancing ensures that all the processor in the system or every node in the network does approximately the equal amount of work at any instant of time. 

scholarly journals Evaluating Load Balancing Algorithms for Performance Optimization in Cloud Computing

2019 ◽  
Vol 8 (12) ◽  
pp. 2217-2221
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Performance Optimization ◽  
Memory Capacity ◽  
Load Management ◽  
Performance Parameters ◽  
Network Load ◽  
Important Concern

Cloud computing is a new sort of computing over internet. It has many advantages along with several issues. These issues are related to load management, security of data in cloud. In this paper, the most important concern is to prevent bottleneck in cloud computing. The load can be (CPU load, memory capacity, delay or network-load). Load balancing is the process of distributing the load among various servers so that none of the servers is underloaded. Load-balancing also prevents the situation where some servers are heavily loaded while others are idle. This process of Load balancing ensures that load is distributed equally among the servers. In this paper, some algorithms of load balancing is discussed along with its benefits and drawbacks and also tested these algorithms on some performance parameters.

scholarly journals Enhanced Weighted Round Robin Load Balancing Algorithm in Cloud Computing

2019 ◽  
Vol 8 (9S2) ◽  
pp. 148-151
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Task Assignment ◽  
Round Robin ◽  
Utility Computing ◽  
Distributed Environment ◽  
Dynamic Task ◽  
Computing Model ◽  
Network Load ◽  
Load Balancing Algorithm

The cloud/utility computing model requires a dynamic task assignment to cloud sites with the goal that the performance and demand handling is done as effectively as would be prudent. Efficient load balancing and proper allocation of resources are vital systems to improve the execution of different services and make legitimate usage of existing assets in the cloud computing atmosphere. Consequently, the cloud-based infrastructure has numerous kinds of load concerns such as CPU load, server load, memory drain, network load, etc. Thus, an appropriate load balancing system helps in realizing failures, reducing backlog problems, adaptability, proper resource distribution, expanding dependability and client fulfillment and so forth in distributed environment. This thesis reviewed various popular load balancing algorithms. Modified round robin algorithms are popularly employed by various giant companies for scheduling issues and load balancing. An enhanced weighted round robin algorithm is discussed in this paper concentrating on efficient load balancing and effective task scheduling and resource management.

A Load Balancing Algorithm for 5G Vehicular Cloud Computing Systems

2020 ◽  
Author(s):  
Eirini Zoumi ◽  
Emmanouil Skondras ◽  
David Veliu ◽  
Angelos Michalas ◽  
Dimitrios D. Vergados
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Computing Systems ◽  
Vehicular Cloud Computing ◽  
Vehicular Cloud ◽  
Load Balancing Algorithm

scholarly journals Virtual Machine Allocation Policy for Load Balancing

2021 ◽  
Vol 2070 (1) ◽  
pp. 012129
Author(s):  
M. Shabina Ghafir ◽  
Afshar Alam ◽  
Farheen Siddiqui ◽  
Sameena Naaz
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Work Load ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Allocation Policy ◽  
Vm Allocation ◽  
Proposed Model ◽  
Load Balancing Algorithm ◽  
Machine Allocation

Abstract This paper focuses on the VM allocation policies for load balancing in cloud computing environment. Intermittent nature of balancing the load scheme into the cloud computing becomes a challenging job and it also affects the load balancing of the cloud. The suggested proposed model generates and step-up the VM allocation policies but also transforms the generated cloud workload. Furthermore, to improve the workload distribution of workload and stability of the overall cloud computing environment the load balancing algorithm is most important for load balancing. The work of load balancing is equally effective in the cloud computing environment and it is most essential one for load balancing algorithms to take care of all issues at the time of the work load. The researchers studied different algorithms to solve the problems of load balancing that generate problems during the distribution of workloads. The analysis VM allocation policies are tested on CloudSim environment and the results, and discussion is about to which one VM allocation policy is superior.

scholarly journals A Load Balancing Algorithm for Mobile Devices in Edge Cloud Computing Environments

Electronics ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 686
Author(s):  
JongBeom Lim ◽  
DaeWon Lee
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Mobile Devices ◽  
Virtual Machines ◽  
Hot Spot ◽  
Mobile User ◽  
Current Data ◽  
Computing Systems ◽  
Computing Environments ◽  
Load Balancing Algorithm

As current data centers and servers are growing in size by orders of magnitude when needed, load balancing is a great concern in scalable computing systems, including mobile edge cloud computing environments. In mobile edge cloud computing systems, a mobile user can offload its tasks to nearby edge servers to support real-time applications. However, when users are located in a hot spot, several edge servers can be overloaded due to suddenly offloaded tasks from mobile users. In this paper, we present a load balancing algorithm for mobile devices in edge cloud computing environments. The proposed load balancing technique features an efficient complexity by a graph coloring-based implementation based on a genetic algorithm. The aim of the proposed load balancing algorithm is to distribute offloaded tasks to nearby edge servers in an efficient way. Performance results show that the proposed load balancing algorithm outperforms previous techniques and increases the average CPU usage of virtual machines, which indicates a high utilization of edge servers.

scholarly journals Cloud computing based load balancing algorithm for erlang concurrent traffic

2020 ◽  
Vol 17 (2) ◽  
pp. 1109
Author(s):  
Chanintorn Jittawiriyanukoon
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Performance Metrics ◽  
Memory Load ◽  
Performance Parameters ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Concurrent Tasks ◽  
User Access ◽  
Load Balancing Algorithm

<p>The distribution of scheduler from user inquiries in the clouds is complex. In keeping up with the cloud computing environment and the inquirers, the clouds meet with some problematic load balancing complications as an improving load balancing tool induces the rigorous efficiency of the cloud based website’s user access. Overloaded or underloaded conditions originate processing catastrophe regarding the prolonged execution time, bandwidth hog, malfunction, and etc. Besides, to manipulate Erlang concurrent tasks is another skyward situation. Hence, the load balancing is obliged to exhaust all mentioned conditions. The proposed load balancing algorithm for Erlang concurrent tasks (those are and could also be autonomous and unstable.) on VMware workstations is introduced.  There are several load patterns within the clouds corresponding to CPU’s load (utilization), memory load (queue size), link capacity load (bandwidth), and so on. The proposed load balancing is to spot underloaded and overloaded conditions then stabilizes the weight amidst computing nodes. There are countless load balancing approaches in the cloud environment to examine performance parameters. A short outline of corresponding performance metrics in the review and their findings are presented. To investigate the fit efficiency of the proposed algorithm, the simulation is applied then results based on the proposed method are compared to the existing ones. The outcomes settle the weight balancing, outperform others when executing Erlang traffic, and are catered in the context.</p>

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