scholarly journals ENHANCED DYNAMIC RESOURCE ALLOCATION SCHEME BASED ON PACKAGE LEVEL ACCESS IN CLOUD COMPUTING : A REVIEW

2017 ◽  
Vol 16 (2) ◽  
pp. 6207-6212 ◽  
Author(s):  
Manpreet Kaur ◽  
Dr. Rajinder Singh
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Heterogeneous Computing ◽  
Virtual Machines ◽  
Technology Infrastructure ◽  
Computing Systems ◽  
Computing Platform ◽  
Internet Users ◽  
Resource Allocation Scheme ◽  
Heterogeneous Computing Systems

Cloud computing is Internet based development and use of computer technology. It is a style of computing in which dynamically scalable and often virtualized resources are provided as a service over the Internet. Users need not have knowledge of, expertise in, or control over the technology infrastructure "in the cloud" that supports them. Scheduling is one of the core steps to efficiently exploit the capabilities of heterogeneous computing systems. On cloud computing platform, load balancing of the entire system can be  dynamically handled  by  using  virtualization  technology through which it  becomes  possible  to  remap  virtual  machine  and physical resources  according  to  the  change  in  load. However, in order to improve performance, the virtual machines have to fully utilize its resources and services by adapting to computing environment dynamically.  The  load balancing  with  proper  allocation  of  resources  must  be guaranteed  in  order  to  improve  resource  utility.

scholarly journals A Review on Load Balancing In Cloud Environment

2018 ◽  
Vol 17 (1) ◽  
pp. 7120-7125 ◽  
Author(s):  
Amandeep Kaur ◽  
Mr. Pawan Luthra
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Heterogeneous Computing ◽  
Virtual Machines ◽  
Technology Infrastructure ◽  
Computing Systems ◽  
Computing Platform ◽  
Internet Users ◽  
Cloud Computing Platform ◽  
Heterogeneous Computing Systems

Cloud computing is Internet based development and use of computer technology. It is a style of computing in which dynamically scalable and often virtualized resources are provided as a service over the Internet. Users need not have knowledge of, expertise in, or control over the technology infrastructure "in the cloud" that supports them. Scheduling is one of the core steps to efficiently exploit the capabilities of heterogeneous computing systems. On cloud computing platform, load balancing of the entire system can be  dynamically handled  by  using  virtualization  technology through which it  becomes  possible  to  remap  virtual  machine  and physical resources  according  to  the  change  in  load. However, in order to improve performance, the virtual machines have to fully utilize its resources and services by adapting to computing environment dynamically.  The  load balancing  with  proper  allocation  of  resources  must  be guaranteed  in  order  to  improve  resource  utility.

scholarly journals ENHANCING JOB SCHEDULING IN CLOUD ENVIRONMENT: A REVIEW

2015 ◽  
Vol 14 (6) ◽  
pp. 5796-5802
Author(s):  
Mrs. Amita Rani ◽  
Dr. Mohita Garg
Keyword(s):  
Heterogeneous Computing ◽  
Job Scheduling ◽  
Heuristic Algorithms ◽  
Computing System ◽  
Technology Infrastructure ◽  
Computing Systems ◽  
Effective Utilization ◽  
Internet Users ◽  
Np Complete ◽  
Heterogeneous Computing Systems

Cloud computing is Internet based development and use of computer technology. It is a style of computing in which dynamically scalable and often virtualized resources are provided as a service over the Internet. Users need not have knowledge of, expertise in, or control over the technology infrastructure "in the cloud" that supports them. Scheduling is one of the core steps to efficiently exploit the capabilities of heterogeneous computing systems. The problem of mapping meta-tasks to a machine is shown to be NP-complete. The NP-complete problem can be solved only using heuristic approach. There are a number of heuristic algorithms that were tailored to deal with scheduling of independent tasks. Different criteria can be used for evaluating the efficiency of scheduling algorithms. The most important of them are makespan, flowtime and resource utilization. In this paper, a new heuristic algorithm for scheduling meta-tasks in heterogeneous computing system is presented. The proposed algorithm improves the performance in both makespan and effective utilization of resources by reducing the waiting time. 

scholarly journals LOAD BALANCING IN CLOUD ENVIRONMENT: A REVIEW

2016 ◽  
Vol 15 (8) ◽  
pp. 6986-6990
Author(s):  
Sheenam Kamboj ◽  
Mr. Navtej Singh Ghumman
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Computing Platform ◽  
Side Load ◽  
Virtualization Technology ◽  
Cloud Computing Platform ◽  
Demand Changes

An essential role of cloud computing platform is to dynamically balance the load among the different servers in order to improve resource utilization and to avoid hotspots. Load balancing (LB) is done on both sides i.e. on provider as well as on consumer side. On provider side, load balancing is the problem of allocating virtual machines to servers at runtime. Virtual Machine need to be reassigned so that servers do not get overloaded as demand changes. On consumer side application load can be balanced which provides efficiency to the consumers. On cloud computing platform, load balancing of the entire system can be dynamically handled by  using virtualization technology through which itÂbecomes possible to remap virtual machine and physical resources according to  the change in load. However, in order to improve performance, the virtual machines have to fully utilize its resources and services by adapting to computing environment dynamically. The load balancing with proper allocation of resources must be guaranteed in order to improve resource utility.

scholarly journals Load Balancing Algorithms in Cloud Computing

2020 ◽  
Author(s):  
Vignesh Joshi
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Virtual Machines ◽  
Dynamic Scheduling ◽  
The Internet ◽  
Heterogeneous Environment ◽  
Computing Technology ◽  
Cloud Systems ◽  
Internet Users ◽  
Independent Tasks

Cloud computing plays an important role in enhancing the effective sharing of resources in virtual machines. Scheduling and load balancing are the two common concepts that cloud computing relies on ensuring that a prescribed task is assigned to the most appropriate virtual machine. Also, cloud computing should have the ability to handle multiple independent tasks that are arriving and execute them in the same or multiple nodes. In a heterogeneous environment, static and dynamic scheduling plays an important role by enhancing the allocation of tasks to the appropriate resources to satisfy the internet users' requests and making cloud computing technology more efficient. This work aims to evaluate and discuss important algorithms that will help improve the load balancing performance of cloud systems.

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.

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