A hierarchical load balancing algorithm for efficient job scheduling in a computational grid testbed

2012 ◽  
Author(s):  
K. Hemant Kumar Reddy ◽  
Diptendu Shina Roy
Keyword(s):  
Load Balancing ◽  
Job Scheduling ◽  
Computational Grid ◽  
Load Balancing Algorithm

scholarly journals ALLOCATION OF HETEROGENOUS CLOUDLETS ON PRIORITY BASIS IN CLOUD ENVIRONMENT

2017 ◽  
Vol 16 (3) ◽  
pp. 6240-6246
Author(s):  
Sumanpreet Kaur ◽  
Mr. Navtej Singh Ghumman
Keyword(s):  
Load Balancing ◽  
Job Scheduling ◽  
Virtual Machines ◽  
Research Work ◽  
Turnaround Time ◽  
Single Node ◽  
Multiple Parameters ◽  
Class A ◽  
Class B ◽  
Load Balancing Algorithm

Load balancing is one of the main challenges in cloud computing which is required to distribute the dynamic workload across multiple nodes to ensure that no single node is overwhelmed. It helps in optimal utilization of resources and hence in enhancing the performance of the system. In the natural environment, the cloudlets will be processed in the FIFO (First in First Out approach). We propose an improved load balancing algorithm for job scheduling in the Grid environment.  Hence, in this research work, various types of leases have been assigned to the cloudlets like cancellable, suspendable and non-preemtable. The leases have been assigned on the basis of cost assigned to them and the requirement specified by the user. The datacenter broker will receive the list of all the virtual machines and will categorize them into two classes i.e. Class A and Class B. Class A will have high end virtual machines and will process the non-preemptable cloudlets. Class B will contain the low end virtual machines and will process the suspendable and cancellable cloudlets. The machines in each class will be further sorted in descending order according to their MIPS. Multiple parameters have been evaluated like waiting time, turnaround time, execution time and processing cost.  Further, this research also provides the anticipated results with the implementation of the proposed algorithm. In the cloud storage, load balancing is a key issue. It would consume a lot of cost to maintain load information, since the system is too huge to timely disperse load. The main contributions of the research work are to balance the entire system load while trying to minimize the make span of a given set of jobs. Compared with the other job scheduling algorithms, the improved load balancing algorithm can outperform them according to the experimental results.

scholarly journals A NOVEL APPROACH OF OPTIMIZING PERFORMANCE USING K-MEANS CLUSTERING IN CLOUD COMPUTING

2016 ◽  
Vol 15 (14) ◽  
pp. 7435-7443 ◽  
Author(s):  
Sheenam Kamboj ◽  
Mr. Navtej Singh Ghumman
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Virtual Machine ◽  
Job Scheduling ◽  
Virtual Machines ◽  
Turnaround Time ◽  
Cloud Environment ◽  
Single Node ◽  
Novel Approach ◽  
Load Balancing Algorithm

Cloud computing is distributed computing, storing, sharing and accessing data over the Internet. It provides a pool of shared resources to the users available on the basis of pay as you go service that means users pay only for those services which are used by him according to their access times. Load balancing ensures that no single node will be overloaded and used to distribute workload among multiple nodes. It helps to improve system performance and proper utilization of resources. We propose an improved load balancing algorithm for job scheduling in the cloud environment using K-Means clustering of cloudlets and virtual machines in the cloud environment. All the cloudlets given by the user are divided into 3 clusters depending upon client’s priority, cost and instruction length of the cloudlet. The virtual machines inside the datacenter hosts are also grouped into multiple clusters depending upon virtual machine capacity in terms of processor, memory, and bandwidth. Sorting is applied at both the ends to reduce the latency. Multiple number of experiments have been conducted by taking different configurations of cloudlets and virtual machine. Various parameters like waiting time, execution time, turnaround time and the usage cost have been computed inside the cloudsim environment to demonstrate the results. Compared with the other job scheduling algorithms, the improved load balancing algorithm can outperform them according to the experimental results. 

scholarly journals IMPROVED ANT COLONY LOAD BALANCING ALGORITHM IN CLOUD COMPUTING

2015 ◽  
Vol 14 (4) ◽  
pp. 5636-5644
Author(s):  
Jaspreet Singh ◽  
Susmita Mishra
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Job Scheduling ◽  
Virtual Machines ◽  
Ant Colony ◽  
Ant Colony Optimization Algorithm ◽  
Computing Paradigm ◽  
Share Data ◽  
Load Balancing Algorithm ◽  
Scalable Network

Cloud Computing is an emerging computing paradigm. It aims to share data, calculations, and service transparently over a scalable network of nodes. Since Cloud computing stores the data and disseminated resources in the open environment. Since, cloud has inherited characteristic of distributed computing and virtualization there is a possibility of machines getting unused. Hence, in this paper, a load balancing algorithm has been proposed to avoid deadlocks and to provide proper utilization of all the Virtual Machines (VMs) while processing the requests received from the users by VM migration. Further, this paper also provides the anticipated results with the implementation of the proposed algorithm. The main contributions of our work is to balance the entire system load while trying to minimize the make span of a given set of jobs. Compared with the other job scheduling algorithms, the improved Ant Colony Optimization algorithm can outperform them according to the experimental results.

scholarly journals AN IMPROVED RESOURCE ALLOCATION STRATEGY BASED ON PACKAGE LEVEL ACCESS IN CLOUD ENVIRONMENT

2017 ◽  
Vol 16 (7) ◽  
pp. 7021-7030
Author(s):  
Rajveer Kaur ◽  
Mr. Navtej Singh Ghumman
Keyword(s):  
Load Balancing ◽  
Job Scheduling ◽  
Virtual Machines ◽  
Research Work ◽  
Turnaround Time ◽  
Basic Medium ◽  
Heterogeneous Services ◽  
Resource Allocation Strategy ◽  
Load Balancing Algorithm ◽  
And Storage

Cloud computing is an emerging field of computer science, where heterogeneous services such as applications, servers and storage are delivered to an individual or organization's computer and devices through the Internet. In the proposed research work, a load balancing algorithm is designed, to provide proper utilization of all resources while processing the requests received from the users. We have implemented the ‘package’ level access at the Virtual Machines. We have proposed three types of packages like basic, medium and premium according to the requirements of the Cloudlets. In the basic package, we have the Virtual Machines with low capacity and in the premium package we are having the Virtual Machines with higher capacity, whereas the medium is of intermediate capacity of MIPS and RAM. In the proposed approach, the capacity, status and current load of every Virtual Machine is computed before allocating the new request of the user. Different parameters like waiting time, execution time and turnaround time of the Cloudlets are computed and analyzed. The proposed research provides the anticipated results with the implementation of the proposed algorithm. Compared with the other job scheduling algorithms, the proposed load balancing algorithm can outperform them in circumstances where the load and Virtual Machines are heterogeneous.

scholarly journals AN ENHANCED TASK ALLOCATION STRATEGY IN CLOUD ENVIRONMENT

2017 ◽  
Vol 16 (6) ◽  
pp. 6953-6961
Author(s):  
Kavita Redishettywar ◽  
Prof. Rafik Juber Thekiya
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Virtual Machine ◽  
Data Centers ◽  
Job Scheduling ◽  
Virtual Machines ◽  
Cloud Environment ◽  
Cloud Data ◽  
Cloud Data Centers ◽  
Load Balancing Algorithm

Cloud computing is a vigorous technology by which a user can get software, application, operating system and hardware as a service without actually possessing it and paying only according to the usage. Cloud Computing is a hot topic of research for the researchers these days. With the rapid growth of Interne technology cloud computing have become main source of computing for small as well big IT companies. In the cloud computing milieu the cloud data centers and the users of the cloud-computing are globally situated, therefore it is a big challenge for cloud data centers to efficiently handle the requests which are coming from millions of users and service them in an efficient manner. Load balancing ensures that no single node will be overloaded and used to distribute workload among multiple nodes. It helps to improve system performance and proper utilization of resources. We propose an improved load balancing algorithm for job scheduling in the cloud environment using K-Means clustering of cloudlets and virtual machines in the cloud environment. All the cloudlets given by the user are divided into 3 clusters depending upon client’s priority, cost and instruction length of the cloudlet. The virtual machines inside the datacenter hosts are also grouped into multiple clusters depending upon virtual machine capacity in terms of processor, memory, and bandwidth. Sorting is applied at both the ends to reduce the latency. Multiple number of experiments have been conducted by taking different configurations of cloudlets and virtual machine. Various parameters like waiting time, execution time, turnaround time and the usage cost have been computed inside the cloudsim environment to demonstrate the results. Compared with the other job scheduling algorithms, the improved load balancing algorithm can outperform them according to the experimental results.

An Adaptive Load Balancing Algorithm for Computational Grid

2011 ◽  
Vol 1 (2) ◽  
pp. 70 ◽  
Author(s):  
Manpreet Singh ◽  
Vishal Gupta ◽  
SandipKumar Goyal
Keyword(s):  
Load Balancing ◽  
Computational Grid ◽  
Load Balancing Algorithm

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

2017 ◽  
Vol 16 (5) ◽  
pp. 6903-6912
Author(s):  
Manpreet Kaur ◽  
Dr. Rajinder Singh
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Virtual Machine ◽  
Job Scheduling ◽  
Research Work ◽  
Cloud Service ◽  
Current Status ◽  
Cloud Environment ◽  
Single Node ◽  
Load Balancing Algorithm

Cloud computing is distributed computing, storing, sharing and accessing data over the Internet. It provides a pool of shared resources to the users available on the basis of pay as you go service that means users pay only for those services which are used by him according to their access times. This research work deals with the balancing of work load in cloud environment. Load balancing is one of the essential factors to enhance the working performance of the cloud service provider. It would consume a lot of cost to maintain load information, since the system is too huge to timely disperse load. Load balancing is one of the main challenges in cloud computing which is required to distribute the dynamic workload across multiple nodes to ensure that no single node is overwhelmed. It helps in optimal utilization of resources and hence in enhancing the performance of the system. We propose an improved load balancing algorithm for job scheduling in the cloud environment using load distribution table in which the current status, current package, VM Capacity and the number of cloudlets submitted to each and every virtual machine will be stored. Submit the job of the user to the datacenter broker. Data center broker will first find the suitable Vm according to the requirements of the cloudlet and will match and find the most suitable Vm according to its availability or the machine with least load in the distribution table. Multiple number of experiments have been conducted by taking different configurations of cloudlets and virtual machine. Various parameters like waiting time, execution time, turnaround time and the usage cost have been computed inside the cloudsim environment to demonstrate the results. The main contributions of the research work is to balance the entire system load while trying to minimize the make span of a given set of jobs. Compared with the other job scheduling algorithms, the improved load balancing algorithm can outperform them according to the experimental results.

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