A Dynamically-adaptive Resource Aware Load Balancing Scheme for VM migrations in Datacenters

The problem of load balancing parallel applications is particularly challenging on computational grids, since the characteristics of both the application and the platform must be taken into account. This chapter reviews the wide range of solutions that have been proposed. It considers tightly coupled parallel applications that can be described by an undirected graph representing concurrent execution of tasks and communication of tasks, executing on computational grids with static and dynamic network and processor performance. While a rich set of solution techniques have been proposed, there has not been of yet any performance comparisons between them. Such comparisons will require parallel benchmarks and computational grid emulators and simulators.

Download Full-text

A Novel Adaptive Resource-Aware PNN Algorithm Based on Michigan-Nested Pittsburgh PSO

Advances in Neuro-Information Processing - Lecture Notes in Computer Science ◽

10.1007/978-3-642-03040-6_58 ◽

2009 ◽

pp. 477-484

Author(s):

Kuncup Iswandy ◽

Andreas König

Keyword(s):

Resource Aware ◽

Adaptive Resource

Download Full-text

A Resource-Aware Dynamic Load-Balancing Parallelization Algorithm in a Farmer-Worker Environment

Innovations and Approaches for Resilient and Adaptive Systems ◽

10.4018/978-1-4666-2056-8.ch005 ◽

2012 ◽

pp. 88-104

Author(s):

M. Leeman

Keyword(s):

Load Balancing ◽

Dynamic Load ◽

Execution Time ◽

Time Frame ◽

Parallel Programs ◽

Time Constraints ◽

Digital Television ◽

Television Content ◽

Content Processing ◽

Resource Aware

This paper describes an algorithm for dynamically assigning tasks to processing entities in a world where each task has a set of resource or service requirements and each processing entity a set of resources or service capabilities. A task needs to be assigned to a node that offers all required services and the set of tasks is finished within a minimal execution time frame. Dependability and adaptability are inherent to the algorithm so that it accounts for the varying execution time of each task or the failure of a processing node. The algorithm is based on a dependable technique for farmer-worker parallel programs and is enhanced for modeling the time constraints in combination with the required configuration set in a multidimensional resources model. This paper describes how the algorithm is used for dynamically load balancing and parallelizing the nightly tests of a digital television content-processing embedded device.

Download Full-text

Saksham: Resource Aware Block Rearrangement Algorithm for Load Balancing in Hadoop

Procedia Computer Science ◽

10.1016/j.procs.2020.03.181 ◽

2020 ◽

Vol 167 ◽

pp. 47-56 ◽

Cited By ~ 1

Author(s):

Ankit Shah ◽

Mamta Padole

Keyword(s):

Load Balancing ◽

Rearrangement Algorithm ◽

Resource Aware

Download Full-text

An Improved Rasa for Load Balancing in Cloud Computing

Asian Journal of Research in Computer Science ◽

10.9734/ajrcos/2021/v12i430294 ◽

2021 ◽

pp. 52-66

Author(s):

Oyekanmi Ezekiel Olufunminiyi ◽

Oladoja Ilobekemen Perpetual ◽

Omotehinwa Temidayo Oluwatosin

Keyword(s):

Load Balancing ◽

Resource Utilization ◽

Performance Metrics ◽

Scheduling Algorithm ◽

Resource Provisioning ◽

The Common ◽

Resource Aware ◽

Cloud Users ◽

Better Than

Cloud is specifically known to have difficulty in managing resource usage during task scheduling, this is an innate from distributed computing and virtualization. The common issue in cloud is load balancing management. This issue is more prominent in virtualization technology and it affects cloud providers in term of resource utilization and cost and to the users in term of Quality of Service (QoS). Efficient procedures are therefore necessary to achieve maximum resource utilization at a minimized cost. This study implemented a load balancing scheme called Improved Resource Aware Scheduling Algorithm (I-RASA) for resource provisioning to cloud users on a pay-as-you-go basis using CloudSim 3.0.3 package tool. I-RASA was compared with recent load balancing algorithms and the result shown in performance evaluation section of this paper is better than Max-min and RASA load balancing techniques. However, it sometimes outperforms or on equal balance with Improved Max-Min load balancing technique when using makespan, flow time, throughput, and resource utilization as the performance metrics.

Download Full-text