Job Scheduling with Efficient Resource Monitoring in Cloud Datacenter

Cloud computing is an on-demand computing model, which uses virtualization technology to provide cloud resources to users in the form of virtual machines through internet. Being an adaptable technology, cloud computing is an excellent alternative for organizations for forming their own private cloud. Since the resources are limited in these private clouds maximizing the utilization of resources and giving the guaranteed service for the user are the ultimate goal. For that, efficient scheduling is needed. This research reports on an efficient data structure for resource management and resource scheduling technique in a private cloud environment and discusses a cloud model. The proposed scheduling algorithm considers the types of jobs and the resource availability in its scheduling decision. Finally, we conducted simulations using CloudSim and compared our algorithm with other existing methods, like V-MCT and priority scheduling algorithms.

Download Full-text

Enhancement of Security and Energy Efficiency in Cloud Computing

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.b2069.078219 ◽

2019 ◽

Vol 8 (2) ◽

pp. 2459-2462

Keyword(s):

Energy Efficiency ◽

Cloud Computing ◽

Load Balancing ◽

Job Scheduling ◽

Virtual Machines ◽

Scheduling Algorithm ◽

Cloud Environment ◽

Gang Scheduling ◽

Job Scheduler ◽

Heavy Application

This paper focuses on the job scheduling in cloud environment. Here the task has been scheduled in cloud and fog. Cloud provides services to heavy application while fog provides service to lighter application. The job scheduler would be helpful to reduce burden of cloud and help in energy optimization. The jobs are scheduled according to their types and priority. Various job scheduling algorithm such as gang scheduling, FCFS and round robin mechanism have been discussed in this research for load balancing and improve the compilation time. The simulation has been made using Matlab on virtual machines.

Download Full-text

Improved Priority Based Job Scheduling Algorithm in Cloud Computing Using Iterative Method

2014 Fourth International Conference on Advances in Computing and Communications ◽

10.1109/icacc.2014.55 ◽

2014 ◽

Cited By ~ 19

Author(s):

Swachil J. Patel ◽

Upendra R. Bhoi

Keyword(s):

Cloud Computing ◽

Iterative Method ◽

Job Scheduling ◽

Scheduling Algorithm ◽

Job Scheduling Algorithm

Download Full-text

Virtual Machines Scheduling Algorithm Based on Multi-Objective Optimization in Cloud Computing

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.1046.508 ◽

2014 ◽

Vol 1046 ◽

pp. 508-511

Author(s):

Jian Rong Zhu ◽

Yi Zhuang ◽

Jing Li ◽

Wei Zhu

Keyword(s):

Cloud Computing ◽

Energy Consumption ◽

Virtual Machine ◽

Virtual Machines ◽

Scheduling Algorithm ◽

Machine Scheduling ◽

Multi Objective Optimization ◽

Multi Objective ◽

Virtual Machine Scheduling ◽

Set Up

How to reduce energy consumption while improving utility of datacenter is one of the key technologies in the cloud computing environment. In this paper, we use energy consumption and utility of data center as objective functions to set up a virtual machine scheduling model based on multi-objective optimization VMSA-MOP, and design a virtual machine scheduling algorithm based on NSGA-2 to solve the model. Experimental results show that compared with other virtual machine scheduling algorithms, our algorithm can obtain relatively optimal scheduling results.

Download Full-text

A Cloud-Oriented Reference Architecture to Digital Library Systems

Cloud Technology ◽

10.4018/978-1-4666-6539-2.ch022 ◽

2015 ◽

pp. 466-489

Author(s):

K. Palanivel ◽

S. Kuppuswami

Keyword(s):

Cloud Computing ◽

Digital Library ◽

Digital Libraries ◽

Search Engines ◽

Cloud Model ◽

Frame Of Reference ◽

Cloud Services ◽

Reference Architecture ◽

Information Retrieval Systems ◽

Efficient Resource

Cloud computing is an emerging computing model which has evolved as a result of the maturity of underlying prerequisite technologies. There are differences in perspective as to when a set of underlying technologies becomes a “cloud” model. In order to categorize cloud computing services, and to expect some level of consistent characteristics to be associated with the services, cloud adopters need a consistent frame of reference. The Cloud Computing Reference Architecture (CCRA) defines a standard reference architecture and consistent frame of reference for comparing cloud services from different service providers when selecting and deploying cloud services to support their mission requirements. Cloud computing offers information retrieval systems, particularly digital libraries and search engines, a wide variety of options for growth and reduction of maintenance needs and encourages efficient resource use. These features are particularly attractive for digital libraries, repositories, and search engines. The dynamic and elastic provisioning features of a cloud infrastructure allow rapid growth in collection size and support a larger user base, while reducing management issues. Hence, the objective of this chapter is to investigate and design reference architecture to Digital Library Systems using cloud computing with scalability in mind. The proposed reference architecture is called as CORADLS. This architecture accelerates the rate at which library users can get easy, efficient, faster and reliable services in the digital environment. Here, the end user does not have to worry about the resource or disk space in cloud computing.

Download Full-text

Secure and Privacy Preserving Keyword Search over the Large Scale Cloud Data

Handbook of Research on Modern Cryptographic Solutions for Computer and Cyber Security - Advances in Information Security, Privacy, and Ethics ◽

10.4018/978-1-5225-0105-3.ch009 ◽

2016 ◽

pp. 200-215

Author(s):

Wei Zhang ◽

Jie Wu ◽

Yaping Lin

Keyword(s):

Cloud Computing ◽

Large Scale ◽

Keyword Search ◽

Data Encryption ◽

Privacy Preserving ◽

Security And Privacy ◽

Data Utilization ◽

Cloud Data ◽

Efficient Resource ◽

Efficient Data

Cloud computing has attracted a lot of interests from both the academics and the industries, since it provides efficient resource management, economical cost, and fast deployment. However, concerns on security and privacy become the main obstacle for the large scale application of cloud computing. Encryption would be an alternative way to relief the concern. However, data encryption makes efficient data utilization a challenging problem. To address this problem, secure and privacy preserving keyword search over large scale cloud data is proposed and widely developed. In this paper, we make a thorough survey on the secure and privacy preserving keyword search over large scale cloud data. We investigate existing research arts category by category, where the category is classified according to the search functionality. In each category, we first elaborate on the key idea of existing research works, then we conclude some open and interesting problems.

Download Full-text

ENERGY EFFICIENT LOAD BALANCING FOR CLOUD DATA CENTER

Asian Journal of Pharmaceutical and Clinical Research ◽

10.22159/ajpcr.2017.v10s1.19604 ◽

2017 ◽

Vol 10 (13) ◽

pp. 162

Author(s):

Amey Rivankar ◽

Anusooya G

Keyword(s):

Cloud Computing ◽

Load Balancing ◽

Energy Efficient ◽

Large Scale ◽

Virtual Machines ◽

Cloud Data Center ◽

Cloud Data ◽

Efficient Resource ◽

Cloud Data Centers ◽

Near Future

Cloud computing is the latest trend in large-scale distributed computing. It provides diverse services on demand to distributive resources such asservers, software, and databases. One of the challenging problems in cloud data centers is to manage the load of different reconfigurable virtual machines over one another. Thus, in the near future of cloud computing field, providing a mechanism for efficient resource management will be very significant. Many load balancing algorithms have been already implemented and executed to manage the resources efficiently and adequately. The objective of this paper is to analyze shortcomings of existing algorithms and implement a new algorithm which will give optimized load balancingresult.

Download Full-text

Efficient task scheduling on virtual machine in cloud computing environment

International Journal of Pervasive Computing and Communications ◽

10.1108/ijpcc-04-2020-0029 ◽

2020 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Mahfooz Alam ◽

Mahak ◽

Raza Abbas Haidri ◽

Dileep Kumar Yadav

Keyword(s):

Cloud Computing ◽

Load Balancing ◽

Response Time ◽

Virtual Machine ◽

Task Allocation ◽

Completion Time ◽

Virtual Machines ◽

Scheduling Algorithm ◽

Content Type ◽

Minimum Completion Time

Purpose Cloud users can access services at anytime from anywhere in the world. On average, Google now processes more than 40,000 searches every second, which is approximately 3.5 billion searches per day. The diverse and vast amounts of data are generated with the development of next-generation information technologies such as cryptocurrency, internet of things and big data. To execute such applications, it is needed to design an efficient scheduling algorithm that considers the quality of service parameters like utilization, makespan and response time. Therefore, this paper aims to propose a novel Efficient Static Task Allocation (ESTA) algorithm, which optimizes average utilization. Design/methodology/approach Cloud computing provides resources such as virtual machine, network, storage, etc. over the internet. Cloud computing follows the pay-per-use billing model. To achieve efficient task allocation, scheduling algorithm problems should be interacted and tackled through efficient task distribution on the resources. The methodology of ESTA algorithm is based on minimum completion time approach. ESTA intelligently maps the batch of independent tasks (cloudlets) on heterogeneous virtual machines and optimizes their utilization in infrastructure as a service cloud computing. Findings To evaluate the performance of ESTA, the simulation study is compared with Min-Min, load balancing strategy with migration cost, Longest job in the fastest resource-shortest job in the fastest resource, sufferage, minimum completion time (MCT), minimum execution time and opportunistic load balancing on account of makespan, utilization and response time. Originality/value The simulation result reveals that the ESTA algorithm consistently superior performs under varying of batch independent of cloudlets and the number of virtual machines’ test conditions.

Download Full-text

Job Scheduling Algorithm for Cloud Computing Based on Particle Swarm Optimization

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.662.957 ◽

2013 ◽

Vol 662 ◽

pp. 957-960 ◽

Cited By ~ 8

Author(s):

Jing Liu ◽

Xing Guo Luo ◽

Xing Ming Zhang ◽

Fan Zhang

Keyword(s):

Cloud Computing ◽

Particle Swarm Optimization ◽

High Performance ◽

Large Scale ◽

Job Scheduling ◽

Scheduling Algorithm ◽

Autonomous Systems ◽

Particle Swarm ◽

Cost Benefit ◽

Swarm Optimization

Cloud computing is an emerging high performance computing environment with a large scale, heterogeneous collection of autonomous systems and flexible computational architecture. The performance of the scheduling system influences the cost benefit of this computing paradigm. To reduce the energy consumption and improve the profit, a job scheduling model based on the particle swarm optimization(PSO) algorithm is established for cloud computing. Based on open source cloud computing simulation platform CloudSim, compared to GA and random scheduling algorithms, the results show that the proposed algorithm can obtain a better solution concerning the energy cost and profit.

Download Full-text