Elastic Optical Network Service-Oriented Architecture (SOA) Used for Cloud Computing and Its Resource Mapping Optimization Scheme

2020 ◽  
Vol 15 (4) ◽  
pp. 442-449
Author(s):  
Xun Xia ◽  
Ling Chen
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Resource Utilization ◽  
Service Oriented Architecture ◽  
Optical Network ◽  
Spectrum Utilization ◽  
Mapping Algorithm ◽  
Resource Mapping ◽  
Elastic Optical Network ◽  
Service Oriented

In this study, starting from the elastic optical network, the layered and function isolated service-oriented architecture (SOA) is introduced, so as to propose an elastic optical network SOA for cloud computing, and further study the resource mapping of optical network. Linear mapping model, random routing mapping algorithm, load balancing mapping algorithm and link separation mapping algorithm are introduced respectively, and the resource utilization effect of different mapping algorithms for the proposed optical network is compared. During the experiment, firstly, the elastic optical network is tested. It is found that the node utilization and spectrum utilization of the underlying optical fiber level network are significantly improved. Within the average service time of 0.312 s∼0.416 s, the corresponding node utilization and spectrum utilization are 90% and 80% respectively. In the resource mapping experiment, load balancing algorithm and link separation algorithm can effectively improve the mapping success rate of services. Among them, the link separation mapping algorithm can improve the spectrum resource utilization of optical network by 15.6%. The elastic optical network SOA proposed in this study is helpful to improve the use of network resources.

scholarly journals Min-Time TS: task resource mapping algorithm in cloud computing

2021 ◽  
Vol 1055 (1) ◽  
pp. 012096
Author(s):  
G K Kamalam ◽  
T Kalaiyarasi ◽  
S V Monaa ◽  
B Gurudharshini
Keyword(s):  
Cloud Computing ◽  
Mapping Algorithm ◽  
Resource Mapping

Applying Service Oriented Architecture and Cloud Computing for a Greener Traffic Management

2011 ◽  
pp. 678-693
Author(s):  
Ishan Bhalla ◽  
Kamlesh Chaudhary
Keyword(s):  
Cloud Computing ◽  
Traffic Management ◽  
Management System ◽  
Carbon Emission ◽  
Service Oriented Architecture ◽  
Heavy Traffic ◽  
Wireless Data ◽  
Service Oriented ◽  
Traffic Management System ◽  
It Application

Traffic Management System (TMS) is a possible implementation of a Green IT application. It can have direct impact on reducing the greenhouse gases. The focus of this report is to illustrate how event driven SOA design principles can be applied in designing traffic management system. It also discusses how cloud computing concept can be used for TMS application. Traffic during peak hours is a problem in any major city where population growth far exceeds the infrastructure. Frequent stop and start of the cars on the heavy traffic roads and slow moving traffic causes greater fuel consumption, which results in greater emission of carbon gases. If efficient traffic management system can speed up the traffic average speed it will help reduce the carbon emission. As the WiMAX technology reaches maturity and achieves greater reliability and speed for wireless data transmissions new mobile applications are possible. Traffic Management System is one such example. WiMAX can facilitate communication to and from fast moving cars. WiMAX combined with GPS (Global Positioning System) technology can facilitate building an efficient traffic management system. The authors have also discussed various scenarios where Cloud computing technology can be utilised resulting in further optimisation of the computing resources and therefore reducing the carbon emission.

Convergence of Interoperability of Cloud Computing, Service Oriented Architecture and Enterprise Architecture

2013 ◽  
Vol 4 (1) ◽  
pp. 43-51
Author(s):  
Susan Sutherland
Keyword(s):  
Cloud Computing ◽  
Enterprise Architecture ◽  
Service Oriented Architecture ◽  
Proof Of Concept ◽  
Cloud Computing Service ◽  
Architectural Model ◽  
Service Oriented ◽  
State Of Art ◽  
Dynamic Links

The research identifies the gap that there is a convergence of interoperability of Cloud Computing (CC), Service Oriented Architecture (SOA) and Enterprise Architecture (EA). Furthermore, it outlines the existing non dynamic links between EA and SOA that are currently practiced in the industry and confirmed by scholarly articles; and provides a state of art of the link that could exist in practice between cloud computing and SOA as researched from the published scholarly material. This researched paper also refers to the planned research to test this theory first by developing a logical architectural model of such a feasibility followed by a Proof of Concept

A Proficient Approach for Load Balancing in Cloud Computing-Join Minimum Loaded Queue

2020 ◽  
Vol 11 (1) ◽  
pp. 12-36
Author(s):  
Minakshi Sharma ◽  
Rajneesh Kumar ◽  
Anurag Jain
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Response Time ◽  
Resource Utilization ◽  
Cloud Service ◽  
Cloud Environment ◽  
Cloud Service Provider ◽  
Qos Parameters ◽  
Load Balancing Algorithm

Cloud load balancing is done to persist the services in the cloud environment along with quality of service (QoS) parameters. An efficient load balancing algorithm should be based on better optimization of these QoS parameters which results in efficient scheduling. Most of the load balancing algorithms which exist consider response time or resource utilization constraints but an efficient algorithm must consider both perspectives from the user side and cloud service provider side. This article presents a load balancing strategy that efficiently allocates tasks to virtualized resources to get maximum resource utilization in minimum response time. The proposed approach, join minimum loaded queue (JMLQ), is based on the existing join idle queue (JIQ) model that has been modified by replacing idle servers in the I-queues with servers having one task in execution list. The results of simulation in CloudSim verify that the proposed approach efficiently maximizes resource utilization by reducing the response time in comparison to its other variants.

A Survey on Load Balancing Algorithms for Cloud Environment

2019 ◽  
Vol 16 (2) ◽  
pp. 764-767
Author(s):  
P. Chitra ◽  
Karthika D. Renuka ◽  
K. Senathipathi ◽  
S. Deepika ◽  
R. Geethamani
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Comparative Analysis ◽  
Load Balancing ◽  
Resource Utilization ◽  
The Internet ◽  
Cloud Environment ◽  
Web Based ◽  
Qos Metrics

Cloud computing is the cutting edge technology in the information field to provide services to the users over the internet through web–based tools and applications. One of the major aspects of cloud computing is load balancing. Challenges like Quality of service (QoS) metrics and resource utilization can be improved by balancing the load in cloud environment. Specific scheduling criteria can be applied using load balancing for users prioritization. This paper surveys different load balancing algorithms. The approaches that are existing are discussed and analyzed to provide fair load balancing and also a comparative analysis was presented for the performance of the existing different load balancing schemes.

Efficient on Demand Dynamic Availability-Distribution-Span Scheduling and Load Balancing Scheme for Cloud Computing

2016 ◽  
Vol 13 (10) ◽  
pp. 7655-7660 ◽  
Author(s):  
V Jeyakrishnan ◽  
P Sengottuvelan
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Resource Utilization ◽  
Scheduling Algorithms ◽  
Time Factor ◽  
Cloud Environment ◽  
On Demand ◽  
Availability Factor ◽  
Scheduling Method

The problem of load balancing in cloud environment has been approached by different scheduling algorithms. Still the performance of cloud environment has not been met to the point and to overcome these issues, we propose a naval ADS (Availability-Distribution-Span) Scheduling method to perform load balancing as well as scheduling the resources of cloud environment. The method performs scheduling and load balancing in on demand nature and takes dynamic actions to fulfill the request of users. At the time of request, the method identifies set of resources required by the process and computes Availability Factor, Distributional Factor and Span Time factor for each of the resource available. Based on all these factors computed, the method schedules the requests to be processed in least span time. The proposed method produces efficient result on scheduling as well as load balancing to improve the performance of resource utilization in the cloud environment.

Provisioning of Virtual Machines in the Context of an Auto-Scaling Cloud Computing Environment

2020 ◽  
Vol 17 (6) ◽  
pp. 2430-2434
Author(s):  
R. S. Rajput ◽  
Dinesh Goyal ◽  
Rashid Hussain ◽  
Pratham Singh
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Resource Utilization ◽  
Virtual Machines ◽  
Cloud Environment ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Auto Scaling ◽  
Adequate Resource ◽  
Cloud Resources

The cloud computing environment is accomplishing cloud workload by distributing between several nodes or shift to the higher resource so that no computing resource will be overloaded. However, several techniques are used for the management of computing workload in the cloud environment, but still, it is an exciting domain of investigation and research. Control of the workload and scaling of cloud resources are some essential aspects of the cloud computing environment. A well-organized load balancing plan ensures adequate resource utilization. The auto-scaling is a technique to include or terminate additional computing resources based on the scaling policies without involving humans efforts. In the present paper, we developed a method for optimal use of cloud resources by the implementation of a modified auto-scaling feature. We also incorporated an auto-scaling controller for the optimal use of cloud resources.

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