scholarly journals An Approach towards Development of a Migration enabled Improved Datacenter Broker Policy

2019 ◽  
Vol 4 (3) ◽  
pp. 112-124
Author(s):  
Sourav Banerjee ◽  
Debashis Das ◽  
Ayan Kundu ◽  
Saptarshi Pal ◽  
Utpal Biswas
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Waiting Time ◽  
Load Capacity ◽  
Cloud Service ◽  
Turnaround Time ◽  
Cloud Service Provider ◽  
Allocation Policy ◽  
Critical Issues

Cloud computing has left its remarkable note on the computing world over the last few years. Through its effectiveness, litheness, scalability & availability cloud computing has changed the nature of computer system deployment. The Quality of Service (QoS)of a cloud service provider (CSP) is an important element of research interest which includes different critical issues such as proper load, minimization of waiting time, turnaround time, makespan and suppressing the wastage of bandwidth of the system. The Datacenter Broker (DCB) policy help assigning a cloudlet to a VM. In the present study, we proposed an algorithm, i.e., Migration enabled Cloudlet Allocation Policy (MCAP) for allocation of cloudlets to the VMs in a Datacenter by taking into account the load capacity of VMs and length of the cloudlets. The experimental results obtained using CloudSim toolkit under extensive loads that establish performance supremacy of MCAP algorithm over the existing algorithms.

scholarly journals An approach towards development of a migration enabled improved datacenter broker policy

2020 ◽  
Vol 4 (3) ◽  
pp. 112-124
Author(s):  
Debashis Das ◽  
Sourav Banerjee ◽  
Ayan Kundu ◽  
Swagata Chandra ◽  
Saptarshi Pal ◽  
...  
Keyword(s):  
Quality Of Service ◽  
Waiting Time ◽  
Service Provider ◽  
Cloud Service ◽  
Turnaround Time ◽  
Experimental Results ◽  
Cloud Service Provider ◽  
Allocation Policy ◽  
Critical Issues

Cloud computinghas left its remarkable note on the computing world over the last few years. Through itseffectiveness, litheness, scalability & availability cloud computinghas changed the nature of computer systemdeployment. The Quality of Service (QoS) of a cloud service provider (CSP) is an important element of research interestwhich includes different critical issues such as proper load, minimization of waiting time, turnaround time, makespanand suppressing the wastage of bandwidth of the system. The Datacenter Broker (DCB) policy helpsassigning acloudletto a VM. In present study, we proposed an algorithm, i.e., Migration enabled Cloudlet Allocation Policy(MCAP) for allocation of cloudlets to the VMs in a Datacenter by taking into accounttheload capacity of VMs andlength of the cloudlets. The experimental results obtained using CloudSim toolkit under extensive loads that establishperformance supremacy of MCAP algorithm over the existing algorithms.

Issues in On-Demand Cloud-Based Gaming Storage

2017 ◽  
pp. 115-138
Author(s):  
Ebin Deni Raj ◽  
L. D. Dhinesh Babu
Keyword(s):  
Mathematical Model ◽  
Cloud Computing ◽  
Quality Of Service ◽  
Service Provider ◽  
Quality Of Experience ◽  
Cloud Service ◽  
End User ◽  
Cloud Service Provider ◽  
On Demand

Cloud computing is the most utilized and evolving technology in the past few years and has taken computing to a whole new level such that even common man is receiving the benefits. The end user in cloud computing always prefers a cloud service provider which is efficient, reliable and best quality of service at the lowest possible price. A cloud based gaming system relieves the player from the burden of possessing high end processing and graphic units. The storage of games hosted in clouds using the latest technologies in cloud has been discussed in detail. The Quality of service of games hosted in cloud is the main focus of this chapter and we have proposed a mathematical model for the same. The various factors in dealing with the quality of service on cloud based games have been analyzed in detail. The quality of experience of cloud based games and its relation with quality of service has been derived. This chapter focuses on the various storage techniques, quality of experience factors and correlates the same with QoS in cloud based games.

scholarly journals Priority-Based Virtual Machine Selection Algorithm in Cloud Computing

2019 ◽  
Vol 8 (3) ◽  
pp. 1457-1462
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Service Level Agreement ◽  
Cloud Service ◽  
Service Level ◽  
Cloud Services ◽  
Cloud Service Provider

Cloud computing technology has gained the attention of researchers in recent years. Almost every application is using cloud computing in one way or another. Virtualization allows running many virtual machines on a single physical computer by sharing its resources. Users can store their data on datacenter and run their applications from anywhere using the internet and pay as per service level agreement documents accordingly. It leads to an increase in demand for cloud services and may decrease the quality of service. This paper presents a priority-based selection of virtual machines by cloud service provider. The virtual machines in the cloud datacenter are configured as Amazon EC2 and algorithm is simulated in cloud-sim simulator. The results justify that proposed priority-based virtual machine algorithm shortens the makespan, by 11.43 % and 5.81 %, average waiting time by 28.80 % and 24.50%, and cost of using the virtual machine by 21.24% and 11.54% as compared to FCFS and ACO respectively, hence improving quality of service.

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.

scholarly journals EVALUATION OF CLOUD COMPUTING CLUSTER PERFORMANCE

T-Comm ◽  
2020 ◽  
Vol 14 (12) ◽  
pp. 72-79
Author(s):  
Aleksandr O. Volkov ◽  
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Service Providers ◽  
Poisson Model ◽  
Cloud Service ◽  
Computing System ◽  
Processor Sharing ◽  
Cloud Systems ◽  
Cloud Computing System

For cloud service providers, one of the most relevant tasks is to maintain the required quality of service (QoS) at an acceptable level for customers. This condition complicates the work of providers, since now they need to not only manage their resources, but also provide the expected level of QoS for customers. All these factors require an accurate and well-adapted mechanism for analyzing the performance of the service provided. For the reasons stated above, the development of a model and algorithms for estimation the required resource is an urgent task that plays a significant role in cloud systems performance evaluation. In cloud systems, there is a serious variance in the requirements for the provided resource, as well as there is a need to quickly process incoming requests and maintain the proper level of quality of service – all of these factors cause difficulties for cloud providers. The proposed analytical model for processing requests for a cloud computing system in the Processor Sharing (PS) service mode allows us to solve emerging problems. In this work, the flow of service requests is described by the Poisson model, which is a special case of the Engset model. The proposed model and the results of its analysis can be used to evaluate the main characteristics of the performance of cloud systems.

A Salp Swarm Optimization for Dynamic Resource Management to Improve Quality-of-Service in Cloud Computing and IoT Environment

2021 ◽  
Vol 11 ◽  
Author(s):  
Narander Kumar ◽  
Surendra Kumar
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Data Centers ◽  
Service Providers ◽  
Cloud Service ◽  
Research Problem ◽  
Resource Provisioning ◽  
Quality Of Services ◽  
Computing Services

Background: Cloud Computing can utilize processing and efficient resources on a metered premise. This feature is a significant research problem, like giving great Quality-of-Services (QoS) to the cloud clients. Objective: Quality of Services confirmation with minimum utilization of resource and their time/costs, cloud service providers ought to receive self-versatile of the resource provisioning at each level. Currently, various guidelines, as well as model-based methodologies, have been intended to the management of resources aspects in the cloud computing services. Method: In this Research article, manage resource allocations dependent optimization Salp Swarm Algorithm (SSA) areused to merge various numbers of VMs on lessening Data Centers to SLA as well as required Quality-of-Service (QoS) with most extreme data centers use. Result: We compared with the various approaches like the First fit (FF), greedy crow search (GCS), and hybrid crow search with the response time and resource utilization. Conclusion: The proposed mechanism is simulated on Cloudsim Simulator, the simulation results show less migration time that improves the QoS as well minimize the energy consumssion in a cloud computing and IoT environment.

scholarly journals Efficient Task Scheduling for Quality of Service in Cloud Computing Network

2020 ◽  
Vol 8 (5) ◽  
pp. 3193-3196
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Response Time ◽  
Task Scheduling ◽  
Waiting Time ◽  
Threshold Values ◽  
Specific Time ◽  
Required Quality ◽  
Cloud Resources

Task scheduling in cloud is the process of allocating a resource to a task at specific time. The allocation of limited cloud resources to large number of tasks to satisfy the required quality of service is the key challenge in cloud. Allocation of a resource with less capability to a task increases the response time, makespan of the task and waiting time of the entire tasks in the waiting queue. This problem will result to an unsatisfied Quality of Service. In this paper we proposed an efficient task scheduling that uses three threshold values to specify the resource to be allocated to a task at a given time. This method ensures that a capable resource is allocated to task such that the response time and makespan of the all task are minimized. The proposed method was simulated using CloudSim and the result shows a better response time and makespan than the well known Min-Min and Max-Min Method.

scholarly journals An Integrated Triple Type Security System in Cloud Computing

2019 ◽  
Vol 8 (9) ◽  
pp. 3419-3422
Keyword(s):  
Cloud Computing ◽  
Cloud Storage ◽  
Cloud Service ◽  
Web Security ◽  
Security System ◽  
Cloud Service Provider ◽  
Cloud Data ◽  
Service Companies ◽  
Data Owner

Cloud computing is most widely used in many companies now a days. Cloud means services available and provided in the web. Security plays a major role in cloud computing to store the various forms of data. Providing quality of security for the cloud storage data is very important. Many cloud providing service companies takes various steps to secure the data. In this paper, the integrated triple type security system is provided for the cloud data. The proposed three way security system provides the encryption to the data uploaded by the data owner and if the user wants to download the available data with encryption key sent by the data owner and decryption key sent by the cloud service provider then the verification of the user can be done by the cloud admin. In this way, the three way data security is implemented.

Dynamic partner selection in Cloud Federation for ensuring the quality of service for cloud consumers

2017 ◽  
Vol 08 (03) ◽  
pp. 1750036 ◽  
Author(s):  
Manoj V. Thomas ◽  
K. Chandrasekaran
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Large Scale ◽  
Service Providers ◽  
Partner Selection ◽  
Cloud Service ◽  
Analytic Hierarchy ◽  
Cloud Federation ◽  
Global Coordination

Cloud Computing has become the popular paradigm for accessing the various scalable and on-demand computing services over the internet. Nowadays, individual Cloud Service Providers (CSPs) offering specialized services to the customers collaborate to form the Cloud Federation, in order to reap the real benefits of Cloud Computing. By collaboration, the member CSPs of the federation achieve better resource utilization and Quality of Service (QoS), thereby increasing their business prospects. When a CSP runs out of resources in the Cloud Federation, in order to offload the customer requests for resources to other CSP(s), identifying a suitable partner is a challenging task due to the lack of global coordination among them. In this paper, we propose the design and implementation of an efficient partner selection mechanism in the Cloud Federation, using the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods, and also considering the trust values of various CSPs in the federation. The AHP method is used to calculate the weights of the QoS parameters used in the TOPSIS method which is used to rank the various CSPs in the Cloud Federation according to the user requirements. Simulation results show the effectiveness of this approach in order to efficiently select the trustworthy partners in large scale federations to ensure the required QoS to the cloud consumers.

Automation of Discovery and Aggregation of Cloud Services

2015 ◽  
Vol 3 (1) ◽  
Author(s):  
Sreedevi R. Nagarmunoli ◽  
Nandini S. Sidnal
Keyword(s):  
Cloud Computing ◽  
Service Discovery ◽  
Service Level Agreement ◽  
Cloud Service ◽  
Service Level ◽  
Cloud Services ◽  
Direct Service ◽  
Cloud Service Provider ◽  
Multiple Services

Cloud computing is a technology where IT-related resources are dynamically provided as a service to the customers through Internet. The customer can demand for the services dynamically from Cloud Service Provider (CSP)s, take them on lease based on Service Level Agreement (SLA), release the resources after completion of task and pay for what is used. The required services may not be available from a single CSP. There are many CSPs providing multiple services with different Quality of Service (QoS). The customer has to discover the available services with the expected QoS which is one of the major challenges to be solved in cloud computing today. In this paper we dynamically create a repository of the cloud services and aggregate them whenever there is a demand for service and then derive that the services obtained from the repository are time efficient as compared to direct service discovery.

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