scholarly journals A Unified Algorithm for Virtual Desktops Placement in Distributed Cloud Computing

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Jiangtao Zhang ◽  
Lingmin Zhang ◽  
Hejiao Huang ◽  
Xuan Wang ◽  
Chonglin Gu ◽  
...  
Keyword(s):  
Cloud Service ◽  
Support Service ◽  
Long Distance ◽  
Cloud Service Provider ◽  
User Request ◽  
Unified Algorithm ◽  
Baseline Algorithm ◽  
Distributed Cloud ◽  
Selection Of

Distributed cloud has been widely adopted to support service requests from dispersed regions, especially for large enterprise which requests virtual desktops for multiple geodistributed branch companies. The cloud service provider (CSP) aims to deliver satisfactory services at the least cost. CSP selects proper data centers (DCs) closer to the branch companies so as to shorten the response time to user request. At the same time, it also strives to cut cost considering both DC level and server level. At DC level, the expensive long distance inter-DC bandwidth consumption should be reduced and lower electricity price is sought. Inside each tree-like DC, servers are trying to be used as little as possible so as to save equipment cost and power. In nature, there is a noncooperative relation between the DC level and server level in the selection. To attain these objectives and capture the noncooperative relation, multiobjective bilevel programming is used to formulate the problem. Then a unified genetic algorithm is proposed to solve the problem which realizes the selection of DC and server simultaneously. The extensive simulation shows that the proposed algorithm outperforms baseline algorithm in both quality of service guaranteeing and cost saving.

Dynamic QoS-Aware Cloud Service Selection Using Best-Worst Method and Timeslot Weighted Satisfaction Scores

2020 ◽  
Author(s):  
Falak Nawaz ◽  
Naeem Khalid Janjua
Keyword(s):  
Decision Making ◽  
Service Selection ◽  
Cloud Service ◽  
Cloud Services ◽  
Satisfaction Score ◽  
Analytic Hierarchy ◽  
Hierarchy Process ◽  
Best Worst Method ◽  
Selection Of

Abstract The number of cloud services has dramatically increased over the past few years. Consequently, finding a service with the most suitable quality of service (QoS) criteria matching the user’s requirements is becoming a challenging task. Although various decision-making methods have been proposed to help users to find their required cloud services, some uncertainties such as dynamic QoS variations hamper the users from employing such methods. Additionally, the current approaches use either static or average QoS values for cloud service selection and do not consider dynamic QoS variations. In this paper, we overcome this drawback by developing a broker-based approach for cloud service selection. In this approach, we use recently monitored QoS values to find a timeslot weighted satisfaction score that represents how well a service satisfies the user’s QoS requirements. The timeslot weighted satisfaction score is then used in Best-Worst Method, which is a multi-criteria decision-making method, to rank the available cloud services. The proposed approach is validated using Amazon’s Elastic Compute Cloud (EC2) cloud services performance data. The results show that the proposed approach leads to the selection of more suitable cloud services and is also efficient in terms of performance compared to the existing analytic hierarchy process-based cloud service selection approaches.

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 User Prediction in a Role for Secure Data Sharing Through Cloud

2019 ◽  
Vol 8 (10) ◽  
pp. 162-166
Keyword(s):  
Data Sharing ◽  
Cloud Service ◽  
Searchable Encryption ◽  
Security Issue ◽  
Cloud Service Provider ◽  
Insider Attack ◽  
Data Owner ◽  
User Request ◽  
Secure Data ◽  
Role Based

Nowadays cloud is being used by both individuals and organizations to store and share the data without establishing their own data center. The outsourcings of these data are becoming a major security issue for businesses. Searchable encryption is one of the prominent techniques which allow the data owner to securely store the data and then share the data for their growth in business. With this technique, Cloud Service Provider can process the user request by searching on encrypted stored data without decrypting the data. In this paper we analyze different searchable encryption techniques for secure data sharing and their preventive attacks. We also proposed a method named “User Prediction in Role” to reduce the insider attack possibility in Role Based Data Sharing (RBDS), which is based on user p

A mixed ideal and anti-ideal DEA model: an application to evaluate cloud service providers

2019 ◽  
Author(s):  
Majid Azadi ◽  
Mohammad Izadikhah ◽  
Fahimeh Ramezani ◽  
Farookh Khadeer Hussain
Keyword(s):  
Service Providers ◽  
Rapid Development ◽  
Cloud Service ◽  
Data Envelopment ◽  
Ranking Methods ◽  
Discrimination Power ◽  
Cloud Service Providers ◽  
Complete Ranking ◽  
Selection Of

Abstract The rapid development of cloud computing and the sharp increase in the number of cloud service providers (CSPs) have resulted in many challenges in the suitability and selection of the best CSPs according to quality of service requirements. The main objective of this study is to propose three novel models based on the enhanced Russell model to increase the discrimination power in the evaluation and selection of CSPs. The proposed models are designed based on the distances to two special decision-making units (DMUs), namely the ideal DMU and the anti-ideal DMU. There are two advantages to the proposed ranking methods. First, they consider both pessimistic and optimistic scenarios of data envelopment analysis, so they are more equitable than methods that are based on only one of these scenarios. The second strength of this approach is its discrimination power, enabling it to provide a complete ranking for all CSPs. The proposed method can help customers to choose the most appropriate CSP while at the same time, it helps software developers to identify inefficient CSPs in order to improve their performance in the marketplace.

A Novel Hybrid Optimization-Based Approach for Efficient Development of Business-Applications in Cloud

2020 ◽  
Vol 12 (4) ◽  
pp. 14-35
Author(s):  
Soumia Zertal ◽  
Mohamed Batouche ◽  
Zakaria Laboudi
Keyword(s):  
Optimization Algorithm ◽  
Cloud Service ◽  
Cloud Services ◽  
Ant Colony Optimization Algorithm ◽  
Composite Service ◽  
Business Applications ◽  
User Request ◽  
Business Application ◽  
Multiple Qos

The requests of the companies for the development and deployment of their business-applications in Cloud become more complex so that, sometimes, a one single service cannot carry out the target task on its own. Hence, a user-request is provided as a composite service. On another note, the number of available services is significantly increasing. Therefore, the authors would need to find the optimal cloud service-compositions that satisfy the quality of service values as well as user requirements. The methods proposed in literature for composing cloud services do not consider the composition and deployment constraints of candidate cloud services. This paper presents a novel optimization-based approach for building business-application in Cloud. The proposed approach combines the particle swarm optimization algorithm with some principles of ant colony optimization algorithm to deal with multiple QoS parameters, but also to satisfy the composition and deployment constraints of cloud services. The experimental results show the efficiency of the method for all tests instances.

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.

Cloud Provider Selection Based on Accountability and Security Using Interval Valued Fuzzy TOPSIS

2022 ◽  
Vol 14 (1) ◽  
pp. 0-0
Keyword(s):  
Cloud Service ◽  
Fuzzy Topsis ◽  
Cloud Provider ◽  
Cloud Service Provider ◽  
Public Resource ◽  
Ranking Systems ◽  
Financial Benefits ◽  
Criteria For Evaluation ◽  
Cloud Users ◽  
Selection Of

Cloud computing enables on-demand access to a public resource pool. Many businesses are migrating to the cloud due to its popularity and financial benefits. As a result, finding a suitable and best Cloud Service Provider is a difficult task for all cloud users. Many ranking systems, such as ANP, AHP and TOPSIS, have been proposed in the literature .However, many of the studies concentrated on quantitative data. But qualitative attributes are equally significant in many applications where the user is more concerned with the qualitative features.The implementation of MCDM approach for the ranking and the selection of the best player in the market as per the qualitative need of the cloud users like business organization or cloud brokers is the aim of this article. An ISO approved standard SMI framework is available for the evaluation of the CSPs.The authors have considered SMI attributes like accountability and security as the criteria for evaluation of the CSPs. The MCDM approach called IVF-TOPSIS that can handle the inherent vagueness in the cloud dataset is implemented in this work

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