scholarly journals SLA-constrained service selection for minimizing costs of providing composite cloud services under stochastic runtime performance

SpringerPlus ◽  
2016 ◽  
Vol 5 (1) ◽  
Author(s):  
Kuo-Chan Huang ◽  
Mu-Jung Tsai ◽  
Sin-Ji Lu ◽  
Chun-Hao Hung
2016 ◽  
Vol 9 (3) ◽  
pp. 394-407 ◽  
Author(s):  
Shuiguang Deng ◽  
Longtao Huang ◽  
Daning Hu ◽  
J. Leon Zhao ◽  
Zhaohui Wu

Author(s):  
Ajai K. Daniel

The cloud-based computing paradigm helps organizations grow exponentially through means of employing an efficient resource management under the budgetary constraints. As an emerging field, cloud computing has a concept of amalgamation of database techniques, programming, network, and internet. The revolutionary advantages over conventional data computing, storage, and retrieval infrastructures result in an increase in the number of organizational services. Cloud services are feasible in all aspects such as cost, operation, infrastructure (software and hardware) and processing. The efficient resource management with cloud computing has great importance of higher scalability, significant energy saving, and cost reduction. Trustworthiness of the provider significantly influences the possible cloud user in his selection of cloud services. This chapter proposes a cloud service selection model (CSSM) for analyzing any cloud service in detail with multidimensional perspectives.


2020 ◽  
Author(s):  
Falak Nawaz ◽  
Naeem Khalid Janjua

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.


SIMULATION ◽  
2007 ◽  
Vol 83 (1) ◽  
pp. 93-106 ◽  
Author(s):  
Dimitrios Tsesmetzis ◽  
Ioanna Roussaki ◽  
Efstathios Sykas

Sign in / Sign up

Export Citation Format

Share Document