A Multi-Criteria Decision-making Model for an IaaS Provider Selection

Transcription

1 A Multi-Criteria Decision-making Model for an IaaS Provider Selection Problem 1 Sangwon Lee, 2 Kwang-Kyu Seo 1, First Author Department of Industrial & Management Engineering, Hanyang University ERICA, upcircle@hanyang.ac.kr *2,Corresponding Author Department of Management Engineering, Sangmyung University, kwangkyu@smu.ac.kr Abstract In rapid chaining business environment, information and communication technology (ICT) is a must for the survival of a company and is becoming increasingly important. The emergence of cloud computing represents a fundamental change of ICT services and cloud services continue to grow rapidly with increasing functionality and more users. As a result of this growth, it is a critical issue to select the suitable cloud service provider which meets all the business strategies and the goals of the company. This study explores an approach to select a suitable cloud service provider focused on the IaaS provider for companies users. In order to achieve this goal, the criteria for IaaS provider selection were determined and then compared according to their importance. The candidate IaaS providers were selected to evaluate according to the predetermined criteria. In this study, the analytic hierarchy process (AHP) as the multi-criteria decision-making technique was used to compare these IaaS providers. Keywords: Multi-Criteria Decision-making Model, IaaS, Provider Selection, AHP, Cloud Service 1. Introduction In rapid chaining business environment, information and communication technology (ICT) is a must for the survival of a company and is becoming increasingly important. The emergence of cloud computing represents a fundamental change of ICT services and cloud services continue to grow rapidly. As a result of this growth, the global and Korean major cloud service providers launched commercial B2B and B2C cloud services such as IaaS (Infrastructure as a Service), PaaS (Platform as a Service) and SaaS (Software as a Service). Cloud services are expected to give an opportunity for enterprises to make new business models. Companies are to deliver a network of virtual services so that companies users can access them from anywhere in the world without making high capital investment to procure ICT infrastructure, skilled ICT experts and system managers. Thus, they do not invest infrastructure to deploy and operate their services. According to increasing companies users of cloud services, it is a critical issue to select the suitable cloud service provider which meets all the business strategies and the goals of the company. This study explores an approach to select a suitable cloud service provider focused on the IaaS provider for companies users. In order to achieve this goal, the criteria for IaaS provider selection are determined and then compared according to their importance. The candidate IaaS providers are chosen to evaluate according to the predetermined criteria. In this study, the analytic hierarchy process (AHP) as the multi-criteria decision-making technique is applied to compare and estimate these IaaS providers. The paper is structured as follows. In Section 2, research background consisted of cloud service and the analytic hierarchy process (AHP) is briefly described. In section 3, we propose our research model and present IaaS provider selection processes. Section 4 concludes the study with a brief summary. 2. Research Background 2.1. Cloud service Cloud services change the ICT paradigm and are novel business models. They comprise ways of delivering and applying computing services through network called the Internet. Cloud services are carried out on behalf of customers on hardware, platform and software that the customers do not own, operate, control or manage. The users of cloud services sends their data to the cloud, these data are International Journal of Advancements in Computing Technology(IJACT) Volume 5, Number 12, August

2 processed and operated by an application provided by the cloud service provider, and the results are returned to the users [1]. Therefore they are valuable service solutions based on the cloud computing system, and they consist of a new way of utilizing and consuming ICT services based on the Internet. In addition, the important characteristics of cloud services are as follows: First of all, cloud services allow organizations to focus on core business processes and to implement supporting applications that can deliver competitive advantage; and secondly, cloud services free organizations from the burden of having to develop and maintain large-scale ICT systems [2]. As we know, the representative cloud service providers are as follows: (1) typical IaaS offerings are: Amazon s Elastic Compute Cloud (EC2) and Simple Storage Service (S3), whereas KT ucloud, SKT cloud and LG U cloud in Korea. (2) typical PaaS offerings are: Google s App Engine, and Salesforce s Force.com, whereas there is no special providers in Korea. (3) typical SaaS offerings is: Salesforce.com, whereas there are some SaaS providers provided by KT s OASIS and SKT s Tcloud in Korea Analytic Hierarchy Process (AHP) The analytic hierarchy process (AHP) proposed by Saaty [3] is a structured technique to organize and analyze complex decision-making problems. It has particular application in group decision-making problems [4] and is used around the world in a wide variety of decision situations such as government, business, industry, healthcare, and education and so on. The AHP helps decision makers find one that best suits their goal and their understanding of the problem. It provides a comprehensive and rational framework to structure a decision-making problem, for representing and quantifying its elements, for relating those elements to overall goals, and for evaluating alternative solutions [5]. Users of the AHP first decompose their decision problem into a hierarchy of more easily comprehended sub-problems, each of which can be analyzed independently. The elements of the hierarchy can relate to any aspect of the decision problem - qualitative or quantitative, carefully measured or roughly estimated. Once the hierarchy is built, the decision makers systematically evaluate its various elements by comparing them to one another two at a time, with respect to their impact on an element above them in the hierarchy. In making the comparisons, the decision makers can use concrete data about the elements, but they typically use their judgments about the elements' relative meaning and importance. It is the essence of the AHP that human judgments, and not just the underlying information, can be used in performing the evaluations [6]. Using AHP, opinions and evaluations of experts can be integrated, and a complex problem can be devised into a simple hierarchy system with higher levels to lower ones. Figure 1 presents the general analytical hierarchy process model. Figure 1. The General Analytical Hierarchy Process Model 364

3 It consists of an overall goal, a group of options or alternatives for reaching the goal, and a group of factors or criteria that relate the alternatives to the goal. The criteria can be further broken down into subcriteria, sub-subcriteria, and so on, in as many levels as the problem requires. The design of any AHP hierarchy will depend not only on the nature of the problem at hand, but also on the knowledge, judgments, values, opinions, needs, wants, etc. of the participants in the decision-making process. Constructing a hierarchy typically involves significant discussion, research, and discovery by those involved. Even after its initial construction, it can be changed to accommodate newly-thought-of criteria or criteria not originally considered to be important; alternatives can also be added, deleted, or changed [5] [7] [8] [9] [10]. The application of AHP to a complex problem involves the following six essential steps [11] [12]: (1) Define the unstructured problem and state clearly the objectives and outcomes. (2) Decompose the complex problem into a hierarchical structure with decision elements (criteria and alternatives). (3) Employ pairwise comparisons among decision elements and form comparison matrices. (4) Use the eigenvalue method to estimate the relative weights of decision elements. (5) Check the consistency property of matrices to ensure the judgments of decision makers are consistent. (6) Aggregate the relative weights of decision elements to obtain an overall rating for the alternatives. 3. IaaS Provider Selection Model In the first part of the study, the most important factors for evaluating traditional ICT providers and for evaluating cloud service providers, especially IaaS providers, are examined. After a detailed review of the literature and interviews with domain experts, the three criteria and the 8 sub-criteria are identified as shown in Table 1. Table 1.Criteria for Decision-making Model Criteria Provider perspective Service perspective Support perspective - Service Provider's Name - Service Availability - Service Level Recognition - Service Performance Agreement (SLA) Sub-criteria - Service Price - Service Scalability - Service support - Security The constructed hierarchy model for decision-making is also presented in Figure 2. This is implemented in expert choice Figure 2. The Constructed Hierarchy Model To determine the importance of the three criteria and the 8 sub-criteria, a nine-point scale is used in the questionnaires to collect experts opinions. Fifteen experts consisted of cloud experts, ICT consultants, CTO and so on are asked to fill out the first questionnaire and they calculate the weight according to their importance. 365

4 In the second part of the study, we compared the five IaaS providers according to the predetermined importance of criteria. Figure 3 shows five IaaS providers which are domestic and international providers and used in Korean cloud service market. Figure 3. The candidate IaaS providers We use the expert choice 11.5 to compare and select the optimal IaaS provider. The final results of importance of criteria and sub-criteria and the optimal IaaS provider selection present in Figure 4. As shown in Figure 4, IaaS provider 5 was selected with finally. Figure 4. The final results of importance of criteria and the optimal IaaS provider selection 4. Conclusions Information and communication technology (ICT) is a must for the survival of a company in a competitive business environment. The emergence of cloud computing represents a fundamental change of ICT services and cloud services continue to grow rapidly with increasing functionality and more users. As a result of this growth, it is a critical issue to select the suitable cloud service provider which meets all the business strategies and the goals of the company. This study explores an approach to select a suitable cloud service provider focused on the IaaS provider for companies users. In order 366

5 to achieve this goal, the criteria for IaaS provider selection were determined and then compared according to their importance. The candidate IaaS providers were selected to evaluate according to the predetermined criteria. In this study, the analytic hierarchy process (AHP) as the multi-criteria decision-making technique was used to compare these IaaS providers. This paper presented the AHP based decision-making model to select a suitable cloud service provider focused on the IaaS provider for companies users. The criteria and sub-criteria for the proposed decision-making model were introduced and identified by considering the characteristics of IaaS and they were determined and then compared according to their importance. The IaaS providers were selected to evaluate for the proposed model. In this study, we compared the five IaaS providers which are domestic and international providers and serviced in Korean cloud service market. The proposed IaaS provider selection methodology was applied successfully. The proposed methodology can be used for other cloud service providers selection or cloud service selection problems. 5. Acknowledgement This research was supported by a 2013 Research Grant from Sangmyung University. 6. References [1] M. Mowbray, S. Pearson, A Client-Based Privacy Manager for Cloud Computing, In Proceeding of the Conference on Communication System Software and Middleware, pp. 1-8, [2] W. -W. Wu, Developing an explorative model for SaaS adoption, Expert Systems with Applications, Elsevier, vol. 38, no. 12, pp , [3] L. Saaty, The Analytic Hierarchy Process, McGraw-Hill, USA, [4] L. Saaty, K. Peniwati, Group Decision Making: Drawing out and Reconciling Differences, RWS Publications, USA, [5] [6] L. Saaty, Decision Making for Leaders: The Analytic Hierarchy Process for Decisions in a Complex World, RWS Publications, USA, [7] L. Saaty, Relative Measurement and its Generalization in Decision Making: Why Pairwise Comparisons are Central in Mathematics for the Measurement of Intangible Factors The Analytic Hierarchy/Network Process, RACSAM: Review of the Royal Spanish Academy of Sciences, Series A, Mathematics), Springer, vol. 102, no. 2, pp , [8] L. Saaty, F. Thomas, The Hierarchon: A Dictionary of Hierarchies, RWS Publications, USA, [9] N. Subramaniana, R. Ramanathan, A review of applications of Analytic Hierarchy Process in operations management, International Journal of Production Economics, Elsevier, vol. 138, no. 2, pp , [10] D. Ergu, G. Kou, Y. Peng, Y. Shi, Y. Shi, The analytic hierarchy process: task scheduling and resource allocation in cloud computing environment, The Journal of Supercomputing, Springer, vol. 64, no. 3, pp , [11] A. H. I. Lee, H. Y. Kang, W. P. Wang, Analysis of priority mix planning for semiconductor fabrication under uncertainty, International Journal of Advanced Manufacturing Technology, Springer, vol. 28, no. 3-4, pp , [12] A. H. I. Lee, H. -Y. Kang, C. -F. Hsu, H. -C. Hung, A green supplier selection model for hightech industry, Expert Systems with Applications, Elsevier, vol. 36, no. 4, pp ,