Selecting Cloud Deployment Model Using a Delphi Analytic Hierarchy Process (DAHP)

Cloud computing is a significant paradigm shift in information technology (IT) service offerings that has been receiving enormous attention in academic and IT industry. Recent years has seen exponential growth in cloud use adoption, where many organizations are moving their IT resources into cloud due to flexibility and low-cost. However, on account of rapid innovation and growth in cloud technologies and service providers, selecting the right cloud services, provider and strategy is becoming increasing a common challenge to organization during cloud adoption. In an attempt to address this challenge, we propose application of Delphi Analytic Hierarchy Process (DAHP) method in selecting cloud deployment model. There are several cloud deployment models and organizations must identify the right model that best suits their business needs. The proposed approach facilitates a collaborative decision making process, consisting a number of decision makers whom, with consensus facilitated by the DAHP process, identifies feasible approaches, decision making factors and ultimate selection of a cloud deployment model alternative that is based on organizational business needs and capabilities. The DAHP process is illustrated by a means of a case study. The DAHP result analysis, as was illustrated in the case study, helps in explaining and justifying the choice selected as the best cloud deployment model

AHP Aided Decision-Making in Virtual Machine Migration for Green Cloud

In this study, an analytical hierarchy process based model is proposed to perform the decision-making for virtual machine migration towards green cloud computing. The virtual machine migration evaluation index system is established based on the process of constructing hierarchies for evaluation of virtual machine migration, and selection of task usage. A comparative judgment of two hierarchies has been conducted. In the experimental study, five-point rating scale has been adopted to map the raw data to the scaled rating score; this rating method is used to analyze the performance of each virtual machine and its task usage data. The results show a significant improvement in the decision-making process for the virtual machine migration. The deduced results are useful for the system administrators to migrate the exact virtual machine, and then switch on the power of physical machine that the migrated virtual machine resides on. Thus the proposed method contributes to the green cloud computing environment

Decision Model for Selecting a Cloud Provider: A Study of Service Model Decision Priorities

This article describes a methodology to support the decision-making process for Cloud customers, using the Analytic Hierarchy Process (AHP). For this purpose, we present a decision model to select an appropriate Cloud provider. Despite its success in the industry, Cloud Computing still struggles with fulfilling customer expectations regarding provider characteristics. Due to limited transparency of existing Cloud providers, the evaluation and selection becomes a key issue. With the help of this decision model Cloud providers can be selected on the infrastructure, platform or application level. Subsequently, seven IT executives were interviewed and the decisions related to each level are discussed. Furthermore, differences and similarities between the infrastructure, platform and application levels are presented as most companies have similar requirements for basic systems and standard Cloud use cases. We enrich existing research on Cloud Computing adoption and present a systematic approach to assess Cloud providers and to apply a prioritization of selection criteria for all Cloud models

Security based partner selection in Inter-organizational workflow systems

The creation of inter-organizational workflow implies the coalition of partners' efforts and resources in order to achieve a set of common objectives and goals. However, this openness may cause a huge damage to the participating entities due to security breaches. The risk of unsuccessful collaboration should be well studied. Thus, the key for successful collaboration is to select the appropriate collaborators based on specific security criteria for each outsourced task. In this sense, several criteria have to be considered, among them: trust and reputation level, policy similarity level, security level and privacy compliance level. The proposed security based partner selection approach allows us to rank participating entities in the collaboration based on the main security criteria in order to assign each task to the suitable partner with the most appropriate and efficient way

Cloud computing adoption decision modelling for SMEs: a conjoint analysis

Cloud computing is an emerging technology that promises competitive advantages, cost savings, enhanced business processes and services, and various other benefits to enterprises. Despite the rapid technological advancement, the adoption of cloud computing is still growing slowly among small and mediumsized enterprises (SMEs). This paper presents a model to support the decisionmaking process, using a multi-criteria decision method PAPRIKA for the socio-technical aspects influencing SMEs cloud adoption decision. Due to the multifaceted nature of the cloud computing adoption process, the evaluation of various cloud services and deployment models have become a major challenge. This paper presents a systematic approach to evaluating cloud computing services and deployment models. Subsequently, we have conducted conjoint analysis activities with five SMEs decision makers as part of the distribution process of this decision modelling based on predetermined criteria. With the help of the proposed model, cloud services and deployment models can be ranked and selected

Towards multi-criteria cloud service selection

Cloud computing despite being in an early stage of adoption is becoming a popular choice for businesses to replace in-house IT infrastructure due to its technological advantages such as elastic computing and cost benefits resulting from pay-as-you-go pricing and economy of scale. These factors have led to a rapid increase in both the number of cloud vendors and services on offer. Given that cloud services could be characterized using multiple criteria (cost, pricing policy, performance etc.) it is important to have a methodology for selecting cloud services based on multiple criteria. Additionally, the end user requirements might map to different criteria of the cloud services. This diversity in services and the number of available options have complicated the process of service and vendor selection for prospective cloud users and there is a need for a comprehensive methodology for cloud service selection. The existing research literature in cloud service selection is mostly concerned with comparison between similar services based on cost or performance benchmarks. In this paper we discuss and formalize the issue of cloud service selection in general and propose a multi-criteria cloud service selection methodology