MADMAC: Multiple Attribute Decision Methodology for Adoption of Clouds

Saripalli, Prasad; Pingali, Gopal

doi:10.1109/cloud.2011.61

Cited by 79 publications

(54 citation statements)

References 6 publications

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“…(Saripalli & Pingali, 2011;Bibi et al 2010;Frey & Hasselbring, 2011;Zardari & Bahsoon, 2011). In recent years, several experience reports have started appearing discussing the replacement and migration of existing systems and applications to cloud solutions (Chauhan & Babar, 2011;Khajeh-Hosseini et al 2010), illustrating the multi-dimensionality of the problem.…”

Section: Decision Framework and Tools For Supporting Cloud Saas Migrmentioning

confidence: 99%

A Holistic Decision Framework to Avoid Vendor Lock-in for Cloud SaaS Migration

Opara-Martins¹,

Sahandi²,

Tian³

2017

CIS

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Cloud computing offers an innovative business model to enterprise for IT services consumption and delivery. Software as a Service (SaaS) is one of the cloud offerings that attract organisations as a potential solution in reducing their IT cost. However, the vast diversity among the available cloud SaaS services makes it difficult for customers to decide whose vendor services to use or even to determine a valid basis for their selections. Moreover, this variety of cloud SaaS services has led to proprietary architectures and technologies being used by cloud vendors, increasing the risk of vendor lock-in for customers. Therefore, when enterprises interact with SaaS providers within the purview of the current cloud marketplace, they often encounter significant lock-in challenges to migrating and interconnecting cloud. Hence, the complexity and variety of cloud SaaS service offerings makes it imperative for businesses to use a clear and well understood decision process to procure, migrate and/or discontinue cloud services. To date, the expertise and technological solutions to simplify such transition and facilitate good decision making to avoid lock-in risks in the cloud are limited. Besides, little investigation has been carried out to provide a comprehensive decision framework to support enterprises on how to avoid lock-in risks when selecting and implementing cloud-based SaaS solutions within existing environments. Such decision framework is important to reduce complexity and variations in implementation patterns on the cloud provider side, while at the same time minimising potential switching cost for enterprises by resolving integration issues with existing IT infrastructures. This paper proposes a holistic 6-step decision framework that enables an enterprise to assess its current IT landscape for potential SaaS replacement, and provides effective strategies to mitigate vendor lock-in risks in cloud (SaaS) migration. The framework follows research findings and addresses the core requirements for choosing vendor-neutral interoperable and portable cloud services without the fear of vendor lock-in, and architectural decisions for secure SaaS migration. Therefore, the results of this research can help IT managers have a safe and effective migration to cloud computing SaaS environment.

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Section: Decision Framework and Tools For Supporting Cloud Saas Migrmentioning

confidence: 99%

A Holistic Decision Framework to Avoid Vendor Lock-in for Cloud SaaS Migration

Opara-Martins¹,

Sahandi²,

Tian³

2017

CIS

View full text Add to dashboard Cite

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“…Based on decision-making theories in [23], the authors analysed problems which might be encountered by consumers criteria during service selection process and identified solution which can be used in the process. For the proposed service selection framework-MADMAC (i.e.…”

Section: Related Workmentioning

confidence: 99%

“…This tolerance, however, should be exercised with care, as it might lead to failure of selection process and consequently fail to satisfy the needs of the service consumer. In contrast to SPSE- [25] and SAW-based [23] approaches, we develop an automatic method to autonomously determine the weight value of QoS attributes by calculating correlation dependencies between different QoS attributes and a new service ranking algorithm is introduced by considering partial matching of services, which will be introduced in the following section.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

An efficient algorithm for partially matched services in internet of services

Ahmed

Liu

Hardy

et al. 2016

Pers Ubiquit Comput

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Internet of Things (IoT) connects billions of devices in an Internet-like structure. Each device encapsulated as a real-world service which provides functionality and exchanges information with other devices. This largescale information exchange results in new interactions between things and people. Unlike traditional web services, internet of services is highly dynamic and continuously changing due to constant degrade, vanish and possibly reappear of the devices, this opens a new challenge in the process of resource discovery and selection. In response to increasing numbers of services in the discovery and selection process, there is a corresponding increase in number of service consumers and consequent diversity of quality of service (QoS) available. Increase in both sides' leads to the diversity in the demand and supply of services, which would result in the partial match of the requirements and offers. This paper proposed an IoT service ranking and selection algorithm by considering multiple QoS requirements and allowing partially matched services to be counted as a candidate for the selection process. One of the applications of IoT sensory data that attracts many researchers is transportation especially emergency and accident services which is used as a case study in this paper. Experimental results from real-world services showed that the proposed method achieved significant improvement in the accuracy and performance in the selection process.

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“… Adaptability: the level of service delivery model flexibility with respect to changing user requirements, and needs of the organization adopting cloud computing [29].…”

Section: The Selection Factors Of Cloud Computing Service Modelsmentioning

confidence: 99%

A Group Decision-Making Method for Selecting Cloud Computing Service Model

Al‐Jabri¹,

Eid²,

Sohail³

2018

ijacsa

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Abstract-Cloud computing is a new technology that has great potential for the business world. Many business firms have implemented, are implementing, or planning to implement cloud computing technology. The cloud computing resources are delivered in various forms of service models which make it challenging for business customers to select the model that suits their business needs. This paper proposes a novel group-based decision-making method where a group of decision makers is involved in the decision process. Each decision maker provides weights for the cloud selection criteria. Based on weight aggregations and deviations, decision makers would select the alternative which has the highest ratio of deviation to mean is selected. The method is illustrated with an example on the selection of cloud service models. This method is useful for IT managers in selecting the appropriate cloud service model for their organizations.

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MADMAC: Multiple Attribute Decision Methodology for Adoption of Clouds

Cited by 79 publications

References 6 publications

A Holistic Decision Framework to Avoid Vendor Lock-in for Cloud SaaS Migration

A Holistic Decision Framework to Avoid Vendor Lock-in for Cloud SaaS Migration

An efficient algorithm for partially matched services in internet of services

A Group Decision-Making Method for Selecting Cloud Computing Service Model

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