Fuzzy cloud service selection framework

2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA), 2018

Cloud service selection is complicated by the prospect that there exist a large number of services and each service is characterized by multiple QoS attributes. Various commercial tools have been developed in order to help cloud consumers with selecting best cloud services. This paper provides an in-depth analysis of the three commercial cloud service selection tools as well as the way they represent QoS attributes. Accordingly, it proposes a new model that succinctly represents QoS attributes which cloud consumers can easily use (and understand) when selecting cloud services. The proposed model also classifies the QoS attributes into four main categories of technical, strategic & organizational, economic and political & legislative. These QoS attributes can also be seamlessly fed into the multi-criteria decision (e.g., MCDM)-which compares and ranks different QoS attributes of multiple alternatives in order to decide which services are most suitable for cloud consumers.

International Journal on Recent and Innovation Trends in Computing and Communication

The Internet of Things (IoT) has received a lot of interest from researchers recently. IoT is seen as a component of the Internet of Things, which will include billions of intelligent, talkative "things" in the coming decades. IoT is a diverse, multi-layer, wide-area network composed of a number of network links. The detection of services and on-demand supply are difficult in such networks, which are comprised of a variety of resource-limited devices. The growth of service computing-related fields will be aided by the development of new IoT services. Therefore, Cloud service composition provides significant services by integrating the single services. Because of the fast spread of cloud services and their different Quality of Service (QoS), identifying necessary tasks and putting together a service model that includes specific performance assurances has become a major technological problem that has caused widespread concern. Various strategies are used in the composition o...

International Journal of Cloud Applications and Computing, 2014

Cloud Computing is a promising computing paradigm that provides flexible, Internet-accessible resources allocation on demand on a pay-as-you-go basis. With the growth and expansion of Cloud services and participation of various services providers, the description of quality parameters and measurement units started to diverse and sometimes contradict. Such ambiguity does not only result in the raise of various QoS interoperability problems, but also in the distraction of the services consumers who find themselves unable to match their quality requirements with the providers' offerings. Influenced by such diversity, the available QoS models are limited to either cost-benefit analysis or performance evaluation, without being able to cover a comprehensive set of well-defined quality aspects. In this paper, we provide a complete framework for such problem. We firstly propose a novel QoS ontology that combine and define all of the existing quality aspects in a unified way to efficient...

In a world that sees new technological trends bloom and fade on almost a daily basis, one new trend promises more longevity. This trend is called mobile cloud computing, and it will change the way we use computer and the Internet. In this paper we introduce idea of improving accessibility of Cloud using if then concept of Fuzzy, we have tried to present a model for evaluating user's satisfaction in cloudcomputing. Therefore, a conceptual model has been constructed considering attributes to evaluate cloud computing user's satisfaction in an Internet Service Provider(ISP) companies in Iran. To avoid any ambiguities which are caused by linguistic methods, in this evaluation model wehave used Fuzzy Inference System (FIS).

Cloud computing offers cost-effective, on-demand and pay as you use IT services to service consumers based on Service Level Agreements (SLAs). The cloud services offered by cloud providers raise the need for Quality of Service (QoS) monitoring to ensure that SLAs are maintained for accountability. As a result, service performance, which includes availability, response time and throughput, is one of the core concerns of the cloud users. This paper proposes a fuzzy-based model for QoS violation detection and prediction of service response time and duration for ensuring continuous service availability. Our experimental results show small Root Mean Squared Error (RMSE) of less than 0.50, thus confirming the greater than 99% detection and prediction accuracy for QoS violation. This fuzzy model with 16 fuzzy rules of detecting and predicting QoS violation for Software as a Service (SaaS) allows the cloud administrator to make accurate decisions for appropriate remedial action. Consequently, accountability is taken care of with a win-win benefit for both the cloud users and service providers. This contributes towards a different dimension in the measurement of quality of cloud services where accountability is taken into consideration.

International Journal of Engineering & Technology

In today's world, technological trend offers computing resources as services through the internet in on-demand or pay-as-you-go approach. These services are provided by different cloud service providers. Due to which trust on the any service provider is a choice of any customer. In order to choose a reputed cloud service provider a new method using the concept of fuzzy has proposed in this paper. This method enhanced the customer's satisfaction level of using cloud services by avoiding ambiguities in fuzzy interface system (FIS) through optimization. Proposed fuzzy rule-based decision support system is collaborating with advanced fuzzy system optimized using a swarm intelligent firefly algorithm that facilitates the consumers in selecting right CSP based upon their rating value. It conducts three different reviews of three different components, i.e. customer review, service provider review and public review. Results are carried out on the basis of both simple and the optimized fuzzy, and it is found that the optimized fuzzy surpasses the simple fuzzy logic.

2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2017

With the growing demand for outsourcing the ICT section of enterprises, Cloud Computing service providers increased their popularity. Selecting the most appropriate provider for a demanding enterprise depends on many criteria that are based on the strategies, requirements, and resources of the enterprise. Since this problem is a kind of decision problem and depends on criteria of decisionmaker, it can be modeled as Multi-criteria Decision Making (MCDM) problem. In this research, a pilot case study is conducted in which the Cloud Computing service provider selection problem is modeled as a MCDM problem. For selecting the most appropriate provider, Fuzzy Extend Analysis is implemented in the case study.

Advances in Intelligent Systems and Computing, 2018

The growing number of cloud computing providers has made the selection process difficult and time consuming. This motivates many research to propose cloud computing recommendation system. However, generating an overall rating of a provider based on accumulation of several performance parameters involves uncertainties especially when the computation comprises network-related performance parameters. Hence, this paper proposes a fuzzy logic-based model that evaluates providers based on downlink, uplink and latency parameters, and determines the best provider. The model was constructed based on historical data of the real cloud computing providers implementation. The model was compared against non-fuzzy model, and it showed that the proposed fuzzy logic-based model is better in terms of accuracy. This work implies faster and accurate selection of cloud computing provider.

International Journal of Computers Communications & Control, 2016

Cloud Computing (CC) is a technology that surely brings innovations in today’s business world, more and more companies around the world are widely incorporating this technology into their businesses. From a technical, as well as organizational point of view transferring enterprise IT to the Cloud is a complex task. Various factors have to be taken into consideration in order to make a right choice when moving IT services to the Cloud. The goal of this paper is to identify and to discuss in detail all factors that influence organization’s decision to adopt Cloud. General model for Cloud adoption, introduced in Pantelic et al. [13]a, consists of the key factors driving the organizational benefits when moving to the Cloud. The purpose of the model is to support decision makers in evaluating the benefits, risks and costs of using Cloud Computing. In this paper the general model is extended with two new aggregation methods for harmonization of alternatives rankings in a group decision pr...

Advances in Fuzzy Systems

Cloud computing can be considered as one of the leading-edge technological advances in the current IT industry. Cloud computing or simply cloud is attributed to the Service Oriented Architecture. Every organization is trying to utilize the benefit of cloud not only to reduce the cost overhead in infrastructure, network, hardware, software, etc., but also to provide seamless service to end users with the benefit of scalability. The concept of multitenancy assists cloud service providers to leverage the costs by providing services to multiple users/companies at the same time via shared resource. There are several cloud service providers currently in the market and they are rapidly changing and reorienting themselves as per market demand. In order to gain market share, the cloud service providers are trying to provide the latest technology to end users/customers with the reduction of costs. In such scenario, it becomes extremely difficult for cloud customers to select the best service ...