scholarly journals Survey on QoS metrics and ranking in cloud services

2017 ◽  
Vol 7 (1.3) ◽  
pp. 146
Author(s):  
Rajeswari P ◽  
Jayashree K
Keyword(s):  
Cloud Computing ◽  
High Speed ◽  
Service Selection ◽  
Cloud Services ◽  
Utilization Efficiency ◽  
Essential Requirement ◽  
Optimal Service ◽  
Cloud Applications ◽  
Qos Metrics

The Cloud Computing uses high speed broadband for good Quality of Service (QoS) so that Cloud based application can be used with high speed which entails the minimum response time, less latency rate and reduced amount of loss of packets. Because of the ample range within the delivered Cloud solutions, from the customer’s aspect, it's emerged as irksome to decide whose providers they need to utilize and then what's the thought of his or her option. Bestowing suitable metrics is vital in assessing practices. QoS metrics are playing an important role in selecting Cloud providers and also revamping resource utilization efficiency. To guarantee a specialized product is published, describing metrics for assessing the QoS might be an essential requirement. To obtain high quality Cloud applications, Optimal Service Selection is needed. With the increasing number of Cloud services, QoS is usually selected for describing non-functional characteristics of Cloud services. In this paper, a widespread survey on QoS metrics for service vendors and QoS Ranking in Cloud Computing is presented.

An Optimal Service Selection with Constraints Based on QoS Algorithm

2012 ◽  
Vol 487 ◽  
pp. 357-364
Author(s):  
Xin Jun Li
Keyword(s):  
Computing Time ◽  
Service Selection ◽  
Optimal Service ◽  
Availability Constraints ◽  
The One ◽  
Qos Performance ◽  
The Impact ◽  
Structural Aspects ◽  
Reliability And Availability

In the paper, we propose an allocation scheme that minimizes the response time and cost of the solution subject to reliability and availability constraints in terms of expected value. The algorithm proposed in this paper aims to discover services with high QoS performance, and reduce the execute time at the same time. First, we identify the impact of various structural aspects of the composition in terms of the performance and outcomes of the composition. Then, an algorithm is proposed which can reduce the computing time and makes sure better quality of the services selection at the same time by examining a very tiny fraction of the solution space.Finally, we proves the advantage of the new algorithm by comparing the time obtained by our proposed algorithm with the one achieved by other algorithm.

Quality of Cloud Services

2012 ◽  
pp. 1609-1620
Author(s):  
Anette Weisbecker
Keyword(s):  
Information Technology ◽  
Cloud Computing ◽  
Business Models ◽  
Value Added ◽  
Cloud Services ◽  
The Internet ◽  
Success Factor ◽  
Distributed Resources ◽  
Critical Success

Cloud Computing has become the predominant paradigm in information technology for the use of distributed resources. It enables the Internet of Services where different provider offer services and compose services to new value added services. For the emerging service value chains the quality the services plays an important role. Therefore, beside software engineering methods aspects like quality of services, business models, and the interaction with the customer have to be considered during the development of cloud services. This chapter describes how these aspects can be integrated in the development process by combining software and service engineering methods and considering quality as a critical success factor in the design time.

A Cloud Trusting Mechanism Based on Resource Ranking

2020 ◽  
pp. 130-155
Author(s):  
Ajai K. Daniel
Keyword(s):  
Cloud Computing ◽  
Resource Management ◽  
Service Selection ◽  
Cloud Service ◽  
Cloud Services ◽  
Storage And Retrieval ◽  
Computing Paradigm ◽  
Efficient Resource ◽  
Software And Hardware ◽  
Cloud User

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.

Novel Taxonomy to Select Fog Products and Challenges Faced in Fog Environments

2021 ◽  
pp. 2558-2571
Author(s):  
Akashdeep Bhardwaj
Keyword(s):  
Cloud Computing ◽  
Distributed Computing ◽  
High Speed ◽  
Low Cost ◽  
Fog Computing ◽  
Research Work ◽  
Cloud Services ◽  
Smart Devices ◽  
Viable Solution ◽  
Last Mile

This article describes how the rise of fog computing to improve cloud computing performance and the acceptance of smart devices is slowly but surely changing our future and shaping the computing environment around us. IoT integrated with advances in low cost computing, storage and power, along with high speed networks and big data, supports distributed computing. However, much like cloud computing, which are under constant security attacks and issues, distributed computing also faces similar challenges and security threats. This can be mitigated to a great extent using fog computing, which extends the limits of Cloud services to the last mile edge near to the nodes and networks, thereby increasing the performance and security levels. Fog computing also helps increase the reach and comes across as a viable solution for distributed computing. This article presents a review of the academic literature research work on the Fog Computing. The authors discuss the challenges in Fog environment and propose a new taxonomy.

Cloud Computing Economics

2016 ◽  
pp. 88-111
Author(s):  
Stamatia Bibi ◽  
Dimitrios Katsaros ◽  
Panayiotis Bozanis
Keyword(s):  
Information Technology ◽  
Cloud Computing ◽  
Distributed Computing ◽  
Decision Problem ◽  
High Speed ◽  
Business Case ◽  
Cloud Services ◽  
It Systems ◽  
Basic Parameters ◽  
User Demand

Cloud services and technologies are currently receiving increased attention from the industry mostly due to business-driven promises and expectations. Significant innovations in virtualization and distributed computing, as well as improved access to high-speed Internet and a weak economy, have accelerated interest in cloud computing. However, is the migration to the Cloud the most profitable option for every business? Enterprise adoption of cloud computing often requires a significant transformation of existing Information Technology (IT) systems and processes. To justify such a change, a viable business case must be made based on the economics of transformation. This chapter presents a study of the basic parameters for estimating the potential infrastructure and software costs deriving from building and deploying applications on cloud and on-premise assets. Estimated user demand and desired quality attributes related to an application are also addressed in this chapter as they are aspects of the decision problem that also influence the choice between cloud and in-house solutions.

A Mobile Cloud Middleware to Support Mobility and Cloud Interoperability

2016 ◽  
Vol 7 (1) ◽  
pp. 41-58 ◽  
Author(s):  
Khadija Akherfi ◽  
Hamid Harroud ◽  
Michael Gerndt
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
Data Storage ◽  
Mobile Cloud Computing ◽  
Relevant Information ◽  
Cloud Services ◽  
Mobile Cloud ◽  
Computing Power ◽  
Cloud Interoperability

With the recent advances in cloud computing and the improvement in the capabilities of mobile devices in terms of speed, storage, and computing power, Mobile Cloud Computing (MCC) is emerging as one of important branches of cloud computing. MCC is an extension of cloud computing with the support of mobility. In this paper, the authors first present the specific concerns and key challenges in mobile cloud computing. They then discuss the different approaches to tackle the main issues in MCC that have been introduced so far, and finally focus on describing the proposed overall architecture of a middleware that will contribute to providing mobile users data storage and processing services based on their mobile devices capabilities, availability, and usage. A prototype of the middleware is developed and three scenarios are described to demonstrate how the middleware performs in adapting the provision of cloud web services by transforming SOAP messages to REST and XML format to JSON, in optimizing the results by extracting relevant information, and in improving the availability by caching. Initial analysis shows that the mobile cloud middleware improves the quality of service for mobiles, and provides lightweight responses for mobile cloud services.

IoT Based Agriculture as a Cloud and Big Data Service

2020 ◽  
pp. 1499-1521
Author(s):  
Sukhpal Singh Gill ◽  
Inderveer Chana ◽  
Rajkumar Buyya
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Cloud Services ◽  
Cloud Environment ◽  
Big Data Technologies ◽  
Sensor Networking ◽  
New Applications

Cloud computing has transpired as a new model for managing and delivering applications as services efficiently. Convergence of cloud computing with technologies such as wireless sensor networking, Internet of Things (IoT) and Big Data analytics offers new applications' of cloud services. This paper proposes a cloud-based autonomic information system for delivering Agriculture-as-a-Service (AaaS) through the use of cloud and big data technologies. The proposed system gathers information from various users through preconfigured devices and IoT sensors and processes it in cloud using big data analytics and provides the required information to users automatically. The performance of the proposed system has been evaluated in Cloud environment and experimental results show that the proposed system offers better service and the Quality of Service (QoS) is also better in terms of QoS parameters.

Dynamic QoS-Aware Cloud Service Selection Using Best-Worst Method and Timeslot Weighted Satisfaction Scores

2020 ◽  
Author(s):  
Falak Nawaz ◽  
Naeem Khalid Janjua
Keyword(s):  
Decision Making ◽  
Service Selection ◽  
Cloud Service ◽  
Cloud Services ◽  
Satisfaction Score ◽  
Analytic Hierarchy ◽  
Hierarchy Process ◽  
Best Worst Method ◽  
Selection Of

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.

scholarly journals Moving to the Edge-Cloud-of-Things: Recent Advances and Future Research Directions

Electronics ◽  
2018 ◽  
Vol 7 (11) ◽  
pp. 309 ◽  
Author(s):  
Hind Bangui ◽  
Said Rakrak ◽  
Said Raghay ◽  
Barbora Buhnova
Keyword(s):  
Cloud Computing ◽  
Leading Edge ◽  
Cloud Services ◽  
Future Research ◽  
Research Directions ◽  
Iot Applications ◽  
Future Research Directions ◽  
Iot Devices ◽  
The Internet Of Things

Cloud computing has significantly enhanced the growth of the Internet of Things (IoT) by ensuring and supporting the Quality of Service (QoS) of IoT applications. However, cloud services are still far from IoT devices. Notably, the transmission of IoT data experiences network issues, such as high latency. In this case, the cloud platforms cannot satisfy the IoT applications that require real-time response. Yet, the location of cloud services is one of the challenges encountered in the evolution of the IoT paradigm. Recently, edge cloud computing has been proposed to bring cloud services closer to the IoT end-users, becoming a promising paradigm whose pitfalls and challenges are not yet well understood. This paper aims at presenting the leading-edge computing concerning the movement of services from centralized cloud platforms to decentralized platforms, and examines the issues and challenges introduced by these highly distributed environments, to support engineers and researchers who might benefit from this transition.

scholarly journals Efficient and Optimal Service Component Distribution across Multiple Clouds

2018 ◽  
Vol 6 (3) ◽  
pp. 44 ◽  
Author(s):  
Driss Riane ◽  
Ahmed Ettalbi
Keyword(s):  
Cloud Services ◽  
Main Step ◽  
Service Component ◽  
Component Distribution ◽  
Cloud Broker ◽  
Optimal Service ◽  
Multiple Clouds ◽  
Lock In ◽  
Better Than

<span class="fontstyle0">Cloud computing technology is one of the key considerations for business willing to access to different cloud services over the Internet and to benefit from the diversity of IaaS offers and pricing models. Although several solutions are available in the market, there are still some issues to solve. The main important aspect to address is the user’s request complexity, the vendor lock-in risk and the SLA fulfillment. In this paper, we propose a Multi-Cloud Broker called MCB that allows an efficient and optimal service component distribution among different clouds in flexible and dynamic infrastructure provisioning environment, in order to achieve better Quality of Service and cost efficiency. The request partitioning is the main step of our approach, this step is performed using Gomory-Hu tree based algorithm. Our simulation results show how our algorithm is better than existing partitioning algorithms in terms of running time.</span>

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