Towards Benefiting Both Cloud Users and Service Providers Through Resource Provisioning

2019 ◽  
Vol 12 (1) ◽  
pp. 37-51
Author(s):  
Durga S. ◽  
Mohan S. ◽  
Dinesh Peter J. ◽  
Martina Rebecca Nittala
Keyword(s):  
Resource Utilization ◽  
Service Providers ◽  
Service Level Agreement ◽  
Cost Savings ◽  
Cloud Service ◽  
Turnaround Time ◽  
Service Level ◽  
Resource Provisioning ◽  
Cloud Users ◽  
Rp Technique

Cloud users expect high Quality of service (QoS) levels within their budget and the cloud service providers (CSPs) to maximize their profits, always strive for the cost and energy minimization and better resource utilization. Any error in the management of resources causes Service Level Agreement (SLA) violations, high penalties, low customer satisfaction, and long-term losses. The objective of this article is to present a literature review on various resource provisioning strategies and also to present a novel cluster-based resource provisioning (CB-RP) technique that satisfies the needs of both cloud users and CSP. CB-RP employs a heart algorithm to cluster the arriving requests based on its characteristics. The CB-RP technique aims to analyze the requests and provision the resources according to the request category. Simulation results show that our technique produces significant improvements in terms of cost savings, resource utilization and turnaround time compared with state of art technique.

Broker-based optimization of SLA negotiations in cloud computing

2021 ◽  
Vol 17 (2) ◽  
pp. 179-195
Author(s):  
Priyanka Bharti ◽  
Rajeev Ranjan ◽  
Bhanu Prasad
Keyword(s):  
Cloud Computing ◽  
Service Providers ◽  
Service Level Agreement ◽  
Cloud Service ◽  
Service Level ◽  
Cloud Environment ◽  
Negotiation Strategies ◽  
Sla Negotiation ◽  
Conflicting Interests ◽  
The Impact

Cloud computing provisions and allocates resources, in advance or real-time, to dynamic applications planned for execution. This is a challenging task as the Cloud-Service-Providers (CSPs) may not have sufficient resources at all times to satisfy the resource requests of the Cloud-Service-Users (CSUs). Further, the CSPs and CSUs have conflicting interests and may have different utilities. Service-Level-Agreement (SLA) negotiations among CSPs and CSUs can address these limitations. User Agents (UAs) negotiate for resources on behalf of the CSUs and help reduce the overall costs for the CSUs and enhance the resource utilization for the CSPs. This research proposes a broker-based mediation framework to optimize the SLA negotiation strategies between UAs and CSPs in Cloud environment. The impact of the proposed framework on utility, negotiation time, and request satisfaction are evaluated. The empirical results show that these strategies favor cooperative negotiation and achieve significantly higher utilities, higher satisfaction, and faster negotiation speed for all the entities involved in the negotiation.

SLA (Service Level Agreement) Driven Orchestration Based New Methodology for Cloud Computing Services

2013 ◽  
Vol 660 ◽  
pp. 196-201 ◽  
Author(s):  
Muhammad Irfan ◽  
Zhu Hong ◽  
Nueraimaiti Aimaier ◽  
Zhu Guo Li
Keyword(s):  
Cloud Computing ◽  
Computer Science ◽  
Service Providers ◽  
Service Level Agreement ◽  
Cloud Service ◽  
Service Level ◽  
Cloud Services ◽  
Computing Services ◽  
Cloud Service Providers ◽  
Cloud Computing Services

Cloud Computing is not a revolution; it’s an evolution of computer science and technology emerging by leaps and bounds, in order to merge all computer science tools and technologies. Cloud Computing technology is hottest to do research and explore new horizons of next generations of Computer Science. There are number of cloud services providers (Amazon EC2), Rackspace Cloud, Terremark and Google Compute Engine) but still enterprises and common users have a number of concerns over cloud service providers. Still there is lot of weakness, challenges and issues are barrier for cloud service providers in order to provide cloud services according to SLA (Service Level agreement). Especially, service provisioning according to SLAs is core objective of each cloud service provider with maximum performance as per SLA. We have identified those challenges issues, as well as proposed new methodology as “SLA (Service Level Agreement) Driven Orchestration Based New Methodology for Cloud Computing Services”. Currently, cloud service providers are using “orchestrations” fully or partially to automate service provisioning but we are trying to integrate and drive orchestration flows from SLAs. It would be new approach to provision cloud service and deliver cloud service as per SLA, satisfying QoS standards.

User Opinion and Differentiated Attribute based Ranking in Federated Cloud

2016 ◽  
Vol 9 (2) ◽  
pp. 78-88
Author(s):  
C. S. Rajarajeswari ◽  
M. Aramudhan
Keyword(s):  
Service Provider ◽  
Service Providers ◽  
Cloud Service ◽  
Resource Provisioning ◽  
Experimental Result ◽  
Innovative Technology ◽  
Cloud Service Provider ◽  
Rank List ◽  
Optimal Service ◽  
Cloud Users

Cloud computing is an innovative technology which provides services to users on-demand and pay per use. Since there are many providers in cloud, users get confused in selecting the optimal service provider for their tasks. To overcome this limitation, federated cloud management architecture was proposed. The proposed work provides a new federated cloud mechanism, in which Broker Manager takes the responsibility of providing optimal and ranked service provider for user requirements. To rank the service providers in the federated cloud, Differentiated Priority based Ranking algorithm is implemented at the level of BM. Attributes are differentiated based on their weights assigned by a user. Service providers are discovered and ranked based on the differentiated attributes. The proposed algorithm chooses the cloud service provider for execution, not only based on the rank list generated by the BM; but also based on the suggestion given by the user. The experimental result shows that the proposed algorithm improves the performance of resource provisioning than the existing model by 13%.

An Innovative SLA-Based Service Monitoring Framework in Cloud

2018 ◽  
Vol 17 (02) ◽  
pp. 1850017
Author(s):  
Mridul Paul ◽  
Ajanta Das
Keyword(s):  
Service Providers ◽  
Service Level Agreement ◽  
Cloud Service ◽  
Service Level ◽  
Information Communication ◽  
Computing Services ◽  
Service Monitoring ◽  
Arduous Task ◽  
Monitoring Framework ◽  
E Learning

Cloud computing encompasses powerful technology to perform complex computing for large applications. It provides access to various resources from any location with reduced Information Communication Technology overhead, enabling availability and scalability of resources based on consumer needs. Therefore, it has brought a paradigm shift in the way computing services are delivered. However, due to its increasing usage and rising expectations from cloud service provisioning, providing optimal and effective service is becoming an arduous task for service providers. Thus, maintaining quality of service (QoS) through regular monitoring is the utmost priority for the service provider. The key ingredient of managing QoS is a service level agreement (SLA). SLAs form a basis of measuring service quality. The cloud can be leveraged for provisioning e-Learning services to serve millions of users. The e-Learning service providers can enter into a contract with available cloud providers, which is transparent to the learners. Hence, it is critical to focus on the SLAs that need to be formulated and managed by the service providers for consumers of their e-Learning services. The objective of this paper is to propose SLA-based e-Learning service framework. This paper also identifies SLA parameters and related metrics to measure SLAs relevant to the provisioning of the proposed e-Learning service. It also proposes an innovative e-Learning service monitoring framework for managing QoS. This paper further evaluates the effectiveness of the proposed framework by provisioning of e-Learning service on Google App Engine cloud platform. It also presents experimental analysis using response graph in order to monitor associated SLAs in the proposed framework.

scholarly journals QoS Aware Resource Scheduling and Performance Assessment of Heuristics for Processing Jobs on Cloud

2020 ◽  
Vol 9 (4) ◽  
pp. 2202-2207
Keyword(s):  
Cloud Computing ◽  
Completion Time ◽  
High Speed ◽  
Service Providers ◽  
Research Work ◽  
Cloud Service ◽  
Service Level ◽  
Cloud Services ◽  
Heuristic Approaches ◽  
Cloud Users

Cloud computing or in other words, shared computing is a unique way of sharing resources via the Internet. It combines and extends features of parallel processing, grid computing, and distributed computing. Cloud Computing environments provide a competent way to schedule and process various jobs on remote machines. Rather than relying on local machines, Cloud users access services remotely via high-speed networks. Various users submitting jobs to be processed to Cloud would expect Quality of Service (QoS). So, currently, many researchers are proposing various heuristics that provide QoS to cloud users. The job scheduler is responsible for scheduling various jobs to its best-matched resource to achieve desired QoS. There are Service Level Agreements (SLAs) between Cloud Service Providers (CSPs) and Cloud users, which need to be followed by both the parties. Benefits would be affected in case of not complying with SLAs. In this paper various SLAs like Hard SLA, Best Effort SLA and Soft SLA are proposed. Jobs with required QoS parameters like Reliability, Execution Time and Priority are submitted to the scheduler. QoS of resources is determined by parameters like Reliability, Job Completion Time and the Cost of the resource. Schedulers then assign the Job to the best-matched resource according to specified SLA. Simulation is performed for First Fit and Best Fit heuristic approaches. Performances of both the heuristic approaches are evaluated with performance parameters like Average Resource Utilization (ARU), Success Rate of Jobs (SR) and Total Completion Time (TCT). This research work is useful for various organizations that provide various Cloud services to users who seek different levels of QoS for various applications.

scholarly journals An integrated three-tier trust management framework in mobile edge computing using fuzzy logic

2021 ◽  
Vol 7 ◽  
pp. e700
Author(s):  
Merrihan B.M. Mansour ◽  
Tamer Abdelkader ◽  
Mohamed Hashem ◽  
El-Sayed M. El-Horbaty
Keyword(s):  
Service Provider ◽  
Trust Management ◽  
Service Providers ◽  
Service Level Agreement ◽  
Cloud Service ◽  
Service Level ◽  
Edge Computing ◽  
Trust Value ◽  
Management Framework ◽  
Cloud Service Providers

Mobile edge computing (MEC) is introduced as part of edge computing paradigm, that exploit cloud computing resources, at a nearer premises to service users. Cloud service users often search for cloud service providers to meet their computational demands. Due to the lack of previous experience between cloud service providers and users, users hold several doubts related to their data security and privacy, job completion and processing performance efficiency of service providers. This paper presents an integrated three-tier trust management framework that evaluates cloud service providers in three main domains: Tier I, which evaluates service provider compliance to the agreed upon service level agreement; Tier II, which computes the processing performance of a service provider based on its number of successful processes; and Tier III, which measures the violations committed by a service provider, per computational interval, during its processing in the MEC network. The three-tier evaluation is performed during Phase I computation. In Phase II, a service provider total trust value and status are gained through the integration of the three tiers using the developed overall trust fuzzy inference system (FIS). The simulation results of Phase I show the service provider trust value in terms of service level agreement compliance, processing performance and measurement of violations independently. This disseminates service provider’s points of failure, which enables a service provider to enhance its future performance for the evaluated domains. The Phase II results show the overall trust value and status per service provider after integrating the three tiers using overall trust FIS. The proposed model is distinguished among other models by evaluating different parameters for a service provider.

scholarly journals Virtual Machine Customization Using Resource Using Prediction for Efficient Utilization of Resources in IaaS Public Clouds

2021 ◽  
Vol 6 (2) ◽  
pp. 170-182
Author(s):  
Derdus Kenga ◽  
Vincent Omwenga ◽  
Patrick Ogao
Keyword(s):  
Energy Consumption ◽  
Resource Utilization ◽  
Virtual Machines ◽  
Service Providers ◽  
Cloud Service ◽  
Cloud Data ◽  
Efficient Resource ◽  
Server Utilization ◽  
Auto Scaling ◽  
Cloud Users

The main cause of energy wastage in cloud data centres is the low level of server utilization. Low server utilization is a consequence of allocating more resources than required for running applications. For instance, in Infrastructure as a Service (IaaS) public clouds, cloud service providers (CSPs) deliver computing resources in the form of virtual machines (VMs) templates, which the cloud users have to choose from. More often, inexperienced cloud users tend to choose bigger VMs than their application requirements. To address the problem of inefficient resources utilization, the existing approaches focus on VM allocation and migration, which only leads to physical machine (PM) level optimization. Other approaches use horizontal auto-scaling, which is not a visible solution in the case of IaaS public cloud. In this paper, we propose an approach of customizing user VM’s size to match the resources requirements of their application workloads based on an analysis of real backend traces collected from a VM in a production data centre. In this approach, a VM is given fixed size resources that match applications workload demands and any demand that exceeds the fixed resource allocation is predicted and handled through vertical VM auto-scaling. In this approach, energy consumption by PMs is reduced through efficient resource utilization. Experimental results obtained from a simulation on CloudSim Plus using GWA-T-13 Materna real backend traces shows that data center energy consumption can be reduced via efficient resource utilization

Game the Oretic Approach for Cloud Service Negotiation

2021 ◽  
Vol 13 (4) ◽  
pp. 65-74
Author(s):  
Ramesh C. ◽  
Santhiya K. ◽  
Rakesh Kumar S. ◽  
Rizwan Patan
Keyword(s):  
Time Delays ◽  
Service Providers ◽  
Service Level Agreement ◽  
Cloud Service ◽  
Service Level ◽  
Negotiation Process ◽  
Trade Off ◽  
Game Of Chicken ◽  
Service Consumer

Cloud computing is a booming technology in the area of digital markets. Tackling the nonfunctional characteristics is a big challenge between service consumers (SC) and service providers (SP). Without proper negotiation between the participants specifying their quality of service (QoS) requirements, service level agreement (SLA) cannot be achieved. Two strategies that are commonly prevalent in the negotiation process are concession model and trade off model. The concession model assures the service consumer (SC) receiving the services on time without any deferment. But service consumer has only limited utility. To balance the utility and achievement rates, the authors propose a mixed negotiation approach for cloud service negotiation, which is based on “Game of Chicken.” Extensive results show that a mixed negotiation approach brings equal amount of satisfaction to both service consumer and service provider in terms of achieving higher utility and outperforms the concession approach, while taking fewer time delays than that of a tradeoff approach.

scholarly journals Game Theory Based Trust Model for Cloud Environment

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
K. Gokulnath ◽  
Rhymend Uthariaraj
Keyword(s):  
Service Providers ◽  
Service Level Agreement ◽  
Cloud Service ◽  
Service Level ◽  
Trust Model ◽  
Cloud Computing Environment ◽  
Game Theoretic ◽  
Time Accuracy ◽  
First Time ◽  
Compare And Contrast

The aim of this work is to propose a method to establish trust at bootload level in cloud computing environment. This work proposes a game theoretic based approach for achieving trust at bootload level of both resources and users perception. Nash equilibrium (NE) enhances the trust evaluation of the first-time users and providers. It also restricts the service providers and the users to violate service level agreement (SLA). Significantly, the problem of cold start and whitewashing issues are addressed by the proposed method. In addition appropriate mapping of cloud user’s application to cloud service provider for segregating trust level is achieved as a part of mapping. Thus, time complexity and space complexity are handled efficiently. Experiments were carried out to compare and contrast the performance of the conventional methods and the proposed method. Several metrics like execution time, accuracy, error identification, and undecidability of the resources were considered.

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