An Adaptive Service Monitoring System in a Cloud Computing Environment

2020 ◽  
Vol 12 (2) ◽  
pp. 47-63
Author(s):  
Sathiyamoorthy E. ◽  
Karthikeyan P
Keyword(s):  
Cloud Computing ◽  
Rapid Development ◽  
Service Level Agreement ◽  
Cloud Service ◽  
Service Level ◽  
Cloud Services ◽  
Cloud Environment ◽  
Computing Environment ◽  
Time Duration ◽  
Cloud Computing Environment

Cloud computing is a trending area of information technology (IT). In a cloud environment, the Cloud service provider (CSP) provides all the functionalities to the users or customers in terms of services. With the rapid development of cloud computing, the performance of any cloud environment relies on the quality of services (QoS) at the time of providing the services. A service level agreement (SLA) increases the confidence of the user or customer to use the cloud services in a cloud environment. There should be negotiation between the CSP and users to achieve a strong SLA. Many existing SLA models are already developed. However, these models do not concentrate to maintain the quality in a long-time duration period. To solve this issue, a novel SLA model has been proposed in this article by using Fuzzy logic. Both the theoretical and simulation results show the proficiency of the proposed scheme over the existing schemes in a cloud computing environment.

scholarly journals A Survey on Improving QoS in Service Level Agreement for Cloud Computing Environment

2021 ◽  
Vol 15 (21) ◽  
pp. 119
Author(s):  
Afaf Edinat ◽  
Rizik M. H. Al-Sayyed ◽  
Amjad Hudaib
Keyword(s):  
Cloud Computing ◽  
Learning Process ◽  
Service Providers ◽  
Service Level Agreement ◽  
Cloud Service ◽  
Service Level ◽  
Shared Services ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
The Relationship

Cloud computing is considered one of the most important techniques in the field of distributed computing which contributes to maintain increased scalability and flexibility in computer processing. This is achieved because it, using the Internet, provides different resources and shared services with minimum costs. Cloud service providers (CSPs) offer many different services to their customers, where the customers’ needs are met seeking the highest levels of quality at the lowest considerate prices. The relationship between CSPs and customers must be determined in a formal agreement, and to ensure how the QoS between them will be fulfilled, a clear Service Level Agreement (SLA) must be called for. Several previously-proposed models used in the literature to improve the QoS in the SLA for cloud computing and to face many of the challenges in the SLA are reviewed in this paper. We also addressed the challenges that are related to the violations of SLAs, and how overcoming them will enhance customers’ satisfaction. Furthermore, we proposed a model based on Deep Reinforcement Learning (DRL) and an enhanced DRL agent (EDRLA). In this model, and by optimizing the learning process in EDRLA, proposed agents would be able to have optimal CSPs by improving the learning process in EDRLA. This improvement will be reflected in the agent's performance and considerably affect it, especially in identifying cloud computing requirements based on the QoS metrics.

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.

Resource Allocation Policies in Cloud Computing Environment

2017 ◽  
pp. 115-132 ◽  
Author(s):  
Suvendu Chandan Nayak ◽  
Sasmita Parida ◽  
Chitaranjan Tripathy ◽  
Prasant Kumar Pattnaik
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Resource Utilization ◽  
Service Level Agreement ◽  
Service Level ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
On Demand ◽  
Different Types ◽  
Cloud Datacenter

The basic concept of cloud computing is based on “Pay per Use”. The user can use the remote resources on demand for computing on payment basis. The on-demand resources of the user are provided according to a Service Level Agreement (SLA). In real time, the tasks are associated with a time constraint for which they are called deadline based tasks. The huge number of deadline based task coming to a cloud datacenter should be scheduled. The scheduling of this task with an efficient algorithm provides better resource utilization without violating SLA. In this chapter, we discussed the backfilling algorithm and its different types. Moreover, the backfilling algorithm was proposed for scheduling tasks in parallel. Whenever the application environment is changed the performance of the backfilling algorithm is changed. The chapter aims implementation of different types of backfilling algorithms. Finally, the reader can be able to get some idea about the different backfilling scheduling algorithms that are used for scheduling deadline based task in cloud computing environment at the end.

scholarly journals Service Level Agreement Violation Preventive Task Scheduling for Quality of Service Delivery in Cloud Computing Environment

2020 ◽  
Vol 178 ◽  
pp. 375-385
Author(s):  
Ismail Zahraddeen Yakubu ◽  
Zainab Aliyu Musa ◽  
Lele Muhammed ◽  
Badamasi Ja’afaru ◽  
Fatima Shittu ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Service Delivery ◽  
Task Scheduling ◽  
Service Level Agreement ◽  
Service Level ◽  
Computing Environment ◽  
Cloud Computing Environment

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.

scholarly journals An Effiecient Approach for Resource Auto-Scaling in Cloud Environments

2016 ◽  
Vol 6 (5) ◽  
pp. 2415
Author(s):  
Bahar Asgari ◽  
Mostafa Ghobaei Arani ◽  
Sam Jabbehdari
Keyword(s):  
Service Level Agreement ◽  
Service Level ◽  
Resource Provisioning ◽  
Cloud Services ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Sla Violation ◽  
Markov Decision ◽  
Cloud Environments ◽  
Auto Scaling

<p>Cloud services have become more popular among users these days. Automatic resource provisioning for cloud services is one of the important challenges in cloud environments. In the cloud computing environment, resource providers shall offer required resources to users automatically without any limitations. It means whenever a user needs more resources, the required resources should be dedicated to the users without any problems. On the other hand, if resources are more than user’s needs extra resources should be turn off temporarily and turn back on whenever they needed. In this paper, we propose an automatic resource provisioning approach based on reinforcement learning for auto-scaling resources according to Markov Decision Process (MDP). Simulation Results show that the rate of Service Level Agreement (SLA) violation and stability that the proposed approach better performance compared to the similar approaches.</p>

Controlled Intelligent Agents' Security Model for Multi-Tenant Cloud Computing Infrastructures

2017 ◽  
Vol 9 (1) ◽  
pp. 1-13
Author(s):  
Howard Hamilton ◽  
Hadi Alasti
Keyword(s):  
Cloud Computing ◽  
Data Security ◽  
Intelligent Agents ◽  
Cloud Service ◽  
Cloud Services ◽  
Service Users ◽  
Security Model ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Service Models

Data security in the cloud continues to be a huge concern. The adoption of cloud services continues to increase with more businesses transitioning from on premise technology infrastructures to outsourcing cloud-based infrastructures. As the cloud becomes more popular, users are increasingly demanding control over critical security elements of the data and technology assets that are in the cloud. In addition, there are still cries for greater data and security in the cloud. The goal of this paper is to provide cloud service users with greater control over data security in the cloud while at the same time optimizing overall security in the multi-tenant cloud computing environment. This paper introduces cloud-based intelligent agents that are configurable by the users and are expected to give greater compliance for data security in any of the cloud service models.

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