Service-level agreement

About: Service-level agreement is a research topic. Over the lifetime, 4358 publications have been published within this topic receiving 75333 citations. The topic is also known as: SLA.

QoS-aware service composition in cloud computing using data mining techniques and genetic algorithm

Abstract: One of the requirements of QoS-aware service composition in cloud computing environment is that it should be executed on-the-fly. It requires a trade-off between optimality and the execution speed of service composition. In line with this purpose, many researchers used combinatorial methods in previous works to achieve optimality within the shortest possible time. However, due to the ever-increasing number of services which leads to the enlargement of the search space of the problem, previous methods do not have adequate efficiency in composing the required services within reasonable time. In this paper, genetic algorithm was used to achieve global optimization with regard to service level agreement. Moreover, service clustering was used for reducing the search space of the problem, and association rules were used for a composite service based on their histories to enhance service composition efficiency. The conducted experiments acknowledged the higher efficiency of the proposed method in comparison with similar related works.

Method of displaying real-time service level performance, breach, and guaranteed uniformity with automatic alerts and proactive rebating for utility computing environment

Abstract: The present invention provides a method, apparatus, and computer program product for displaying real-time service level performance, breach, and guaranteed uniformity with automatic alerts and proactive rebating for a utility computing environment. Service level agreement parameters, based on a service level agreement between a customer and a service provider, are used to identify discrepancies in a promised service level for the utility computing environment. A real-time view of a current service level and the promised service level for the customer are displayed. When a discrepancy between the promised service level and the current service level occurs, a rebate is generated for the customer. Alerts identifying the discrepancy and its root cause are provided to the customer and the service provider for the discrepancy. Alerts may also be provided prior to the occurrence of the discrepancy so that an action may be performed to eliminate the potential discrepancy.

GRUBER: a grid resource usage SLA broker

Abstract: Resource sharing within grid collaborations usually implies specific sharing mechanisms at participating sites. Challenging policy issues can arise in such scenarios that integrate participants and resources spanning multiple physical institutions. Resource owners may wish to grant to one or more virtual organizations (VOs) the right to use certain resources subject to local usage policies and service level agreements, and each VO may then wish to use those resources subject to its usage policies. This paper describes GRUBER, an architecture and toolkit for resource usage service level agreement (SLA) specification and enforcement in a grid environment, and a series of experiments on a real grid, Grid3. The proposed mechanism allows resources at individual sites to be shared among multiple user communities.

An Architecture of IoT Service Delegation and Resource Allocation Based on Collaboration between Fog and Cloud Computing

Abstract: Despite the wide utilization of cloud computing (e.g., services, applications, and resources), some of the services, applications, and smart devices are not able to fully benefit from this attractive cloud computing paradigm due to the following issues: (1) smart devices might be lacking in their capacity (e.g., processing, memory, storage, battery, and resource allocation), (2) they might be lacking in their network resources, and (3) the high network latency to centralized server in cloud might not be efficient for delay-sensitive application, services, and resource allocations requests. Fog computing is promising paradigm that can extend cloud resources to edge of network, solving the abovementioned issue. As a result, in this work, we propose an architecture of IoT service delegation and resource allocation based on collaboration between fog and cloud computing. We provide new algorithm that is decision rules of linearized decision tree based on three conditions (services size, completion time, and VMs capacity) for managing and delegating user request in order to balance workload. Moreover, we propose algorithm to allocate resources to meet service level agreement (SLA) and quality of services (QoS) as well as optimizing big data distribution in fog and cloud computing. Our simulation result shows that our proposed approach can efficiently balance workload, improve resource allocation efficiently, optimize big data distribution, and show better performance than other existing methods.