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.

Load-Balancing Tactics in Cloud

Abstract: Cloud computing enables shared servers to provide resources, software and data for collaborative services on demand with high interoperability and scalability. However, there are a number of technical challenges that need to be tackled before these benefits can be fully realized, which include system reliability, resource provisioning, and efficient resources consuming, etc. Among them, load-balancing is a necessary mechanism to increase the service level agreement (SLA) and better uses of the resources. Unfortunately, serversi¦ capability varies much in practice and is not easy to record in ordered positions in a server farm, which will causes non resource-aware load-balancing algorithms to distribute workloads evenly. We discuss this issue and show why such algorithms doni¦t fit the cloud computing environment and then present a feasible resource-aware load-balancing mechanism by using existing proven technologies to meet higher SLA and the return of investment as well.

A novel trust management framework for multi-cloud environments based on trust service providers

Abstract: In this paper, we address the problem of trust management in multi-cloud environments based on a set of distributed Trust Service Providers (TSPs). These are independent third-party providers/trust agents, trusted by Cloud Providers (CPs), Cloud Service Providers (CSPs) and Cloud Service Users (CSUs), that provide trust related services to cloud participants. TSPs are distributed over the clouds, and they elicit raw trust evidence from different sources and in different formats. This evidence is information regarding the adherence of a CSP to a Service Level Agreement (SLA) for a cloud-based service and the feedback sent by CSUs. Using this information, they evaluate an objective trust and a subjective trust of CSPs. TSPs communicate among themselves through a trust propagation network that permits a TSP to obtain trust information about a CSP from other TSPs. Experiments show that our proposed framework is effective and relatively stable in differentiating trustworthy and untrustworthy CSPs in a multi-cloud environment.

Service level agreement design and enforcement for outsourced call center

Abstract: A method for managing support services includes storing one or more support level agreements (SLAs), each having an associated attribute, in a database as one or more corresponding data objects. One or more trouble tickets, each having one or more associated attributes, are entered into the database as one or more corresponding data objects. One or more of the one or more stored SLAs are automatically applied to each of the one or more trouble tickets by matching the attributes of the one or more trouble tickets with the attributes of the one or more SLAs.

A Framework and Algorithm for Energy Efficient Container Consolidation in Cloud Data Centers

Abstract: One of the major challenges that cloud providers face is minimizing power consumption of their data centers. To this point, majority of current research focuses on energy efficient management of resources in the Infrastructure as a Service model and through virtual machine consolidation. However, containers are increasingly gaining popularity and going to be major deployment model in cloud environment and specifically in Platform as a Service. This paper focuses on improving the energy efficiency of servers for this new deployment model by proposing a framework that consolidates containers on virtual machines. We first formally present the container consolidation problem and then we compare a number of algorithms and evaluate their performance against metrics such as energy consumption, Service Level Agreement violations, average container migrations rate, and average number of created virtual machines. Our proposed framework and algorithms can be utilized in a private cloud to minimize energy consumption, or alternatively in a public cloud to minimize the total number of hours the virtual machines leased.

Data-aware remaining time prediction of business process instances

Abstract: Accurate prediction of the completion time of a business process instance would constitute a valuable tool when managing processes under service level agreement constraints. Such prediction, however, is a very challenging task. A wide variety of factors could influence the trend of a process instance, and hence just using time statistics of historical cases cannot be sufficient to get accurate predictions. Here we propose a new approach where, in order to improve the prediction quality, both the control and the data flow perspectives are jointly used. To achieve this goal, our approach builds a process model which is augmented by time and data information in order to enable remaining time prediction. The remaining time prediction of a running case is calculated combining two factors: (a) the likelihood of all the following activities, given the data collected so far; and (b) the remaining time estimation given by a regression model built upon the data.