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.

SLA-driven container consolidation with usage prediction for green cloud computing

Abstract: Since service level agreement (SLA) is essentially used to maintain reliable quality of service between cloud providers and clients in cloud environment, there has been a growing effort in reducing power consumption while complying with the SLA by maximizing physical machine (PM)-level utilization and load balancing techniques in infrastructure as a service. However, with the recent introduction of container as a service by cloud providers, containers are increasingly popular and will become the major deployment model in the cloud environment and specifically in platform as a service. Therefore, reducing power consumption while complying with the SLA at virtual machine (VM)-level becomes essential. In this context, we exploit a container consolidation scheme with usage prediction to achieve the above objectives. To obtain a reliable characterization of overutilized and underutilized PMs, our scheme jointly exploits the current and predicted CPU utilization based on local history of the considered PMs in the process of the container consolidation. We demonstrate our solution through simulations on real workloads. The experimental results show that the container consolidation scheme with usage prediction reduces the power consumption, number of container migrations, and average number of active VMs while complying with the SLA.

Task Classification Based Energy-Aware Consolidation in Clouds

Abstract: We consider a cloud data center, in which the service provider supplies virtual machines (VMs) on hosts or physical machines (PMs) to its subscribers for computation in an on-demand fashion. For the cloud data center, we propose a task consolidation algorithm based on task classification (i.e., computation-intensive and data-intensive) and resource utilization (e.g., CPU and RAM). Furthermore, we design a VM consolidation algorithm to balance task execution time and energy consumption without violating a predefined service level agreement (SLA). Unlike the existing research on VM consolidation or scheduling that applies none or single threshold schemes, we focus on a double threshold (upper and lower) scheme, which is used for VM consolidation. More specifically, when a host operates with resource utilization below the lower threshold, all the VMs on the host will be scheduled to be migrated to other hosts and then the host will be powered down, while when a host operates with resource utilization above the upper threshold, a VM will be migrated to avoid using 100% of resource utilization. Based on experimental performance evaluations with real-world traces, we prove that our task classification based energy-aware consolidation algorithm (TCEA) achieves a significant energy reduction without incurring predefined SLA violations.

Service level agreement based storage access

Abstract: A method and a system implementing a service level agreement based storage access system. A service level agreement based storage access system presents a single interface for data storage consumers and translates generic data operation requests to data operation request specific to a storage server. The SLA based storage access system also monitors storage server performance and may throttle processes to ensure service level agreements are not violated.

An optimal infrastructure design method of cloud computing services from the BDIM perspective

Abstract: For IT service providers, infrastructure construction plays a significant role in the maximization of business profits. Infrastructure design is becoming more and more crucial as IT service environments evolve from deployment on site to Software as a Service (SaaS), and, most recently, to cloud computing. In this paper, a cloud computing architecture is proposed from the viewpoint of Business-Driven IT Management (BDIM); then an optimal cloud infrastructure design methodology is devised, whereby numbers of servers, routers and communication bandwidth can be calculated through considering both infrastructure costs and business losses incurred by Service Level Agreement (SLA) violations. Finally, a complete numerical example is discussed to testify the proposed method.

An efficient energy-aware approach for dynamic VM consolidation on cloud platforms

Abstract: The cloud computing environments rely heavily on virtualization that enables the physical hardware resources to be shared among cloud users by creating virtual machines (VMs). With an overloaded physical machine, the resource requests by virtual machines may not be fulfilled, which results in Service Level Agreement (SLA) violations. Moreover, the high performance servers in cloud data centers consume large amount of energy. The dynamic VM consolidation techniques use live migration of virtual machines to optimize resource utilization and minimize energy consumption. An excessive migration of virtual machines may however deteriorate application performance due to the overhead incurring at runtime. In this paper, we propose a normalization-based VM consolidation (NVMC) strategy that aims at placing virtual machines in an online manner while minimizing energy consumption, SLA violations, and the number of VM migrations. The proposed strategy uses resource parameters for determining over-utilized hosts in a virtualized cloud environment. The comparative capacity of virtual machines and hosts is incorporated for determining over-utilized hosts, while the cumulative available-to-total ratio (CATR) is used to find under-utilized hosts. For migrating virtual machines to appropriate hosts, the VM placement uses a criteria based on normalized resource parameters of hosts and virtual machines. For evaluating the performance of VM consolidation, we have performed experimentation with a large number of virtual machines using traces from the PlanetLab workloads. The results show that the NVMC approach outperforms other well-known approaches by achieving a significant improvement in energy consumption, SLA violations, and number of VM migrations.