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.

Context-Aware Adaptive Services: The PLASTIC Approach

Abstract: The near future envisions a pervasive heterogeneous computing infrastructure that makes it possible for mobile users to run software services on a variety of devices, from networks of devices to stand-alone wireless resource-constrained ones. To ensure that users meet their non-functional requirements by experiencing the best Quality of Service according to their needs and specific contexts of use, services need to be context-aware and adaptable. The development and the execution of such services is a big challenge and it is far to be solved. In this paper we present our experience in this direction by describing our approach to context-aware adaptive services within the IST PLASTIC project. The approach makes use of Chameleon , a formal framework for adaptive Java applications.

Cloud Computing: Overview & Current Research Challenges

Abstract: Cloud computing is a set of IT services that are provided to a customer over a network on a leased basis and with the ability to scale up or down their service requirements. Usually Cloud Computing services are delivered by a third party provider who owns the infrastructure.Cloud Computing holds the potential to eliminate the requirements for setting up of high-cost computing infrastructure for IT-based solutions and services that theindustry uses. It promises to provide a flexible IT architecture, accessible through internet from lightweight portable devices.This would allow multi-fold increase in the capacity and capabilities of the existing and new software.This new economic model for computing has found fertile ground and is attracting massive global investment. Many industries, such as banking, healthcare and education are moving towards the cloud due to the efficiency of services provided by the pay-per-use pattern based on the resources such as processing power used, transactions carried out, bandwidth consumed, data transferred, or storage space occupied etc.In a cloud computing environment, the entire data resides over a set of networked resources, enabling the data to be accessed through virtual machines. Despite the potential gains achieved from the cloud computing, the organizations are slow in accepting it due to security issues and challenges associated with it. Security is one of the major issues which hamper the growth of cloud. There are various research challenges also there for adopting cloud computing such as well managed service level agreement (SLA), privacy, interoperability and reliability.This research paper presents what cloud computing is, the various cloud models and the overview of the cloud computing architecture. This research paper also analyzes the key research challenges present in cloud computing and offers best practices to service providers as well as enterprises hoping to leverage cloud service to improve their bottom line in this severe economic climate.

PAPSO: A Power-Aware VM Placement Technique Based on Particle Swarm Optimization

Abstract: With the widespread usage of cloud computing to benefit from its services, cloud service providers have invested in constructing large scale data centers. Consequently, a tremendous increase in energy consumption has arisen in conjunction with its results, including a remarkable rise in costs of operating and cooling servers. Besides, increasing energy consumption has a significant impact on the environment due to emissions of carbon dioxide. Dynamic consolidation of Virtual Machines (VMs) into the minimal number of Physical Machines (PMs) is considered as one of the magic solutions to manage power consumption. The virtual machine placement problem is a critical issue for good VM consolidation. This paper proposes a Power-Aware technique depending on Particle Swarm Optimization (PAPSO) to determine the near-optimal placement for the migrated VMs. A discrete version of Particle Swarm Optimization (PSO) is adopted based on a decimal encoding to map the migrated VMs to the best appropriate PMs. Furthermore, an effective minimization fitness function is employed to reduce power consumption without violating the Service Level Agreement (SLA). Specifically, PAPSO consolidates the migrated VMs into the minimum number of PMs with a major constraint to decrease the number of overloaded hosts as much as possible. Therefore, the number of VM migrations can be reduced drastically by taking into consideration the main sources for VM migrations; overloaded hosts and underloaded ones. PAPSO is implemented in CloudSim and the experimental results on random workloads with different sizes of VMs and PMs show that PAPSO does not violate SLA and outperforms the Power-Aware Best Fit Decreasing algorithm (PABFD). It can reduce about 8.01%, 39.65%, 66.33%, and 11.87% on average in terms of consumed energy, number of VM migrations, number of host shutdowns and the combined metric Energy SLA Violation (ESV), respectively.

Monitoring WS-Agreement s: An Event Calculus–Based Approach

Abstract: In this chapter, we present a framework that we have developed to support the monitoring of service level agreements (SLAs). The agreements that can be monitored by this framework are expressed in an extension of WS-Agreement that we propose. The main characteristic of the proposed extension is that it uses an event calculus–based language, called EC-Assertion, for the specification of the service guarantee terms in a service level agreement that need to be monitored at runtime. The use of EC-Assertion for specifying service guarantee terms provides a well-defined semantics to the specification of such terms and a formal reasoning framework for assessing their satisfiability. The chapter describes also an implementation of the framework and the results of a set of experiments that we have conducted to evaluate it.