Kleopatra Konstanteli

Platform-as-a-Service Architecture for Real-Time Quality of Service Management in Clouds

Cloud computing offers the potential to dramatically reduce the cost of software services through the commoditization of information technology assets and on-demand usage patterns. However, the complexity of determining resource provision policies for applications in such complex environments introduces significant inefficiencies and has driven the emergence of a new class of infrastructure called Platform-as-a-Service (PaaS). In this paper, we present a novel PaaS architecture being developed in the EU IST IRMOS project targeting real-time Quality of Service (QoS) guarantees for online interactive multimedia applications. The architecture considers the full service lifecycle including service engineering, service level agreement design, provisioning and monitoring. QoS parameters at both application and infrastructure levels are given specific attention as the basis for provisioning policies in the context of temporal constraints. The generic applicability of the architecture is being verified and validated through implemented scenarios from three important application sectors (film post-production, virtual augmented reality for engineering design, collaborative e-Learning in virtual worlds).

Admission Control for Elastic Cloud Services

This paper presents an admission control test for deciding whether or not it is worth to admit a set of services into a Cloud, and in case of acceptance, obtain the optimum allocation for each of the components that comprise the services. In the proposed model, the focus is on hosting elastic services the resource requirements of which may dynamically grow and shrink, depending on the dynamically varying number of users and patterns of requests. In finding the optimum allocation, the presented admission control test uses an optimization model, which incorporates business rules in terms of trust, eco-efficiency and cost, and also takes into account affinity rules the components that comprise the service may have. The problem is modeled on the General Algebraic Modeling System (GAMS) and solved under realistic providers settings that demonstrate the efficiency of the proposed method.

Elastic Admission Control for Federated Cloud Services

This paper presents a technique for admission control of a set of horizontally scalable services, and their optimal placement, into a federated Cloud environment. In the proposed model, the focus is on hosting elastic services whose resource requirements may dynamically grow and shrink, depending on the dynamically varying number of users and patterns of requests. The request may also be partially accommodated in federated external providers, if needed or more convenient. In finding the optimum allocation, the presented mechanism uses a probabilistic optimization model, which takes into account eco-efficiency and cost, as well as affinity and anti-affinity rules possibly in place for the components that comprise the services. In addition to modelling and solving the exact optimization problem, we also introduce a heuristic solver that exhibits a reduced complexity and solving time. We show evaluation results for the proposed technique under various scenarios.

Managing service level agreement contracts in OGSA-based Grids

Grids and mobile Grids can form the basis and the enabling technology for pervasive and utility computing due to their ability to be open, highly heterogeneous and scalable. However, the process of selecting the appropriate resources and initiating the execution of a job is not enough to provide quality in a dynamic environment such as a mobile Grid, where changes are numerous, highly variable and with unpredictable effects. In this paper we present a scheme for advancing and managing Quality of Service (QoS) attributes contained in Service Level Agreement (SLA) contracts of Grids that follow the Open Grid Services Architecture (OGSA). In order to achieve this, the execution environment of the Grid infrastructure establishes and exploits the synergies between the various modules of the architecture that participate in the management of the execution and the enforcement of the SLA contractual terms. We introduce an Execution Management Service which is in collaboration with both the application services and the network services in order to provide an adjustable quality of the requested services. The components that manage and control the execution in the Grid environment interact with the suit of the SLA-related services exchanging information that is used to provide the quality framework of the execution with respect to the agreed contractual terms. The described scheme has been implemented in the framework of the Akogrimo IST project.

Workflow management for soft real-time interactive applications in virtualized environments

Many applications, especially the ones implementing multi-user collaborative environments, fall within the context of soft real-time systems in which only small deviations from timing constraints are allowed. The advancements in distributed computing have made it possible to follow a service oriented approach, taking advantage of the benefits this provides. In this context, applications consist of soft real-time critical application service components that interact with each other to provide the corresponding application functionality, forming application workflows. In this paper we present a new architectural design and implementation of a Workflow Management approach. This approach covers enacting soft real-time application service components according to a workflow description language, synchronizing the application components, monitoring the execution and reacting to events within a distributed virtualized environment. We also demonstrate the operation of the implemented mechanism and evaluate its effectiveness using an application scenario with soft real-time interactivity characteristics, namely Film post-production, under realistic settings.

A Service-Oriented Framework for GNU Octave-Based Performance Prediction

Cloud/Grid environments are characterized by a diverse set of technologies used for communication, execution and management. Service Providers, in this context, need to be equipped with an automated process in order to optimize service provisioning through advanced performance prediction methods. Furthermore, existing software solutions such as GNU Octave offer a wide range of possibilities for implementing these methods. However, their automated use as services in the distributed computing paradigm includes a number of challenges from a design and implementation point of view. In this paper, a loosely coupled service-oriented implementation is presented, for taking advantage of software like Octave in the process of creating and using prediction models during the service lifecycle of a SOI. In this framework, every method is applied as an Octave script in a plug-in fashion. The design and implementation of the approach is validated through a case study application which involves the transcoding of raw video to MPEG4.

Translation of application-level terms to resource-level attributes across the Cloud stack layers

The emergence of new environments such as Cloud computing highlighted new challenges in traditional fields like performance estimation. Most of the current cloud environments follow the Software, Platform, Infrastructure service model in order to map discrete roles / providers according to the offering in each “layer”. However, the limited amount of information passed from one layer to the other has raised the level of difficulty in translating user-understandable application terms from the Software layer to resource specific attributes, which can be used to manage resources in the Platform and Infrastructure layers. In this paper, a generic black box approach, based on Artificial Neural Networks is used in order to perform the aforementioned translation. The efficiency of the approach is presented and validated through different application scenarios (namely FFMPEG encoding and real-time interactive e-Learning) that highlight its applicability even in cases where accurate performance estimation is critical, as in cloud environments aiming to facilitate real-time and interactivity.

Optimum allocation of distributed service workflows with probabilistic real-time guarantees

This paper addresses the problem of optimum allocation of distributed real-time workflows with probabilistic service guarantees over a set of physical resources. The discussion focuses on how such a problem may be mathematically formalized, in terms of both constraints and objective function to be optimized, which also accounts for possible business rules for regulating the deployment of the workflows. The presented formal problem constitutes a probabilistic admission control test that may be run by a provider in order to decide whether or not it is worth to admit new workflows into the system and to decide what the optimum allocation of the workflow to the available resources is. Various options are presented, which may be plugged into the formal problem description, depending on the specific needs of individual workflows. The presented problem has been implemented using GAMS and has been tested under various solvers. An illustrative numerical example and an analysis of the results of the implemented model under realistic settings are presented.

Virtualised e-Learning on the IRMOS real-time Cloud

This paper presents the real-time virtualised Cloud infrastructure that was developed in the context of the IRMOS European Project. The paper shows how different concepts, such as real-time scheduling, QoS-aware network protocols, and methodologies for stochastic modelling and run-time provisioning were practically combined to provide strong performance guarantees to soft real-time interactive applications in a virtualised environment. The efficiency of the IRMOS Cloud is demonstrated by two real interactive e-Learning applications, an e-Learning mobile content delivery application and a Virtual World e-Learning application.

Real-Time Guarantees in Flexible Advance Reservations

This paper deals with the problem of scheduling workflow applications with Quality of Service (QoS) constraints, comprising real-time and interactivity constraints, over a service-oriented Grid network. A novel approach is proposed, in which high-level Advance Reservations, supporting flexible start and end time, are combined with low-level soft real-time scheduling,allowing for the concurrent deployment of multiple services on the same host while fulfilling their QoS requirements. By undertaking a stochastic approach, in which a-priori knowledge is leveraged about the probability of activation of the application workflows within the reserved time-frame, the proposed methodology allows for the achievement of various trade-offs between the need for respecting QoS constraints (user perspective) and the need for having good resource saturation levels (service provider perspective).