Cloud Workload Prediction by Means of Simulations

Clouds hide the complexity of maintaining a physical infrastructure with a disadvantage: they also hide their internal workings. Should users need to know about these details e.g., to increase the reliability or performance of their applications, they would need to detect slight behavioural changes in the underlying system. Existing solutions for such purposes offer limited capabilities. This paper proposes a technique for predicting background workload by means of simulations that are providing knowledge of the underlying clouds to support activities like cloud orchestration or workflow enactment. We propose these predictions to select more suitable execution environments for scientific workflows. We validate the proposed prediction approach with a biochemical application

An SLA-based resource virtualization approach for on-demand service provision

Cloud computing is a newly emerged research infrastructure that builds on the latest achievements of diverse research areas, such as Grid computing, Service-oriented computing, business processes and virtualization. In this paper we present an architecture for SLA-based resource virtualization that provides an extensive solution for executing user applications in Clouds. This work represents the first attempt to combine SLA-based resource negotiations with virtualized resources in terms of on-demand service provision resulting in a holistic virtualization approach. The architecture description focuses on three topics: agreement negotiation, service brokering and deployment using virtualization. The contribution is also demonstrated with a real-world case study

Flexible Representation of IoT Sensors for Cloud Simulators

In Internet of Things (IoT), sensors, actuators and smart devices are connected to the Internet. Application providers combine this connectivity with novel scenarios involving cloud computing. Some require in depth analysis of the interaction between IoT devices and clouds. Research focuses on questions like how to govern such large cohort of devices (i.e., often over tens of thousands). Distributed systems simulators help in such analysis, but they are problematic to apply in this newly emerging domain. Most simulators are either too detailed (e.g., need extensive knowledge on networking), or not extensible enough to support the new scenarios. This paper introduces our attempt to show how a state of the art simulator could model generic IoT sensors. We show the fundamental properties of IoT entities represented in the simulator. Based on these properties, we present an XML based, declarative modelling language aiming at: (i) describing the behaviour of sensors and their relation to clouds, and (ii) allowing rapid prototyping of simulations. Finally, we validate the applicability of our IoT extensions in five scenarios in the field of weather forecasting

Cost-efficient Datacentre Consolidation for Cloud Federations

Cloud Computing has become mature enough to enable the virtualized management of multiple datacentres. Datacentre consolidation is an important method for the efficient operation of such distributed infrastructures. Several approaches have been developed to improve the efficiency e.g. in terms of power consumption, but only a few attention has been turned to combining pricing methods with consolidation techniques. In this paper we discuss how we introduced cost models to the DISSECT-CF simulator to foster the development of cost efficient datacentre consolidation solutions. We also exemplify the usage of this extended simulator by performing cost-aware datacentre consolidation. We apply real world traces to simulate cloud load, and propose 7 strategies to address the problem

An interoperable and self-adaptive approach for SLA-based service virtualization in heterogeneous Cloud environments

Cloud computing is a newly emerged computing infrastructure that builds on the latest achievements of diverse research areas, such as Grid computing, Service-oriented computing, business process management and virtualization. An important characteristic of Cloud-based services is the provision of non-functional guarantees in the form of Service Level Agreements (SLAs), such as guarantees on execution time or price. However, due to system malfunctions, changing workload conditions, hard- and software failures, established SLAs can be violated. In order to avoid costly SLA violations, flexible and adaptive SLA attainment strategies are needed. In this paper we present a self-manageable architecture for SLA-based service virtualization that provides a way to ease interoperable service executions in a diverse, heterogeneous, distributed and virtualized world of services. We demonstrate in this paper that the combination of negotiation, brokering and deployment using SLA-aware extensions and autonomic computing principles are required for achieving reliable and efficient service operation in distributed environments. © 2012 Elsevier B.V. All rights reserved

Autonomic SLA-Aware service virtualization for distributed systems

Cloud Computing builds on the latest achievements of diverse research areas, such as Grid Computing, Service-oriented computing, business processes and virtualization. Managing such heterogeneous environments requires sophisticated interoperation of adaptive coordinating components. In this paper we introduce an SLA-aware Service Virtualization architecture that provides non-functional guarantees in the form of Service Level Agreements and consists of a three-layered infrastructure including agreement negotiation, service brokering and on demand deployment. In order to avoid costly SLA violations, flexible and adaptive SLA attainment strategies are used with a failure propagation approach. We demonstrate the advantages of our proposed solution with a biochemical case study in a Cloud simulation environment. © 2011 IEEE

STUDY OF THE LEUKOCYTE MIGRATION INHIBITORY FACTOR IN HUMAN GLOMERULONEPHRITIS FROM THE ASPECT OF THE PROGNOSIS

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Facilitating self-adaptable inter-cloud management

Cloud Computing infrastructures have been developed as individual islands, and mostly proprietary solutions so far. However, as more and more infrastructure providers apply the technology, users face the inevitable question of using multiple infrastructures in parallel. Federated cloud management systems offer a simplified use of these infrastructures by hiding their proprietary solutions. As the infrastructure becomes more complex underneath these systems, the situations (like system failures, handling of load peaks and slopes) that users cannot easily handle, occur more and more frequently. Therefore, federations need to manage these situations autonomously without user interactions. This paper introduces a methodology to autonomously operate cloud federations by controlling their behavior with the help of knowledge management systems. Such systems do not only suggest reactive actions to comply with established Service Level Agreements (SLA) between provider and consumer, but they also find a balance between the fulfillment of established SLAs and resource consumption. The paper adopts rule-based techniques as its knowledge management solution and provides an extensible rule set for federated clouds built on top of multiple infrastructures. © 2012 IEEE

LAYSI: A layered approach for SLA-violation propagation in self-manageable cloud infrastructures

Cloud computing represents a promising comput ing paradigm where computing resources have to be allocated to software for their execution. Self-manageable Cloud in frastructures are required to achieve that level of flexibility on one hand, and to comply to users' requirements speci fied by means of Service Level Agreements (SLAs) on the other. Such infrastructures should automatically respond to changing component, workload, and environmental conditions minimizing user interactions with the system and preventing violations of agreed SLAs. However, identification of sources responsible for the possible SLA violation and the decision about the reactive actions necessary to prevent SLA violation is far from trivial. First, in this paper we present a novel approach for mapping low-level resource metrics to SLA parameters necessary for the identification of failure sources. Second, we devise a layered Cloud architecture for the bottom-up propagation of failures to the layer, which can react to sensed SLA violation threats. Moreover, we present a communication model for the propagation of SLA violation threats to the appropriate layer of the Cloud infrastructure, which includes negotiators, brokers, and automatic service deployer. © 2010 IEEE

Enhancing Federated Cloud Management with an Integrated Service Monitoring Approach

Cloud Computing enables the construction and the provisioning of virtualized service-based applications in a simple and cost effective outsourcing to dynamic service environments. Cloud Federations envisage a distributed, heterogeneous environment consisting of various cloud infrastructures by aggregating different IaaS provider capabilities coming from both the commercial and the academic area. In this paper, we introduce a federated cloud management solution that operates the federation through utilizing cloud-brokers for various IaaS providers. In order to enable an enhanced provider selection and inter-cloud service executions, an integrated monitoring approach is proposed which is capable of measuring the availability and reliability of the provisioned services in different providers. To this end, a minimal metric monitoring service has been designed and used together with a service monitoring solution to measure cloud performance. The transparent and cost effective operation on commercial clouds and the capability to simultaneously monitor both private and public clouds were the major design goals of this integrated cloud monitoring approach. Finally, the evaluation of our proposed solution is presented on different private IaaS systems participating in federations. © 2013 Springer Science+Business Media Dordrecht