Generic Methods for Adaptive Management of Service Level Agreements in Cloud Computing

The adoption of cloud computing to build and deliver application services has been nothing less than phenomenal. Service oriented systems are being built using disparate sources composed of web services, replicable datastores, messaging, monitoring and analytics functions and more. Clouds augment these systems with advanced features such as high availability, customer affinity and autoscaling on a fair pay-per-use cost model. The challenge lies in using the utility paradigm of cloud beyond its current exploit. Major trends show that multi-domain synergies are creating added-value service propositions. This raises two questions on autonomic behaviors, which are specifically ad- dressed by this thesis. The first question deals with mechanism design that brings the customer and provider(s) together in the procurement process. The purpose is that considering customer requirements for quality of service and other non functional properties, service dependencies need to be efficiently resolved and legally stipulated. The second question deals with effective management of cloud infrastructures such that commitments to customers are fulfilled and the infrastructure is optimally operated in accordance with provider policies. This thesis finds motivation in Service Level Agreements (SLAs) to answer these questions. The role of SLAs is explored as instruments to build and maintain trust in an economy where services are increasingly interdependent. The thesis takes a wholesome approach and develops generic methods to automate SLA lifecycle management, by identifying and solving relevant research problems. The methods afford adaptiveness in changing business landscape and can be localized through policy based controls. A thematic vision that emerges from this work is that business models, services and the delivery technology are in- dependent concepts that can be finely knitted together by SLAs. Experimental evaluations support the message of this thesis, that exploiting SLAs as foundations for market innovation and infrastructure governance indeed holds win-win opportunities for both cloud customers and cloud providers

Microservices-based IoT Applications Scheduling in Edge and Fog Computing: A Taxonomy and Future Directions

Edge and Fog computing paradigms utilise distributed, heterogeneous and resource-constrained devices at the edge of the network for efficient deployment of latency-critical and bandwidth-hungry IoT application services. Moreover, MicroService Architecture (MSA) is increasingly adopted to keep up with the rapid development and deployment needs of the fast-evolving IoT applications. Due to the fine-grained modularity of the microservices along with their independently deployable and scalable nature, MSA exhibits great potential in harnessing both Fog and Cloud resources to meet diverse QoS requirements of the IoT application services, thus giving rise to novel paradigms like Osmotic computing. However, efficient and scalable scheduling algorithms are required to utilise the said characteristics of the MSA while overcoming novel challenges introduced by the architecture. To this end, we present a comprehensive taxonomy of recent literature on microservices-based IoT applications scheduling in Edge and Fog computing environments. Furthermore, we organise multiple taxonomies to capture the main aspects of the scheduling problem, analyse and classify related works, identify research gaps within each category, and discuss future research directions.Comment: 35 pages, 10 figures, submitted to ACM Computing Survey

Neural Adaptive Admission Control Framework: SLA-driven action termination for real-time application service management

Although most modern cloud-based enterprise systems, or operating systems, do not commonly allow configurable/automatic termination of processes, tasks or actions, it is common practice for systems administrators to manually terminate, or stop, tasks or actions at any level of the system. The paper investigates the potential of automatic adaptive control with action termination as a method for adapting the system to more appropriate conditions in environments with established goals for both system’s performance and economics. A machine-learning driven control mechanism, employing neural networks, is derived and applied within data-intensive systems. Control policies that have been designed following this approach are evaluated under different load patterns and service level requirements. The experimental results demonstrate performance characteristics and benefits as well as implications of termination control when applied to different action types with distinct run-time characteristics. An automatic termination approach may be eminently suitable for systems with harsh execution time Service Level Agreements, or systems running under conditions of hard pressure on power supply or other constraints. The proposed control mechanisms can be combined with other available toolkits to support deployment of autonomous controllers in high-dimensional enterprise information systems

Predicting Wireless sensor readings with Neural network

Wireless sensor networks are becoming a part of our daily lives, as they act as a bridge between the physical world and the virtual world.One of the problems encountered by this type of networks while trying to fulfill their goals is the rate of energy consumption. The approach considered in this paper was that of an artificial neural network with the aim of reducing the rate of power consumption and thereby increasing the performance and durability of the network. Support vector machines backed artificial neural model was the best of all models picked. It was then compared with a linear regression model to see if there would be any good reasons to migrate to the this new approach. At the end, it was observed that the chosen network performed slightly above the level of the existing model. The implications of the observed results were that another form of prediction model can replace the existing one or alternated with one another in the process of operation of a wireless sensor network.Juhtmevabadest sensorvõrkudest on saamas osa meie igapäevalust. Tegemist on sillaga füüsilise ja virtuaalse maailma vahel. Üheks probleemiks seda laadi võrkude puhul on aga energia tarbimise määr. Käesolevas lõputöös uuriti lähenemist, kus kasutatakse tehisneurovõrke eesmärgiga vähendada energiatarvet ja seeläbi parendada sensorvõrgu efektiivsust ning vastupidavust. Tugivektormasinatega toetatud tehisneuromudel valiti välja kui parim vaatluse all olnud mudel. Seda mudelit võrreldi lineaarse regressiooni mudeliga, et näha kas väljavalitud mudeli puhul leidub mõjuvaid põhjuseid just seda eelistada. Lõpuks selgitati välja, et uuritava mudeli efektiivsus oli veidi kõrgem kui võrreldaval mudelil. Töö tulemustest järeldub, et olemasolevaid ennustusmudeleid võib asendada alternatiivsetega või kasutada neid vaheldumisi juhtmevaba sensorvõrgu töö käigus

SLA-Driven Cloud Computing Domain Representation and Management

The assurance of Quality of Service (QoS) to the applications, although identified as a key feature since long ago [1], is one of the fundamental challenges that remain unsolved. In the Cloud Computing context, Quality of Service is defined as the measure of the compliance of certain user requirement in the delivery of a cloud resource, such as CPU or memory load for a virtual machine, or more abstract and higher level concepts such as response time or availability. Several research groups, both from academia and industry, have started working on describing the QoS levels that define the conditions under which the service need to be delivered, as well as on developing the necessary means to effectively manage and evaluate the state of these conditions. [2] propose Service Level Agreements (SLAs) as the vehicle for the definition of QoS guarantees, and the provision and management of resources. A Service Level Agreement (SLA) is a formal contract between providers and consumers, which defines the quality of service, the obligations and the guarantees in the delivery of a specific good. In the context of Cloud computing, SLAs are considered to be machine readable documents, which are automatically managed by the provider's platform. SLAs need to be dynamically adapted to the variable conditions of resources and applications. In a multilayer architecture, different parts of an SLA may refer to different resources. SLAs may therefore express complex relationship between entities in a changing environment, and be applied to resource selection to implement intelligent scheduling algorithms. Therefore SLAs are widely regarded as a key feature for the future development of Cloud platforms. However, the application of SLAs for Grid and Cloud systems has many open research lines. One of these challenges, the modeling of the landscape, lies at the core of the objectives of the Ph. D. Thesis.García García, A. (2014). SLA-Driven Cloud Computing Domain Representation and Management [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/36579TESI