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

An Adaptive Mediation Framework for Workflow Management in the Internet of Things

Tärkavad värkvõrksüsteemid koosnevad arvukast hulgast heterogeensetest füüsilistest seadmetest, mis ühenduvad Internetiga. Need seadmed suudavad pidevalt ümbritseva keskkonnaga suhelda ja osana lõppkasutaja rakendusestest edendada valdkondi nagu tark kodu, e-tervis, logistika jne. Selleks, et integreerida füüsilisi seadmeid värkvõrgu haldussüssteemidega, on töövoo haldussüsteemid kerkinud esile sobiva lahendusena. Ent töövoo haldussüsteemide rakendamine värkvõrku toob kaasa reaalajas teenuste komponeerimise väljakutseid nagu pidev teenusavastus ja -käivitus. Lisaks kerkib küsimus, kuidas piiratud resurssidega värkvõrgu seadmeid töövoo haldussüsteemidega integreerida ning kuidas töövooge värkvõrgu seadmetel käivitada. Tööülesanded (nagu pidev seadmeavastus) võivad värkvõrgus osalevatele piiratud arvutusjõudluse ja akukestvusega seadmetele nagu nutitelefonid koormavaks osutuda. Siinkohal on võimalikuks lahenduseks töö delegeerimine pilve. Käesolev magistritöö esitleb kontekstipõhist raamistikku tööülesannete vahendamiseks värkvõrgurakendustes. Antud raamistikus modelleeritakse ning käitatakse tööülesandeid kasutades töövoogusid. Raamistiku prototüübiga läbi viidud uurimus näitas, et raamistik on võimeline tuvastama, millal seadme avastusülesannete pilve delegeerimine on kuluefektiivsem. Vahel aga pole töövoo käitamistarkvara paigaldamine värkvõrgu seadmetele soovitav, arvestades energiasäästlikkust ning käituskiirust. Käesolev töö võrdles kaht tüüpi töövookäitust: a) töövoo mudeli käitamine käitusmootoriga ning b) töövoo mudelist tõlgitud programmikoodi käitamine. Lähtudes katsetest päris seadmetega, võrreldi nimetatud kahte meetodit silmas pidades süsteemiressursside- ning energiakasutust.Emerging Internet of Things (IoT) systems consist of great numbers of heterogeneous physical entities that are interconnected via the Internet. These devices can continuously interact with the surrounding environment and be used for user applications that benefit human life in domains such as assisted living, e-health, transportation etc. In order to integrate the frontend physical things with IoT management systems, Workflow Management Systems (WfMS) have gained attention as a viable option. However, applying WfMS in IoT faces real-time service composition challenges such as continuous service discovery and invocation. Another question is how to integrate resource-contained IoT devices with the WfMS and execute workflows on the IoT devices. Tasks such as continuous device discovery can be taxing for IoT-involved devices with limited processing power and battery life such as smartphones. In order to overcome this, some tasks can be delegated to a utility Cloud instance. This thesis proposes a context-based framework for task mediation in Internet of Things applications. In the framework, tasks are modelled and executed as workflows. A case study carried out with a prototype of the framework showed that the proposed framework is able to decide when it is more cost-efficient to delegate discovery tasks to the cloud. However, sometimes embedding a workflow engine in an IoT device is not beneficial considering agility and energy conservation. This thesis compared two types of workflow execution: a) execution of workflow models using an embedded workflow engine and b) execution of program code translations based on the workflow models. Based on experiments with real devices, the two methods were compared in terms of system resource and energy usage

Bootstrapping provisioning engines for on-demand provisioning in cloud environments

The assumption that services should run continuously is no longer reasonable in science oriented environments, where dynamic working approaches lead to fluctuating service utilization. Making services available on-demand would be better suited in those situations. For on-demand provisioning of services in cloud environments, suitable provisioning engines have to be set up first. This diploma thesis presents the design for a 2-tiered bootware component that deploys provisioning engines into remote environments that can then be used to provision services on-demand. The bootware can be called by other components via a web service interface and supports multiple provisioning engines and cloud environment via plugins. The integration of the bootware into the SimTech SWfMS with an Eclipse plugin is also described, the bootware however is designed to be generic and can be used together with other systems

Software Defined Application Delivery Networking

In this thesis we present the architecture, design, and prototype implementation details of AppFabric. AppFabric is a next generation application delivery platform for easily creating, managing and controlling massively distributed and very dynamic application deployments that may span multiple datacenters. Over the last few years, the need for more flexibility, finer control, and automatic management of large (and messy) datacenters has stimulated technologies for virtualizing the infrastructure components and placing them under software-based management and control; generically called Software-defined Infrastructure (SDI). However, current applications are not designed to leverage this dynamism and flexibility offered by SDI and they mostly depend on a mix of different techniques including manual configuration, specialized appliances (middleboxes), and (mostly) proprietary middleware solutions together with a team of extremely conscientious and talented system engineers to get their applications deployed and running. AppFabric, 1) automates the whole control and management stack of application deployment and delivery, 2) allows application architects to define logical workflows consisting of application servers, message-level middleboxes, packet-level middleboxes and network services (both, local and wide-area) composed over application-level routing policies, and 3) provides the abstraction of an application cloud that allows the application to dynamically (and automatically) expand and shrink its distributed footprint across multiple geographically distributed datacenters operated by different cloud providers. The architecture consists of a hierarchical control plane system called Lighthouse and a fully distributed data plane design (with no special hardware components such as service orchestrators, load balancers, message brokers, etc.) called OpenADN . The current implementation (under active development) consists of ~10000 lines of python and C code. AppFabric will allow applications to fully leverage the opportunities provided by modern virtualized Software-Defined Infrastructures. It will serve as the platform for deploying massively distributed, and extremely dynamic next generation application use-cases, including: Internet-of-Things/Cyber-Physical Systems: Through support for managing distributed gather-aggregate topologies common to most Internet-of-Things(IoT) and Cyber-Physical Systems(CPS) use-cases. By their very nature, IoT and CPS use cases are massively distributed and have different levels of computation and storage requirements at different locations. Also, they have variable latency requirements for their different distributed sites. Some services, such as device controllers, in an Iot/CPS application workflow may need to gather, process and forward data under near-real time constraints and hence need to be as close to the device as possible. Other services may need more computation to process aggregated data to drive long term business intelligence functions. AppFabric has been designed to provide support for such very dynamic, highly diversified and massively distributed application use-cases. Network Function Virtualization: Through support for heterogeneous workflows, application-aware networking, and network-aware application deployments, AppFabric will enable new partnerships between Application Service Providers (ASPs) and Network Service Providers (NSPs). An application workflow in AppFabric may comprise of application services, packet and message-level middleboxes, and network transport services chained together over an application-level routing substrate. The Application-level routing substrate allows policy-based service chaining where the application may specify policies for routing their application traffic over different services based on application-level content or context. Virtual worlds/multiplayer games: Through support for creating, managing and controlling dynamic and distributed application clouds needed by these applications. AppFabric allows the application to easily specify policies to dynamically grow and shrink the application\u27s footprint over different geographical sites, on-demand. Mobile Apps: Through support for extremely diversified and very dynamic application contexts typical of such applications. Also, AppFabric provides support for automatically managing massively distributed service deployment and controlling application traffic based on application-level policies. This allows mobile applications to provide the best Quality-of-Experience to its users without This thesis is the first to handle and provide a complete solution for such a complex and relevant architectural problem that is expected to touch each of our lives by enabling exciting new application use-cases that are not possible today. Also, AppFabric is a non-proprietary platform that is expected to spawn lots of innovations both in the design of the platform itself and the features it provides to applications. AppFabric still needs many iterations, both in terms of design and implementation maturity. This thesis is not the end of journey for AppFabric but rather just the beginning

Bringing pervasive embedded networks to the service cloud: a lightweight middleware approach

The emergence of novel pervasive networks that consist of tiny embedded nodes have reduced the gap between real and virtual worlds. This paradigm has opened the Service Cloud to a variety of wireless devices especially those with sensorial and actuating capabilities. Those pervasive networks contribute to build new context-aware applications that interpret the state of the physical world at real-time. However, traditional Service-Oriented Architectures (SOA), which are widely used in the current Internet are unsuitable for such resource-constraint devices since they are too heavy. In this research paper, an internetworking approach is proposed in order to address that important issue. The main part of our proposal is the Knowledge-Aware and Service-Oriented (KASO) Middleware that has been designed for pervasive embedded networks. KASO Middleware implements a diversity of mechanisms, services and protocols which enable developers and business processing designers to deploy, expose, discover, compose, and orchestrate real-world services (i.e. services running on sensor/actuator devices). Moreover, KASO Middleware implements endpoints to offer those services to the Cloud in a REST manner. Our internetworking approach has been validated through a real healthcare telemonitoring system deployed in a sanatorium. The validation tests show that KASO Middleware successfully brings pervasive embedded networks to the Service Cloud

Software Platforms for Smart Cities: Concepts, Requirements, Challenges, and a Unified Reference Architecture

Making cities smarter help improve city services and increase citizens' quality of life. Information and communication technologies (ICT) are fundamental for progressing towards smarter city environments. Smart City software platforms potentially support the development and integration of Smart City applications. However, the ICT community must overcome current significant technological and scientific challenges before these platforms can be widely used. This paper surveys the state-of-the-art in software platforms for Smart Cities. We analyzed 23 projects with respect to the most used enabling technologies, as well as functional and non-functional requirements, classifying them into four categories: Cyber-Physical Systems, Internet of Things, Big Data, and Cloud Computing. Based on these results, we derived a reference architecture to guide the development of next-generation software platforms for Smart Cities. Finally, we enumerated the most frequently cited open research challenges, and discussed future opportunities. This survey gives important references for helping application developers, city managers, system operators, end-users, and Smart City researchers to make project, investment, and research decisions.Comment: Accepted for publication in ACM Computing Survey

Survey and Analysis of Production Distributed Computing Infrastructures

This report has two objectives. First, we describe a set of the production distributed infrastructures currently available, so that the reader has a basic understanding of them. This includes explaining why each infrastructure was created and made available and how it has succeeded and failed. The set is not complete, but we believe it is representative. Second, we describe the infrastructures in terms of their use, which is a combination of how they were designed to be used and how users have found ways to use them. Applications are often designed and created with specific infrastructures in mind, with both an appreciation of the existing capabilities provided by those infrastructures and an anticipation of their future capabilities. Here, the infrastructures we discuss were often designed and created with specific applications in mind, or at least specific types of applications. The reader should understand how the interplay between the infrastructure providers and the users leads to such usages, which we call usage modalities. These usage modalities are really abstractions that exist between the infrastructures and the applications; they influence the infrastructures by representing the applications, and they influence the ap- plications by representing the infrastructures