382 research outputs found

    The Glasgow raspberry pi cloud: a scale model for cloud computing infrastructures

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    Data Centers (DC) used to support Cloud services often consist of tens of thousands of networked machines under a single roof. The significant capital outlay required to replicate such infrastructures constitutes a major obstacle to practical implementation and evaluation of research in this domain. Currently, most research into Cloud computing relies on either limited software simulation, or the use of a testbed environments with a handful of machines. The recent introduction of the Raspberry Pi, a low-cost, low-power single-board computer, has made the construction of a miniature Cloud DCs more affordable. In this paper, we present the Glasgow Raspberry Pi Cloud (PiCloud), a scale model of a DC composed of clusters of Raspberry Pi devices. The PiCloud emulates every layer of a Cloud stack, ranging from resource virtualisation to network behaviour, providing a full-featured Cloud Computing research and educational environment

    Software Defined Application Delivery Networking

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    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

    Small cell cloud proof of concept implementation and monitoring schemes analysis

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    Cloud Computing has grown exponentially in popularity in the last few years, becoming a key technology for both personal and enterprise applications due to the numerous benefits it offers. On the other hand, Small Cell technology is considered by many to be the solution to the challenges that are expected to arise caused by the continuously increasing number of interconnected mobile devices. This project presents a basic design and a proof of concept implementation of a Small Cell Cloud, a current research field on mobile communications that aims to leverage the capabilities offered by the parallel and distributed computation of Cloud Computing to enhance Small Cells functionality. The purpose of the described Small Cell Cloud is to allow application offloading of mobile devices to Small Cells, allowing the execution of more resource demanding applications at the same time energy consumption is reduced in those devices. Furthermore, a detailed analysis on different Small Cell monitoring schemes is carried out, comparing the achieved performance with each of them in terms of data reliability and generated network traffic. Finally, based on the proof of concept implementation and a series of stress performance test, conclusions on the viability of the proposed Small Cell Cloud design and the most appropriate monitoring scheme are presented. Guidelines for future research work are also provided, considering the work developed in this project as a first step towards a new mobile technology.Ingeniería de Telecomunicació

    Towards a Flexible, Lightweight Virtualization Alternative

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    In recent times, two virtualization approaches have become dominant: hardware-level and operating system-level virtualization. They differ by where they draw the virtualization boundary between the virtualizing and the virtualized part of the system, resulting in vastly different properties. We argue that these two approaches are extremes in a continuum, and that boundaries in between the extremes may combine several good properties of both. We propose abstractions to make up one such new virtualization boundary, which combines hardware-level flexibility with OS-level resource sharing. We implement and evaluate a first prototype

    Security Audit Compliance for Cloud Computing

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    Cloud computing has grown largely over the past three years and is widely popular amongst today's IT landscape. In a comparative study between 250 IT decision makers of UK companies they said, that they already use cloud services for 61% of their systems. Cloud vendors promise "infinite scalability and resources" combined with on-demand access from everywhere. This lets cloud users quickly forget, that there is still a real IT infrastructure behind a cloud. Due to virtualization and multi-tenancy the complexity of these infrastructures is even increased compared to traditional data centers, while it is hidden from the user and outside of his control. This makes management of service provisioning, monitoring, backup, disaster recovery and especially security more complicated. Due to this, and a number of severe security incidents at commercial providers in recent years there is a growing lack of trust in cloud infrastructures. This thesis presents research on cloud security challenges and how they can be addressed by cloud security audits. Security requirements of an Infrastructure as a Service (IaaS) cloud are identified and it is shown how they differ from traditional data centres. To address cloud specific security challenges, a new cloud audit criteria catalogue is developed. Subsequently, a novel cloud security audit system gets developed, which provides a flexible audit architecture for frequently changing cloud infrastructures. It is based on lightweight software agents, which monitor key events in a cloud and trigger specific targeted security audits on demand - on a customer and a cloud provider perspective. To enable these concurrent cloud audits, a Cloud Audit Policy Language is developed and integrated into the audit architecture. Furthermore, to address advanced cloud specific security challenges, an anomaly detection system based on machine learning technology is developed. By creating cloud usage profiles, a continuous evaluation of events - customer specific as well as customer overspanning - helps to detect anomalies within an IaaS cloud. The feasibility of the research is presented as a prototype and its functionality is presented in three demonstrations. Results prove, that the developed cloud audit architecture is able to mitigate cloud specific security challenges

    QoS-aware architectures, technologies, and middleware for the cloud continuum

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    The recent trend of moving Cloud Computing capabilities to the Edge of the network is reshaping how applications and their middleware supports are designed, deployed, and operated. This new model envisions a continuum of virtual resources between the traditional cloud and the network edge, which is potentially more suitable to meet the heterogeneous Quality of Service (QoS) requirements of diverse application domains and next-generation applications. Several classes of advanced Internet of Things (IoT) applications, e.g., in the industrial manufacturing domain, are expected to serve a wide range of applications with heterogeneous QoS requirements and call for QoS management systems to guarantee/control performance indicators, even in the presence of real-world factors such as limited bandwidth and concurrent virtual resource utilization. The present dissertation proposes a comprehensive QoS-aware architecture that addresses the challenges of integrating cloud infrastructure with edge nodes in IoT applications. The architecture provides end-to-end QoS support by incorporating several components for managing physical and virtual resources. The proposed architecture features: i) a multilevel middleware for resolving the convergence between Operational Technology (OT) and Information Technology (IT), ii) an end-to-end QoS management approach compliant with the Time-Sensitive Networking (TSN) standard, iii) new approaches for virtualized network environments, such as running TSN-based applications under Ultra-low Latency (ULL) constraints in virtual and 5G environments, and iv) an accelerated and deterministic container overlay network architecture. Additionally, the QoS-aware architecture includes two novel middlewares: i) a middleware that transparently integrates multiple acceleration technologies in heterogeneous Edge contexts and ii) a QoS-aware middleware for Serverless platforms that leverages coordination of various QoS mechanisms and virtualized Function-as-a-Service (FaaS) invocation stack to manage end-to-end QoS metrics. Finally, all architecture components were tested and evaluated by leveraging realistic testbeds, demonstrating the efficacy of the proposed solutions
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