26,643 research outputs found
Reporting an Experience on Design and Implementation of e-Health Systems on Azure Cloud
Electronic Health (e-Health) technology has brought the world with
significant transformation from traditional paper-based medical practice to
Information and Communication Technologies (ICT)-based systems for automatic
management (storage, processing, and archiving) of information. Traditionally
e-Health systems have been designed to operate within stovepipes on dedicated
networks, physical computers, and locally managed software platforms that make
it susceptible to many serious limitations including: 1) lack of on-demand
scalability during critical situations; 2) high administrative overheads and
costs; and 3) in-efficient resource utilization and energy consumption due to
lack of automation. In this paper, we present an approach to migrate the ICT
systems in the e-Health sector from traditional in-house Client/Server (C/S)
architecture to the virtualised cloud computing environment. To this end, we
developed two cloud-based e-Health applications (Medical Practice Management
System and Telemedicine Practice System) for demonstrating how cloud services
can be leveraged for developing and deploying such applications. The Windows
Azure cloud computing platform is selected as an example public cloud platform
for our study. We conducted several performance evaluation experiments to
understand the Quality Service (QoS) tradeoffs of our applications under
variable workload on Azure.Comment: Submitted to third IEEE International Conference on Cloud and Green
Computing (CGC 2013
Review of the environmental and organisational implications of cloud computing: final report.
Cloud computing – where elastic computing resources are delivered over the Internet by external service providers – is generating significant interest within HE and FE. In the cloud computing business model, organisations or individuals contract with a cloud computing service provider on a pay-per-use basis to access data centres, application software or web services from any location. This provides an elasticity of provision which the customer can scale up or down to meet demand. This form of utility computing potentially opens up a new paradigm in the provision of IT to support administrative and educational functions within HE and FE. Further, the economies of scale and increasingly energy efficient data centre technologies which underpin cloud services means that cloud solutions may also have a positive impact on carbon footprints. In response to the growing interest in cloud computing within UK HE and FE, JISC commissioned the University of Strathclyde to undertake a Review of the Environmental and Organisational Implications of Cloud Computing in Higher and Further Education [19]
Evaluating load balancing policies for performance and energy-efficiency
Nowadays, more and more increasingly hard computations are performed in
challenging fields like weather forecasting, oil and gas exploration, and
cryptanalysis. Many of such computations can be implemented using a computer
cluster with a large number of servers. Incoming computation requests are then,
via a so-called load balancing policy, distributed over the servers to ensure
optimal performance. Additionally, being able to switch-off some servers during
low period of workload, gives potential to reduced energy consumption.
Therefore, load balancing forms, albeit indirectly, a trade-off between
performance and energy consumption. In this paper, we introduce a syntax for
load-balancing policies to dynamically select a server for each request based
on relevant criteria, including the number of jobs queued in servers, power
states of servers, and transition delays between power states of servers. To
evaluate many policies, we implement two load balancers in: (i) iDSL, a
language and tool-chain for evaluating service-oriented systems, and (ii) a
simulation framework in AnyLogic. Both implementations are successfully
validated by comparison of the results.Comment: In Proceedings QAPL'16, arXiv:1610.0769
Introducing mobile edge computing capabilities through distributed 5G Cloud Enabled Small Cells
Current trends in broadband mobile networks are addressed towards the placement of different capabilities at the edge of the mobile network in a centralised way. On one hand, the split of the eNB between baseband processing units and remote radio headers makes it possible to process some of the protocols in centralised premises, likely with virtualised resources. On the other hand, mobile edge computing makes use of processing and storage capabilities close to the air interface in order to deploy optimised services with minimum delay. The confluence of both trends is a hot topic in the definition of future 5G networks. The full centralisation of both technologies in cloud data centres imposes stringent requirements to the fronthaul connections in terms of throughput and latency. Therefore, all those cells with limited network access would not be able to offer these types of services. This paper proposes a solution for these cases, based on the placement of processing and storage capabilities close to the remote units, which is especially well suited for the deployment of clusters of small cells. The proposed cloud-enabled small cells include a highly efficient microserver with a limited set of virtualised resources offered to the cluster of small cells. As a result, a light data centre is created and commonly used for deploying centralised eNB and mobile edge computing functionalities. The paper covers the proposed architecture, with special focus on the integration of both aspects, and possible scenarios of application.Peer ReviewedPostprint (author's final draft
Status Report of the DPHEP Study Group: Towards a Global Effort for Sustainable Data Preservation in High Energy Physics
Data from high-energy physics (HEP) experiments are collected with
significant financial and human effort and are mostly unique. An
inter-experimental study group on HEP data preservation and long-term analysis
was convened as a panel of the International Committee for Future Accelerators
(ICFA). The group was formed by large collider-based experiments and
investigated the technical and organisational aspects of HEP data preservation.
An intermediate report was released in November 2009 addressing the general
issues of data preservation in HEP. This paper includes and extends the
intermediate report. It provides an analysis of the research case for data
preservation and a detailed description of the various projects at experiment,
laboratory and international levels. In addition, the paper provides a concrete
proposal for an international organisation in charge of the data management and
policies in high-energy physics
Energy Efficient Cloud Networks
Cloud computing is expected to be a major factor that will dominate the future Internet service model. This paper summarizes our work on energy efficiency for cloud networks. We develop a framework for studying the energy efficiency of four cloud services in IP over WDM networks: cloud content delivery, storage as a service (StaaS), and virtual machines (VMS) placement for processing applications and infrastructure as a service (IaaS).Our approach is based on the co-optimization of both external network related factors such as whether to geographically centralize or distribute the clouds, the influence of users’ demand distribution, content popularity, access frequency and renewable energy availability and internal capability factors such as the number of servers, switches and routers as well as the amount of storage demanded in each cloud. Our investigation of the different energy efficient approaches is backed with Mixed Integer Linear Programming (MILP) models and real time heuristic
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