14 resultados para service-oriented computing (SOC)

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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A Web-service based approach is presented which enables geographically dispersed users to share software resources over the Internet. A service-oriented software sharing system has been developed, which consists of shared applications, client applications and three types of services: application proxy service, proxy implementation service and application manager service. With the aids of the services, the client applications interact with the shared applications to implement a software sharing task. The approach satisfies the requirements of copyright protection and reuse of legacy codes. In this paper, the role of Web-services and the architecture of the system are presented first, followed by a case study to illustrate the approach developed.

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This paper tries to achieve a balanced view of the ethical issues raised by emotion-oriented technology as it is, rather than as it might be imagined. A high proportion of applications seem ethically neutral. Uses in entertainment and allied areas do no great harm or good. Empowering professions may do either, but regulatory systems already exist. Ethically positive aspirations involve mitigating problems that already exist by supporting humans in emotion-related judgments, by replacing technology that treats people in dehumanized and/or demeaning ways, and by improving access for groups who struggle with existing interfaces. Emotion-oriented computing may also contribute to revaluing human faculties other than pure intellect. Many potential negatives apply to technology as a whole. Concerns specifically related to emotion involve creating a lie, by simulate emotions that the systems do not have, or promoting mechanistic conceptions of emotion. Intermediate issues arise where more general problems could be exacerbated-helping systems to sway human choices or encouraging humans to choose virtual worlds rather than reality. "SIIF" systems (semi-intelligent information filters) are particularly problematic. These use simplified rules to make judgments about people that are complex, and have potentially serious consequences. The picture is one of balances to recognize and negotiate, not uniform good or evil. © 2010-2012 IEEE.

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This paper focuses on two main areas. We first investigate various aspects of subscription and session Service Level Agreement (SLA) issues such as negotiating and setting up network services with Quality of Service (QoS) and pricing preferences. We then introduce an agent-enhanced service architecture that facilitates these services. A prototype system consisting of real-time agents that represent various network stakeholders was developed. A novel approach is presented where the agent system is allowed to communicate with a simulated network. This allows functional and dynamic behaviour of the network to be investigated under various agent-supported scenarios. This paper also highlights the effects of SLA negotiation and dynamic pricing in a competitive multi-operator networks environment.

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Software-as-a-service (SaaS) is a type of software service delivery model which encompasses a broad range of business opportunities and challenges. Users and service providers are reluctant to integrate their business into SaaS due to its security concerns while at the same time they are attracted by its benefits. This article highlights SaaS utility and applicability in different environments like cloud computing, mobile cloud computing, software defined networking and Internet of things. It then embarks on the analysis of SaaS security challenges spanning across data security, application security and SaaS deployment security. A detailed review of the existing mainstream solutions to tackle the respective security issues mapping into different SaaS security challenges is presented. Finally, possible solutions or techniques which can be applied in tandem are presented for a secure SaaS platform.

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Embedded memories account for a large fraction of the overall silicon area and power consumption in modern SoC(s). While embedded memories are typically realized with SRAM, alternative solutions, such as embedded dynamic memories (eDRAM), can provide higher density and/or reduced power consumption. One major challenge that impedes the widespread adoption of eDRAM is that they require frequent refreshes potentially reducing the availability of the memory in periods of high activity and also consuming significant amount of power due to such frequent refreshes. Reducing the refresh rate while on one hand can reduce the power overhead, if not performed in a timely manner, can cause some cells to lose their content potentially resulting in memory errors. In this paper, we consider extending the refresh period of gain-cell based dynamic memories beyond the worst-case point of failure, assuming that the resulting errors can be tolerated when the use-cases are in the domain of inherently error-resilient applications. For example, we observe that for various data mining applications, a large number of memory failures can be accepted with tolerable imprecision in output quality. In particular, our results indicate that by allowing as many as 177 errors in a 16 kB memory, the maximum loss in output quality is 11%. We use this failure limit to study the impact of relaxing reliability constraints on memory availability and retention power for different technologies.

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How can GPU acceleration be obtained as a service in a cluster? This question has become increasingly significant due to the inefficiency of installing GPUs on all nodes of a cluster. The research reported in this paper is motivated to address the above question by employing rCUDA (remote CUDA), a framework that facilitates Acceleration-as-a-Service (AaaS), such that the nodes of a cluster can request the acceleration of a set of remote GPUs on demand. The rCUDA framework exploits virtualisation and ensures that multiple nodes can share the same GPU. In this paper we test the feasibility of the rCUDA framework on a real-world application employed in the financial risk industry that can benefit from AaaS in the production setting. The results confirm the feasibility of rCUDA and highlight that rCUDA achieves similar performance compared to CUDA, provides consistent results, and more importantly, allows for a single application to benefit from all the GPUs available in the cluster without loosing efficiency.

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Many cloud-based applications employ a data centre as a central server to process data that is generated by edge devices, such as smartphones, tablets and wearables. This model places ever increasing demands on communication and computational infrastructure with inevitable adverse effect on Quality-of-Service and Experience. The concept of Edge Computing is predicated on moving some of this computational load towards the edge of the network to harness computational capabilities that are currently untapped in edge nodes, such as base stations, routers and switches. This position paper considers the challenges and opportunities that arise out of this new direction in the computing landscape.