Grid service discovery with rough sets

Copyright [2008] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.The computational grid is evolving as a service-oriented computing infrastructure that facilitates resource sharing and large-scale problem solving over the Internet. Service discovery becomes an issue of vital importance in utilising grid facilities. This paper presents ROSSE, a Rough sets based search engine for grid service discovery. Building on Rough sets theory, ROSSE is novel in its capability to deal with uncertainty of properties when matching services. In this way, ROSSE can discover the services that are most relevant to a service query from a functional point of view. Since functionally matched services may have distinct non-functional properties related to Quality of Service (QoS), ROSSE introduces a QoS model to further filter matched services with their QoS values to maximise user satisfaction in service discovery. ROSSE is evaluated in terms of its accuracy and efficiency in discovery of computing services

Flexible provisioning of Web service workflows

Web services promise to revolutionise the way computational resources and business processes are offered and invoked in open, distributed systems, such as the Internet. These services are described using machine-readable meta-data, which enables consumer applications to automatically discover and provision suitable services for their workflows at run-time. However, current approaches have typically assumed service descriptions are accurate and deterministic, and so have neglected to account for the fact that services in these open systems are inherently unreliable and uncertain. Specifically, network failures, software bugs and competition for services may regularly lead to execution delays or even service failures. To address this problem, the process of provisioning services needs to be performed in a more flexible manner than has so far been considered, in order to proactively deal with failures and to recover workflows that have partially failed. To this end, we devise and present a heuristic strategy that varies the provisioning of services according to their predicted performance. Using simulation, we then benchmark our algorithm and show that it leads to a 700% improvement in average utility, while successfully completing up to eight times as many workflows as approaches that do not consider service failures

Can a web-based community of practice be established and operated to lead falls prevention activity in residential care?

The aims of this study were to evaluate establishing and operating a web-based community of practice (CoP) to lead falls prevention in a residential aged care (RAC) setting. A mixed methods evaluation was conducted in two phases using a survey and transcripts from interactive electronic sources. Nurses and allied health staff (n = 20) with an interest in falls prevention representing 13 sites of an RAC organization participated. In Phase 1, the CoP was developed, and the establishment of its structure and composition was evaluated using determinants of success reported in the literature. In Phase 2, all participants interacted using the web, but frequency of engagement by any participant was low. Participatory barriers, including competing demands from other tasks and low levels of knowledge about information communication technology (ICT) applications, were identified by CoP members. A web-based CoP can be established and operated across multiple RAC sites if RAC management support dedicated time for web-based participation and staff are given web-based training

Context Aware Computing for The Internet of Things: A Survey

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201

Systems Practice: How to Act in a Climate-Change World

It is now accepted that humans are changing the climate of the Earth and this is the most compelling amongst a long litany of reasons as to why, collectively, we have to change our ways of thinking and acting. Most people now recognise that we have to be capable of adapting quickly as new and uncertain circumstances emerge: this capability will need to exist at personal, group, community, regional, national and international levels, all at the same time. Systems Practice is structured into four parts. Part I introduces the societal need to move towards a more systemic and adaptive governance against the backdrop of human-induced climate change. Part II unpacks what is involved in systems practice by means of a juggler metaphor; examining situations where systems thinking offers useful understanding and opportunities for change. Part III identifies the main factors that constrain the uptake of systems practice and makes the case for innovation in practice by means of systemic inquiry, systemic action research and systemic intervention. The book concludes with Part IV, which critically examines how systems practice is, or might be, utilised at different levels from the personal to the societal. The development of our capabilities to think and act systemically is an urgent priority and Systems Practice aims to show how to do systems thinking and translate that thinking into praxis (theory informed practical action) which will be welcomed by those managing in situations of complexity and uncertainty across all domains of professional and personal concern