Autonomous Fault Detection in Self-Healing Systems using Restricted Boltzmann Machines

Autonomously detecting and recovering from faults is one approach for reducing the operational complexity and costs associated with managing computing environments. We present a novel methodology for autonomously generating investigation leads that help identify systems faults, and extends our previous work in this area by leveraging Restricted Boltzmann Machines (RBMs) and contrastive divergence learning to analyse changes in historical feature data. This allows us to heuristically identify the root cause of a fault, and demonstrate an improvement to the state of the art by showing feature data can be predicted heuristically beyond a single instance to include entire sequences of information.Comment: Published and presented in the 11th IEEE International Conference and Workshops on Engineering of Autonomic and Autonomous Systems (EASe 2014

From missions to systems : generating transparently distributable programs for sensor-oriented systems

Early Wireless Sensor Networks aimed simply to collect as much data as possible for as long as possible. While this remains true in selected cases, the majority of future sensor network applications will demand much more intelligent use of their resources as networks increase in scale and support multiple applications and users. Specifically, we argue that a computational model is needed in which the ways that data flows through networks, and the ways in which decisions are made based on that data, is transparently distributable and relocatable as requirements evolve. In this paper we present an approach to achieving this using high-level mission specifications from which we can automatically derive transparently distributable programs.Postprin

Multiplex networks in metropolitan areas: generic features and local effects

Most large cities are spanned by more than one transportation system. These different modes of transport have usually been studied separately: it is however important to understand the impact on urban systems of the coupling between them and we report in this paper an empirical analysis of the coupling between the street network and the subway for the two large metropolitan areas of London and New York. We observe a similar behaviour for network quantities related to quickest paths suggesting the existence of generic mechanisms operating beyond the local peculiarities of the specific cities studied. An analysis of the betweenness centrality distribution shows that the introduction of underground networks operate as a decentralising force creating congestions in places located at the end of underground lines. Also, we find that increasing the speed of subways is not always beneficial and may lead to unwanted uneven spatial distributions of accessibility. In fact, for London -- but not for New York -- there is an optimal subway speed in terms of global congestion. These results show that it is crucial to consider the full, multimodal, multi-layer network aspects of transportation systems in order to understand the behaviour of cities and to avoid possible negative side-effects of urban planning decisions.Comment: 12 pages, 8 figures. Final version with an additional discussion on the total congestio

epyc : computational experiment management in Python

epyc is a Python module for designing, executing, storing, and analysing the results of large sets of (possibly long-running) computational experiments, as are often found when writing simulations of complex networks and other domains. It allows the same experimental code to be run on single machines, multicore machines, and computational clusters without modification, and automatically manages the execution of an experiment for different parameter values and for multiple repetitions.Publisher PDFPeer reviewe

Trajectories of point particles in cosmology and the Zel'dovich approximation

Using a Green's function approach, we compare the trajectories of classical Hamiltonian point particles in an expanding space-time to the effectively inertial trajectories in the Zel'dovich approximation. It is shown that the effective gravitational potential accelerating the particles relative to the Zel'dovich trajectories vanishes exactly initially as a consequence of the continuity equation, and acts only during a short, early period. The Green's function approach suggests an iterative scheme for improving the Zel'dovich trajectories, which can be analytically solved. We construct these trajectories explicitly and show how they interpolate between the Zel'dovich and the exact trajectories. The effective gravitational potential acting on the improved trajectories is substantially smaller at late times than the potential acting on the exact trajectories. The results may be useful for Lagrangian perturbation theory and for numerical simulations.Comment: 7 pages, 3 figure

Detecting abnormal events on binary sensors in smart home environments

With a rising ageing population, smart home technologies have been demonstrated as a promising paradigm to enable technology-driven healthcare delivery. Smart home technologies, composed of advanced sensing, computing, and communication technologies, offer an unprecedented opportunity to keep track of behaviours and activities of the elderly and provide context-aware services that enable the elderly to remain active and independent in their own homes. However, experiments in developed prototypes demonstrate that abnormal sensor events hamper the correct identification of critical (and potentially life-threatening) situations, and that existing learning, estimation, and time-based approaches to situation recognition are inaccurate and inflexible when applied to multiple people sharing a living space. We propose a novel technique, called CLEAN, that integrates the semantics of sensor readings with statistical outlier detection. We evaluate the technique against four real-world datasets across different environments including the datasets with multiple residents. The results have shown that CLEAN can successfully detect sensor anomaly and improve activity recognition accuracies.PostprintPeer reviewe

Open Badges : a best-practice framework

The widespread adoption of online education is severely challenged by issues of verifiability, reliability, security and credibility. Open Badges exist to address these challenges, but there is no consensus as to what constitutes best practices regarding the implementation of an Open Badge system within an educational context. In this paper we survey the current landscape of Open Badges from educational and technological perspectives. We analyze a broad set of openly-reported pilot projects and case studies, and derive a comprehensive best practice framework that tries to capture the requirements for successful implementation within educational institutions. We conclude by identifying some significant gaps in the technology and identify some possible future research directions.Postprin

Self-stabilising target counting in wireless sensor networks using Euler integration

Target counting is an established challenge for sensor networks: given a set of sensors that can count (but not identify) targets, how many targets are there? The problem is complicated because of the need to disambiguate duplicate observations of the same target by different sensors. A number of approaches have been proposed in the literature, and in this paper we take an existing technique based on Euler integration and develop a fully-distributed, self-stabilising solution. We derive our algorithm within the field calculus from the centralised presentation of the underlying integration technique, and analyse the precision of the counting through simulation of several network configurations.Postprin

University-private sector partnerships:assessing long-term collaboration to deliver economic impact in the Northwest of England

Objectives Private and public sector working together for mutual benefit is nothing new and in the context of education, this has historically focussed on areas such as employability-related experiences for students, supply-chains for goods and services, and within higher education specifically, the growing need to demonstrate research impact. In this presentation, we explore the impact of private and public-sector working together to deliver regional economic growth through technology transfer. The objectives of this research stems from a twelve-year collaborative relationship between a higher education institute (HEI) and a private sector, technology value-added reseller (VAR). The authors assess and reflect on this activity, funded through the European Regional Development Fund (ERDF) to help understand the inputs, processes and outcomes of that relationship. Approach / Methodology The approach undertaken was firstly to identify the ERDF-funded projects since 2002 that the VAR (Quadra Solutions Ltd) has been a part of, as a private sector partner, with the HEI (Lancaster University’s Engineering Department). This is defined as where there is a service level agreement in place and the provision of match-funding is committed-to in that contract. This differs from that of a sub-contractor where the relationship may be better defined as purchaser-supplier and emphasizes the collaborative nature of the relationship being explored. We subsequently identified the ‘interventions’ in which both the knowledge exchange team (Lancaster Product Development Unit) and Quadra Solutions Ltd had worked with a ‘beneficiary’ as part of those ERDF initiatives. Retaining confidential information, these interventions were aggregated and basic company information collected in terms of location, size (by turnover) and sector. Analysis was then undertaken on the results collected as a consequence of that intervention, based on the following economic key performance indicators (KPIs): businesses improving performance; safeguarding of jobs; and the creation of new jobs. Qualitative reflection was carried out to assess wider impacts of the relationship and the development of a model that articulates this way of working. We highlight both the benefits and drawbacks based on extensive experience of providing technology-transfer solutions to SMEs, part-funded by ERDF. Results The results show that 93 interventions have been undertaken between Lancaster University’s Engineering Department and Quadra Solutions Ltd, in-part funded by ERDF between 2003 and 2015, spanning seven major projects. All of these interventions supported technology transfer by the introduction of a new or enhanced design process within the beneficiary, using the Autodesk family of software. All beneficiaries receiving support were SMEs, complying with national and regional eligibility guidelines as defined by the funding body secretariat. Sectoral breakdown unsurprisingly shows that the vast majority were in the engineering/manufacturing sector, accounting for 94.6% of the total. Of those SMEs that were assisted, all received increased functionality via the introduction or improvement to design software than that previously being used, demonstrating clear technology transfer. Where data was obtained, this intervention led to the cumulative safeguarding of 102.1 jobs and the creation of 71 jobs. As noted elsewhere, there is considerable ambiguity in using figures that attempt to provide a unit cost per result, and whilst one can attempt to draw comparison with other initiatives in other areas, this can be problematic due to assumptions made. For the purposes of this investigation, we have benchmarked against ourselves and show that for all cumulative ERDF assistance provided by the Engineering Department, the average job created per intervention is 0.64 and the average job safeguarded is 0.91. For the technology transfer work carried out in partnership with Quadra Solutions Ltd, the figures are 0.76 and 1.10, respectively. More widely, there are other impacts from joint collaboration with private sector partners that have been created, for the HEI: • Clear access to the latest in engineering design functionality, informed by globally-operating OEMs spanning many sectors; • Provision of a match-funding contribution through the time of company representatives contributing towards the objectives of the project; • Sharing of a networks of users and manufactures in close proximity, with a ‘seal-of-approval’ for quality of work; • Local, regional, national and international market intelligence; • Formalisation in the pursuit of similar objectives; • Contribution to the state-of-the-art and hence vital commercial-sector input to other future programmes of business support. The benefits created by such a relationship for private sector partners include: • Promotion of joint-funding opportunities to potential beneficiaries generating in-house advocates, or ‘funding champions’; • Ability to join-up wider business-support allied to technology transfer, which may include time-bound financial incentives, training offers, subscriptions, hardware support and so on. • Increased knowledge and experience of public-funding processes, regulations and conditions; • Externally-visible partnerships with a world-ranked university. Arguably the most important benefits relate to the end-user, which in this case is the beneficiary. The following model outlines a typical journey taken by a beneficiary through the technology acquisition route of intervention. Additional benefits to the beneficiaries in these cases may include: • Increased ability to develop new products • Awareness of how new technology processes can be further exploited, such as through expansion, training, add-ons; • A route into higher education to explore other research and development opportunities that may exist beyond that of the intervention; Implications and Recommendations The authors fully accept that there are a number of issues with the data collected which include that our assessment methods: • Only take account of the reported results when/if engaged with the beneficiary. Some beneficiaries become reluctant to undertake evaluation after the assistance has been delivered. • It does not record the exact time input to each intervention made by either the HEI or the VAR. • The package of support (or agreed solution) has not been specified and will include some differences, in this case in software, including for example upgrades or new packages. Notwithstanding some of the limitations outlined above, we have been able to demonstrate that the work carried-out by the partnership of a private sector VAR and an HEI to support SMEs in technology transfer has clear, demonstrable impact, both quantitatively and qualitatively. Such a model can be applied to future initiatives that have technology transfer as a theme within business support. Areas for development / future research There are a number of important areas underpinned by this work that would be useful to explore further: • Sector transference, for example application in other disciplines requiring software, such as for example architecture, construction, chemicals, food and drink, creative. • Technology transference, for example application of using other technologies beyond software, such as for example, manufacturing hardware. • Longer-term assessment of the impact to beneficiaries of these interventions, which may include aspects related to innovation culture, new product development or increased capacity for R&D. • Exploration of opportunities that may be available beyond the intervention provided, by the HEI, such as access to graduates, and the ‘completion of the circle’