The uptake and increasing prevalence of Web 2.0 applications, promoting new largescale and complex systems such as Cloud computing and the emerging Internet of Services/Things, requires tools and techniques to analyse and model methods to ensure the robustness of these new systems. This paper reports on assessing and improving complex system resilience using distributed redundancy, termed degeneracy in biological systems, to endow large-scale complicated computer systems with the same robustness that emerges in complex biological and natural systems. However, in order to promote an evolutionary approach, through emergent self-organisation, it is necessary to specify the systems in an 'open-ended' manner where not all states of the system are prescribed at designtime. In particular an observer system is used to select robust topologies, within system components, based on a measurement of the first non-zero Eigen value in the Laplacian spectrum of the components' network graphs; also known as the algebraic connectivity. It is shown, through experimentation on a simulation, that increasing the average algebraic connectivity across the components, in a network, leads to an increase in the variety of individual components termed distributed redundancy; the capacity for structurally distinct components to perform an identical function in a particular context. The results are applied to a specific application where active clustering of like services is used to aid load balancing in a highly distributed network. Using the described procedure is shown to improve performance and distribute redundancy.
Abstract. In a quest to modernise their activities and underpin their publicprivate partnerships, many governments around the globe have initiated their local eGovernment programmes. In this regard, best-practice, emerging Information Communications Technology (ICT) and e-business potential are leveraged to provide 24*7 access to online public services, ranging from online tax forms, to online voting. Whilst much may have been achieved towards developing and supporting one-stop shop to a range of online government services, more research is required, for instance, to provide a seamless integration and interoperation of these services, their integration with legacy systems, and risk management strategy. Based on an ongoing research focused on risk modelling and analysis of eGovernment web services, this paper introduces a categorisation of the main generic risk factors. The paper only elaborates on the first two categories of the risk factors and develops a set of potential success factors for eGovernment.
Technology plays an important role in both primary and secondary healthcare. With widespread use of mobile devices and ubiquitous communications, new and novel platforms are emerging to administer care. Ordinary and everyday appliances used in the home are becoming integral components within these platforms and this could potentially revolutionise how health related information is monitored, accessed and used to administer better treatments. Despite the many challenges that exist, such platforms will allow for better exploitation of networked devices to provide benefits to patients with conditions, such as arthritis and back pain. Currently these conditions are treated through physiotherapy sessions in the community, which are often costly and difficult to resource. Physiotherapists alternate between patients. This means that assessments are sporadic and subjective. This paper aims to address these limitations using a system to implement body area and sensor networks within the home with data management functions for collecting and storing motion data. This data can be accessed via the home or remotely in one or more medical facilities. Using this data, quantitative assessments are performed and used to measure the patient's progress. A case study is presented that successfully illustrates tour approach.
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