Increasing Data Resilience of Mobile Devices with a Collaborative Backup Service

Whoever has had his cell phone stolen knows how frustrating it is to be unable to get his contact list back. To avoid data loss when losing or destroying a mobile device like a PDA or a cell phone, data is usually backed-up to a fixed station. However, in the time between the last backup and the failure, important data can have been produced and then lost. To handle this issue, we propose a transparent collaborative backup system. Indeed, by saving data on other mobile devices between two connections to a global infrastructure, we can resist to such scenarios. In this paper, after a general description of such a system, we present a way to replicate data on mobile devices to attain a prerequired resilience for the backup

Increasing Data Resilience of Mobile Devices with a Collaborative Backup Service

Whoever has had his cell phone stolen knows how frustrating it is to be unable to get his contact list back. To avoid data loss when losing or destroying a mobile device like a PDA or a cell phone, data is usually backed-up to a fixed station. However, in the time between the last backup and the failure, important data can have been produced and then lost. To handle this issue, we propose a transparent collaborative backup system. Indeed, by saving data on other mobile devices between two connections to a global infrastructure, we can resist to such scenarios. In this paper, after a general description of such a system, we present a way to replicate data on mobile devices to attain a prerequired resilience for the backup

Energy Efficient Distributed Processing for IoT

The number of connected objects in the Internet of Things (IoT) is growing exponentially. IoT devices are expected to number between 26 billion to 50 billion devices by 2020 and this figure can grow even further due to the production of miniaturised portable devices that are lightweight, energy and cost efficient together with the widespread use of the Internet and the added value organisations and individuals can gain from IoT devices, if their data is processed. These connected objects are expected to be used in multitudes of applications, of which, some are, highly resource intensive such as visual processing services for surveillance based object recognition applications. The sensed data requires processing by the cloud in order to extract knowledge and make decisions accordingly. Given the pervasiveness of future IoT-based visual processing applications, massive amounts of data will be collected due to the nature of multimedia files. Transporting all that collected data to the cloud at the core of the network, is prohibitively costly, in terms of energy consumption. Hence, to tackle the aforementioned challenges, distributed processing is proposed by academia and industry to make use of a large number of devices located in the edge of the network to process some or all of the data before it gets to the cloud. Due to the heterogeneity of the devices in the edge of the network, it is crucial to develop energy efficient models that take care of resource provisioning optimally. The focus in today’s network design and development has shifted towards energy efficiency, due to the rising cost of electricity, resource scarcity and increasing emission of carbon dioxide (CO2). This thesis addresses some of the challenges associated with service placement in a distributed architecture such as the fog. First, a Passive Optical Network (PON) is used to connect IoT devices and to support the fog infrastructure. A metro network is also used to connect to the fog and aggregate traffic from the PON towards the core network. An IP/WDM backbone network is considered to model the core layer and to interconnect the cloud data centres. The entire network was modelled and optimised through Mixed Integer Linear Programming (MILP) and the total end to end power consumption was jointly minimised for processing and networking. Two aspects of service placements were examined: 1) non-splitable services, and 2) splitable services. The results obtained showed that, in the capacitated problem, service splitting introduced power consumption savings of up to 86% compared to 46% with non-splitable services. Moreover, an energy efficient special purposed data centre (SP-DC) was deployed in addition to its general purpose counterpart (GP-DC). The results showed that, for very high demands, power savings of up to 50% could be achieved compared to 30% without SP-DC. The performance of the proposed architecture was further examined by considering additional dimensions to the problem of service placements such as resiliency dimension in terms of 1+1 server protection, in the long term network design problem (un-capacitated) and the impact of inter-service synchronisation overhead on the total number service splits per task

The future of social is personal: the potential of the personal data store

This chapter argues that technical architectures that facilitate the longitudinal, decentralised and individual-centric personal collection and curation of data will be an important, but partial, response to the pressing problem of the autonomy of the data subject, and the asymmetry of power between the subject and large scale service providers/data consumers. Towards framing the scope and role of such Personal Data Stores (PDSes), the legalistic notion of personal data is examined, and it is argued that a more inclusive, intuitive notion expresses more accurately what individuals require in order to preserve their autonomy in a data-driven world of large aggregators. Six challenges towards realising the PDS vision are set out: the requirement to store data for long periods; the difficulties of managing data for individuals; the need to reconsider the regulatory basis for third-party access to data; the need to comply with international data handling standards; the need to integrate privacy-enhancing technologies; and the need to future-proof data gathering against the evolution of social norms. The open experimental PDS platform INDX is introduced and described, as a means of beginning to address at least some of these six challenges

Smartphone-based safety planning and self-monitoring for suicidal patients: Rationale and study protocol of the CASPAR (Continuous Assessment for Suicide Prevention And Research) study

Background: It remains difficult to predict and prevent suicidal behaviour, despite growing understanding of the aetiology of suicidality. Clinical guidelines recommend that health care professionals develop a safety plan in collaboration with their high-risk patients, to lower the imminent risk of suicidal behaviour. Mobile health applications provide new opportunities for safety planning, and enable daily self-monitoring of suicide-related symptoms that may enhance safety planning. This paper presents the rationale and protocol of the Continuous Assessment for Suicide Prevention And Research (CASPAR) study. The aim of the study is two-fold: to evaluate the feasibility of mobile safety planning and daily mobile self-monitoring in routine care treatment for suicidal patients, and to conduct fundamental research on suicidal processes. Methods: The study is an adaptive single cohort design among 80 adult outpatients or day-care patients, with the main diagnosis of major depressive disorder or dysthymia, who have an increased risk for suicidal behaviours. There are three measurement points, at baseline, at 1 and 3 months after baseline. Patients are instructed to use their mobile safety plan when necessary and monitor their suicidal symptoms daily. Both these apps will be used in treatment with their clinician. Conclusion: The results from this study will provide insight into the feasibility of mobile safety planning and self-monitoring in treatment of suicidal patients. Furthermore, knowledge of the suicidal process will be enhanced, especially regarding the transition from suicidal ideation to behaviour

Towards service protection in Fog-to-Cloud (F2C) computing systems

Internet of Things (IoT) services are unstoppably demanding more computing and storage resources. Aligned to this trend, cloud and fog computing came up as the proper paradigms meeting such IoT services demands. More recently, a new paradigm, so-called fog to cloud (F2C) computing, promises to make the most out of both Fog and Cloud, paving the way to new IoT services development. Nevertheless, the benefits of F2C architectures may be diminished by failures affecting the computing commodities. In order to withstand possible failures, the design of novel protection strategies, specifically designed for distributed computing scenarios is required. In this paper, we study the impact of distinct protection strategies on several key performance aspects, including service response time, and usage of computing resources. Numerical results indicate that under distinct failure scenarios, F2C significantly outperforms the conventional cloud.Peer ReviewedPostprint (published version

Developing a Framework for Stigmergic Human Collaboration with Technology Tools: Cases in Emergency Response

Information and Communications Technologies (ICTs), particularly social media and geographic information systems (GIS), have become a transformational force in emergency response. Social media enables ad hoc collaboration, providing timely, useful information dissemination and sharing, and helping to overcome limitations of time and place. Geographic information systems increase the level of situation awareness, serving geospatial data using interactive maps, animations, and computer generated imagery derived from sophisticated global remote sensing systems. Digital workspaces bring these technologies together and contribute to meeting ad hoc and formal emergency response challenges through their affordances of situation awareness and mass collaboration. Distributed ICTs that enable ad hoc emergency response via digital workspaces have arguably made traditional top-down system deployments less relevant in certain situations, including emergency response (Merrill, 2009; Heylighen, 2007a, b). Heylighen (2014, 2007a, b) theorizes that human cognitive stigmergy explains some self-organizing characteristics of ad hoc systems. Elliott (2007) identifies cognitive stigmergy as a factor in mass collaborations supported by digital workspaces. Stigmergy, a term from biology, refers to the phenomenon of self-organizing systems with agents that coordinate via perceived changes in the environment rather than direct communication. In the present research, ad hoc emergency response is examined through the lens of human cognitive stigmergy. The basic assertion is that ICTs and stigmergy together make possible highly effective ad hoc collaborations in circumstances where more typical collaborative methods break down. The research is organized into three essays: an in-depth analysis of the development and deployment of the Ushahidi emergency response software platform, a comparison of the emergency response ICTs used for emergency response during Hurricanes Katrina and Sandy, and a process model developed from the case studies and relevant academic literature is described

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]