The Data of Things: Strategies, Patterns and Practice of Cloud-based Participatory Sensing

The broad capabilities of current mobile devices have paved the way for Mobile Crowd Sensing (MCS) applications. The success of this emerging paradigm strongly depends on the quality of received data which, in turn, is contingent to mass user participation; the broader the participation, the more useful these systems become. However, there is an ongoing trend that tries to integrate MCS applications with emerging computing paradigms such as cloud computing. The intuition is that such a transition can significantly improve the overall efficiency while at the same time it offers stronger security and privacy-preserving mechanisms for the end-user. In this position paper, we dwell on the underpinnings of incorporating cloud computing techniques to facilitate the vast amount of data collected in MCS applications. That is, we present a list of core system, security and privacy requirements that must be met if such a transition is to be successful. To this end, we first address several competing challenges not previously considered in the literature such as the scarce energy resources of battery-powered mobile devices as well as their limited computational resources that they often prevent the use of computationally heavy cryptographic operations and thus offering limited security services to the end-user. Finally, we present a use case scenario as a comprehensive example. Based on our findings, we posit open issues and challenges, and discuss possible ways to address them, so that security and privacy do not hinder the migration of MCS systems to the cloud.

Longitudinal evaluation of quality of life in 288 patients with Neurofibromatosis 2

Advances in molecular biology have resulted in novel therapy for neurofibromatosis 2-related (NF2) tumours, highlighting the need for robust outcome measures. The disease-focused NF2 impact on quality of life (NFTI-QOL) patient questionnaire was assessed as an outcome measure for treatment in a multi-centre study. NFTI-QOL was related to clinician-rated severity (ClinSev) and genetic severity (GenSev) over repeated visits. Data were evaluated for 288 NF2 patients (n = 464 visits) attending the English national NF2 clinics from 2010 to 2012. The male-to-female ratio was equal and the mean age was 42.2 (SD 17.8) years. The analysis included NFTI-QOL eight-item score, ClinSev graded as mild, moderate, or severe, and GenSev as a rank order of the number of NF2 mutations (graded as mild, moderate, severe). The mean (SD) 8.7 (5.4) score for NFTI-QOL for either a first visit or all visits 9.2 (5.4) was similar to the published norm of 9.4 (5.5), with no significant relationships with age or gender. NFTI-QOL internal reliability was good, with a Cronbach’s alpha score of 0.85 and test re-test reliability r = 0.84. NFTI related to ClinSev (r = 0.41, p < 0.001; r = 0.46 for all visits), but weakly to GenSev (r = 0.16, p < 0.05; r = 0.15 for all visits). ClinSev related to GenSev (r = 0.41, p < 0.001; r = 0.42 for all visits). NFTI-QOL showed a good reliability and ability to detect significant longitudinal changes in the QOL of individuals. The moderate relationships of NFTI-QOL with clinician- and genetic-rated severity suggest that NFTI-QOL taps into NF2 patient experiences that are not encompassed by ClinSev rating or genotype.