Applications and Challenges of Real-time Mobile DNA Analysis

The DNA sequencing is the process of identifying the exact order of nucleotides within a given DNA molecule. The new portable and relatively inexpensive DNA sequencers, such as Oxford Nanopore MinION, have the potential to move DNA sequencing outside of laboratory, leading to faster and more accessible DNA-based diagnostics. However, portable DNA sequencing and analysis are challenging for mobile systems, owing to high data throughputs and computationally intensive processing performed in environments with unreliable connectivity and power. In this paper, we provide an analysis of the challenges that mobile systems and mobile computing must address to maximize the potential of portable DNA sequencing, and in situ DNA analysis. We explain the DNA sequencing process and highlight the main differences between traditional and portable DNA sequencing in the context of the actual and envisioned applications. We look at the identified challenges from the perspective of both algorithms and systems design, showing the need for careful co-design

MIPv6 Experimental Evaluation using Overlay Networks

The commercial deployment of Mobile IPv6 has been hastened by the concepts of Integrated Wireless Networks and Overlay Networks, which are present in the notion of the forthcoming generation of wireless communications. Individual wireless access networks show limitations that can be overcome through the integration of different technologies into a single unified platform (i.e., 4G systems). This paper summarises practical experiments performed to evaluate the impact of inter-networking (i.e. vertical handovers) on the Network and Transport layers. Based on our observations, we propose and evaluate a number of inter-technology handover optimisation techniques, e.g., Router Advertisements frequency values, Binding Update simulcasting, Router Advertisement caching, and Soft Handovers. The paper concludes with the description of a policy-based mobility support middleware (PROTON) that hides 4G networking complexities from mobile users, provides informed handover-related decisions, and enables the application of different vertical handover methods and optimisations according to context.Publicad

Data as a Service (DaaS) for sharing and processing of large data collections in the cloud

Data as a Service (DaaS) is among the latest kind of services being investigated in the Cloud computing community. The main aim of DaaS is to overcome limitations of state-of-the-art approaches in data technologies, according to which data is stored and accessed from repositories whose location is known and is relevant for sharing and processing. Besides limitations for the data sharing, current approaches also do not achieve to fully separate/decouple software services from data and thus impose limitations in inter-operability. In this paper we propose a DaaS approach for intelligent sharing and processing of large data collections with the aim of abstracting the data location (by making it relevant to the needs of sharing and accessing) and to fully decouple the data and its processing. The aim of our approach is to build a Cloud computing platform, offering DaaS to support large communities of users that need to share, access, and process the data for collectively building knowledge from data. We exemplify the approach from large data collections from health and biology domains.Peer ReviewedPostprint (author's final draft