Low-cost mobile personal clouds

We propose a mobile peer to peer personal cloud architecture which allows users to capture, store, analyse, interact with and share different types of personal and context data with no privacy leakage. Our mobile personal cloud can host multiple different services which are intelligent, distributed, dynamic and operate in real time. In this paper we describe one service that we designed and deployed on our mobile personal cloud called Mobile Wellbeing Companion Cloud (MWCC). Using low-cost, off-the-shelf hardware components and open-source software, our MWCC combines several sensor network technologies to allow users to monitor and interact with their personal data and environment in real time without privacy leakage. MWCC augments heterogeneous sensors data with state of the art machine learning algorithms for signal filtering, fast classification and analysis and provides interactive data visualisation for transparent user interaction. We show that our MWCC is easy to use and highly accurate while managing to keep resource costs low

Towards low cost prototyping of mobile opportunistic disconnection tolerant networks and systems

Fast emerging mobile edge computing, mobile clouds, Internet of Things (IoT) and cyber physical systems require many novel realistic real time multi-layer algorithms for a wide range of domains, such as intelligent content provision and processing, smart transport, smart manufacturing systems and mobile end user applications. This paper proposes a low cost open source platform, MODiToNeS, which uses commodity hardware to support prototyping and testing of fully distributed multi-layer complex algorithms over real world (or pseudo real) traces. MODiToNeS platform is generic and comprises multiple interfaces that allow real time topology and mobility control, deployment and analysis of different self-organised and self-adaptive routing algorithms, real time content processing, and real time environment sensing with predictive analytics. Our platform also allows rich interactivity with the user. We show deployment and analysis of two vastly different complex networking systems: fault and disconnection aware smart manufacturing sensor network and cognitive privacy for personal clouds. We show that our platform design can integrate both contexts transparently and organically and allows a wide range of analysis

Next Generation Cloud Computing: New Trends and Research Directions

The landscape of cloud computing has significantly changed over the last decade. Not only have more providers and service offerings crowded the space, but also cloud infrastructure that was traditionally limited to single provider data centers is now evolving. In this paper, we firstly discuss the changing cloud infrastructure and consider the use of infrastructure from multiple providers and the benefit of decentralising computing away from data centers. These trends have resulted in the need for a variety of new computing architectures that will be offered by future cloud infrastructure. These architectures are anticipated to impact areas, such as connecting people and devices, data-intensive computing, the service space and self-learning systems. Finally, we lay out a roadmap of challenges that will need to be addressed for realising the potential of next generation cloud systems.Comment: Accepted to Future Generation Computer Systems, 07 September 201