Cognitive privacy for personal clouds

This paper proposes a novel Cognitive Privacy (CogPriv) framework that improves privacy of data sharing between Personal Clouds for different application types and across heterogeneous networks. Depending on the behaviour of neighbouring network nodes, their estimated privacy levels, resource availability, and social network connectivity, each Personal Cloud may decide to use different transmission network for different types of data and privacy requirements. CogPriv is fully distributed, uses complex graph contacts analytics and multiple implicit novel heuristics, and combines these with smart probing to identify presence and behaviour of privacy compromising nodes in the network. Based on sensed local context and through cooperation with remote nodes in the network, CogPriv is able to transparently and on-the-fly change the network in order to avoid transmissions when privacy may be compromised. We show that CogPriv achieves higher end-to-end privacy levels compared to both noncognitive cellular network communication and state-of-the-art strategies based on privacy-aware adaptive social mobile networks routing for a range of experiment scenarios based on real-world user and network traces. CogPriv is able to adapt to varying network connectivity and maintain high quality of service while managing to keep low data exposure for a wide range of privacy leakage levels in the infrastructure

Flexible and dynamic network coding for adaptive data transmission in DTNs

Existing network coding approaches for Delay-Tolerant Networks (DTNs) do not detect and adapt to congestion in the network. In this paper we describe CafNC (Congestion aware forwarding with Network Coding) that combines adaptive network coding and adaptive forwarding in DTNs. In CafNC each node learns the status of its neighbours, and their egonetworks in order to detect coding opportunities, and codes as long as the recipients can decode. Our flexible design allows CafNC to efficiently support multiple unicast flows, with dynamic traffic demands and dynamic senders and receivers. We evaluate CafNC with two real connectivity traces and a realistic P2P application, introducing congestion by increasing the number of unicast flows in the network. Our results show that CafNC improves the success ratio, delay and packet loss, as the number of flows grows in comparison to no coding and hub-based static coding, while at the same time achieving efficient utilisation of network resources. We also show that static coding misses a number of coding opportunities and increases packet loss rates at times of increased congestion

Enabling rapid and cost-effective creation of massive pervasive games in very unstable environments

Pervasive gaming is a new form of multimedia entertainment that extends the traditional computer gaming experience out into the real world. Through a combination of personal devices, positioning systems and other sensors, combined with wireless networking, a pervasive game can respond to player's movements and context and enable them to communicate with a game engine and other players. We review our recent deployment examples of pervasive games in order to explain their distinctive characteristics as wireless ad-hoc networking applications. We then identify the network support challenges of scaling pervasive games to include potentially mass numbers of players across extremely heterogeneous and unreliable networks. We propose a P2P overlay capable of storing large amount of game related data, which is the key to combating the loss of coverage and potential dishonesty of players. The proposed protocol decreases the deployment costs of the gaming infrastructure by self organization and utilizing storage space of users' devices. We demonstrate scalability and increased availability of data offered by the proposed protocol in simulation based evaluatio

Wireless mobile ad-hoc sensor networks for very large scale cattle monitoring

This paper investigates the use of wireless mobile ad hoc sensor networks in the nationwide cattle monitoring systems. This problem is essential for monitoring general animal health and detecting outbreaks of animal diseases that can be a serious threat for the national cattle industry and human health. We begin by describing a number of related approaches for supporting animal monitoring applications and identify a comprehensive set of requirements that guides our approach. We then propose a novel infrastructure-less, self -organized peer to peer architecture that fulfills these requirements. The core of our work is the novel data storage and routing protocol for large scale, highly mobile ad hoc sensor networks that is based on the Distributed Hash Table (DHT) substrate that we optimize for disconnections. We show over a range of extensive simulations that by exploiting nodes’ mobility, packet overhearing and proactive caching we significantly improve availability of sensor data in these extreme conditions

GPSR-TARS: congestion aware geographically targeted remote surveillance for VANETs

Video over vehicular networks continues to receive warranted attention, with envisioned applications having the potential to present entirely new opportunities and revolutionise existing services. Many video systems have been proposed, ranging from safety to advertising. We propose a novel system for VANETs, namely the TArgeted Remote Surveillance (TARS) module for the existing Greedy Perimeter Stateless Routing (GPSR) protocol which permits multiple mobile vehicles to request and receive live video feeds from vehicles within a select geographic region. The multi-hop, vehicle-to-vehicle system enables mobile units to surveil a target area in real time by leveraging the dashboard cameras of vehicles moving within the target region. We combine several proposed extensions to the core protocol to introduce a dynamic real time congestion aware clustering scheme to achieve this. Our proposed system is compared against existing routing protocols using mobility data from Nottingham. GPSR-TARS outperforms the protocols assessed in key criteria crucial for meeting the quality of service demands of live multimedia dissemination

Congestion aware forwarding in delay tolerant and social opportunistic networks

We propose an approach for opportunistic forwarding that supports optimization of multipoint high volume data flow transfer while maintaining high buffer availability and low delays. This paper explores a number of social, buffer and delay heuristics to offload the traffic from congested parts of the network and spread it over less congested parts of the network in order to keep low delays, high success ratios and high availability of nodes. We conduct an extensive set of experiments for assessing the performance of four newly proposed heuristics and compare them with Epidemic, Prophet, Spay and Wait and Spay and Focus protocols over real connectivity driven traces (RollerNet) and with a realistic publish subscribe filecasting application. We look into success ratio of answered queries, download times (delays) and availability of buffer across eight protocols for varying congestion levels in the face of increasing number of publishers and topic popularity. We show that all of our combined metrics perform better than Epidemic protocol, Prophet, Spray and Wait, Spray and Focus and our previous prototype across all the assessed criteria

Wireless mobile ad-hoc sensor networks for very large scale cattle monitoring

This paper investigates the use of wireless mobile ad hoc sensor networks in the nationwide cattle monitoring systems. This problem is essential for monitoring general animal health and detecting outbreaks of animal diseases that can be a serious threat for the national cattle industry and human health. We begin by describing a number of related approaches for supporting animal monitoring applications and identify a comprehensive set of requirements that guides our approach. We then propose a novel infrastructure-less, self -organized peer to peer architecture that fulfills these requirements. The core of our work is the novel data storage and routing protocol for large scale, highly mobile ad hoc sensor networks that is based on the Distributed Hash Table (DHT) substrate that we optimize for disconnections. We show over a range of extensive simulations that by exploiting nodes’ mobility, packet overhearing and proactive caching we significantly improve availability of sensor data in these extreme conditions

Scaleable audio for collaborative environments

This thesis is concerned with supporting natural audio communication in collaborative environments across the Internet. Recent experience with Collaborative Virtual Environments, for example, to support large on-line communities and highly interactive social events, suggest that in the future there will be applications in which many users speak at the same time. Such applications will generate large and dynamically changing volumes of audio traffic that can cause congestion and hence packet loss in the network and so seriously impair audio quality. This thesis reveals that no current approach to audio distribution can combine support for large number of simultaneous speakers with TCP-fair responsiveness to congestion. A model for audio distribution called Distributed Partial Mixing (DPM) is proposed that dynamically adapts both to varying numbers of active audio streams in collaborative environments and to congestion in the network. Each DPM component adaptively mixes subsets of its input audio streams into one or more mixed streams, which it then forwards to the other components along with any unmixed streams. DPM minimises the amount of mixing performed so that end users receive as many separate audio streams as possible within prevailing network resource constraints. This is important in order to allow maximum flexibility of audio presentation (especially spatialisation) to the end user. A distributed partial mixing prototype is realised as part of the audio service in MASSIVE-3. A series of experiments over a single network link demonstrate that DPM gracefully manages the tradeoff between preserving stable audio quality and being responsive to congestion and achieving fairness towards competing TCP traffic. The problem of large scale deployment of DPM over heterogeneous networks is also addressed. The thesis proposes that a shared tree of DPM servers and clients, where the nodes of the tree can perform distributed partial mixing, is an effective basis for wide area deployment. Two models for realising this in two contrasting situations are then explored in more detail: a static, centralised, subscription-based DPM service suitable for fully managed networks, and a fully distributed self-organising DPM service suitable for unmanaged networks (such as the current Internet)