The fans united will always be connected: building a practical DTN in a football stadium

Football stadia present a difficult environment for the deployment of digital services, due to their architectural design and the capacity problems from the numbers of fans. We present preliminary results from deploying an Android app building an ad hoc network amongst the attendees at matches at Brighton and Hove Albion's AMEX stadium, so as to share the available capacity and supply digital services to season ticket holders. We describe the protocol, how we engaged our users in service design so that the app was attractive to use and the problems we encountered in using Android

Efficient and adaptive congestion control for heterogeneous delay-tolerant networks

Detecting and dealing with congestion in delay-tolerant networks (DTNs) is an important and challenging problem. Current DTN forwarding algorithms typically direct traffic towards more central nodes in order to maximise delivery ratios and minimise delays, but as traffic demands increase these nodes may become saturated and unusable. We pro- pose CafRep, an adaptive congestion aware protocol that detects and reacts to congested nodes and congested parts of the network by using implicit hybrid contact and resources congestion heuristics. CafRep exploits localised relative utility based approach to offload the traffic from more to less congested parts of the network, and to replicate at adaptively lower rate in different parts of the network with non-uniform congestion levels. We extensively evaluate our work against benchmark and competitive protocols across a range of metrics over three real connectivity and GPS traces such as Sassy [44], San Francisco Cabs [45] and Infocom 2006 [33]. We show that CafRep performs well, independent of network connectivity and mobility patterns, and consistently outperforms the state-of-the-art DTN forwarding algorithms in the face of increasing rates of congestion. CafRep maintains higher availability and success ratios while keeping low delays, packet loss rates and delivery cost. We test CafRep in the presence of two application scenarios, with fixed rate traffic and with real world Facebook application traffic demands, showing that regardless of the type of traffic CafRep aims to deliver, it reduces congestion and improves forwarding performance

Robotic Wireless Sensor Networks

In this chapter, we present a literature survey of an emerging, cutting-edge, and multi-disciplinary field of research at the intersection of Robotics and Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system that aims to achieve certain sensing goals while meeting and maintaining certain communication performance requirements, through cooperative control, learning and adaptation. While both of the component areas, i.e., Robotics and WSN, are very well-known and well-explored, there exist a whole set of new opportunities and research directions at the intersection of these two fields which are relatively or even completely unexplored. One such example would be the use of a set of robotic routers to set up a temporary communication path between a sender and a receiver that uses the controlled mobility to the advantage of packet routing. We find that there exist only a limited number of articles to be directly categorized as RWSN related works whereas there exist a range of articles in the robotics and the WSN literature that are also relevant to this new field of research. To connect the dots, we first identify the core problems and research trends related to RWSN such as connectivity, localization, routing, and robust flow of information. Next, we classify the existing research on RWSN as well as the relevant state-of-the-arts from robotics and WSN community according to the problems and trends identified in the first step. Lastly, we analyze what is missing in the existing literature, and identify topics that require more research attention in the future

Named data networking for efficient IoT-based disaster management in a smart campus

Disasters are uncertain occasions that can impose a drastic impact on human life and building infrastructures. Information and Communication Technology (ICT) plays a vital role in coping with such situations by enabling and integrating multiple technological resources to develop Disaster Management Systems (DMSs). In this context, a majority of the existing DMSs use networking architectures based upon the Internet Protocol (IP) focusing on location-dependent communications. However, IP-based communications face the limitations of inefficient bandwidth utilization, high processing, data security, and excessive memory intake. To address these issues, Named Data Networking (NDN) has emerged as a promising communication paradigm, which is based on the Information-Centric Networking (ICN) architecture. An NDN is among the self-organizing communication networks that reduces the complexity of networking systems in addition to provide content security. Given this, many NDN-based DMSs have been proposed. The problem with the existing NDN-based DMS is that they use a PULL-based mechanism that ultimately results in higher delay and more energy consumption. In order to cater for time-critical scenarios, emergence-driven network engineering communication and computation models are required. In this paper, a novel DMS is proposed, i.e., Named Data Networking Disaster Management (NDN-DM), where a producer forwards a fire alert message to neighbouring consumers. This makes the nodes converge according to the disaster situation in a more efficient and secure way. Furthermore, we consider a fire scenario in a university campus and mobile nodes in the campus collaborate with each other to manage the fire situation. The proposed framework has been mathematically modeled and formally proved using timed automata-based transition systems and a real-time model checker, respectively. Additionally, the evaluation of the proposed NDM-DM has been performed using NS2. The results prove that the proposed scheme has reduced the end-to-end delay up from 2% to 10% and minimized up to 20% energy consumption, as energy improved from 3% to 20% compared with a state-of-the-art NDN-based DMS

Efficient geocasting in opportunistic networks

With the proliferation of smartphones and their advanced connectivity capabilities, opportunistic networks have gained a lot of traction during the past years; they are suitable for increasing network capacity and sharing ephemeral, localised content. They can also offload traffic from cellular networks to device-to-device ones, when cellular networks are heavily stressed. Opportunistic networks can play a crucial role in communication scenarios where the network infrastructure is inaccessible due to natural disasters, large-scale terrorist attacks or government censorship. Geocasting, where messages are destined to specific locations (casts) instead of explicitly identified devices, has a large potential in real world opportunistic networks, however it has attracted little attention in the context of opportunistic networking. In this paper we propose Geocasting Spray And Flood (GSAF), a simple and efficient geocasting protocol for opportunistic networks. GSAF follows an elegant and flexible approach where messages take random walks towards the destination cast. Messages that are routed away from the destination cast are extinct when devices’ buffers get full, freeing space for new messages to be delivered. In GSAF, casts do not have to be pre-defined; instead users can route messages to arbitrarily defined casts. GSAF does that in a privacy-preserving fashion. We also present DA-GSAF, a Direction-Aware extension of GSAF in which messages are forwarded to encountered nodes based on whether a node is moving towards their destination cast. In DA-GSAF only the direction of a mobile node is revealed to other devices. We experimentally evaluate our protocols and compare their performance to prominent geocasting protocols in a very wide set of scenarios, including different maps, mobility models and user populations. Both GSAF and DA-GSAF perform significantly better compared to all other studied protocols, in terms of message delivery ratio, latency and network overhead. DA-GSAF is particularly efficient in sparse scenarios minimising network overhead compared to all other studied protocols. Both GSAF and DA-GSAF perform very well for a wide range of device/user populations indicating that our proposal is viable for crowded and sparse opportunistic networks

Towards efficacy and efficiency in sparse delay tolerant networks

The ubiquitous adoption of portable smart devices has enabled a new way of communication via Delay Tolerant Networks (DTNs), whereby messages are routed by the personal devices carried by ever-moving people. Although a DTN is a type of Mobile Ad Hoc Network (MANET), traditional MANET solutions are ill-equipped to accommodate message delivery in DTNs due to the dynamic and unpredictable nature of people\u27s movements and their spatio-temporal sparsity. More so, such DTNs are susceptible to catastrophic congestion and are inherently chaotic and arduous. This manuscript proposes approaches to handle message delivery in notably sparse DTNs. First, the ChitChat system [69] employs the social interests of individuals participating in a DTN to accurately model multi-hop relationships and to make opportunistic routing decisions for interest-annotated messages. Second, the ChitChat system is hybridized [70] to consider both social context and geographic information for learning the social semantics of locations so as to identify worthwhile routing opportunities to destinations and areas of interest. Network density analyses of five real-world datasets is conducted to identify sparse datasets on which to conduct simulations, finding that commonly-used datasets in past DTN research are notably dense and well connected, and suggests two rarely used datasets are appropriate for research into sparse DTNs. Finally, the Catora system is proposed to address congestive-driven degradation of service in DTNs by accomplishing two simultaneous tasks: (i) expedite the delivery of higher quality messages by uniquely ordering messages for transfer and delivery, and (ii) avoid congestion through strategic buffer management and message removal. Through dataset-driven simulations, these systems are found to outperform the state-of-the-art, with ChitChat facilitating delivery in sparse DTNs and Catora unencumbered by congestive conditions --Abstract, page iv

Reputation aware obfuscation for mobile opportunistic networks

© 2013 IEEE. Current anonymity techniques for mobile opportunistic networks typically use obfuscation algorithms to hide node's identity behind other nodes. These algorithms are not well suited to sparse and disconnection prone networks with large number of malicious nodes and new opportunistic, adaptive. So, new, opportunistic, adaptive fully localized mechanisms are needed for improving user anonymity. This paper proposes reputation aware localized adaptive obfuscation for mobile opportunistic networks that comprises of two complementary techniques: opportunistic collaborative testing of nodes' obfuscation behaviour (OCOT) and multidimensional adaptive anonymisation (AA). OCOT-AA is driven by both explicit and implicit reputation building, complex graph connectivity analytics and obfuscation history analyses. We show that OCOT-AA is very efficient in terms of achieving high levels of node identity obfuscation and managing low delays for answering queries between sources and destinations while enabling fast detection and avoidance of malicious nodes typically within the fraction of time within the experiment duration. We perform extensive experiments to compare OCOT-AA with several other competitive and benchmark protocols and show that it outperforms them across a range of metrics over a one month real-life GPS trace. To demonstrate our proposal more clearly, we propose new metrics that include best effort biggest length and diversity of the obfuscation paths, the actual percentage of truly anonymised sources' IDs at the destinations and communication quality of service between source and destination