Opportunistic Sensing in Train Safety Systems

Train safety systems are complex and expensive, and changing them requires huge investments. Changes are evolutionary and small. Current developments, like faster - high speed - trains and a higher train density on the railway network, have initiated research on safety systems that can cope with the new requirements. This paper presents a novel approach for a safety subsystem that checks the composition of a train, based on opportunistic sensing with a wireless sensor network. Opportunistic sensing systems consist of changing constellations sensors that, for a limited amount of time, work together to achieve a common goal. Such constellations are selforganizing and come into being spontaneously. The proposed opportunistic sensing system selects a subset of sensor nodes from a larger set based on a common context.We show that it is possible to use a wireless sensor network to make a distinction between carriages from different trains. The common context is acceleration, which is used to select the subset of carriages that belong to the same train out of all the carriages from several trains in close proximity. Simulations based on a realistic set of sensor data show that the method is valid, but that the algorithm is too complex for implementation on simple wireless sensor nodes. Downscaling the algorithm reduces the number of processor execution cycles as well as memory usage, and makes it suitable for implementation on a wireless sensor node with acceptable loss of precision. Actual implementation on wireless sensor nodes confirms the results obtained with the simulations

A low-power opportunistic communication protocol for wearable applications

© 2015 IEEE.Recent trends in wearable applications demand flexible architectures being able to monitor people while they move in free-living environments. Current solutions use either store-download-offline processing or simple communication schemes with real-time streaming of sensor data. This limits the applicability of wearable applications to controlled environments (e.g, clinics, homes, or laboratories), because they need to maintain connectivity with the base station throughout the monitoring process. In this paper, we present the design and implementation of an opportunistic communication framework that simplifies the general use of wearable devices in free-living environments. It relies on a low-power data collection protocol that allows the end user to opportunistically, yet seamlessly manage the transmission of sensor data. We validate the feasibility of the framework by demonstrating its use for swimming, where the normal wireless communication is constantly interfered by the environment

Cross-layer design of multi-hop wireless networks

MULTI -hop wireless networks are usually defined as a collection of nodes equipped with radio transmitters, which not only have the capability to communicate each other in a multi-hop fashion, but also to route each others’ data packets. The distributed nature of such networks makes them suitable for a variety of applications where there are no assumed reliable central entities, or controllers, and may significantly improve the scalability issues of conventional single-hop wireless networks. This Ph.D. dissertation mainly investigates two aspects of the research issues related to the efficient multi-hop wireless networks design, namely: (a) network protocols and (b) network management, both in cross-layer design paradigms to ensure the notion of service quality, such as quality of service (QoS) in wireless mesh networks (WMNs) for backhaul applications and quality of information (QoI) in wireless sensor networks (WSNs) for sensing tasks. Throughout the presentation of this Ph.D. dissertation, different network settings are used as illustrative examples, however the proposed algorithms, methodologies, protocols, and models are not restricted in the considered networks, but rather have wide applicability. First, this dissertation proposes a cross-layer design framework integrating a distributed proportional-fair scheduler and a QoS routing algorithm, while using WMNs as an illustrative example. The proposed approach has significant performance gain compared with other network protocols. Second, this dissertation proposes a generic admission control methodology for any packet network, wired and wireless, by modeling the network as a black box, and using a generic mathematical 0. Abstract 3 function and Taylor expansion to capture the admission impact. Third, this dissertation further enhances the previous designs by proposing a negotiation process, to bridge the applications’ service quality demands and the resource management, while using WSNs as an illustrative example. This approach allows the negotiation among different service classes and WSN resource allocations to reach the optimal operational status. Finally, the guarantees of the service quality are extended to the environment of multiple, disconnected, mobile subnetworks, where the question of how to maintain communications using dynamically controlled, unmanned data ferries is investigated

Plausible Mobility: Inferring Movement from Contacts

We address the difficult question of inferring plausible node mobility based only on information from wireless contact traces. Working with mobility information allows richer protocol simulations, particularly in dense networks, but requires complex set-ups to measure, whereas contact information is easier to measure but only allows for simplistic simulation models. In a contact trace a lot of node movement information is irretrievably lost so the original positions and velocities are in general out of reach. We propose a fast heuristic algorithm, inspired by dynamic force-based graph drawing, capable of inferring a plausible movement from any contact trace, and evaluate it on both synthetic and real-life contact traces. Our results reveal that (i) the quality of the inferred mobility is directly linked to the precision of the measured contact trace, and (ii) the simple addition of appropriate anticipation forces between nodes leads to an accurate inferred mobility.Comment: 8 pages, 8 figures, 1 tabl

MOSDEN: A Scalable Mobile Collaborative Platform for Opportunistic Sensing Applications

Mobile smartphones along with embedded sensors have become an efficient enabler for various mobile applications including opportunistic sensing. The hi-tech advances in smartphones are opening up a world of possibilities. This paper proposes a mobile collaborative platform called MOSDEN that enables and supports opportunistic sensing at run time. MOSDEN captures and shares sensor data across multiple apps, smartphones and users. MOSDEN supports the emerging trend of separating sensors from application-specific processing, storing and sharing. MOSDEN promotes reuse and re-purposing of sensor data hence reducing the efforts in developing novel opportunistic sensing applications. MOSDEN has been implemented on Android-based smartphones and tablets. Experimental evaluations validate the scalability and energy efficiency of MOSDEN and its suitability towards real world applications. The results of evaluation and lessons learned are presented and discussed in this paper.Comment: Accepted to be published in Transactions on Collaborative Computing, 2014. arXiv admin note: substantial text overlap with arXiv:1310.405