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 novel cross-layer framework for large scale emergency communications

This paper explores the problem of improving coverage and capacity of large-scale communication networks in disaster-struck areas. We propose a novel integrated dynamic cross-layer distributed energy aware emergency framework, E3F, that spans large geographical areas and variable time ranges. E3F enables adaptive storage, dynamic packet scheduling and utility driven forwarding that avoids congestion and energy depletion. Our extensive experiments with realistic traces show significantly improved energy efficiency and low overheads while maintaining high success ratios for both data dissemination and query answering

Graphical Query Builder in Opportunistic Sensor Networks to discover Sensor Information

ABSTRAC

Models and Protocols for Resource Optimization in Wireless Mesh Networks

Wireless mesh networks are built on a mix of fixed and mobile nodes interconnected via wireless links to form a multihop ad hoc network. An emerging application area for wireless mesh networks is their evolution into a converged infrastructure used to share and extend, to mobile users, the wireless Internet connectivity of sparsely deployed fixed lines with heterogeneous capacity, ranging from ISP-owned broadband links to subscriber owned low-speed connections. In this thesis we address different key research issues for this networking scenario. First, we propose an analytical predictive tool, developing a queuing network model capable of predicting the network capacity and we use it in a load aware routing protocol in order to provide, to the end users, a quality of service based on the throughput. We then extend the queuing network model and introduce a multi-class queuing network model to predict analytically the average end-to-end packet delay of the traffic flows among the mobile end users and the Internet. The analytical models are validated against simulation. Second, we propose an address auto-configuration solution to extend the coverage of a wireless mesh network by interconnecting it to a mobile ad hoc network in a transparent way for the infrastructure network (i.e., the legacy Internet interconnected to the wireless mesh network). Third, we implement two real testbed prototypes of the proposed solutions as a proof-of-concept, both for the load aware routing protocol and the auto-configuration protocol. Finally we discuss the issues related to the adoption of ad hoc networking technologies to address the fragility of our communication infrastructure and to build the next generation of dependable, secure and rapidly deployable communications infrastructures

A Data Protection Architecture for Derived Data Control in Partially Disconnected Networks

Every organisation needs to exchange and disseminate data constantly amongst its employees, members, customers and partners. Disseminated data is often sensitive or confidential and access to it should be restricted to authorised recipients. Several enterprise rights management (ERM) systems and data protection solutions have been proposed by both academia and industry to enable usage control on disseminated data, i.e. to allow data originators to retain control over whom accesses their information, under which circumstances, and how it is used. This is often obtained by means of cryptographic techniques and thus by disseminating encrypted data that only trustworthy recipients can decrypt. Most of these solutions assume data recipients are connected to the network and able to contact remote policy evaluation authorities that can evaluate usage control policies and issue decryption keys. This assumption oversimplifies the problem by neglecting situations where connectivity is not available, as often happens in crisis management scenarios. In such situations, recipients may not be able to access the information they have received. Also, while using data, recipients and their applications can create new derived information, either by aggregating data from several sources or transforming the original data’s content or format. Existing solutions mostly neglect this problem and do not allow originators to retain control over this derived data despite the fact that it may be more sensitive or valuable than the data originally disseminated. In this thesis we propose an ERM architecture that caters for both derived data control and usage control in partially disconnected networks. We propose the use of a novel policy lattice model based on information flow and mandatory access control. Sets of policies controlling the usage of data can be specified and ordered in a lattice according to the level of protection they provide. At the same time, their association with specific data objects is mandated by rules (content verification procedures) defined in a data sharing agreement (DSA) stipulated amongst the organisations sharing information. When data is transformed, the new policies associated with it are automatically determined depending on the transformation used and the policies currently associated with the input data. The solution we propose takes into account transformations that can both increase or reduce the sensitivity of information, thus giving originators a flexible means to control their data and its derivations. When data must be disseminated in disconnected environments, the movement of users and the ad hoc connections they establish can be exploited to distribute information. To allow users to decrypt disseminated data without contacting remote evaluation authorities, we integrate our architecture with a mechanism for authority devolution, so that users moving in the disconnected area can be granted the right to evaluate policies and issue decryption keys. This allows recipients to contact any nearby user that is also a policy evaluation authority to obtain decryption keys. The mechanism has been shown to be efficient so that timely access to data is possible despite the lack of connectivity. Prototypes of the proposed solutions that protect XML documents have been developed. A realistic crisis management scenario has been used to show both the flexibility of the presented approach for derived data control and the efficiency of the authority devolution solution when handling data dissemination in simulated partially disconnected networks. While existing systems do not offer any means to control derived data and only offer partial solutions to the problem of lack of connectivity (e.g. by caching decryption keys), we have defined a set of solutions that help data originators faced with the shortcomings of current proposals to control their data in innovative, problem-oriented ways