Vehicular cyber-physical systems are implemented to share taxi resource eciently using intensive algorithms running on telematics devices. However, due to the lack of social interactions, conventional systems are hard to improve user experience without considering passengers inner connections. In this paper, we propose an optimization scheme for these vehicular cyber-physical systems which integrate social interaction with real time street data to improve the sharing eciency and user experience. To answer the sharing requirement from potential passengers, our system allocates the taxi resource under the trade-o between cost and social interactions. We state and solve the sharing arrangement problem by computing a heuristic algorithm called SONETS to satisfy overwhelming requests from streets with limited taxi resource in peak time. e simulation results show that our algorithm can increase the integrated benet than other solutions.
Technological and market evolution motivates investigation into quantitative evaluation of performability of gas distribution networks. This paper proposes an approach for assessing the impact of multi-phased repair procedures, capturing time-variable load profiles for different classes of users, suspension of activities during non-working hours, and random execution times depending on topological, physical, and geographical characteristics of the network. The method interleaves fluid-dynamic analysis of the gas behavior and stochastic analysis of the time spent in the repair procedure, decoupling complexities and making stochastic analysis almost insensitive to the network size and topology, thus making application feasible for real scale cases. Moreover, by encompassing general (non-Markovian) distributions, the approach enables effective fitting of durational properties as emerging in each specific application context.
This article describes a system to facilitate dynamic en route formation of truck platoons with the goal of reducing fuel consumption. Safe truck platooning is a maturing technology which leverages modern sensor, control, and communication technology to automatically regulate the inter-vehicle distances. Truck platooning has been shown to reduce fuel consumption through slipstreaming by up to ten percent under realistic highway conditions. In order to further benefit from this technology, a platoon coordinator is proposed, which interfaces with fleet management systems and suggests how platoons can be formed in a fuel-efficient manner over a large region. The coordinator frequently updates the plans to react to newly available information. This way, it requires a minimum of information about the logistic operations. We discuss the system architecture in detail and introduce important underlying methodological foundations. Plans are derived in computationally tractable stages optimizing fuel savings from platooning. The effectiveness of this approach is verified in a simulation study. It shows that the coordinated platooning system can improve over spontaneously occurring platooning even under the presence of disturbances. A real demonstrator has also been developed. We present data from an experiment in which three vehicles were coordinated to form a platoon on public highways under normal traffic conditions. It demonstrates the feasibility of coordinated en route platoon formation with current communication and on-board technology. Simulations and experiments support that the proposed system is technically feasible and a potential solution to the problem of using truck platooning in an operational context.
Wireless sensor networks (WSNs) typically consist of nodes that collect and transmit data periodically. In this context, we are concerned with unacknowledged communication, i.e., where data packets are not confirmed upon successful reception. This allows reducing traffic on the communication channel --- neither acknowledgments nor retransmissions are sent --- and results in less overhead and less energy consumption, which are meaningful goals in the era of Internet of Things (IoT). On the other hand, packets can be lost and, hence, we do not know how long it takes to convey data from one node to another, which hinders any form of real-time operation and/or quality of service. To overcome this problem, we propose a medium access control (MAC) protocol, which consists in transmitting each packet at a random instant, but within a specified time interval from the last transmission. In contrast to existing approaches from the literature, the proposed MAC can be configured to meet reliability requirements --- given by the probability that at least one data packet reaches its destination within a specified deadline --- in the absence of acknowledgments. We illustrate this and other benefits of the proposed approach based on an detailed OMNeT++ simulation.
Z-Wave is a proprietary Internet of Things substrate providing distributed home and office automation services. The proprietary nature of Z-Wave devices make it difficult to determine the security aptitude of these devices. While there are a variety of open source tools for analyzing Z-Wave frames, inspecting non-volatile memory, and disassembling firmware, there are no dynamic analysis tools allowing one to inspect the internal state of a Z-Wave transceiver while it is running. In this work, a memory introspection capability is developed for the ZW0301, a Z-Wave transceiver device component found on many Z-Wave devices. The firmware image of a Z-Wave door lock is modified to include the memory introspection capability, allowing both volatile and non-volatile memory of the transceiver module to be remotely extracted over the Z-Wave communication protocol. The memory introspection capability is applied to several reverse engineering activities requiring access to volatile memory. The stack memory is analyzed to determine the sequence of function calls leading up to the introspection code. The buffers used for holding incoming and outgoing Z-Wave communication frames are identified. By combining memory introspection with static analysis, several algorithms used by the Z-Wave security layer are revealed and validated. The memory locations of several encryption keys are also located in memory.