Performance of a connectionless protocol over ATM

Recent studies show the existence of a demand for a connectionless broadband service. In order to cope with this demand, a connectionless protocol for the B-ISDN needs to be designed. Such a protocol should make use of ATM and the ATM Adaptation Layer. It needs to specify destination and bandwidth of connections to the ATM network without advance knowledge of the traffic that has to be transferred over these connection. A possible mechanism which can cope with this problem, the 'On-demand Connection with Delayed Release' (OCDR) mechanism, is described. Its eficient operation is based on the assumption that there exists a certain correlation between subsequently arriving CL packets. Two different arrival processes are used to evaluate the performance of the OCDR mechanism: a Poisson arrival process, and a Markov Modulated Poisson Process (MMPP) which models a bursty trafic source. Markov models of the OCDR mechanism have been constructed for both arrival processes. For the madel with Poisson arrivals, a closed form solution is presented. The model with MMPP arrivals is solved numerically.\ud Compared to a 'Permanent Connection' mechanism significant bandwidth reductions can be obtained provided that the offered trafic has a bursty nature. Furthermore, the OCDR mechanism has the advantageous property that the obtained average node delay is not strongly related to the intensity and burstiness of the offered trafic

Effective Scheduling for Coded Distributed Storage in Wireless Sensor Networks

A distributed storage approach is proposed to access data reliably and to cope with node failures in wireless sensor networks. This approach is based on random linear network coding in combination with a scheduling algorithm based on backpressure. Upper bounds are provided on the maximum rate at which data can be reliably stored. Moreover, it is shown that the backpressure algorithm allows to operate the network in a decentralized fashion for any rate below this maximum

Improving Operational Efficiency In EV Ridepooling Fleets By Predictive Exploitation of Idle Times

In ridepooling systems with electric fleets, charging is a complex decision-making process. Most electric vehicle (EV) taxi services require drivers to make egoistic decisions, leading to decentralized ad-hoc charging strategies. The current state of the mobility system is often lacking or not shared between vehicles, making it impossible to make a system-optimal decision. Most existing approaches do not combine time, location and duration into a comprehensive control algorithm or are unsuitable for real-time operation. We therefore present a real-time predictive charging method for ridepooling services with a single operator, called Idle Time Exploitation (ITX), which predicts the periods where vehicles are idle and exploits these periods to harvest energy. It relies on Graph Convolutional Networks and a linear assignment algorithm to devise an optimal pairing of vehicles and charging stations, in pursuance of maximizing the exploited idle time. We evaluated our approach through extensive simulation studies on real-world datasets from New York City. The results demonstrate that ITX outperforms all baseline methods by at least 5% (equivalent to $70,000 for a 6,000 vehicle operation) per week in terms of a monetary reward function which was modeled to replicate the profitability of a real-world ridepooling system. Moreover, ITX can reduce delays by at least 4.68% in comparison with baseline methods and generally increase passenger comfort by facilitating a better spread of customers across the fleet. Our results also demonstrate that ITX enables vehicles to harvest energy during the day, stabilizing battery levels and increasing resilience to unexpected surges in demand. Lastly, compared to the best-performing baseline strategy, peak loads are reduced by 17.39% which benefits grid operators and paves the way for more sustainable use of the electrical grid

Connect & Drive: design and evaluation of cooperative adaptive cruise control for congestion reduction

Road throughput can be increased by driving at small inter-vehicle time gaps. The amplification of velocity disturbances in upstream direction, however, poses limitations to the minimum feasible time gap. This effect is covered by the notion of string stability. String-stable behavior is thus considered an essential requirement for the design of automatic distance control systems, which are needed to allow for safe driving at time gaps well below 1 s. Using wireless inter-vehicle communications to provide real-time information of the preceding vehicle, in addition to the information obtained by common Adaptive Cruise Control (ACC) sensors, appears to significantly decrease the feasible time gap, which is shown by practical experiments with a test fleet consisting of six passenger vehicles. The large-scale deployment of this system, known as Cooperative ACC (CACC), however, poses challenges with respect to the reliability of the wireless communication system. A solution for this scalability problem can be found in decreasing the transmission power and/or beaconing rate, or adapting the communications protocol. Although the main CACC objective is to increase road throughput, the first commercial application of CACC is foreseen to be in truck platooning, since short distance following is expected to yield significant fuel savings in this case