Traffic simulations are becoming a standard way to study urban mobility patterns, to evaluate new traffic policies and to test modern vehicular technologies. For this reason, in recent years, mobility projects pushed ...
Traffic simulations are becoming a standard way to study urban mobility patterns, to evaluate new traffic policies and to test modern vehicular technologies. For this reason, in recent years, mobility projects pushed towards an increase in the demand of traffic simulators and towards an extension of their area of investigation, aiming at covering a whole city and its suburbs. In this paper we describe the methodology we followed in the creation of a large-scale traffic simulation of a 400-Km 2 area around the Municipality of Turin. Our preliminary results demonstrate that a complete modeling of such a wide tool is possible at the expense of minor simplifications.
Several issues related to Smart City development require the knowledge of accurate human mobility models, such as in the case of urban development planning or evacuation strategy definition. Nevertheless, the exploita...
Several issues related to Smart City development require the knowledge of accurate human mobility models, such as in the case of urban development planning or evacuation strategy definition. Nevertheless, the exploitation of real data about users' mobility results in severe threats to their privacy, since it allows to infer highly sensitive information. On the contrary, the adoption of simulation tools to handle mobility models allows to neglect privacy during the design of location-based services. In this work, we propose a simulation tool capable of generating synthetic datasets of human mobility traces; then, we exploit them to evaluate the effectiveness of algorithms which aim to detect Points of Interest visited by users of a Smart Campus. Our simulator exploits an activity-based mobility model, thus it is based on the assumption that mobility of campus users is motivated by the activities they plan to perform. It is capable of simulating the weekly repetitiveness of human behavior and to model different mobility profiles for each day of the week through a fifth-order Markov model.
In this paper we explain how the isolation or decoupling of actors can help in developing efficient analysis techniques. The Reactive Object Language, Rebeca, and its timed extension are introduced as actor-based lang...
In this paper we explain how the isolation or decoupling of actors can help in developing efficient analysis techniques. The Reactive Object Language, Rebeca, and its timed extension are introduced as actor-based languages for modeling and analyzing distributed systems. We show how floating-time transition system can be used for model checking of timed actor models when we are interested in event-based properties, and how it helps in state space reduction. We explain how the model of computation of actors helps in devising an efficient state distribution policy in distributed model checking. We show how we use Rebeca to verify the routing algorithms of mobile adhoc networks. The paper is written in a way to make the ideas behind each technique clear such that it can be reused in similar domains.
In this paper, we describe a fair comparison of the performance of a microscopic road traffic simulation performed on a GPU and on a CPU. The aim of our work is to determine the speedup, which can be achieved if the G...
In this paper, we describe a fair comparison of the performance of a microscopic road traffic simulation performed on a GPU and on a CPU. The aim of our work is to determine the speedup, which can be achieved if the GPU is used for the same simulation instead of the (multi-core) CPU. A microscopic road traffic simulator capable of running on both platforms was created for this purpose with the aim to make the GPU-based and the CPU-based simulations as similar as possible. The performances of both the GPU-based and the CPU-based simulations were tested using two different road traffic models (a car-following model and a cellular automaton model), four road traffic networks (regular square grids of crossroads) of different sizes, and three different hardware configurations. The maximal achieved speedup using the GPU instead of the multi-core CPU for the cellular automaton model was 12.4. For the car-following model, the maximal achieved speedup was 10.7.
The advancements in mobile hardware and network technologies facilitate the processing power, storage capability, and connection quality. Such developments enable sophistic functions, ubiquitous power- and bandwidth-h...
The advancements in mobile hardware and network technologies facilitate the processing power, storage capability, and connection quality. Such developments enable sophistic functions, ubiquitous power- and bandwidth-hungry applications that fundamentally changes the individual's lifestyle. Although Cloud Computing technologies have already been leveraged to coordinate with the capability and battery-constraint mobile User Equipment (UE), the long-distance propagation delay downgrades the network QoS and user QoE. In this paper, we propose a queueing-based Mobile Edge Computing (MEC) model that concerns the offloading procedure, especially in the time-constraint scenarios. A queueing model is proposed for the offloading process, considering the dynamic network queueing delay. A heuristic scheduling model is designed to maximize the offloading energy and execution efficiency. A regression prediction model is implemented to achieve dynamic resource allocation. In the experiment, the proposed model is compared to the recent studies, and the results indicate that the proposed model can outperform the current studies in terms of execution time and energy reservation.
It is not an entirely trivial matter to ensure the security of VoIP services and analyze attacks on telecommunication solutions the possible gains of which are attracting a growing number of active attackers. In many ...
It is not an entirely trivial matter to ensure the security of VoIP services and analyze attacks on telecommunication solutions the possible gains of which are attracting a growing number of active attackers. In many situations, it is necessary to detect and analyze these attacks, monitor their progress and then prepare an effective defence against them. The best way how to detect attacks on VoIP infrastructure is by implementing VoIP honeypot. To attract the highest number of attackers possible, our VoIP honeypots create fake VoIP traffic among themselves. This feature is based on a Markov chains principle. In this paper, we provide a complete implementation of a SIP emulation model which ensures the exchange process of SIP signaling messages between the honeypots.
Synthetic workloads are commonly used to exercise simulation tools for performance, performance tuning, and scalability studies. Sometimes these workloads are simple streams of test data following various distribution...
Synthetic workloads are commonly used to exercise simulation tools for performance, performance tuning, and scalability studies. Sometimes these workloads are simple streams of test data following various distributions and in other cases these workloads are generated by more complex, configurable systems. An example of the former is a stream of input events at different arrival rates that might be used to test the performance of an event queue data structure. An example of the latter is the PHOLD simulation model that is often used to contrast the performance implications of different design solutions in a parallel simulation engine. One of the key challenges for synthetic workloads is the question of setting the parameters so that the workload properly reflects the behavior of actual workloads. This paper collects profile data from multiple real-world discrete-event simulation models in multiple configurations and sizes from the ROSS and WARPED2 repositories. A principle focus of this paper is the capture and reporting of profiling data to understand event granularities and event profile data to assist in the configuration of synthetic discrete event model generators.
Unmanned Aerial Vehicles (UAVs) can act as re-lays in areas with limited infrastructure to support car-to-car communications. Prior studies on UAV-to-car communications showed that the irregularity of the terrains has...
Unmanned Aerial Vehicles (UAVs) can act as re-lays in areas with limited infrastructure to support car-to-car communications. Prior studies on UAV-to-car communications showed that the irregularity of the terrains has a significant impact on link quality. Thus, in this paper, we propose a positioning technique that relies on Particle Swarm optimization (PSO) to optimize the positioning of a UAV in the vehicular environment by considering the irregularities of the terrains that might hinder Line-of-Sight (LOS) conditions. The proposed technique takes into account the path loss caused by the terrains. simulation results show that the optimization algorithm allows us to determine the best position for the deployed UAVs throughout time by considering the movement of the cars, and also accounting for adjustments in terms of flight altitude. In particular, the latter is adjusted by considering the position of the cars on the ground and the profile of surrounding terrains to determine potential communications blockages, while respecting international regulations regarding flight altitude restrictions.
Mobility as a Service (MaaS) implies the integration of different transport services in a unique platform accessible by commuters on demand. Collection and processing of data concerning the mobility of customers is cr...
Mobility as a Service (MaaS) implies the integration of different transport services in a unique platform accessible by commuters on demand. Collection and processing of data concerning the mobility of customers is crucial to calculate trips options satisfying users' needs and preferences. In this paper, we propose to exploit Multi-access Edge Computing (MEC) facilities to more efficiently deploy MaaS solutions. Specifically, we design a MEC-based MaaS framework that is fully compliant with the Open Mobile Alliance (OMA) Lightweight Machine-to-Machine (LwM2M) protocol. The OMA LwM2M server hosted in the MEC platform continuously collects data from the commuters, and uses native MEC applications to provide value-added services. The OBSERVE extension of the Constrained Application Protocol (CoAP) is used to reduce energy consumption during data collection from the OMA LwM2M clients installed in the mobile user devices. Preliminary results are collected that show the performance of the proposed MaaS framework, integrated with a mobility generator tool (i.e., SUMO) that emulates the commuter paths.
作者:
Azzedine BoukercheFiEEE. FEiC
FCAE FAAAS Distinguished University Professor Canada Research Chair Tier-1 Scientific Director of DIVA Strategic Research Network Director of CREATE-TRANSIT Network University of Ottawa Canada
Every year, natural and human-induced disasters result in infrastructural damages, monetary costs, distresses, injuries and deaths. Unfortunately, climate change is strengthening the destructive power of natural disas...
Every year, natural and human-induced disasters result in infrastructural damages, monetary costs, distresses, injuries and deaths. Unfortunately, climate change is strengthening the destructive power of natural disasters. In this context, distributedsimulation-based disaster management and response systems have been proposed to cope with disasters and emergencies by training first responder with the latest ICT technology, and improving the disaster detection and search/rescue missions during disaster response. With the recent advances in wireless communication, and the proliferation of portable computer and micro-sensor devices, we are witnessing a growing interest in using wireless multimedia sensor networks and collaborative virtual environment technologies for safety and security class of applications. In this talk, we will give an overview of some research projects related to smart emergency preparedness and response that are currently being investigated at the PARADISE Research Laboratory at the Ottawa. We will show how collaborative virtual environment, context aware computing, wireless multimedia, and wireless sensor networks can be used to ensure public safety and security. We will focus upon the design of large-scale distributedsimulation system for applications that require critical condition monitoring using both location/context aware computing and wireless sensor technologies. The second part of the talk will conclude by presenting two testbeds that are currently under development at PARADISE: the LIVE testbed, and the SWiMNet testbed. LIVE is a testbed for applications that require emergency preparedness and response. LIVE's architecture integrates wireless sensor networks with wireless multimedia and virtual environment technologies. SWiMNet is a testbed of a high-performance simulation system that supports very detailed and realistic model specifications to enable the design and evaluation of new protocols and applications for future generations o
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