CARMESH. Deliverable 1.1 Summary. Title: Modeling User Demand & Telematics Services

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1 CARMESH IAPP CARMESH Deliverable 1.1 Summary Title: Modeling User Demand & Telematics Services 1. Introduction In order to build the Carmesh system it is important to start with extensive system modeling, simulation and analysis. This would allow to capture the complex interactions between the end-user traffic demand, end-user mobility patterns, and the wireless mesh network capacity. This document will focus on the first two of the three topics mentioned above, which have direct influence on system s capacity. End-user service demand needs to be described using state-of-the-art models, which can predict service consumption over time by considering also peak and off-peak demand periods. End-user mobility should be described using accurate car mobility models, which take into consideration traffic lights, multiple lanes and speed differentiation. Using the resulting model it should be possible to generate a realistic car mobility pattern in a metropolitan area. The key objective of this report is also to characterize main telematics services, which will be offered in the Carmesh system. Appropriate modeling, simulation and emulation of the telematics services will be the base for the design of the supporting network level and service level mechanism. The goal is to test all the proposed solutions in an emulation environment, which will enable fine-tuning and testing in close to real conditions. 2. Telematics Services Characterisation One of the goals of the Carmesh system is to improve the safety on the roads through active, interactive, and regular safety announcements. The system may also provide an easy access to points of interest by combining location-based services with the navigation system. Another goal is to provide interfaces for local businesses to announce special events/offers to passing by cars. Dedicated services might be deployed to improve the driving experience around metropolitan areas through constant location-based traffic updates. On top of the above mentioned services, other entertainment and infotainment services might be delivered to the on-board units in each car. The Carmesh project will enable three main types of services: Safety announcement broadcasts: will enable reception of safety alerts and traffic updates from local traffic authorities in a timely fashion. This is one of the essential services for drivers, which can increase road safety and decrease traffic pollution. Location-based services: in which geo-localized service and commercial advertisements may be created and distributed to interested users. These personalized services will be beneficial for both users and merchants/content providers.

2 Infotainment content download and streaming: downloading infotainment data (e.g. audio, news or broadcast) from local or remote servers might be provided to end-users in the form of streaming or download. Figure 1 : Emulation setup For the initial testing and performance evaluation we have selected one exemplary application from each type of the service mentioned above: emergency VoIP calls from the safety applications group, location-based announcements from the second group and video streaming from the infotainment applications group. These three services were tested in an emulation environment using the ns-3 network simulator. In our research experiments we used three different computers to build the emulation testbed (Figure 1). Each computer hosted one important part of the end-to-end telematics service delivery system. One computer hosts the server-side (one or more server instances can be hosted on a single computer by using virtualization software - e.g. VirtualBox), the second computer hosts the simulated network topology used to enable emulation, and the third computer hosts user applications and services. Figure 2: Visualization of the simulation and the emulated system components

3 In our simulation scenario a mobile client was roaming in an area of a 3x3 mesh grid (as depicted in Figure 2). The iperf application was used on the client and server side to generate the traffic patterns, which correspond to different telematics services (location based announcements, emergency VoIP calls and video streaming). Each type of service was appropriately modeled and validated through tests using real network traffic. The results obtained in experiments have shown that all three types of services can be offered in the proposed system with good QoS levels. 3. User Demand Modeling In wireless networks it is important to rely on a solid idea of users demand dynamics and service consumption patterns in order to appropriately dimension network capacity and establish costconscious service pricing. In many cases researchers use different traffic models to simulate a saturation condition in the network to assess the theoretical performance and capacity limits in the system. Many works study the behavior of UDP flows or TCP flows in the system based on synthetic traffic in the network. There are also works that apply packet rate models, which use stochastic distributions such as Poisson, Pareto and Markov. Another approach is to record traces from a real system and use them to perform simulations of user demand modeling. This last approach can only be used when a real or prototype deployment of a given system exists. Due to the above mentioned constrain, this approach cannot be used in the Carmesh project and the most appropriate solution is to study the UDP and TCP flows generated in the system. The flows should be generated according to appropriate stochastic processes to emulate a realistic environment for traffic demand simulations. User demand modelling in wireless networks is strictly related to user mobility patterns, network topology and radio links conditions. End-user service consumption patterns in a system like Carmesh are very complex and depend on many factors: type of user (light user, medium user, heavy user); users location; speed of vehicles; service types and traffic characteristic of each service; client sessions parameters; popularity of different services. Types of end-users Types of Telematic services Light user model Medium user model Heavy user model Safety announcments Location based services Infotainment services Users modelling Modelling & experimentation Mobility modelling Network simulation Traffic paterns generation Statistical analysis Output Network traffic distribution and volumes Figure 3 : Carmesh system modeling

4 Figure 3 presents the simulation framework proposed for the Carmesh system modeling and analysis, which takes all the above factors into consideration. Using the proposed simulation framework it is possible to analyze and estimate user demand for different users density and intensity (heavy, medium, light users). The same simulation framework can also be used to analyze systems capacity under different conditions. All the performance results obtained through such simulations can be used for appropriate dimensioning and network resources planning. The results for capacity estimation sing the proposed framework will be presented in Deliverable D1.2 Analysis and Network Resources Dimensioning. 4. Mobility Pattern Characterisation Vehicular communication system must be designed with high mobility in mind. Aditionally different mobility scenarios should be simulated and evaluated during the design phase of the system. In order to make the tests as realistic as possible it is important to model car mobility in an accurate way. The mobility model used in a simulation should reflect as closely as possible the real behavior of vehicular traffic. There are many car mobility models, which can be used in simulations/emulations of vehicular communications. For the Carmesh system we have developed a method which uses three different tools to generate mobility patterns for the cars. SUMO (Simulation of Urban MObility) - an open-source road traffic simulation package designed to handle large road networks,; OpeenStreetMap - used to obtain the XML file containing the map information from a specified area on the map; TraNS Lite (Traffic and Network Simulation Environment), which serves as a link between the vehicular traffic simulator and the wireless network simulator. In order to demonstrate the above method we applied it for the main Carmesh use case scenario, which is based on the small part of Manhattan in New York. The area was selected based on grid-like topology which maps naturally into a wireless mesh network deployment. For the test scenario we have selected an area of around 0,065 square kilometers (240m by 270m) in downtown Manhattan. We have placed 16 access points to model a 4 by 4 grid. Each access point was spaced 80~100m from each other depending on physical deployment constraints (junctions, high buildings, etc). The placement of access points (red dots) and the selected Manhattan area are illustrated in Figure 4. Figure 4 : Manhattan scenario with a grid of 4x4 APs

5 The car mobility traces generated using Sumo and TraNS Lite were incorporated in NS-3 to recreate the car mobility patterns within the wireless mesh network simulator. Figure 5 presents the wireless network visualizer view from NS-3, which shows the movement of cars during the simulation. Red dots in Figure 5 represent mesh access points and the blue dots represent cars roaming within the mesh network area. Each car moves on the streets according to the traffic rules and follows a predefined realistic mobility pattern. Figure 5 : Vehicular communications simulation in NS-3 with car mobility