1 / 6

CoMob: A Scenario Focusing on Pervasiveness, Distribution, and Scale

This scenario focuses on the pervasive and distributed nature of cooperative mobility, where individuals use GPS-equipped phones to collect traffic information, predict future traffic, and coordinate with others to avoid congestion. The scenario also explores the use of sensors, traffic lights, and collaborative applications to enhance traffic management and optimize routes.

hharden
Download Presentation

CoMob: A Scenario Focusing on Pervasiveness, Distribution, and Scale

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. CoMob: A Scenario Focusing on Pervasiveness, Distribution, and Scale Gianpaolo Cugola & Matteo Rossi DeepSE Group Dipartimento di Elettronica e Informazione Politecnico di Milano, Italy

  2. Why a new scenario • We feel the need of a scenario centered around pervasiveness, ubiquity, strong distribution, coordination without centralized control • Typical domains: p2p applications, WSNs, IoT, ... • Scenarios centered on services and service-oriented computing stress a different form of distribution and a different kind of dynamics • Clearly, we need both kind of scenarios. Possibly, but not necessarily, integrated together in a single “macro-scenario” Meeting on scenarios

  3. CoMob: Cooperative Mobility • People roam around with their gps-equipped phone • Collect information about current traffic (along their route) based on the position of others (FCD) • Collect information about others’ route to predict future traffic • Coordinate with others to avoid future jams Meeting on scenarios

  4. CoMob: An analysis • Good • Strong distribution • Large scale • Ubiquitous • Dynamic • Discourages centralized solutions (efficiency, administrative issues) • Game theory may suggest optimal solution with zero coordination • Small (limited) devices • Bad • Fixed requirements • No “open-world” • Small devices but not “really small” Meeting on scenarios

  5. Per-CoMob • Sensors (pressure, cameras, ...) build a WSN that contribute information about traffic • Traffic lights contribute controlling routes and limiting traffic jams • Drivers may prefer a route if they know they will “sync” with green • But they must coordinate – the number of cars on a street determines the average speed Meeting on scenarios

  6. Open-CoMob • Before getting in the street, people define what cooperative application they want to run (e.g., a tourist might want to maximize the number of locations visited) • The system builds the application by setting up a collaboration with other devices • E.g., with devices of other people belonging to a community “tourists”, to determine at what time it is best to visit a monument Meeting on scenarios

More Related