/TrajEdge

The source code for the paper "TrajEdge: An Efficient and Lightweight Trajectory Data Analysis Framework in Edge Environment".

Primary LanguageJava

TrajEdge: An Efficient and Lightweight Trajectory Data Analysis Framework in Edge Environment

Introduction

This repository holds source code for the paper "TrajEdge: An Efficient and Lightweight Trajectory Data Analysis Framework in Edge Environment".

Environment Preparation

  • Java 11
  • Docker
  • CentOS 7.0

To set a edge simulated environment, you need to install Docker first, then configure the virtual network:

docker network create --driver bridge my-bridge-network

Then you can use tcconfig to set the network latency and bandwidth between docker container.

tcset eth0 --delay 100ms --rate 100Kbps --network 192.168.0.10

Datasets Description

We use 2 publicly available real-world trajectory and road map data, which can be obtained from Geolife, T-Drive. And the synthetic dataset of Oldenburg can be generated in LINK.

Usage

  1. Prepare your trajectory data like below:

    [Lat] [Lng] [TimeStamp]

    Each column is separated by a blank.

  2. Modify your data loader class in directory Spout

  3. Pack the project into fat jar TrajEdge.jar using Maven

  4. Run the topology TrajectoryUploadTopology to store trajectory data

    java -jar TrajEdge.jar --classpath org.example.TrajectoryUploadTopology

  5. Run the query topology, including TrajectoryIdQueryTopology , TrajectorySpacialRangeQueryTopology and TrajectoryTimeRangeQueryTopology.