https://github.com/ZJU-DAILY/TrajEdge
The source code for the paper "TrajEdge: An Efficient and Lightweight Trajectory Data Analysis Framework in Edge Environment".
https://github.com/ZJU-DAILY/TrajEdge
Last synced: 27 days ago
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The source code for the paper "TrajEdge: An Efficient and Lightweight Trajectory Data Analysis Framework in Edge Environment".
- Host: GitHub
- URL: https://github.com/ZJU-DAILY/TrajEdge
- Owner: ZJU-DAILY
- Created: 2024-07-30T08:28:10.000Z (almost 2 years ago)
- Default Branch: master
- Last Pushed: 2024-11-28T16:48:55.000Z (over 1 year ago)
- Last Synced: 2024-11-28T17:26:20.235Z (over 1 year ago)
- Language: Java
- Homepage:
- Size: 18.2 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-java - TrajEdge
README
# 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
- Docker Compose
- CentOS 7.0
To set a edge simulated environment, you need to install Docker first, then configure the docker cluster:
```bash
cd TrajEdge
docker-compose up -d
```
Then you will get a cluster of storm in docker container.
Next you can use [tcconfig](https://tcconfig.readthedocs.io/en/latest/pages/usage/tcset/index.html#basic-usage) to set the network latency and bandwidth between docker container for better simulated the edge-to-edge and edge-to-cloud communication.
```bash
tcset eth0 --delay 100ms --rate 100Kbps --network 192.168.0.10
```
BTW, we also provide detailed scripts for configuring the network by running:
```bash
chmod +x ./scripts/configureNetwork.sh & ./scripts/configureNetwork.sh
```
Last, you need to run `python ./scripts/allocateNode.py` for mapping the external node into edge device.
## Datasets Description
We use 2 publicly available real-world trajectory and road map data, which can be obtained from [Geolife](https://research.microsoft.com/en-us/projects), [T-Drive](http://www.geolink.pt/ecmlpkdd2015-challenge/dataset.html). And the synthetic dataset of Oldenburg can be generated in [LINK](https://research.microsoft.com/en-us/projects).
Don't forget to upload your data to all docker container in cluster by using:
```bash
chmod +x ./scripts/copyData.sh & ./scripts/copyData.sh
```
## 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-storage.jar` and `TrajEdge-stream.jar` using Maven
4. Set up the storage cluster of TrajEdge
```bash
chmod +x ./scripts/deployStorage.sh & ./scripts/deployStorage.sh
```
5. Copy the jar to docker and run the topology `TrajectoryUploadTopology` to store trajectory data
```bash
docker cp ./TrajEdge-stream/target/TrajEdge-stream-1.0-SNAPSHOT.jar nimbus:/opt/storm/lib/
docker exec -it nimbus storm jar /opt/storm/lib/TrajEdge-stream-1.0-SNAPSHOT.jar org.example.TrajectoryUploadTopology test-1 true 1000
```
6. Run the query topology, including `TrajectoryIdQueryTopology` , `TrajectorySpacialRangeQueryTopology`, `TrajectoryTimeRangeQueryTopology` and `TrajectorykNNQueryTopology`.
```bash
# ID temporal
docker exec -it nimbus storm jar /opt/storm/lib/TrajEdge-stream-1.0-SNAPSHOT.jar org.example.TrajectoryIdQueryTopology 1 0 8 geolife
# space range
docker exec -it nimbus storm jar /opt/storm/lib/TrajEdge-stream-1.0-SNAPSHOT.jar org.example.TrajectorySpacialRangeQueryTopology 1 true 1 geolife
# space time range
docker exec -it nimbus storm jar /opt/storm/lib/TrajEdge-stream-1.0-SNAPSHOT.jar org.example.TrajectorySpacialTemporalRangeQueryTopology 1 8 geolife
# k-nn
docker exec -it nimbus storm jar /opt/storm/lib/TrajEdge-stream-1.0-SNAPSHOT.jar org.example.TrajectorykNNQueryTopology 1 true 8 geolife 1
```
## Citation
If you use our code for research work, please cite our paper as below:
```
@article{,
title={TrajEdge: An Efficient and Lightweight Trajectory Data Analysis Framework in Edge Environment},
author={Changhao He, Ziquan Fang, Linsen Li, Yunjun Gao},
year={2025},
}
```