基於群眾感知的平台架設 - 應用於行動通訊資料處理與分析

Design and Development of Crowd-Sensing Platform for Mobile Communication Data Processing and Analysis

李宜珊(Yi-Shan Li)

指導教授 ： 陳志成

國立交通大學/資訊學院/網路工程研究所/碩士(2017年)

摘要

在網路普及的時代，人們對於網路的使用與需求與日俱增，人們透過智慧型裝置連上行動網路(3G/4G)的需求也不斷增加，下世代行動網路(5G)研究希望能夠依照使用者不同的需求做資源分配，但網路最佳化需要有大量數據資料作為決策的依據，而電信商通常會將搜集到的數據資料作為商業保密，不對外公開，造成網路相關數據資料不易取得，因此我們希望藉由建立一個資料搜集平台，讓任何研究者皆可以從此平台獲得所需的資料。
Crowd Measurement (CM)透過群眾感知的概念，收集並整合多樣化的數據資料，並將這些巨量資料公開給群眾下載使用，並開放平台的原始碼供相關研究者參考。在本篇論文中，提出一個分類演算法，分類出高鐵資料，並分析不同電信商的高鐵數據，如高鐵訊號地圖、高鐵基地台平均停留時間。除了分析高鐵資料之外，也展示訊號強度、換手、移動速度、應用程式網路流量等等數據。

關鍵字

群眾感知 ； 移動群眾感知 ； 訊號測量 ； 行動通訊資料

並列摘要

Nowadays, mobile networks play important roles in our daily live. For the design of next generation telecom networks (5G), it is critical to analyze the behaviors of mobile users. Mobile data are so privacy and precious, so telecom operators/carriers do not want to share it. Therefore, it is hard to get mobile data of users from the operators. To solve the problem, we propose a crowdsensing based platform named Crowd Measurement (CM), which is built to collect data from mobile users voluntarily around the world. The data collected is stored in database anonymously and is open to public for everyone who is interested in getting it. In this thesis, we propose an algorithm to classify data in Taiwan High Speed Rail. We demonstrate the results by drawing signal map and cell residence time distribution in different operators. We also demonstrate the figures of signal strengths, handover, and network utilization from collected data.

並列關鍵字

crowd-sensing ； mobile crowd-sensing ； signal measurement ； mobile communication data

參考文獻

[1] Tingting Li, Jun Liu, Zhenming Lei, "Characterizing Service Providers Traffic of Mobile Internet Services in Cellular Data Network," Intelligent Human-Machine Systems and Cybernetics, IEEE 5th International Conference, vol. 1, pp. 134-139, 2013.

[2] Kan Zheng,Zhe Yang,Kuan Zhang, "Big data-driven optimization for mobile networks toward 5G," IEEE Network, pp. 44 - 51, 25 January 2016.

[3] J. Surowiecki, The Wisdom of Crowds:Why the Many Are Smarter Than the Few and How Collective, Knopf Doubleday Publisher., 2005.

[4] Willian Zamora, Carlos T. Calafate, Juan-Carlos Cano, and Pietro Manzoni, “A Survey on Smartphone-Based Crowdsensing Solutions,” Mobile Information Systems, 2016.

[5] Jinghao Shi, Lei Meng, Aaron Striegel, “A walk on the client side: Monitoring enterprise Wifi networks using smartphone channel scans,” Computer Communications, IEEE INFOCOM 2016, 2016.