參與者信譽度感知的MCS數據收集機制

楊靜; 李鵬程; 閆俊杰

doi:10.13374/j.issn2095-9389.2017.12.020

參與者信譽度感知的MCS數據收集機制

doi: 10.13374/j.issn2095-9389.2017.12.020

楊靜^1,2,
李鵬程^1,2, ,,
閆俊杰^1,2

1) 重慶郵電大學通信與信息工程學院, 重慶 400065
2) 重慶郵電大學光通信與網絡重點實驗室, 重慶 400065

基金項目:

國家自然科學基金資助項目（61371097，61271261）；重慶市青年科技人才培養計劃資助項目（CSTC2014KJRC-QNRC40001）；重慶高校創新團隊建設計劃資助項目（CXTDX201601020）

詳細信息

中圖分類號: TP393.04
計量
- 文章訪問數: 638
- HTML全文瀏覽量: 205
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- 被引次數: 0
出版歷程
- 收稿日期: 2017-01-15

MCS data collection mechanism for participants' reputation awareness

YANG Jing^1,2,
LI Peng-cheng^{1,2
, ,},
YAN Jun-jie^1,2

1) School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
2) Key Laboratory of Optical Communication and Networks, Chongqing University of Posts and Telecommunications, Chongqing 400065, China

摘要

摘要: 在群智感知（mobile crowd sensing，MCS）數據收集過程中，任務參與者的惡意行為能夠顯著降低感知結果的真實性.為解決此問題，提出了一種參與者信譽度感知的數據收集機制，通過意愿程度和數據質量分析信任狀態、量化歷史信譽度，進而，根據邏輯回歸模型動態更新參與者當前信譽度.同時，為準確衡量感知數據可信程度，利用剩余可發送時間和移動設備剩余能量將參與者分為直接發送和間接轉發兩類，從而在多任務并發場景下，服務器根據結果合理地選擇任務參與者，達到準確可靠收集感知數據的目的.結果表明所提出數據收集機制能大幅度提升感知任務實時性，顯著提高感知數據質量，有效降低服務器總獎勵開銷.
- 群智感知 /
- 數據收集 /
- 參與者信譽度 /
- 信任狀態 /
- 多任務并發場景
Abstract: Task participants' malicious behavior can significantly reduce the credibility of mobile crowd sensing (MCS). To solve this problem, this paper proposed a data collection mechanism that analyzed and quantified participants' historical reputation according to their willingness and the quality of data they had shared, and then updated their current reputation through the logistic regression model. Simultaneously, to measure the authenticity of the collected data, the participants were divided into two types:those who were related to direct transmission of sensing data and second, those who were involved in indirect forwarding of these, which was based on the remaining transmission time of sensing data and residual energy of mobile equipment. Then the server analyzed the accuracy of data collected by participants according to the multitasking scenario. Simulation results show that the proposed mechanism can significantly improve the perceived tasks performed in real time, greatly upgrade the quality of sensing data, and effectively reduce the reward expenses.
- mobile crowd sensing (MCS) /
- data collecting /
- participant's reputation /
- reputation state /
- multitasking scenario

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參考文獻(24)

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