基于信譽(yù)機(jī)制的分布式擴(kuò)散最小均方算法
doi: 10.11999/JEIT140851
基金項(xiàng)目:
國(guó)家自然科學(xué)基金(61271276, 61301091)，陜西省國(guó)際合作項(xiàng)目(2013KW01-03)，工業(yè)和信息化部通信軟科學(xué)項(xiàng)目(2014R33)和陜西省自然科學(xué)基金(2014JM8299)資助課題
Distributed Diffusion Least Mean Square Algorithm Based on the Reputation Mechanism
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摘要: 非安全環(huán)境中的無(wú)線傳感器網(wǎng)絡(luò)(WSN)可能存在惡意攻擊節(jié)點(diǎn)，惡意節(jié)點(diǎn)將會(huì)篡改其觀測(cè)數(shù)據(jù)以影響參數(shù)估計(jì)的準(zhǔn)確性。為此，該文提出基于信譽(yù)機(jī)制的分布式擴(kuò)散最小均方(R-dLMS)算法和擴(kuò)散歸一化最小均方(R-dNLMS)算法。該算法能夠根據(jù)各節(jié)點(diǎn)對(duì)整個(gè)網(wǎng)絡(luò)參數(shù)估計(jì)的貢獻(xiàn)來(lái)設(shè)置相應(yīng)的信譽(yù)值，從而減小惡意節(jié)點(diǎn)對(duì)網(wǎng)絡(luò)攻擊的影響。仿真結(jié)果表明，與無(wú)信譽(yù)值的算法相比，該算法的性能得到大幅度提高，且R-dNLMS算法在R-dLMS算法的基礎(chǔ)上，算法性能得到進(jìn)一步提升。
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關(guān)鍵詞:
- 無(wú)線傳感器網(wǎng)絡(luò) /
- 惡意攻擊 /
- 分布式 /
- 擴(kuò)散最小均方 /
- 信譽(yù)值
Abstract: To deal with the problem of signal estimation for Wireless Sensor Networks (WSN) in a untrustworthy environment where malicious nodes tamper the measured data, two reputation-based algorithms, that are, Reputation-based diffusion Least Mean Square (R-dLMS) algorithm and Reputation-based diffusion Normalized Least Mean Square (R-dNLMS) algorithm, are proposed. The proposed algorithms could assign the appropriate reputation value to each node according to its contribution to the whole network, and minimize the reputation value of malicious nodes to lower the impact of malicious nodes in the network. Simulation results show that the proposed algorithms can greatly improve the performance compared with the one without reputation value, and the performance of R-dNLMS algorithm has been further improved based on R-dLMS algorithm. -
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