發(fā)布時間：2019-07-03 20:10

【摘要】：為了解決P2P網(wǎng)絡(luò)系統(tǒng)中節(jié)點頻繁退出和加入引起的系統(tǒng)數(shù)據(jù)信息誤差,并針對數(shù)據(jù)獲取對中心節(jié)點依賴度較大和系統(tǒng)中節(jié)點的數(shù)據(jù)信息獲取不完整等問題,提出了進(jìn)化算法迭代優(yōu)化的P2P網(wǎng)絡(luò)信任模型。首先將P2P網(wǎng)絡(luò)系統(tǒng)中節(jié)點數(shù)據(jù)信息獲取的系統(tǒng)信任度估計模型轉(zhuǎn)化為從源節(jié)點到目標(biāo)節(jié)點最優(yōu)信任關(guān)系的路徑尋優(yōu)問題;然后利用改進(jìn)的粒子群算法對信任關(guān)系路徑方案進(jìn)行粒子映射,并通過對粒子粒距聚集度和粒子信息熵進(jìn)行計算而修正粒子權(quán)值,再對粒子局部最優(yōu)解和全局最優(yōu)解進(jìn)行更新;最后迭代的對信任關(guān)系路徑解空間中的最優(yōu)解進(jìn)行搜索,并對最優(yōu)路徑的節(jié)點進(jìn)行推薦信任度加權(quán)。仿真結(jié)果表明,改進(jìn)算法具有較好的收斂速度和較強的有效性,且當(dāng)節(jié)點跳級數(shù)較少時,可使系統(tǒng)數(shù)據(jù)信息估算獲得最優(yōu)的系統(tǒng)信任度。
[Abstract]:In order to solve the error of system data information caused by frequent withdrawal and addition of nodes in P2P network system, and aiming at the problems of high dependence of data acquisition on central node and incomplete acquisition of data information of nodes in system, an iterative optimization P2P network trust model based on evolutionary algorithm is proposed. Firstly, the system trust estimation model obtained by node data information in P2P network system is transformed into the path optimization problem of optimal trust relationship from source node to target node, then the improved particle swarm optimization algorithm is used to map the trust relationship path scheme, and the particle weight is modified by calculating the particle distance aggregation degree and particle information entropy, and then the local optimal solution and global optimal solution of particles are updated. Finally, the optimal solution in the solution space of trust relationship path is searched iteratively, and the recommended trust degree of the node of the optimal path is weighted. The simulation results show that the improved algorithm has good convergence speed and strong effectiveness, and when the number of node hops is small, the system data information estimation can obtain the optimal system trust.
【作者單位】： 山西大學(xué);南京理工大學(xué);
【分類號】：TP393.02

【參考文獻(xiàn)】

相關(guān)期刊論文 前3條

1 陽春華;谷麗姍;桂衛(wèi)華;;自適應(yīng)變異的粒子群優(yōu)化算法[J];計算機工程;2008年16期

2 劉濤;;無線傳感器網(wǎng)絡(luò)簇頭節(jié)點分配固定聚簇算法研究[J];科技通報;2012年10期

3 黃澤霞;俞攸紅;黃德才;;慣性權(quán)自適應(yīng)調(diào)整的量子粒子群優(yōu)化算法[J];上海交通大學(xué)學(xué)報;2012年02期

【共引文獻(xiàn)】

相關(guān)期刊論文 前10條

1 王正帥;鄧喀中;;老采空區(qū)殘余沉降的GM-Markov預(yù)測模型研究[J];大地測量與地球動力學(xué);2010年06期

2 錢偉懿;王艷杰;;帶自適應(yīng)壓縮因子粒子群優(yōu)化算法[J];遼寧工程技術(shù)大學(xué)學(xué)報(自然科學(xué)版);2010年05期

3 張s，

本文編號：2509632