دانلود رایگان مقاله تشخیص توزیع مبتنی بر توافق با کاهش بخش های مجزا برای شبکه های حسگر بی سیم

Abstract

In wireless sensor networks, intruders can manipulate some sensors’ observations locally, which results in outliers in distributed detection. These outliers can be detected and removed by a fusion centre as all the sensors’ observations are available. For wireless sensor networks without a fusion centre, however, the detection performance can be significantly degraded as distributed consensus algorithms are vulnerable to outliers. In this paper, we consider the outlier detection for wireless sensor networks without a fusion centre when a distributed consensus algorithm is employed for distributed detection.

VI. CONCLUDING REMARKS

We studied outlier detection for WSNs when consensusbased distributed detection algorithms are used. Since central processing is not available, each sensor node has to perform outlier detection with an iterative distributed detection algorithm. We showed that the proposed two-step approach for the outlier detection can effectively detect the presence of outliers within a WSN and mitigate them at each sensor level without central processing. Through simulation results, we have observed that the performance of the outlier detection decides the performance of target detection in the second run of the iterative distributed detection algorithm. Furthermore, it was shown that the performance of target detection after removing outliers is improved as PU , the probability of intruders, increases.