How to improve the efficiency with security with the extension of lifetime of sensor nodes is the interesting area in the field of Heterogeneous Wireless Sensor Network (WSN). Key management is also an important concept of any secure communication. Expiring secure connections cause that connectivity in network decrease. For decreasing effect of compromising a node on expiring secure connections. The heterogeneity among sensor nodes help provides scalability, notable energy efficiency and security benefits. The previous protocol uses both probabilistic key pre-distribution in the lower tier of the network architecture and public key cryptography in the upper tier to distribute session keys. We proposed a protocol for key establishment which provides a high level of security and minimizes the resource consumption of the sensor devices. This provide a better suited for heterogeneous environment when applied with sensor devices. Finally our proposed protocol is better in comparison from others by applying different simulators.
In our daily life human can remember many faces and can recognize them irrespective of illumination, aging, obstructions, variation in views. Most of researchers have worked on the problem of face recognition to develop an automatic face recognition system with capabilities to recognize faces as human beings can do. However, in unconstrained situations where a face may be captured in outdoor environmental conditions, while under changing illumination and pose variations Face Recog-nition Techniques fails to work. Here, a new face recognition method is implemented based on Gabor filter and Voting based extreme learning machine, it presents an effective algorithm to pose invariant face recognition called as Multiscale and Multi-orientation face classification using voting based extreme learning machine. In proposed approach, facial features are extracted by applying set of Gabor filters and Local directional Pattern (LDP), then histogram pattern of result is obtained which is subjected to generate distinctive feature vectors and further classified using V-ELM classifier.The application area of Wireless sensor network(WSN) in real time environment are unreliable and inaccessible , leads to degradation of network performance. The major issues of WSN are QoS ,power and it is impossible to access the WSN to change its power capacity. Long -hops transmission i.e. high range communication which provides the QoS with more energy consumption leads to reduction in network lifetime. The paper concentrates on adjustment of power , range and bit rates to attain adaptive topology control(ATC) at physical layer to maintain equivalent QoS. The simulation are carries out by using MIXIM 2.3 framework Omnet++ 4.6.The comparison of QoS for non-ATC and ATC is presented and an improvement of 29 percentage was resulted.
In the current era there are lots of work have been carried out in the direction of cluster heads (CHs) selection in wireless sensor network (WSN). Despite of these works there is still need of improvement in the suggested methods and approach. This paper provides a computational analysis of the related method published of clustering techniques for the efficient cluster head selection and based on the other approaches. In general k-means, fuzzy c-means (FCM) and hierarchical clustering have been considered for the analysis along with the computational measures. This study explores the analytical and experimental discussion and the trends for the efficient cluster head selection.
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