A Progressive Approach to Enhance Lifetime for Barrier Coverage in Wireless Sensor Network

Wireless sensor networks have their applications deployed in all the fields of area of research beyond the visualization of smart sensors. The sensors installed may experience many coverage related faults e.g., Barrier coverage problem. This problem affects the random deployment in sensor network to conserve energy and therefore has to be rectified, confined and approved. The protocol CSP andVSP defined extends the advantageoreducingtheenergyconsumption and increases the lifetime of sensor nodes with the intrusion detection model over heterogeneous deployment. Inspite of low connectivity and multihop signal paths, the protocols is entirely scalabl e in terms of computational control and communication bandwidth. Two diverse cases are employed between th e nodes with the protocols: position to position connectivity and load balancing. The former produces better results with a linear increase in network lifetime whereas through latter achieves 40 percent of energy utilization. Simul ation results are provide d to display the efficiency of the protocol designed

A Novel Data Generation Approach for Digital Forensic Application in Data Mining

With the rapid advancements in information and communication technology in the world, crimes committed are also becoming technically intensive. When crimes committed use digital devices, forensic examiners have to adopt practical frameworks and methods for recovering data for analysis as evidence. Data Generation, Data Warehousing and Data Mining, are the three essential features involved in this process. This paper proposes a unique way of generating, storing and analyzing data, retrieved from digital devices which pose as evidence in forensic analysis. A statistical approach is used in validating the reliability of the pre-processed data. This work proposes a practical framework for digital forensics on flash drives

Feature level fusion based bimodal biometric using transformation domine techniques

Bimodal biometric used to authenticate a person is more accurate compared to single biometric trait. In this paper we propose Feature Level Fusion based Bimodal Biometric using Transformation Domine Techniques (FLFBBT). The algorithm uses two physiological traits viz., Fingerprint and Face to identify a person. The Region of Interest (ROI) of fingerprint is obtained using preprocessing. The features of fingerprint are extracted using Dual Tree Complex Wavelet Transforms (DTCWT) by computing absolute values of high and low frequency components. The final features of fingerprint are computed by applying log on concatenated absolute value of high and low frequency components. The face image is preprocessed by cropping only face part and Discrete Wavelet Transforms (DWT) is applied. The approximation band coefficients are considered as features of face. The fingerprint and face image features are concatenated to derive final feature vector of bimodal biometric. The Euclidian Distance (ED) is used in matching section to compare test biometric in the database, it is observed that the values of EER and TSR are better in the case of proposed algorithm compared to individual transformation domain techniques

Performance of AODV Routing Protocol using Group and Entity Mobility Models in Wireless Sensor Networks

Wireless Sensor Network is Multihop Self-configuring Wireless Network consisting of sensor nodes. The patterns of movement of nodes can be classified into different mobility models and each is characterized by their own distinctive features. The significance of this study is that there has been very limited investigations of the effect of mobility models on routing protocol performance such as Packet Delivery Ratio, Throughput and Latency in Wireless Sensor Network. In this paper, we have considered the influence of pursue group and random based entity mobility models on the performance of Ad Hoc On-Demand Distance Vector Routing Protocol (AODV) routing protocol. The simulation results show that Pursue Group Mobility model is better than Random Based Entity model

Routing Protocol using Group and Random Based Mobility Models in Wireless Sensor Networks

Wireless Sensor Network is Multihop Self configuring Wireless Network consisting of sensor nodes. The patterns of movement of nodes can be classified into different mobility models and each is characterized by their own distinctive features. The significance of this study is that there has been a very limited investigation of the effect of mobility models on routing protocol performance such as Packet Delivery Ratio, Throughput and Latency in Wireless Sensor Network. In this paper, we have considered the influence of pursue group and random based entity mobility models on the performance of Ad Hoc On-Demand Distance Vector Routing Protocol (AODV) routing protocol. The simulation results show that Pursue Group Mobility model is better than Random Based Entity model

A data mining approach for data generation and analysis for digital forensic application

With the rapid advancements in information and communication technology in the world, crimes committed are becoming technically intensive. When crimes committed use digital devices, forensic examiners have to adopt practical frameworks and methods to recover data for analysis which can pose as evidence. Data Generation, Data Warehousing and Data Mining, are the three essential features involved in the investigation process. This paper proposes a unique way of generating, storing and analyzing data, retrieved from digital devices which pose as evidence in forensic analysis. A statistical approach is used in validating the reliability of the pre-processed data. This work proposes a practical framework for digital forensics on flash drives

Member, IAENG, Prasanth G Rao, Abhilash VR, P. Deepa Shenoy, Venugopal KR and LM Patnaik. A Data Mining Approach for Data Generation and Analysis for Digital Forensic Application

With the rapid advancements in information and communication technology in the world, crimes committed are becoming technically intensive. When crimes committed use digital devices, forensic examiners have to adopt practical frameworks and methods to recover data for analysis which can pose as evidence. Data Generation, Data Warehousing and Data Mining, are the three essential features involved in the investigation process. This paper proposes a unique way of generating, storing and analyzing data, retrieved from digital devices which pose as evidence in forensic analysis. A statistical approach is used in validating the reliability of the pre-processed data. This work proposes a practical framework for digital forensics on flash drive

Optimal connectivity for target coverage using prediction filter in wireless sensor networks

Deployment of sensor networks has traditionally been a significant interest during the most recent period of years. Coverage problem is a vital and primary issue in sensor networks. We propose the r-coverage to implement the target/point coverage problem in this paper. We make use of Reduced Minimum Spanning Tree (R-MST) to construct the topology, so that less packet loss and less delay occur with increase in the lifetime of the network. Experimental results have been performed using simulation on existing FST and R-MST proposed method. The obtained result shows that our approach achieves better throughput and packet delivery ratio over the FST topology with random node deployment in wireless sensor network

Split and Schedule (SS): A Progressive Lifetime for Barrier Coverage using Relay Clusters in Wireless Sensor Network

In wireless sensor networks, barrier coverage is one of the major challenge for high density area. To overcome this challenge, coverage control is the key solution for making more efficient and can program the sensors in active or idle state to maintain network coverage. Also, the random deployment with clustering of detection nodes plays a crucial role in the presence of an obstruction else that can become a viable route for attackers. In this paper, two strategies are proposed to resolve the problem of barrier coverage and to improve lifespan of the network. A Split and Schedule (SS) algorithm is proposed and the formation of clusters overcomes limitations with better solution. By comparing with other efficient algorithms, proposed SS algorithm sustains the better quality of network coverage and enhances the longevity of the sensor network

Energy Efficient Relaying For Target Coverage In Dense Wireless Sensor Networks

Wireless Sensor Networks (WSN) have been the most widely selected research area for a decade now. Researchers have identified the usability of sensor networks in huge variety of applications. The emergence of cognitive networks has led the sensor networks to adapt to the network conditions and the application dynamics. The work presented in this paper proves a unique cognitive solution for the problem of dynamic target coverage problem in the designated area of military surveillance. The nodes used for the acquisition of target coverage problem in the network remains static and transmits the information to the neighboring nodes using a movement prediction algorithm. The proposed approach shows better improvement in coverage and network lifetime in terms of position estimation and tracking target when compared to non-relaying techniques