An Energy E cient Routing Protocol for extending Lifetime of Wireless Sensor Networks by Transmission Radius Adjustment

Wireless Sensor Networks needs energy e cient routing protocols for increasing the network lifetime. e en- ergy consumption of sensor nodes can be decreased by reducing the transmission radius range. In this proposed work an Energy E cient Routing Protocol (EERP) is developed for wireless sensor network by adjusting the node transmission radius and conserves the node energy. EERP follows on demand routing method for packet forwarding from source to destination. When the node’s energy reaches certain threshold then node reduces its transmission radius again in order to achieve less energy consumption under the circumstance. e trans- mission range distribution optimizations for networks are developed in order to obtain the maximum lifetime. Analysis of the solution shows that network lifetime improvement can be obtained through optimization comes at the expense of energy-ine ciency and a wasting of system resources. e simulation results shows that EERP protocol outperforms the existing routing protocols in terms of network lifetime, energy consumption and has a balanced network load and routing tra c

An Energy E cient Routing Protocol for extending Lifetime of Wireless Sensor Networks by Transmission Radius Adjustment

Wireless Sensor Networks needs energy e cient routing protocols for increasing the network lifetime. e en- ergy consumption of sensor nodes can be decreased by reducing the transmission radius range. In this proposed work an Energy E cient Routing Protocol (EERP) is developed for wireless sensor network by adjusting the node transmission radius and conserves the node energy. EERP follows on demand routing method for packet forwarding from source to destination. When the node’s energy reaches certain threshold then node reduces its transmission radius again in order to achieve less energy consumption under the circumstance. e trans- mission range distribution optimizations for networks are developed in order to obtain the maximum lifetime. Analysis of the solution shows that network lifetime improvement can be obtained through optimization comes at the expense of energy-ine ciency and a wasting of system resources. e simulation results shows that EERP protocol outperforms the existing routing protocols in terms of network lifetime, energy consumption and has a balanced network load and routing tra c

Deep multimodal biometric recognition using contourlet derivative weighted rank fusion with human face, fingerprint and iris images

The goal of multimodal biometric recognition system is to make a decision by identifying their physiological behavioural traits. Nevertheless, the decision-making process by biometric recognition system can be extremely complex due to high dimension unimodal features in temporal domain. This paper explains a deep multimodal biometric system for human recognition using three traits, face, fingerprint and iris. With the objective of reducing the feature vector dimension in the temporal domain, first pre-processing is performed using Contourlet Transform Model. Next, Local Derivative Ternary Pattern model is applied to the pre-processed features where the feature discrimination power is improved by obtaining the coefficients that has maximum variation across pre-processed multimodality features, therefore improving recognition accuracy. Weighted Rank Level Fusion is applied to the extracted multimodal features, that efficiently combine the biometric matching scores from several modalities (i.e. face, fingerprint and iris). Finally, a deep learning framework is presented for improving the recognition rate of the multimodal biometric system in temporal domain. The results of the proposed multimodal biometric recognition framework were compared with other multimodal methods. Out of these comparisons, the multimodal face, fingerprint and iris fusion offers significant improvements in the recognition rate of the suggested multimodal biometric system

Dynamic Load Balanced Clustering using Elitism based Random Immigrant Genetic Approach for Wireless Sensor Networks

Wireless Sensor Network (WSN) consists of a large number of small sensors with restricted energy. Prolonged network lifespan, scalability, node mobility and load balancing are important needs for several WSN applications. Clustering the sensor nodes is an efficient technique to reach these goals. WSN have the characteristics of topology dynamics because of factors like energy conservation and node movement that leads to Dynamic Load Balanced Clustering Problem (DLBCP). In this paper, Elitism based Random Immigrant Genetic Approach (ERIGA) is proposed to solve DLBCP which adapts to topology dynamics. ERIGA uses the dynamic Genetic Algorithm (GA) components for solving the DLBCP. The performance of load balanced clustering process is enhanced with the help of this dynamic GA. As a result, the ERIGA achieves to elect suitable cluster heads which balances the network load and increases the lifespan of the network

Dynamic Load Balanced Clustering using Elitism based Random Immigrant Genetic Approach for Wireless Sensor Networks

Wireless Sensor Network (WSN) consists of a large number of small sensors with restricted energy. Prolonged network lifespan, scalability, node mobility and load balancing are important needs for several WSN applications. Clustering the sensor nodes is an efficient technique to reach these goals. WSN have the characteristics of topology dynamics because of factors like energy conservation and node movement that leads to Dynamic Load Balanced Clustering Problem (DLBCP). In this paper, Elitism based Random Immigrant Genetic Approach (ERIGA) is proposed to solve DLBCP which adapts to topology dynamics. ERIGA uses the dynamic Genetic Algorithm (GA) components for solving the DLBCP. The performance of load balanced clustering process is enhanced with the help of this dynamic GA. As a result, the ERIGA achieves to elect suitable cluster heads which balances the network load and increases the lifespan of the network

Modern microwave methods in solid state inorganic materials chemistry: from fundamentals to manufacturing

No abstract available

Energy Efficient Low-Cost Virtual Backbone Construction for Optimal Routing in Wireless Sensor Networks

Many prominent applications in wireless sensor networks which require collected information have to be routed to end nodes in an efficient manner. In general, weighted connected dominating Sets (WCDS) based routing is a promising approach for enhancing the routing efficiency in sensor networks. Backbone has been used extensively in routing. Here an efficient WCDS algorithm for constructing a virtual backbone with low total cost, hop spanning ratio, and minimum number of dominators is proposed. We report a systematic approach, which has three phases. Initial phase considers the issues of revoking a partial CDS tree from a complete CDS tree. Secondary and final phases make the design of the complete algorithm by considering the determination of dominators using an iteration process. Our findings reveal better performance than the existing algorithms in terms of total cost, hop spanning ratio, and number of dominators