Sateesh Kumar Pradhan

Load balanced routing in mobile ad hoc networks

We present a new protocol called Load Aware Routing in Ad hoc (LARA) networks protocol for efficient data transmission in mobile ad hoc networks. We also define a new metric for routing called traffic density to represent the degree of contention at the medium access control layer. During the route setup, this metric is used to select the route with the minimum traffic load. We have carried out extensive simulation studies to evaluate the performance of our proposed protocol vis-a-vis the existing protocols. Performance results show that our LARA protocol outperforms existing routing protocols in terms of end-to-end delay, throughput, packet delivery fraction, and battery power consumption at the nodes.

A Multi-Objective QoS Optimization with Fuzzy Based Parameter Setting for Real-Time Multicasting

We propose a multi-objective Pareto-optimal technique using Genetic Algorithm (GA) for group communication, which determines a min-cost multicast tree satisfying end-to-end delay, jitter, packet loss rate and blocking probability constraints. The model incorporates a fuzzy-based selection technique for initialization of QoS parameter values at each instance of multicasting. The simulation results show that the proposed algorithm satisfies on-demand QoS requirements (like high availability, good load balancing and fault-tolerance) made by the hosts in varying topology and bursty data traffic in multimedia communication networks.

MERA: A Multi-clustered Energy Efficient Routing Algorithm in WSN

A synchronized network time is always necessary for scheduling to achieve energy efficiency, data fusion, localization for WSN applications. The major limitation in a WSN is the battery usage and lifetime of the nodes. Due to the power restriction of nodes, efficient routing is very important to save the battery of sensors to enhance the lifetime of the sensor area. The multi-head chain concept is responsible for maximization of network duration. Thus, an algorithm hace been proposed for efficient multi clustered Energy efficient routing protocol (MERA) a multiple-neighbor prototype with minimization of distance control mechanism to obtain almost maximum energy utilisation of WSNs. As the automatic movement of node is steered by energy, there is a need to confine this movement within boundaries and the trajectory of different nodes should be fixed. In our technique, the sink is kept fix and data transfer with aggregation at different nodes guarantee complete data collection. In our algorithm as per the capacity of mobile nodes We ultimately have performed various instance of experiments to find the performance of the cluster chain leader (CCL)where each CCL communicate to its nearest CCL and finally to the sink. The results says that the proposed finding is nearly optimal and also better than PEGASIS with respect various features.

A Novel Cluster Head Selection Method for Energy Efficient Wireless Sensor Network

In the development of wireless sensor networks (WSNs) applications, organizing sensor nodes into a communication network and route the sensed data from sensor nodes to a remote sink is a challenging task. Energy efficient and reliable routing of data from the source to destination with minimal power consumption remains as a core research problem. So, in WSN we need an efficient protocol to route any transmitted data with extended lifetime of network. In this paper, we propose a novel clustering algorithm, Front-Leading Energy Efficient Cluster Heads (FLEECH), in which the whole network is partitioned into regions with diminishing sizes. In each region, we form multiple clusters. The selection of the Cluster Head (CH) is based on residual energy and distance of each node to the sink as its parameter. Simulation results show that our proposed model FLEECH outperforms Low Energy Adaptive Clustering Hierarchy (LEACH) with respect to energy consumption and extension of network life time.

A Multi-Objective Pareto-Optimal Genetic Algorithm for QoS Multicasting

The increasing demand of real-time multimedia applications in wireless environment requires stringent Quality of Service (QoS) provisioning to the Mobile Hosts (MI. The scenario becomes more complex during group communication from single source to multiple destinations. Fulfilling users demand with respect to delay, jitter, available bandwidth, packet loss rate and cost associated with the communication needs Multi-Objective Optimization (MOO) with QoS satisfaction, is a NP-complete problem. In this paper we propose a multi-objective optimal algorithm to determine a min-cost multicast tree with end-to-end delay, jitter, packet loss rate and blocking probability constraints. The simulation result shows that the proposed algorithm satisfies QoS requirements (like high availability, good load balancing and fault-tolerance) made by the hosts in varying topology and bursty data traffic for multimedia communication networks. The performance of the algorithm for scalability is also highly encouraged.

Effect of Sr doping on electrical properties of lead zirconate titanate nanoceramics

ABSTRACT Pb1-xSrxZr0.52Ti0.48O3 (PSZT) with x = 0–10 mole % were prepared by sol-gel process. X-ray diffraction (XRD) patterns show both rhombohedral and tetragonal crystal symmetries. Increase in lattice strain due to Sr incorporation results in enhanced dielectric constant and piezoelectric co-efficient (d33).With the increase in temperature relaxation time increases from 10−6 sec to 10−7 sec and spreading factor increases from 0.21 (±0.05) to 0.26 (±0.05) for 10 mole % PSZT. Also, the maximum remanent electric polarization and coercive electric field of 13.64 µC/cm2 and 15.97 kV/cm respectively have been observed for 10 mole % samples.

A Decision-Driven Computer Forensic Classification Using ID3 Algorithm

Rapid evolution of information technology has caused devices to be used in criminal activities. Criminals have been using the Internet to distribute a wide range of illegal materials globally, making tracing difficult for the purpose of initiating digital investigation process. Forensic digital analysis is unique and inherently mathematical and generally comprises more data from an investigation than is present in other types of forensic investigations. To provide appropriate and sufficient security measures has become a difficult job due to large volume of data and complexity of the devices making the investigation of digital crimes even harder. Data mining and data fusion techniques have been used as useful tools for detecting digital crimes. In this study, we have introduced a forensic classification problem and applied ID3 decision tree learning algorithm for supervised exploration of the forensic data which will also enable visualization and will reduce the complexity involved in digital investigation process.

Data mining techniques for E-business intelligence

With the rapid development of E-business, enormous customer data is been accumulated daily in websites background databases. It is difficult to deal with by business systems due to the large number of online transactions Data mining techniques and tools can be used to analyze customers shopping behavior and consuming habits to better understand their needs and increase the profits of the organization. In this paper we have applied K-Means algorithm over sample data and determined the relationship between the types of customers behavior over their age and gender.

A heuristic job scheduling algorithm for minimizing the waiting time variance

Scheduling number of jobs in a single machine is a “Uni-machine job scheduling problem”. The mean of variation of jobs waiting time is called Waiting time Variance (WTV). Minimization of WTV directly improves the quality of service (QoS) of systems involved with job scheduling. WTV minimization is a NP-hard problem. As a matter of fact minimization of the WTV on computer networks can lead to stable and predictable network performance. The main objective of this paper is to provide a secure and predictable computer and network systems by proposing a heuristic based novel approach to minimize the WTV. This approach illustrated with small size problems along with randomly new generated problems. The experimental results are compared with existing approaches. The experimental result shows the proposed approach gives best performance for the compared approaches and problems tested. The findings of intended algorithm are shown in the form of table for consonant problems.

Dynamic QoS Requirement Aware Service Composition and Adaptation

With the prevalence of SOA, an increasing number of Web Services(WS) are created and composed to construct Web-Service Based Systems(SBS). WSs are independent of formulation of complex business process by multiple WS composition. With the steadily growing number of service providers the competition becomes more and more intense. In order to compose a SBS selecting appropriate service from among a collection independently developed services with the same functionality but different cost and Quality of Service (QoS) properties is essential to meet the client preferences. The existing planning and selection algorithms are mostly designed for service discovery. To our knowledge, there are only a few works that incorporate service selection with respect to end user’s dynamic QoS requirements. Further, in case of QoS variation of composed SBS at provisioning-time due to QoS variation of one or more component services, a proactive adaptation strategy is required to maintain the required overall QoS. In this ongoing PhD work we propose complete, flexible solution for the “Dynamic QoS requirement aware automatic service selection and provisioning-time adaptation”. This approach is a graph based multi-grain clustering and selection model for service composition.