A Cognitive Research Tendency in Data Management of Sensor Network

In today’s World sensor networks offer various opportunities for data management applications because of their low cost, reliability, scalability, high-speed data processing, and other versatile advantageous purposes. It is a great challenge to organize data effectively and to retrieve the appropriate data from the large volume of various data sets in ad-hoc network databases, mobile databases, etc. The sensor network is necessary for routing of data, performance analysis of data management activities, and data incorporation for the right application. Data management involves intranet and extranet query handling, data access mechanism, modeling of data, different data movement algorithm, data warehousing, and data mining of network database. Additionally, connectivity, design, and lifetime are important issues for sensor networks to perform all data management activities smoothly. In this paper, we are trying to give a cognitive research tendency of Sensor network data management in the last two decades considering all the challenges and issues of both sensor network database and data management functions using Scopus and Web of Science database. To analyze data, different assessments are done considering various parameters like the author, time, publication and citation number, place, source, document separately for Web of Science and Scopus database in global perspective. It is noticed that there is a significant growth of research in data management for sensor networks because of the popularity of this topic.

Multicasting Data Routing for Vehicular Ad hoc Network using Fog Computing

A group of vehicles either mobile or stationery that is interconnected through a wireless network generate a vehicular ad hoc network (VANET). Providing comfort as well as safety to the drivers in vehicular scenarios is the main importance of VANETs. Since there is an increase in the number of autonomous vehicles, these networks are now being considered as an infrastructure for an intelligent transportation system. Fog computing can be provided low latent information sharing and more background knowledge by localizing one of the features. This research work is related to data aggregation in vehicular ad hoc networks. In this research work, the technique of multicasting will be proposed for the data aggregation in VANETs. The Network Simulator 2 is used to perform experiments and few performance measures are used for analysing the outcomes.

Energy Aware Enhanced Krill Herd Algorithm Enabled Clustering for Unmanned Aerial Vehicles

Recently, unmanned aerial vehicles (UAV) have gained maximum interest in diverse applications ranging from military to civilian areas. The presence of numerous energy-constrained UAVs in an adhoc manner poses several design issues. At the same time, the limited battery, high mobility, and adaptive characteristics of the UAVs need effective design of clustering techniques for UAVs. In this manner, this paper presents a levy flight with a krill herd optimization algorithm (LF-KHOA) for energy-efficient clustering in UAVs. The proposed LF-KHOA technique integrates the concepts of LF to the KHOA to enhance efficiency and search space exploration. In addition, the LF-KHOA technique derives a fitness function involving three input parameters to elect cluster heads (CHs) and organize clusters. The energy consumed by the UAVs depends on the distance from UAVs to nearby nodes. Therefore, the fitness function aims to decrease communication distance, which mitigates energy utilization when transmitting the information. To ensure the better performance of the LF-KHOA technique, an extensive set of simulations takes place, and the results are inspected in terms of different measures. The experimental results highlighted the betterment of the LF-KHOA technique over the current state of art techniques.

A PSPICE Fast Model for the Single Electron Transistor

Motivated by the merits of low power dissipation, ultra-small size, and high speed of many nanoelectronic devices, They have been demonstrated to ensure future progress. Single-electron devices became one of the most important nanoelectronic devices due to their interesting electrical characteristics and behavior. Many research efforts moved to describe their electrical characteristics to use them with conventional electronic devices. This paper deals with modeling and simulation of such new electronic devices. This paper presents a model for the Single Electron Transistor (SET) and its application in simulating hybrid SET/MOS ADC and DAC converters. This model uses the orthodox theory of single-electron tunneling and determines the average current through the transistor. The proposed model is more flexible that is valid for a large range of drain to source voltage, valid for single or multi-gate SET and symmetric or asymmetric SET. Finally, using this model with MOSFET transistors to realize multi-bit Analog-to-Digital Converters (ADC) and Digital-to-Analog Converters (DAC). The hybrid n-bit DAC nano-circuits are simulated for (n=4 and 8) using Orcad Capture PSPICE. The performance of the SET/MOS hybrid n-bit ADC circuits were simulated (for n=3 and 8). The results show that the transient operation of hybrid SET/MOS circuit-based DAC could successfully operate at 1000K while ADC could operate at 144K. This performance can be compared with the pure SET circuits, the proposed converter circuits have been enhanced in the drive capability and the power dissipation. Compared with the other SET/MOS hybrid circuit, the implemented converter circuits have low simulation time, high speed, high load drivability, and low power dissipation.