Motilal Nehru National Institute of Technology Allahabad

About: Motilal Nehru National Institute of Technology Allahabad is a education organization based out in Allahabad, Uttar Pradesh, India. It is known for research contribution in the topics: Computer science & Control theory. The organization has 2475 authors who have published 5067 publications receiving 61891 citations. The organization is also known as: NIT Allahabad & Motilal Nehru Regional Engineering College.

IP Paging for Mobile Hosts in Distributed and Fixed Hierarchical Mobile IP

Abstract: The concept of Paging has been found useful in existing cellular networks for mobile users with low call-to-mobility ratio CMR. It is necessary for fast mobility users to minimize the signaling burden on the network. Reduced signaling, also, conserves scarce wireless resources and provides power savings at user terminals. However, Mobile IP MIP, a base protocol for IP mobility, does not support paging concept in its original form. Several paging schemes and micro-mobility protocols, centralized and distributed, have been proposed in literature to alleviate the inherent limitations of Mobile IP. In this paper, the authors propose three paging schemes for Distributed and Fixed Hierarchical Mobile IP DFHMIP and develop analytical models for them. Performance evaluations of these schemes have been carried out and results have been compared with DFHMIP without paging and with Dynamic Hierarchical Mobile IP DHMIP for low CMR values.

Assessment of impact of climate change on water resources in a hilly river basin

Abstract: The sensitivity of Sutlej river sub-basin (middle catchment) which is located in N-W Himalaya is investigated for its hydrologic response to potential changes in climate variability. The predictors of two global climate models (GCMs) that are found to perform well over Indian sub-continents are downscaled, and future time series of temperature (maximum and minimum) and precipitation is generated using statistical downscaling model (SDSM) under A1B, A2, and B2 emission scenarios. An overall increase in mean annual temperature and precipitation is predicted under both the models for future periods. The predicted increase in temperature is relatively higher for HadCM3 model compares to CGCM3 model whereas it is opposite for precipitation. The model also predicts considerable shift in monthly pattern of temperature and precipitation. Further, soil and water assessment tool (SWAT) is employed to appraise future changes in stream flow and water balance of the sub-basin under projected climate scenarios. The simulation results show that in future, increase in mean annual stream flow are likely to range from 1.3 to 7.8 % for CGCM3 model and 0.3 to 3.4 % for HadCM3 model, respectively. However, decrease in mean monthly stream flow is predicted under scenarios of CGCM3 model (from January to May and from November to December) and HadCM3 model (from January to April and from October to December), respectively.

Creeping flow of micropolar fluid parallel to the axis of cylindrical cells with porous layer

Abstract: The present paper considers the flow of micropolar fluid through a membrane modeled as a swarm of solid cylindrical particles with porous layer using the cell model technique. Traditional boundary conditions on hypothetical cell surface were added with an additional condition: the no spin condition / no couple stress condition. Expressions for velocity and microrotation vector components have been obtained analytically. Effect of various parameters such as particle volume fraction, permeability parameter, micropolarity number etc. on hydrodynamic permeability of membrane has been discussed.

A day-ahead optimal energy scheduling in a remote microgrid alongwith battery storage system via global best guided ABC algorithm

Abstract: Since last decade, the concept of microgrid (MG) is growing rapidly with increasing electricity generation through renewable energy sources (RES) and small dispatchable sources. A stand-alone MG is a better option for growing unserved electricity demand especially in remote areas, where classical power transmission system is not economically and technically feasible. The energy scheduling of RES and small dispatchable sources can be efficiently handled by the inclusion of battery storage system (BSS) along with RES. Further, the BSS in MG includes some degree of complexity in the objective function of optimal scheduling strategy. This paper deals the optimal energy scheduling in stand-alone MG consisting of wind turbine (WT), photovoltaic (PV), diesel engine generators (DEs) and BSS, which is not an easy task because of uncertainty in nature, dynamic market bid, and demand profiles. The BSS is operated in three different strategies based on fluctuation in RES power, load, and market bid to obtain the optimal energy scheduling of MG in continuous and discrete operation modes of DEs. The scheduling strategies maximize the arbitrage of MG system in both modes of DEs operation. The problem is simulated in MATLAB® environment, using artificial bee colony (ABC) and its variant global best (Gbest) guided ABC (GABC) algorithms, and other existing algorithms as particle swarm optimization (PSO) and genetic algorithm (GA). The obtained results depict that the GABC provides better revenue and, exploration, and exploitation capabilities in all operational strategies, than ABC, PSO and GA algorithms. The operational strategy based on variable market bid, load, and RES power gives optimal revenue and reduced or equal green house gases (GHG) emissions than other strategies in the considered modes of DEs operation.