Samia Shah

Bio: Samia Shah is an academic researcher from COMSATS Institute of Information Technology. The author has contributed to research in topics: Energy consumption & Routing protocol. The author has an hindex of 3, co-authored 4 publications receiving 36 citations.

A Meta-Heuristic Home Energy Management System

Abstract: In this work, we evaluate performance of home energy management system(HEM) by using three meta-heuristic optimization techniques: Harmony search algorithm (HSA), Bacterial foraging optimization (BFO) and Enhanced deferential evolution(EDE). We categorize appliances into three groups on the basis of their energy consumption pattern. Real time pricing (RTP) scheme is used for electricity bill calculation. Our objectives are to minimize electricity cost, energy consumption, reduction in peak to average ratio while maximizing user comfort. However, there exists a trade-off between different objectives. Our simulation results show that there exist a trade-off between user comfort and cost. Results also show that in terms of cost HSA perform better among other techniques.

LPCH and UDLPCH: Location-Aware Routing Techniques in WSNs

Abstract: Wireless sensor nodes along with Base Station (BS) constitute a Wireless Sensor Network (WSN). Nodes comprise of tiny power battery. Nodes sense the data and send it to BS. WSNs need protocol for efficient energy consumption of the network. In direct transmission and minimum transmission energy routing protocols, energy consumption is not well distributed. However, LEACH (Low-Energy Adaptive Clustering Hierarchy) is a clustering protocol, randomly selects the Cluster Heads (CHs) in each round. However, random selection of CHs does not guarantee efficient energy consumption of the network. Therefore, we proposed new clustering techniques in routing protocols, Location-aware Permanent CH (LPCH) and User Defined Location-aware Permanent CH (UDLPCH). In both protocols, network field is physically divided in to two regions, equal number of nodes are randomly deployed in each region. In LPCH, number of CHs are selected by LEACH algorithm in first round. However in UDLPCH, equal and optimum number of CHs are selected in each region, throughout the network life time number of CHs are remain same. Simulation results show that stability period and throughput of LPCH is greater than LEACH, stability period and throughput of UDLPCH is greater than LPCH.

An Optimized Priority Enabled Energy Management System for Smart Homes

Abstract: With the advent of smart grid (SG) and the emergence of information and communication technology, smart meters, bidirectional communication, smart homes and storage systems the energy consumption patterns at the consumer premises have been revolutionized. Moreover, with the rise of renewable energy sources (RESs), storage systems and electric vehicles (EVs) a profound amelioration in the energy management systems has been observed. Home energy management systems (HEMSs) help to control, manage and optimize the energy in smart homes. In this paper, we present a HEMS using multi-agent system (MAS) for smart homes. The HEMS uses priority techniques with the integration of electrical supply system (ESS). Furthermore, a bio-inspired technique, binary particle swarm optimization (BPSO), is used for the optimal scheduling of appliances in a smart home. Simulation results illustrate the effectiveness of the HEMS in terms of electricity cost, demand, user comfort and peak to average ratio (PAR).

LPCH and UDLPCH: Location-aware Routing Techniques in WSNs

Abstract: Wireless sensor nodes along with Base Station (BS) constitute a Wireless Sensor Network (WSN). Nodes comprise of tiny power battery. Nodes sense the data and send it to BS. WSNs need protocol for efficient energy consumption of the network. In direct transmission and minimum transmission energy routing protocols, energy consumption is not well distributed. However, LEACH (Low-Energy Adaptive Clustering Hierarchy) is a clustering protocol; randomly selects the Cluster Heads (CHs) in each round. However, random selection of CHs does not guarantee efficient energy consumption of the network. Therefore, we proposed new clustering techniques in routing protocols, Location-aware Permanent CH (LPCH) and User Defined Location-aware Permanent CH (UDLPCH). In both protocols, network field is physically divided in to two regions, equal number of nodes are randomly deployed in each region. In LPCH, number of CHs are selected by LEACH algorithm in first round. However in UDLPCH, equal and optimum number of CHs are selected in each region, throughout the network life time number of CHs are remain same. Simulation results show that stability period and throughput of LPCH is greater than LEACH, stability period and throughput of UDLPCH is greater than LPCH.

Review of Control and Energy Management Approaches in Micro-Grid Systems

Abstract: The demand for electricity is increased due to the development of the industry, the electrification of transport, the rise of household demand, and the increase in demand for digitally connected devices and air conditioning systems. For that, solutions and actions should be developed for greater consumers of electricity. For instance, MG (Micro-grid) buildings are one of the main consumers of electricity, and if they are correctly constructed, controlled, and operated, a significant energy saving can be attained. As a solution, hybrid RES (renewable energy source) systems are proposed, offering the possibility for simple consumers to be producers of electricity. This hybrid system contains different renewable generators connected to energy storage systems, making it possible to locally produce a part of energy in order to minimize the consumption from the utility grid. This work gives a concise state-of-the-art overview of the main control approaches for energy management in MG systems. Principally, this study is carried out in order to define the suitable control approach for MGs for energy management in buildings. A classification of approaches is also given in order to shed more light on the need for predictive control for energy management in MGs.

AMCTD: Adaptive Mobility of Courier nodes in Threshold-optimized DBR Protocol for Underwater Wireless Sensor Networks

Abstract: In dense underwater sensor networks (UWSN), the major confronts are high error probability, incessant variation in topology of sensor nodes, and much energy consumption for data transmission. However, there are some remarkable applications of UWSN such as management of seabed and oil reservoirs, exploration of deep sea situation and prevention of aqueous disasters. In order to accomplish these applications, ignorance of the limitations of acoustic communications such as high delay and low bandwidth is not feasible. In this paper, we propose Adaptive mobility of Courier nodes in Threshold-optimized Depth-based routing (AMCTD), exploring the proficient amendments in depth threshold and implementing the optimal weight function to achieve longer network lifetime. We segregate our scheme in 3 major phases of weight updating, depth threshold variation and adaptive mobility of courier nodes. During data forwarding, we provide the framework for alterations in threshold to cope with the sparse condition of network. We ultimately perform detailed simulations to scrutinize the performance of our proposed scheme and its comparison with other two notable routing protocols in term of network lifetime and other essential parameters. The simulations results verify that our scheme performs better than the other techniques and near to optimal in the field of UWSN.

AMCTD: Adaptive Mobility of Courier Nodes in Threshold-Optimized DBR Protocol for Underwater Wireless Sensor Networks

Abstract: In dense underwater sensor networks (UWSN), the major confronts are high error probability, incessant variation in topology of sensor nodes, and much energy consumption for data transmission. However, there are some remarkable applications of UWSN such as management of seabed and oil reservoirs, exploration of deep sea situation and prevention of aqueous disasters. In order to accomplish these applications, ignorance of the limitations of acoustic communications such as high delay and low bandwidth is not feasible. In this paper, we propose Adaptive mobility of Courier nodes in Threshold-optimized Depth-based routing (AMCTD), exploring the proficient amendments in depth threshold and implementing the optimal weight function to achieve longer network lifetime. We segregate our scheme in 3 major phases of weight updating, depth threshold variation and adaptive mobility of courier nodes. During data forwarding, we provide the framework for alterations in threshold to cope with the sparse condition of network. We ultimately perform detailed simulations to scrutinize the performance of our proposed scheme and its comparison with other two notable routing protocols in term of network lifetime and other essential parameters. The simulations results verify that our scheme performs better than the other techniques and near to optimal in the field of UWSN.