Muhammad Babar Rasheed

M-GEAR: Gateway-Based Energy-Aware Multi-hop Routing Protocol for WSNs

In this research work, we advise gateway based energy-efficient routing protocol (M-GEAR) for Wireless Sensor Networks (WSNs). We divide the sensor nodes into four logical regions on the basis of their location in the sensing field. We install Base Station (BS) out of the sensing area and a gateway node at the centre of the sensing area. If the distance of a sensor node from BS or gateway is less than predefined distance threshold, the node uses direct communication. We divide the rest of nodes into two equal regions whose distance is beyond the threshold distance. We select cluster heads (CHs)in each region which are independent of the other region. These CHs are selected on the basis of a probability. We compare performance of our protocol with LEACH (Low Energy Adaptive Clustering Hierarchy). Performance analysis and compared statistic results show that our proposed protocol perform well in terms of energy consumption and network lifetime.

Effect of Packet Inter-arrival Time on the Energy Consumption of Beacon Enabled MAC Protocol for Body Area Networks☆

Abstract One of the major concerns for the development of Wireless Body Area Network (WBAN) is to increase the network lifetime. IEEE 802.15.4 standard for Medium Access Control (MAC) layer can be used for energy efficient and reliable transmission by modifying the different control parameters. Such a modification is very difficult, because an accurate model for the influence of these control parameters of minimum energy and delay is not available. Moreover, there is no mechanism available how to adopt and implement these parameters that can implement on the Body Nodes (BNs). In this paper, we provide the mechanism for emergency data along with normal and periodic data by modifying the superframe structure. Coordinator transmits and extra beacon upon the request of emergency data. A comprehensive analysis of energy consumption of BNs including the affect of packet inter-arrival time is given in this paper. Analysis show that, Contention Access Period (CAP) of superframe is not feasible for emergency data due to its extra delay and energy.

Delay and energy consumption analysis of priority guaranteed MAC protocol for wireless body area networks

Wireless body area networks are captivating growing interest because of their suitability for wide range of applications. However, network lifetime is one of the most prominent barriers in deploying these networks for most applications. Moreover, most of these applications have stringent QoS requirements such as delay and throughput. In this paper, the modified superframe structure of IEEE 802.15.4 based MAC protocol is proposed which addresses the aforementioned problems and improves the energy consumption efficiency. Moreover, priority guaranteed CSMA/CA mechanism is used where different priorities are assigned to body nodes by adjusting the data type and size. In order to save energy, a wake-up radio based mechanism to control sleep and active modes of body sensors are used. Furthermore, a discrete time finite state Markov model to find the node states is used. Analytical expressions are derived to model and analyze the behavior of average energy consumption, throughput, packet drop probability, and average delay during normal and emergency data. Extensive simulations are conducted for analysis and validation of the proposed mechanism. Results show that the average energy consumption and delay are relatively higher during emergency data transmission with acknowledgment mode due to data collision and retransmission.

Comparative Analysis of Classifiers for Developing an Adaptive Computer-Assisted EEG Analysis System for Diagnosing Epilepsy

Computer-assisted analysis of electroencephalogram (EEG) has a tremendous potential to assist clinicians during the diagnosis of epilepsy. These systems are trained to classify the EEG based on the ground truth provided by the neurologists. So, there should be a mechanism in these systems, using which a systems incorrect markings can be mentioned and the system should improve its classification by learning from them. We have developed a simple mechanism for neurologists to improve classification rate while encountering any false classification. This system is based on taking discrete wavelet transform (DWT) of the signals epochs which are then reduced using principal component analysis, and then they are fed into a classifier. After discussing our approach, we have shown the classification performance of three types of classifiers: support vector machine (SVM), quadratic discriminant analysis, and artificial neural network. We found SVM to be the best working classifier. Our work exhibits the importance and viability of a self-improving and user adapting computer-assisted EEG analysis system for diagnosing epilepsy which processes each channel exclusive to each other, along with the performance comparison of different machine learning techniques in the suggested system.

An Energy Consumption Analysis of Beacon Enabled Slotted CSMA/CA IEEE 802.15.4

Due to low power consumption and low duty cycle, IEEE 802.15.4 standard is widely used for Low Rate Wireless Personal Area Networks (LR - WPANs). It works in Beacon Enabled (BEn) and Non Beacon Enabled (NBEn) mode. In BEn mode, it has Contention Access Period (CAP) and an optional Contention Free Period (CFP). During CAP, nodes contend to access the medium for communication while CFP period provides Guaranteed Time Slot (GTS) for low latency and applications requiring specific bandwidth. In this paper, we evaluate the comprehensive energy consumption of slotted CSMA/CA algorithm of IEEE 802.15.4 standard during idle and back off periods. Simulation results with acknowledgment frame are given at the end of the paper.

Evaluation of Human Activity Recognition and Fall Detection Using Android Phone

Human Activity Recognition (AR) using kinematic sensors is one of the widely used researched area based on Smartphone. Development in sensor networks technology provided birth to the applications that can give intelligent and amicable services based on the AR of people. Although, this technology supports analyzing different activities pattern, empowering applications to identify the activities performed user independently is still a fundamental concern. For improvement quality of life and personal safety, care giving process can be enhanced by introducing the AR, automatic fall detection, and prevention systems. Modern smartphones have different built in sensors like accelerometer, magnetometer, proximity, and gyroscope which can be used for AR as well as fall detection. In this paper, we present an AR and fall detection system which used built in sensors with alarm notification service. We use Signal Magnitude Vector (SMV) algorithm to analyze the fall like events. To overcome the false alarm activation problem, system uses different threshold values to determine the daily life activities like walking, standing, and sitting, that could be wrongly detected as a fall. For assessment, a trial setup is done to acquire sensors information of diverse positions.

Multiagent Control System for Residential Energy Management under Real Time Pricing Environment

This work proposes a residential load management system using multiagent technology with the objective of cost and comfort management. Smart appliances in a residential unit are modelled as agents which are controlled using optimization algorithm. These agents cooperate and communicate with each other using agent communication language (ACL) to reduce electricity cost and high peaks without affecting end user comfort. In this regards, different types of agents including load agents, price agent, temperature agent, management agent and optimal stopping rule (OSR) agent are considered. To make agent behaviour intelligent and adaptive, OSR is used. Simulations are conducted to provide the overview of residential load management using multiagent system (MAS). Simulation results show the effectiveness of MAS in terms of electricity cost, user comfort and peak shaving.

An Energy Efficient Residential Load Management System for Multi-class Appliances in Smart Homes

Demand Side Management (DSM) mechanism is used for the implementation of different strategies to encourage residential users to reduce electricity bill as well as energy demand. There is also a close relationship between the consumer and utility for equally benefiting to both in terms of grid stability and bill reduction. Extensive research is undertaken now a days in order to make practical implementation on the possible use of different DSM strategies to regulate the energy demand and carbon emission reduction in the World. The major objective of this work is to study the DSM-based approaches which could be helpful in achieving significant electricity demand reduction at the electricity distribution network which is directly connected to the commercial and residential sector especially. In this work, we use an optimization algorithm to obtain the optimal solution for residential electricity load management in a typical household setting. There are two major tasks of this algorithms, firstly, electricity bill minimization of residential user in time of use pricing models, secondly, peaks reduction of demand curve (peak shaving) which will eventually minimize the investment cost of utility including, peak power plants, and transmission lines. Three types of smart appliances are considered, without delay, delay of one hour, delay of five hours. To validate the effectiveness of the proposed algorithm, mathematical models of appliances based on their length of operation time is developed.

A Novel Pricing Mechanism for Demand Side Load Management in Smart Grid

This paper proposes a novel demand response (DR) mechanism based on real time electricity prices with the objective of cost reduction. The novelty of the proposed mechanism lies in the concept that electricity sub-prices are calculated based on the fraction of energy consumed by each unit/home. While, in traditional residential energy management programs, one DR signal applies to each associated unit without considering low, medium or high energy consumers. The proposed mechanism calculates the electricity prices for each individual unit based on which the electricity is calculated. Furthermore, the proposed mechanism is designed in such a way that it is equally feasible for all types of DR programs being used for demand side energy management. To assess the feasibility and practical applicability of the proposed mechanism, extensive simulations are conducted. The simulation results verify that the mechanism is efficient in calculating sub-prices without violating the utility constraint (i.e., the net cost remains same in both traditional and proposed mechanisms).

Transient Stability Analysis of an Islanded Microgrid under Variable Load

In this paper, we investigate some aspects related to microgrid (MG) stability. Due to different applications of MG, its structure and deployment topology vary depending upon the nature of application and operating modes (islanded or grid connected). So, the stability of MGs varies accordingly. This paper precisely explains the stability aspects (e.g., phase angle and power losses) of remotely located islanded MG having the capability to integrate distributed energy sources. Initially, the stability of three bus system is assessed under variable load and find some gaps related to stability as MG involves a high penetration of distributed energy sources. These gaps indicate that stability of a MG is not only in the control of generation/load but also in its coordination with other loads. After that, we implement the load coordination technique and analyze the stability against fixed and dynamic loads. For comprehensive analysis, four different cases are considered in which we vary load at different bus bars and check the performance. Lastly, we integrate the distributed energy source to islanded MG and perform the stability analysis. For validation purpose, extensive simulations of the proposed cases are conducted using Matlab. Simulation results depict that load coordination technique is more efficient regarding MG stability.