Manzoor Ilahi's research while affiliated with COMSATS University Islamabad and other places

Publications (42)

Preprint
Stemming is an essential step in varied Natural Language Processing (NLP) applications. It is used to reduce different variants of the query words to a standard form to avoid the vocabulary mismatch issue in Information Retrieval (IR) systems. There are a lot of stemming algorithms in English language, but Urdu NLP still in its infancy. A stemmer d...
Preprint
Stemming is an essential step in varied Natural Language Processing (NLP) applications. It is used to reduce different variants of the query words to a standard form to avoid the vocabulary mismatch issue in Information Retrieval (IR) systems. There are a lot of stemming algorithms in English language, but Urdu NLP still in its infancy. A stemmer d...
Article
Full-text available
Several software design patterns have cataloged either with canonical or as variants to solve a recurring design problem. However, novice designers mostly adopt patterns without considering their ground reality and relevance to design problems, which causes to increase the development and maintenance efforts. The existing automated systems to selec...
Article
Full-text available
The imbalance energy consumption and high data traffic at intermediate nodes degrade the network performance. In this paper, we propose: energy grade and balance load distribution (EGBLOAD) corona, EG without corona and DA without corona based schemes to distribute data traffic across the network nodes for efficient energy consumption. The dynamic...
Article
Full-text available
As an emerging and promising approach, crowdsourcing-based software development has become popular in many domains due to the participation of talented pool of developers in the contests, and to promote the ability of requesters (or customers) to choose the ‘wining’ solution with respect to their desired quality levels. However, due to lack of a ce...
Article
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Demand side management (DSM) in smart grid authorizes consumers to make informed decisions regarding their energy consumption pattern and helps the utility in reducing the peak load demand during an energy stress time. This results in reduced carbon emission, consumer electricity cost, and increased grid sustainability. Most of the existing DSM tec...
Article
Full-text available
Cloud computing offers various services. Numerous cloud data centers are used to provide these services to the users in the whole world. A cloud data center is a house of physical machines (PMs). Millions of virtual machines (VMs) are used to minimize the utilization rate of PMs. There is a chance of unbalanced network due to the rapid growth of In...
Article
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This paper focuses on analytics of an extremely large dataset of smart grid electricity price and load, which is difficult to process with conventional computational models. These data are known as energy big data. The analysis of big data divulges the deeper insights that help experts in the improvement of smart grid’s (SG) operations. Processing...
Article
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Short-Term Electricity Load Forecasting (STELF) through Data Analytics (DA) is an emerging and active research area. Forecasting about electricity load and price provides future trends and patterns of consumption. There is a loss in generation and use of electricity. So, multiple strategies are used to solve the aforementioned problems. Day-ahead e...
Article
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The emergence of the Demand Response (DR) program optimizes the energy consumption pattern of customers and improves the efficacy of energy supply. The pricing infra-structure of the DR program is dynamic (time-based). It has rather complex features including marginal costs, demand and seasonal parameters. There is variation in DR price rate. Somet...
Article
The latency issue of cloud based system can degrade smart grid's real-time applications. This paper introduces a fog computing layer between the cloud and clients to provide energy management service in near real-time with optimised computing cost. In a region, in proposed system model, two clusters of residential buildings have access to two fogs...
Article
Full-text available
Demand Response Management (DRM) is considered one of the crucial aspects of the smart grid as it helps to lessen the production cost of electricity and utility bills. DRM becomes a fascinating research area when numerous utility companies are involved and their announced prices reflect consumer’s behavior. This paper discusses a Stackelberg game p...
Article
Full-text available
With the increasing size of cloud data centers, the number of users and virtual machines (VMs) increases rapidly. The requests of users are entertained by VMs residing on physical servers. The dramatic growth of internet services results in unbalanced network resources. Resource management is an important factor for the performance of a cloud. Vari...
Article
Full-text available
Designing an efficient association rule mining (ARM) algorithm for multilevel knowledge-based transactional databases that is appropriate for real-world deployments is of paramount concern. However, dynamic decision making that needs to modify the threshold either to minimize or maximize the output knowledge certainly necessitates the extant state-...
Article
Full-text available
IIn this paper, we propose a home energy management system which employs load shifting strategy of demand side management to optimize the energy consumption patterns of a smart home. It aims to manage the load demand in an efficient way to minimize electricity cost and peak to average ratio while maintaining user comfort through coordination among...
Article
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Underwater wireless sensor networks (UWSNs) facilitate a wide range of aquatic applications in various domains. However, the harsh underwater environment poses challenges like low bandwidth, long propagation delay, high bit error rate, high deployment cost, irregular topological structure, etc. Node mobility and the uneven distribution of sensor no...
Article
Full-text available
Localization is one of the major aspects in underwater wireless sensor networks (UWSNs). Therefore, it is important to know the accurate position of the sensor node in large scale applications like disaster prevention, tactical surveillance and monitoring. Due to the inefficiency of the global positioning system (GPS) in UWSN, it is very difficult...
Article
There are a number of research challenges associated with Internet of Things (IoT) security, and one of these challenges is to design novel frameworks to mine malicious frequent patterns for identifying misuse and detecting anomalies without incurring high computational costs (e.g. due to generation and analysis of unnecessary patterns and gap crea...
Article
Full-text available
Mobile Sink (MS) based routing strategies have been widely investigated to prolongs the lifetime of Wireless Sensor Networks (WSNs). In this paper, we propose two schemes for data gathering in WSNs: (i) MS moves on Random paths in the network (RMS), and (ii) the trajectory of MS is Defined (DMS). In both the schemes, the network field is logically...
Conference Paper
Smart grids can be regarded as the revolution in traditional power grids due to integration of Information and Communication Technologies (ICT), Distributed systems and Computational Intelligence (CI) algorithms in existing infras- tructure. Such advancements make it possible to monitor real time power patterns, articulate numerous Demand Response...
Article
Full-text available
In this work, we propose a Realistic Scheduling Mechanism (RSM) to reduce user frustration and enhance appliance utility by classifying appliances with respective constraints and their time of use effectively. Algorithms are proposed regarding functioning of home appliances. A 24 hour time slot is divided into four logical sub-time slots, each comp...
Article
Full-text available
Reliability is a key factor for application-oriented Underwater Sensor Networks (UWSNs) which are utilized for gaining certain objectives and a demand always exists for efficient data routing mechanisms. Cooperative routing is a promising technique which utilizes the broadcast feature of wireless medium and forwards data with cooperation using sens...
Article
Full-text available
As players and soldiers preform strenuous exercises and do difficult and tiring duties, they are usually the common victims of muscular fatigue. Keeping this in mind, we propose FAtigue MEasurement (FAME) protocol for soccer players and soldiers using in-vivo sensors for Wireless Body Area Sensor Networks (WBASNs). In FAME, we introduce a composite...
Article
In this paper, we analyze performance of famous cluster based routing protocols and identify the factors affecting energy consumption in wireless sensor networks. From theoretical and experimental analysis, it is observed that communication distance and cluster node density are the major sources in the formation of energy and coverage holes. To ove...
Article
Wireless Sensor Networks (WSNs) were envisaged to become the fabric of our environment and society. However, they are yet unable to surmount many operational challenges such as limited network lifetime, which strangle their widespread deployment. To prolong WSN lifetime, most of the existing clustering schemes are geared towards homogeneous WSN. Th...
Article
Full-text available
Mobility models play a vital role on the performance accuracy of simulations in Wireless Body Area Networks (WBANs). In this article, we propose a mobility model for the movement of nodes according to the posture patterns formed either because of psychological stress or any kind of mobility. During routine activities, body exhibits different postur...
Article
In this paper, we present two new chain formation techniques, namely, multi-chain energy-efficient routing (ME) and cost optimisation with multi-chaining for energy efficient communication (COME) for wireless sensor networks supported by linear programming based mathematical models. ME protocol divides network area into subareas of equal size, whic...
Article
Wireless Sensors Networks (WSNs) have a big application in heterogeneous networks. In this paper, we propose and evaluate Advanced Low-Energy Adaptive Clustering Hierarchy (Ad-LEACH) which is static clustering based heterogeneous routing protocol. The complete network field is first divided into static clusters and then in each cluster separate Ad-...
Article
Underwater Wireless Sensor Networks are significantly different from terrestrial sensor networks due to peculiar characteristics of low bandwidth, high latency, limited energy, node float mobility and high error probability. These features bring many challenges to the network protocol design of UWSNs. Several routing protocols have been developed i...
Article
In this work, we present a survey of residential load controlling techniques to implement demand side management in future smart grid. Power generation sector facing important challenges both in quality and quantity to meet the increasing requirements of consumers. Energy efficiency, reliability, economics and integration of new energy resources ar...
Article
We present a detailed review of various Home Energy Management Schemes (HEM,s). HEM,s will increase savings, reduce peak demand and Pto Average Ratio (PAR). Among various applications of smart grid technologies, home energy management is probably the most important one to be addressed. Various steps have been taken by utilities for efficient energy...
Article
Full-text available
Obstacle avoidance is an important task in the field of robotics, since the goal of autonomous robot is to reach the destination without collision. Several algorithms have been proposed for obstacle avoidance, having drawbacks and benefits. In this survey paper, we mainly discussed different algorithms for robot navigation with obstacle avoidance....
Article
In this paper, we present path loss model for VANETs and simulate three routing protocols; Destination Sequenced Distance Vector (DSDV), Optimized Link State Routing (OLSR) and Dynamic MANET On-demand (DYMO) to evaluate and compare their performance using NS-2. The main contribution of this work is enhancement of existing techniques to achieve high...
Article
In Wireless Ad-hoc Networks, nodes are free to move randomly and organize themselves arbitrarily, thus topology may change quickly and capriciously. In Mobile Ad-hoc NETworks, specially Wireless Multi-hop Networks provide users with facility of quick communication. In Wireless Multi-hop Networks, routing protocols with energy efficient and delay re...
Article
This paper presents a framework for node distribution with respect to density, network connectivity and communication time. Using NS2, we evaluate and compare performance of three routing protocols; Ad-hoc On-demand Distance Vector (AODV), Dynamic Source Routing (DSR) and Fisheye State Routing (FSR) both in MANETs (IEEE 802.11) and VANETs (IEEE 802...
Article
Wireless Multi-hop Networks (WMhNs) provide users with the facility to communicate while moving with whatever the node speed, the node density and the number of traffic flows they want, without any unwanted delay and/or disruption. This paper contributes Linear Programming models (LP_models) for WMhNs. In WMhNs, different routing protocols are used...

Citations

... All the results which have been obtained after applying the above mentioned algorithms are discussed in the paper which shows the difference between the outputs and accuracy through them. The deep learning approaches have been considered more accurate while getting better accuracy as compared to other conventional techniques (9) . It is also recommended by some researches to use the deep learning algorithms for extraction and identification of text. ...
... This is shown in Table 13, where the swarm-based solutions are organized in the terms of the previously listed algorithms. All those works deal with different optimization scopes in the field of fog infrastructures, such as, resource allocation [156,157,158,159,160], load balancing [161,162,163], infrastructure deployment [164], scheduling [162, 163, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, [178,179,180,181,182,183,184,185], or data placement [186]. ...
... Hussain et al. [122] used an LTR method to create a prototype of an automated recommendation system to classify and select design patterns. Given a design problem description, their approach ranks the design patterns according to the text relevancy. ...
... The rest of the candidate solutions are assumed to be omega (x) wolves. To facilitate the calculation, the initialization parameters for GWO are given below [62,63]: it is assumed that the positions of the wolves of a and b are set to a is 0.5 and b 2 ð0; 2Þ respectively, with b being mainly responsible for assisting a in the decision making. Meanwhile, in order to reduce the number of iterations in the calculation, we assume that the number of wolves seeking value is 5 and the number of grids per dimension is 10. ...
... Researchers consider mainly the day-ahead market, which is the main electricity spot trading place, however in recent years the focus was put on other markets as well, e.g. the intraday market [14][15][16][17][18][19][20][21]. The proven and efficient model estimation methods in point EPF are lasso [15,16,18,[22][23][24] of Tibshirani [25] and artificial neural networks [8,20,[26][27][28][29][30][31]. A substantial stream of new EPF research considers hybrid models [32][33][34][35][36][37], however as Lago et al. [8] conclude, they often avoid proper comparisons to well-established methods. ...
... Statistical methods are more interpretable than those using machine learning algorithms, but they usually need statistical assumptions that make capturing the underlying stochastic progress of load profiles difficult Dumas et al. (2022). Different to statistical ones, machine learning-based methods transform raw data into feature vectors through carefully designed feature extractors and proved their superior ability to address hidden nonlinearity in historical data sets compared to those using statistical algorithms Panapakidis (2016); Zahid et al. (2019); Chicco and Ilie (2009); Wang et al. (2018). ...
... However, a non-optimal ToU electricity price may shift the charging of a large number of EVs and create a new peak hour [59,60]. An optimal ToU electricity pricing is a challenging problem for which several methods such as game theory models are proposed in order to effectively shave the load peaks while minimizing the generation and consumption costs [61][62][63]. These studies can be extended to include massive rollout of EVs as well; however, the uncertainties and complexities related to the EV movement, the owners' different charging behaviors, and driving habits make the problem substantially more challenging. ...
... Several decisions related to power are made on the basis of the information of future load demand. Similarly, a consumer can use the forecasted values of electricity prices and change its energy consumption pattern accordingly [44,45]. Electricity load and price forecasting gained attention of researchers in this area because these two factors have a great influence on maintaining the stability of the grid [46,47,48,49]. ...
... They then applied a stochastic bin packing approach to find efficient server allocations [14]. Fatima et al. evaluated a particle swarm optimization algorithm against other approaches in a scenario where the server capacities are assumed to be variable [15]. Wu et al., on the other hand, used a more traditional genetic algorithm concept in their proposed solution for physical and virtual server instance consolidation [16]. ...
... Since the development of WSN-based IoT, multitudinous routing methods have been presented. [28][29][30][31][32][33][34][35] The network conditions are complex and dynamic; hence, it makes the replacement of battery quixotic. Consequently, the energy expenditure of sensor nodes is a crucial concern which seeks research attention. ...