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Muhammad Qureshi
Department of Computer Science, School of Arts and Sciences, University of Central Asia, 310 Lenin Street, Naryn 722918, Kyrgyzstan

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Journal article
Published: 31 October 2020 in Energies
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Cloud computing is the de facto platform for deploying resource- and data-intensive real-time applications due to the collaboration of large scale resources operating in cross-administrative domains. For example, real-time systems are generated by smart devices (e.g., sensors in smart homes that monitor surroundings in real-time, security cameras that produce video streams in real-time, cloud gaming, social media streams, etc.). Such low-end devices form a microgrid which has low computational and storage capacity and hence offload data unto the cloud for processing. Cloud computing still lacks mature time-oriented scheduling and resource allocation strategies which thoroughly deliberate stringent QoS. Traditional approaches are sufficient only when applications have real-time and data constraints, and cloud storage resources are located with computational resources where the data are locally available for task execution. Such approaches mainly focus on resource provision and latency, and are prone to missing deadlines during tasks execution due to the urgency of the tasks and limited user budget constraints. The timing and data requirements exacerbate the efficient task scheduling and resource allocation problems. To cope with the aforementioned gaps, we propose a time- and cost-efficient resource allocation strategy for smart systems that periodically offload computational and data-intensive load to the cloud. The proposed strategy minimizes the data files transfer overhead to computing resources by selecting appropriate pairs of computing and storage resources. The celebrated results show the effectiveness of the proposed technique in terms of resource selection and tasks processing within time and budget constraints when compared with the other counterparts.

ACS Style

Muhammad Qureshi; Muhammad Qureshi; Muhammad Fayaz; Muhammad Zakarya; Sheraz Aslam; Asadullah Shah. Time and Cost Efficient Cloud Resource Aallocation for Real-Time Data-Intensive Smart Systems. Energies 2020, 13, 5706 .

AMA Style

Muhammad Qureshi, Muhammad Qureshi, Muhammad Fayaz, Muhammad Zakarya, Sheraz Aslam, Asadullah Shah. Time and Cost Efficient Cloud Resource Aallocation for Real-Time Data-Intensive Smart Systems. Energies. 2020; 13 (21):5706.

Chicago/Turabian Style

Muhammad Qureshi; Muhammad Qureshi; Muhammad Fayaz; Muhammad Zakarya; Sheraz Aslam; Asadullah Shah. 2020. "Time and Cost Efficient Cloud Resource Aallocation for Real-Time Data-Intensive Smart Systems." Energies 13, no. 21: 5706.

Review article
Published: 21 August 2020 in International Journal of Distributed Sensor Networks
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An efficient resource allocation scheme plays a vital role in scheduling applications on high-performance computing resources in order to achieve desired level of service. The major part of the existing literature on resource allocation is covered by the real-time services having timing constraints as primary parameter. Resource allocation schemes for the real-time services have been designed with various architectures (static, dynamic, centralized, or distributed) and quality of service criteria (cost efficiency, completion time minimization, energy efficiency, and memory optimization). In this analysis, numerous resource allocation schemes for real-time services in various high-performance computing (distributed and non-distributed) domains have been studied and compared on the basis of common parameters such as application type, operational environment, optimization goal, architecture, system size, resource type, optimality, simulation tool, comparison technique, and input data. The basic aim of this study is to provide a consolidated platform to the researchers working on scheduling and allocating high-performance computing resources to the real-time services. This work comprehensively discusses, integrates, analysis, and categorizes all resource allocation schemes for real-time services into five high-performance computing classes: grid, cloud, edge, fog, and multicore computing systems. The workflow representations of the studied schemes help the readers in understanding basic working and architectures of these mechanisms in order to investigate further research gaps.

ACS Style

Muhammad Shuaib Qureshi; Muhammad Fayaz; Wali Khan Mashwani; Samir Brahim Belhaouari; Saima Hassan; Asadullah Shah. A comparative analysis of resource allocation schemes for real-time services in high-performance computing systems. International Journal of Distributed Sensor Networks 2020, 16, 1 .

AMA Style

Muhammad Shuaib Qureshi, Muhammad Fayaz, Wali Khan Mashwani, Samir Brahim Belhaouari, Saima Hassan, Asadullah Shah. A comparative analysis of resource allocation schemes for real-time services in high-performance computing systems. International Journal of Distributed Sensor Networks. 2020; 16 (8):1.

Chicago/Turabian Style

Muhammad Shuaib Qureshi; Muhammad Fayaz; Wali Khan Mashwani; Samir Brahim Belhaouari; Saima Hassan; Asadullah Shah. 2020. "A comparative analysis of resource allocation schemes for real-time services in high-performance computing systems." International Journal of Distributed Sensor Networks 16, no. 8: 1.

Journal article
Published: 16 June 2020 in Electronics
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Internet of Things (IoT) is getting more popular day by day, which triggers its adoption for solving domain specific problems. Cities are becoming smart by gathering the context knowledge through sensors and controlling specific parameters through actuators. Dynamically discovering and integrating different data streams from different sensors is a major challenge these days. In this paper, a service matchmaking algorithm is presented for service discovery utilizing IoT devices and services in a particular geographic area. It helps us to identify services based on a variety of parameters (location, query size and processing time, etc.). Customization of service selection and discovery are also explored. The conceptual framework is provided for the proposed model along with a matchmaking algorithm based on IoT devices virtualization. The simulation results elaborate the increased complexity of processing time with respect to the increasing pool of available services. The average processing time varies as the number of conditions are multiplied. Query size and complexity increases with additional number of filters and conditions which results in the reduction of the number of matching services. Moreover, upon decreasing the radius of geographic search area, the number of candidate services decreases for service matching algorithm. This is based on the assumption that IoT devices and services are evenly distributed in a given geographic area. Similarly, the remaining energy of IoT devices is also assumed to be uniformly distributed and, therefore, if we are interested in IoT devices or services with more residual energy, then a limited number of IoT devices or services will fulfill this criterion.

ACS Style

Zulfiqar Ali Khan; Israr Ullah; Muhammad Ibrahim; Muhammad Fayaz; Ayman AlJarbouh; Muhammad Shuaib Qureshi. Virtualization Based Efficient Service Matching and Discovery in Internet of Things. Electronics 2020, 9, 1 .

AMA Style

Zulfiqar Ali Khan, Israr Ullah, Muhammad Ibrahim, Muhammad Fayaz, Ayman AlJarbouh, Muhammad Shuaib Qureshi. Virtualization Based Efficient Service Matching and Discovery in Internet of Things. Electronics. 2020; 9 (6):1.

Chicago/Turabian Style

Zulfiqar Ali Khan; Israr Ullah; Muhammad Ibrahim; Muhammad Fayaz; Ayman AlJarbouh; Muhammad Shuaib Qureshi. 2020. "Virtualization Based Efficient Service Matching and Discovery in Internet of Things." Electronics 9, no. 6: 1.

Journal article
Published: 01 June 2020 in International Journal of ADVANCED AND APPLIED SCIENCES
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ACS Style

Qureshi Et Al.. A theoretical model of healthcare monitoring surveillance system for patients with severe allergies. International Journal of ADVANCED AND APPLIED SCIENCES 2020, 7, 69 -75.

AMA Style

Qureshi Et Al.. A theoretical model of healthcare monitoring surveillance system for patients with severe allergies. International Journal of ADVANCED AND APPLIED SCIENCES. 2020; 7 (6):69-75.

Chicago/Turabian Style

Qureshi Et Al.. 2020. "A theoretical model of healthcare monitoring surveillance system for patients with severe allergies." International Journal of ADVANCED AND APPLIED SCIENCES 7, no. 6: 69-75.

Journal article
Published: 21 May 2020 in Systems
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Geometric-Zeno behaviour is a highly challenging problem in the analysis (including simulation) of hybrid systems. Geometric-Zeno can be defined as an infinite number of discrete mode switches in a finite time interval. Typically, for hybrid models exhibiting geometric-Zeno, the numerical simulation either halts or produces false results, because an infinite number of discrete events occur in a given simulation time-step. In this paper, we provide formal methods for regularization of geometric-Zeno behaviour by using a non-standard analysis. In particular, we provide formal conditions for the existence of geometric-Zeno in hybrid systems, and we propose methods to allow geometric-Zeno executions to be continued beyond geometric-Zeno limit points. The concepts are illustrated with a case study throughout the paper.

ACS Style

Ayman AlJarbouh; Muhammad Fayaz; Muhammad Shuaib Qureshi. Non-Standard Analysis for Regularization of Geometric-Zeno Behaviour in Hybrid Systems. Systems 2020, 8, 1 .

AMA Style

Ayman AlJarbouh, Muhammad Fayaz, Muhammad Shuaib Qureshi. Non-Standard Analysis for Regularization of Geometric-Zeno Behaviour in Hybrid Systems. Systems. 2020; 8 (2):1.

Chicago/Turabian Style

Ayman AlJarbouh; Muhammad Fayaz; Muhammad Shuaib Qureshi. 2020. "Non-Standard Analysis for Regularization of Geometric-Zeno Behaviour in Hybrid Systems." Systems 8, no. 2: 1.

Journal article
Published: 25 December 2019 in Symmetry
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The standard manufacturing organizations follow certain rules. The highest ubiquitous organizing principles in infrastructure design are modular idea and symmetry, both of which are of the utmost importance. Symmetry is a substantial principle in the manufacturing industry. Symmetrical procedures act as the structural apparatus for manufacturing design. The rapid growth of population needs outstrip infrastructure such as roads, bridges, railway lines, commercial, residential buildings, etc. Numerous underground facilities are also installed to fulfill different requirements of the people. In these facilities one of the most important facility is water supply pipelines. Therefore, it is essential to regularly analyze the water supply pipelines’ risk index in order to escape from economic and human losses. In this paper, we proposed a simplified hierarchical fuzzy logic (SHFL) model to reduce the set of rules. To this end, we have considered four essential factors of water supply pipelines as input to the proposed SHFL model that are: leakage, depth, length and age. Different numbers of membership functions are defined for each factor according to its distribution. The proposed SHFL model takes only 95 rules as compared to the traditional mamdani fuzzy logic method that requires 1225 rules. It is very hard and time consuming for experts to design 1225 rules accurately and precisely. Further, we proposed a Do-it-Yourself (DIY) system for the proposed SHFL method. The purpose of the DIY system is that one can design the FIS model according to his or her need.

ACS Style

Muhammad Fayaz; Quoc Bao Pham; Nguyen Thi Thuy Linh; Pham Thi Thao Nhi; Dao Nguyen Khoi; Muhammad Shuaib Qureshi; Abdul Salam Shah; Shah Khalid; Nguyen-Khoi Dao. A Water Supply Pipeline Risk Analysis Methodology Based on DIY and Hierarchical Fuzzy Inference. Symmetry 2019, 12, 44 .

AMA Style

Muhammad Fayaz, Quoc Bao Pham, Nguyen Thi Thuy Linh, Pham Thi Thao Nhi, Dao Nguyen Khoi, Muhammad Shuaib Qureshi, Abdul Salam Shah, Shah Khalid, Nguyen-Khoi Dao. A Water Supply Pipeline Risk Analysis Methodology Based on DIY and Hierarchical Fuzzy Inference. Symmetry. 2019; 12 (1):44.

Chicago/Turabian Style

Muhammad Fayaz; Quoc Bao Pham; Nguyen Thi Thuy Linh; Pham Thi Thao Nhi; Dao Nguyen Khoi; Muhammad Shuaib Qureshi; Abdul Salam Shah; Shah Khalid; Nguyen-Khoi Dao. 2019. "A Water Supply Pipeline Risk Analysis Methodology Based on DIY and Hierarchical Fuzzy Inference." Symmetry 12, no. 1: 44.