Quantum-based predictive fog scheduler for IoT applications

Bhatia, Munish; Sood, Sandeep K.; Kaur, Simranpreet

doi:10.1016/j.compind.2019.06.002

Cited by 59 publications

(23 citation statements)

References 22 publications

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“…Quantum genetic algorithms are capable of solving several practical, inspiring difficulties in various manufacturing arenas, shipping, wrapping, and network-based areas, the feature assortment computation problem, traveling salesman computation problem, the variation flow-shop computation problem, the container packing computation problem, the knapsack computation problem, the lot-sizing computation problem, the job-shop computation problem, and the quadratic assignment computation problem. In the field of fog computing [213], the main challenges to be faced are security and trait, mainly for a distributed environment.…”

Section: Future Research Directions In Quantum Algorithms and Dronesmentioning

confidence: 99%

Survey of Promising Technologies for Quantum Drones and Networks

Kumar¹,

Bhatia

Kaushik

et al. 2021

IEEE Access

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Due to recent advancements in quantum drones, the Internet of Quantum Drones (IoQDs), and Drone-to-Satellite connectivity, several advantages have been anticipated for real-time applications. This work examines quantum computing issues, including quantum data processing, techniques, circuits, and algorithms important for quantum drones or their networks. Here, we discussed the current research trends on quantum computing, quantum-safe computing, or post-quantum cryptography important to quantum networks, followed by the numerous advantages, limitations, future advancements, and research issues connected with quantum technologies, drones, and their network. This work has also prepared a taxonomy of quantum-related areas depending upon the logic of their learning, followed by a review of each of these areas. We review the most recent work over quantum algorithms used in various-quantum-related areas and networks, the role of quantum satellites for drone-based networks and communications, how quantum artificial intelligence and quantum machine learning are important for quantum drones, networks and futuristic applications, quantum attacks, quantum genetic algorithms, and the importance of post-quantum and quantum-safe cryptography. The challenges and research directions in these domains are explored as well. Lastly, this work presents an overview of the current state of knowledge in various promising technologies that are recently found to be important for quantum drones and networks.

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Section: Future Research Directions In Quantum Algorithms and Dronesmentioning

confidence: 99%

Survey of Promising Technologies for Quantum Drones and Networks

Kumar¹,

Bhatia

Kaushik

et al. 2021

IEEE Access

View full text Add to dashboard Cite

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“…The second point explains our key software and the automatic and parallel judgment system in more detail. computing [5,10,13]. Especially, CLIK is built with OpenStack [15], the most popular open-source project for creating cloud systems.…”

Section: Designmentioning

confidence: 99%

CLIK: Cloud‐based Linux kernel practice environment and judgment system

Park

Kim

2020

Comp Applic In Engineering

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Assignments on kernel programming are essential parts of operating system (OS) courses taught to computer science students to provide them a deep understanding of real‐world OSs. However, these assignments require tremendous effort from both students and instructors. Students are routinely flustered by the daunting task of building a practice environment from scratch; instructors are pressurized for time while validating a student's work that requires several kernel installations and reboots. To minimize this effort, we propose CLIK, a cloud‐based Linux kernel practice environment supporting automatic judgment. It provides students with an individual and easy‐to‐use kernel practice environment and instructors with a fast and easy evaluation of students' work with live feedback. Our experiences with two assignments from a real‐world OS course carried out on CLIK show that CLIK can successfully provide Linux kernel environments for 40 students and help instructors greatly by validating their kernels within one minute using parallel and automated judgments. We also describe detailed lessons learned from developing CLIK that will help both researchers and instructors building similar systems.

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“…Researchers globally have put forward numerous QC-Algorithms (QCA) to generate effective outputs in real-time applications. Bhatia et al (2019) used QC-inspired (QCI) approach for scheduling tasks in fog computing environments. The experimental simulation was carried out for scheduling 600 tasks over 10 computing nodes.…”

Section: Qci-approach For Optimization Problemsmentioning

confidence: 99%

“…Specifically, 5 related works of literature are mentioned for the comparative assessment. These are , Liu et al (2018), Dey et al (2019), Dey et al (2019), andBhatia et al (2019). Table 5 describes various features for determining the novelty of the presented study.…”

Section: Comparative Analysismentioning

confidence: 99%

A novel quantum-inspired solution for high-performance energy-efficient data acquisition from IoT networks

Bhatia

Sood

Sood³

2020

J Ambient Intell Human Comput

Self Cite

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Accuracy in IoT data acquisition has been an indispensable need to meet the increasing demand for time-sensitive data analysis, and real-time decision-making. Conspicuously, this study proposes a Quantum Computing inspired technique of temporal space optimization for real-time big IoT applications. For this purpose, quantification of IoT sensors is performed in terms of Sensors of Interest (SoI) and Degree of Aptness (DoA) measure to minimize IoT sensor-space in real-time. The proposed methodology incorporates quantum computing-based formalization of IoT sensor parameters to present a Quantum-Temporal Minimization Algorithm. Moreover, 2 key performance indicators in terms of Data Similarity Analysis and Energy Efficiency are estimated for optimized efficacy. To evaluate the presented technique, numerous simulations are performed in real-time scenario of vehicular traffic determination over 1km of Regional National Highway using 70 WiSense nodes comprising of noise sensors, vibration sensors, and Raspberry Pi device. Acquired data comprising of 28,586 segments are stored in the Amazon EC2 cloud database for evaluation. The performance enhancement is estimated based on comparative analysis with several state-of-the-art optimization techniques. Results registered depict that significant improvements are registered for the presented technique in terms of temporal effectiveness, and performance parameters like Accuracy, Correlation Analysis, and Reliability.

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Quantum-based predictive fog scheduler for IoT applications

Cited by 59 publications

References 22 publications

Survey of Promising Technologies for Quantum Drones and Networks

Survey of Promising Technologies for Quantum Drones and Networks

CLIK: Cloud‐based Linux kernel practice environment and judgment system

A novel quantum-inspired solution for high-performance energy-efficient data acquisition from IoT networks

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