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2024 International Conference on Decision Aid Sciences and Applications, DASA 2024

作者： Mahfuri, Mahmoud Ghwanmeh, Sameh Khishe, Mohammad Saeed, Ali International University for Science and Technology Computer and Information Technology Department Syria College of Computer Information Technology American University in the Emirates Computer Science Dept United Arab Emirates Innovation Center for Artificial Intelligence Applications Yuan Ze University Taiwan Jadara Research Center Jadara University Jordan Computer Center Northern Technical University Ninevah Iraq

ISBN: (纸本)9798350369106

in complex scheduling scenarios, such as the Job scheduling Problem (JSP) faced by human operators, the challenge is to optimize the total time mandatory to complete all jobs and the reliability of the schedule. This paper presents a unified approach that combines constraint satisfaction (CSP) techniques with heuristic algorithms to resolve JSP using operators called JSO(n, p), where n is the number of tasks and p is the number of data. The main aims are to minimize the total time required to complete all tasks and to maximize system consistency under uncertainties such as equipment failure or operator unavailability. We analysis branch-and-bound (BB) methods, neural networks, and hybrid algorithms to achieve optimal software solutions. This paper also assesses the impact of bus constraints on traditional scheduling models and suggests solutions for reliability. The evaluation of various algorithmic strategies and extensive experiments on many sampling problems demonstrate the balance between robustness and optimality. © 2024 IEEE.

关键词： scheduling algorithms

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Heuristics with Local Improvements for Two-Processor scheduling Problem with Energy Constraint and Parallelization 4th

Heuristics with Local Improvements for Two-Processor Sched...

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4th International Conference on Numerical Computations: Theory and algorithms, NUMTA 2023

作者： Zakharova, Yulia V. Sakhno, M.Yu. Sobolev Institute of Mathematics SB RAS Novosibirsk Russia

ISBN: (纸本)9783031812408

Modern computer systems offer some type of parallelism and use restricted resources. Parallel jobs require more than one processor at the same moment of time. Processors may operate at variable speeds. Running a job at a slower speed is more energy-efficient. However, it takes a longer time and affects the performance. We propose and experimentally evaluate heuristic methods based on greedy rules and list scheduling for the speed scaling scheduling problem with the total completion time criterion. Series of instances with various structure are constructed and tested. NP-hard and polynomially solvable cases are identified. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： scheduling algorithms

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On-Time Communications Over Fading Channels

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2024年第1期73卷 605-619页

作者： Li, Yan Dong, Yunquan Wang, Jian Shim, Byonghyo Nanjing Univ Informat Sci & Technol Sch Elect & Informat Engn Nanjing 210044 Peoples R China Anhui Jianzhu Univ Sch Elect & Informat Engn Hefei 230009 Peoples R China Fudan Univ Sch Data Sci Shanghai 200433 Peoples R China Seoul Natl Univ Inst New Media & Commun Seoul 151742 South Korea Seoul Natl Univ Dept Elect & Comp Engn Seoul 151742 South Korea

We consider the on-time transmissions of a sequence of packets over a fading channel. Different from traditional in-time communications, we investigate how many packets can be received delta -on-time, meaning that the packet is received around an expected slot with a deviation no larger than delta slots. In this framework, we first derive the on-time reception rate of the random transmission scheme when no packet-controlling is used. Our analytical and simulation results show that the on-time reception rate of random transmissions decreases (to zero) with the sequence length. To improve the on-time reception rate, we further propose to schedule the packets by delaying, dropping, or repeating the transmissions. Specifically, we model the packet scheduling problem as a Markov decision process (MDP) and then obtain the optimal scheduling policy using an efficient iterative algorithm. By using the optimal packet scheduling, the on-time reception rate converges to a much larger constant, thus ensuring better on-timeliness. Moreover, we show that the on-time reception rate increases if the target reception interval and/or the deviation tolerance delta is increased, or the randomness of the fading channel is reduced. By optimally scheduling the packets and choosing these parameters, therefore, wireless channels will be more suitable for the latency-sensitive applications.

关键词： Delays Fading channels Wireless communication 5G mobile communication Ultra reliable low latency communication Wireless sensor networks scheduling algorithms Information freshness On-time communications on-time reception rate packet scheduling

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Prioritized Task Offloading Mechanism in Cloud-Fog Computing Using Improved Asynchronous Advantage Actor Critic Algorithm

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IEEE ACCESS 2024年 12卷 136628-136656页

作者： Mangalampalli, S. Sudheer Karri, Ganesh Reddy Mohanty, Sachi Nandan Ali, Shahid Khan, Muhammad Ijaz Ismail, Emad Awwad, Fuad A. Manipal Acad Higher Educ Manipal Inst Technol Bengaluru Dept Comp Sci & Engn CSE Manipal 576104 India VIT AP Univ Sch Comp Sci & Engn Amaravati 522237 Andhra Pradesh India Peking Univ Sch Elect Engn Beijing 100084 Peoples R China Riphah Int Univ Dept Math & Stat Islamabad 44000 Pakistan King Saud Univ Coll Business Adm Dept Quantitat Anal Riyadh 11587 Saudi Arabia

Task scheduling is a crucial aspect in cloud computing paradigm as tasks with different processing capacities arise from heterogeneous resources and scheduling these different tasks to precise virtual machines (VM) in cloud datacenters is a crucial job for the Cloud Service Provider (CSP) as it is an NP-hard problem. Ineffective scheduling of tasks in cloud paradigm leads to increase in execution time in turn it effects quality of service which is a huge challenge in cloud paradigm. scheduling tasks to VMs in datacenters which are located at far distances also plays a major part in quality of service of CSP especially in the case of time sensitive tasks. Many of the earlier authors proposed task offloading mechanisms using metaheuristic techniques and machine learning approaches but still there is a chance to improve offloading process by prioritizing tasks based on their runtime capacities, sizes onto fog nodes and schedule them onto precise VMs while addressing important concerns in cloud/fog computing paradigm such as makespan, consumption of energy. In this research, we proposed a task offloading mechanism (PTOMCFIA3C) which considers priorities of tasks and based on the priorities induced into the scheduling offloading mechanism will decide whether to offload tasks to fog/cloud nodes. PTOMCFIA3C modeled using improved Asynchronous Advantage Actor Critic algorithm a deep reinforcement learning technique which is improved by inducing RCNN which can accelerate its learning capability and optimizes scheduling process by offloading tasks to Fog/cloud nodes. Extensive simulations are conducted using simpy by taking the real-time computing worklogs. Simulations conducted in two phases. In the first phase, parameters evaluated with fixed nodes while in second phase parameters evaluated with variable nodes. Proposed PTOMCFIA3C evaluated over existing baseline approaches RATS-HM, MOABCQ, FOG-AMOSM and our proposed task offloading mechanism PTOMCFIA3C generated optimized

关键词： Cloud computing Computational modeling Schedules Dynamic scheduling Quality of service Mathematical models scheduling algorithms Edge computing Energy consumption fog computing task offloading makespan consumption of energy

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Peak AoI Minimization With Directional Charging for Data Collection at Wireless-Powered Network Edge

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IEEE TRANSACTIONS ON SERVICES COMPUTING 2024年第5期17卷 2747-2761页

作者： Chen, Quan Guo, Song Xu, Wenchao Li, Jing Wei, Kang Cai, Zhipeng Gao, Hong Guangdong Univ Technol Sch Comp Sci & Technol Guangzhou 510006 Peoples R China Hong Kong Univ Sci & Technol Dept Comp Sci & Engn Kowloon Hong Kong 999077 Peoples R China Hong Kong Polytech Univ Dept Comp Kowloon Hong Kong 999077 Peoples R China Georgia State Univ Dept Comp Sci Atlanta GA 30303 USA Zhejiang Normal Univ Coll Math & Comp Sci Jinhua 321017 Peoples R China

Age of Information (AoI) has emerged as a new metric to measure data freshness from the destination's perspective. To optimize the system AoI, most existing works focused on the point of scheduling of update transmissions. While at wireless-powered network edge, the source nodes can only transmit their updates after being charged ready, which means the system AoI is not only determined by the update transmission strategies, but also the charging strategies. Thus, in this article, we investigate the first work to optimize the weighted peak AoI from the point of charging at wireless-powered network edge. First, the problem of optimizing the weighted sum of average peak AoI with a directional charger is formulated, and then transformed to a charging time optimization problem with respect to the charging orientations and peak AoI, and an approximate algorithm is proposed to obtain the required charging time for each source node. Second, an age-based scheduling algorithm is proposed to compute the charging decisions and transmission decisions simultaneously, which can not only optimize the weighted sum of average peak AoI, but also guarantee the maximum peak AoI of each source node is bounded. The proposed algorithm is proved to have an approximation ratio of up to (1+ phi ), where phi is a small value related to the weight of each source node. When there exist multiple chargers, an approximate algorithm is also proposed to minimize the weighted sum of average peak AoI by scheduling the orientations of these chargers cooperatively. Finally, the extensive simulations demonstrate the high performance of the proposed algorithms in terms of peak AoI.

关键词： Optimization Approximation algorithms scheduling scheduling algorithms Data communication Computer science Internet of Things Age of information data collection directional charging peak AoI wireless-powered network edge

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A Connectionless Entanglement Distribution Protocol Design in Quantum Networks

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IEEE NETWORK 2024年第1期38卷 131-139页

作者： Xiao, Zirui Li, Jian Xue, Kaiping Li, Zhonghui Yu, Nenghai Sun, Qibin Lu, Jun Univ Sci & Technol China Sch Cyber Sci & Technol Hefei Anhui Peoples R China Univ Sci & Technol China Dept Elect Engn & Informat Sci Hefei 230027 Anhui Peoples R China

Remote entanglement distribution plays a crucial role in quantum networks, which can support many essential and exciting quantum applications. As the network scale expands, it is urgent to design a general and efficient remote entanglement distribution protocol. Nowadays, connection-oriented remote entanglement distribution protocols are available to achieve reliable entanglement distribution. However, in memory-limited quantum networks, connection-oriented entanglement distribution protocols cannot utilize entanglement resources fully and increase the delay of End-to-End (E2E) entanglement connection establishment. To overcome these shortcomings of existing entanglement distribution protocols, we design a connectionless remote entanglement distribution protocol to let Source-Destination (S-D) pairs compete for entanglement resources simultaneously. In our protocol, a fair request scheduling algorithm is proposed to reduce the waiting time without entanglement connections between S-D pairs. Furthermore, a fast scheduling trigger mechanism is proposed to perform entanglement swapping timely to reduce the delay of E2E entanglement connection establishment. The simulation results show that the designed protocol has advantages in terms of resource utilization, throughput, the service completion time of S-D pairs, and the maximum waiting time, compared with the existing remote entanglement distribution protocol.

关键词： Protocols Quantum networks Resource management Delays Quantum entanglement scheduling algorithms Repeaters entanglement distribution connectionless protocol

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RFaaS: Function scheduling Across Heterogeneous Clusters 20th

RFaaS: Function Scheduling Across Heterogeneous Clusters

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20th IFIP WG 10.3 International Conference on Network and Parallel Computing, NPC 2024

作者： Tang, Zhihang Li, Yiming Mao, Zezheng Zhao, Laiping Li, Keqiu College of Intelligence and Computing Tianjin University Tianjin300072 China Intelligent Computing Infrastructure Innovation Center Zhejiang Lab Hangzhou311121 China

ISBN: (纸本)9789819628292

The rapid development of cloud computing has attracted a diverse migration of applications. Serverless computing, with its abstract resource management, on-demand billing, and dynamic scaling, has become a popular cloud computing paradigm. X86 signifies traditional computility, while RISC-V symbolizes new potential. Making the most of existing traditional computing resources while exploring the potential of new computility will be a key challenge. The x86 and RISC-V hybrid computility supply will continue for a long time. Task management under diverse instruction set architectures is a critical issue that needs addressing in this evolving landscape. Current research predominantly concentrates on homogeneous instruction set clusters. In this paper, we propose RFaaS, a function job scheduling methodology tailored for RISC-V + X86 heterogeneous instruction set clusters, leveraging the OpenFaaS serverless computing platform. We delve into the affinity traits of function jobs in RISC-V + X86 amalgamated instruction set clusters and devise an affinity classifier alongside an architecture-aware scheduling algorithm. Our methodology dissects scheduling decisions into resource fulfillment and affinity alignment, underpinned by a meticulously crafted update algorithm to uphold and refine job affinities. Experimental results show that RFaaS can provide at least 3x performance improvement and 2.4x throughput increase compared to existing solutions. © IFIP International Federation for Information Processing 2025.

关键词： scheduling algorithms

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Deadline-Aware Task scheduling for Cloud-Fog Systems 28

Deadline-Aware Task Scheduling for Cloud-Fog Systems

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28th Conference on Innovation in Clouds, Internet and Networks, ICIN 2025

作者： Blanco, Gabriela Azucena Ayala Marcelli, Emiliano Nazareno Rojas Duarte, Alex Rubén Stockel Huang, Hsiang-Ting Li, Keng-Ying Chin, Tai-Lin Dept. CSIE National Taiwan University of Science and Technology Taiwan Universidad Politécnica Taiwán-Paraguay Paraguay

ISBN: (纸本)9798331542399

The integration of fog computing with cloud service reduces transmission times to ensure that Internet of Things (IoT) devices satisfy deadline-aware tasks. Existing researches focus on the effective reduction of task transmission delays in hierarchical fog-cloud networks. However, an improper task execution order increases the waiting time and the risk of missing deadlines. To address this problem, the concept of Deadline-Aware Task Offloading and scheduling (DTOS) is introduced. To balance the load of all fog nodes, this research proposes an offloading strategy using a Genetic Algorithm that encodes multiple chromosomes with different offloading decisions for each task. Each evolution round refines the offloading positions, generating a strategy that approaches the optimal solution. Subsequently, the scheduling algorithm finds an effective execution sequence for each fog node based on the generated offloading decision. The simulation results demonstrate that the proposed strategy is more efficient than the baseline algorithms compared in this research. © 2025 IEEE.

关键词： scheduling algorithms

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A dual-kernel scheduling scheme based on TrustZone 4

A dual-kernel scheduling scheme based on TrustZone

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4th International Conference on Electronic Information Engineering and Computer Communication, EIECC 2024

作者： Qiu, Jintao East China Institute of Computing Technology Department of Basic Software Shanghai China

ISBN: (纸本)9798331534622

With the continuous improvement of the performance of embedded hardware platforms, in the fields of aviation and automotive electronics, an important development direction is to concentrate functions including real-time control, information visualization and human-computer interaction into the same hardware platform. Because of its preemptive design and customized drivers for real-time scenarios, RTOS can meet the requirements of real-time control for hard real-time. However, in terms of the functions related to user experience such as human-computer interaction, the mainstream general operating system (GPOS) such as Windows and Linux is obviously a more suitable choice. In TZDKS architecture, with the help of TrustZone technology under AArch64 architecture, RTOS and GPOS are integrated into the same SoC platform, which can run real-time tasks and common tasks at the same time. However, the Idle scheduling scheme of TZDKS makes the responsiveness of GPOS completely sacrificed when the real-time kernel load is heavy. To solve this problem, this paper uses Sporadic Server algorithm to replace Idle scheduling scheme, and significantly improves the response capability of GPOS while ensuring hard real-time tasks in RTOS. © 2024 IEEE.

关键词： scheduling algorithms

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Optimal Task scheduling in 6G Networks: A Variational Quantum Computing Approach 10th

Optimal Task Scheduling in 6G Networks: A Variational Quant...

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10th EAI International Conference on Industrial Networks and Intelligent Systems, INISCOM 2024

作者： Khalid, Uman Rehman, Junaid ur Farooq, Ahmad Zaman, Fakhar Shin, Hyundong Department of Electronics and Information Convergence Engineering Kyung Hee University Yongin Korea Republic of University of Luxembourg Esch-sur-Alzette Luxembourg Department of Electrical Engineering and Automation Aalto University Espoo Finland Clayton Australia

ISBN: (纸本)9783031673566

Optimal task scheduling in 6G networks plays a crucial role in enabling a wide range of applications such as augmented reality, virtual reality, autonomous vehicles, and the Internet of Things (IoT). With the network landscape becoming a more complex and diverse ecosystem, it is critical to advance conventional scheduling algorithms in order to guarantee the necessary efficiency and performance. In this regard, quantum computing can significantly speed up search for optimal schedules, increase the likelihood of finding optimal solutions, and facilitate the creation of correlations between tasks in a scheduling problem by virtue of parallelism, superposition, and entanglement. In this paper, we explore the variational quantum computing approach to tackle the complex task scheduling problem in cloud radio access network (C-RAN) architecture for 6G networks. By leveraging the quantum approximate optimization algorithm (QAOA) and utilizing IBM Qiskit as a simulation testbed, we aim to optimize task scheduling for enhancing wireless network performance. Herein, the classical quadratic constrained integer optimization (QCIO) problem instance is transformed to an Ising Hamiltonian formulation to implement task scheduling optimization on a quantum computer. We also evaluate the effectiveness and stability of QAOA by analyzing the expected cost and the probability of obtaining an optimal schedule as a function of QAOA circuit layers. Our findings highlight the applicability of variational quantum computing in addressing intricate optimization problems as well as setting the stage for the development of more advanced quantum optimization algorithms for 6G networks. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： scheduling algorithms

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