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2nd International Conference on Cyber Intelligence and Information Retrieval, CIIR 2023

作者： Malviya, Abhishek Pandey, Sudhakar Tiwari, Amit Kumar Department of Information Technology NIT-Raipur Chattisgarh Raipur492010 India Department of Computer Science and Engineering United Institute of Technology Uttar Pradesh Prayagraj211010 India

ISBN: (纸本)9789819776023

In the complex world of modern telecommunication networks, Baseband Unit (BBU) pools play a crucial role in optimizing data processing and minimizing response time. This paper presents the Adaptive Queue Dynamics (AQD) scheduling algorithm, a cutting-edge approach specifically tailored for BBU systems. By combining traditional queuing principles with a feedback control mechanism, AQD allows for real-time adaptation to changing network conditions. Through constant monitoring of important system metrics and the use of a real-time feedback loop, AQD is able to intelligently adapt queuing parameters for optimal scheduling. With its ability to dynamically tune and continuously adapt parameters, AQD stands out by enabling the system to swiftly respond to unexpected events or sudden changes, ensuring minimal response time. Mathematical modeling and extensive simulations confirm the effectiveness of AQD in achieving this objective when compared to traditional methods. The AQD approach represents a significant leap forward in telecommunication network efficiency, providing a strong and adaptable solution designed for the demands of modern BBU systems. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： scheduling algorithms

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Low Complexity scheduling algorithms for Wireless Networks with Full Duplex State Exchange 48th

Low Complexity Scheduling Algorithms for Wireless Networks w...

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48th Annual Conference on Information Sciences and Systems (CISS)

作者： Wang, Weihe Subramanian, Vijay Guo, Dongning Northwestern Univ Dept EECS Evanston IL 60208 USA

ISBN: (纸本)9781479930012

In a peer-to-peer wireless network, efficient distributed scheduling algorithms generally require all active nodes to acquire the state information of their respective neighbors, e.g., their queue lengths. However, information exchange between nodes is challenging in the absence of a collision-free schedule, mainly due to the half duplex design of today's radios. This paper studies medium access control (MAC) with the help of a physical layer technique that allows all nodes to efficiently exchange state messages with one-hop neighbors at the same time. Low-complexity distributed scheduling algorithms using simultaneous message exchange are proposed for two interference models. One of the algorithms is shown to produce schedules realizable by the greedy maximal scheduling algorithm under the node-exclusive interference model. Simulations demonstrate that both algorithms outperform some popular distributed random access schemes.

关键词： Distributed algorithms full duplex scheduling algorithms wireless networks

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Energy and Resource Aware scheduling in Cloud-Fog Environment using Advanced Meta Heuristic Algorithm 2

Energy and Resource Aware Scheduling in Cloud-Fog Environmen...

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2nd International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2024

作者： Bennett, Corbin Reginald Oduru, Rohan Reddy McLaughlin, Dominick Parvathaneni, Lokesh Riquelme, Noah Bryan Medishetti, Santhosh Kumar George Mason University United States Nalla Narasimha Reddy Education Society's Group of Institution India VIT-AP University Amaravathi India

ISBN: (纸本)9798350368413

For efficient management of energy and resources, especially in Cloud-Fog Computing (CFC) environment that is constantly changing and is on the rise, effective scheduling of tasks plays a crucial role. The research in this paper proposes a new approach of utilizing the Honey Badger Algorithm (HBA) for Energy and Resource aware scheduling in a CFC environment. The HBA mimics the honey badger's foraging strategy and anyone who has observed a honey badger foraging recognizes that the algorithm is a fair representation;the agent is exploring as well as exploiting, finding the best areas and ensuring minimal energy expenditure. The proposed method prioritizes tasks based on their energy demands and resource requirements, dynamically adjusting schedules to account for varying workloads and environmental conditions. Extensive simulations demonstrate that the HBA outperforms existing algorithms PSO, GA, and IDOA in terms of energy consumption reduced by 15.6%, optimizes the resource utilization by 18.2%, task completion time improved by 17.4%, and maximizes the throughput by 21.2% making it a promising solution for sustainable and scalable CFC environments. © 2024 IEEE.

关键词： scheduling algorithms

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Providing Near Per-Flow scheduling in Commodity Switches Without Per-Flow Queues

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IEEE Access 2023年 11卷 54029-54044页

作者： Wang, Shie-Yuan Sun, Chen-Yo Hsiao, Yu-Chen Lin, Yi-Bing National Yang Ming Chiao Tung University Computer Science Hsinchu300 Taiwan

Network quality of service (QoS) is essential for network applications. For many applications, getting a fair share of available bandwidth for their flows can prevent them from being blocked by other flows that do not respond to congestion. Providing per-flow scheduling in each output port of a commodity switch can isolate the flows that compete for the bandwidth of a bottleneck link. Although per-flow scheduling can maintain fair shares among competing flows, due to the high implementation costs of providing per-flow queues in commodity switches, this capability is rarely provided in commodity switches on the market. To address this need, we design and implement a near-per-flow scheduling scheme named Near Per-flow scheduling (NPFS) in P4 programmable hardware switches and evaluate its performance. NPFS provides near-per-flow scheduling effectiveness in commodity switches that do not have per-flow queues in their output ports. NPFS utilizes the priority queues provided in most commodity switches and dynamically assigns competing flows to these queues based on their protocol types and current sending rates. Experimental results show that, when the number of competing flows is less than three times the number of queues, NPFS guarantees that the achieved bandwidths of these flows only deviate from their ideal fair shares by 5%. © 2013 IEEE.

关键词： scheduling algorithms

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Slow-movement particle swarm optimization algorithms for scheduling security-critical tasks in resource-limited mobile edge computing

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2020年 112卷 148-161页

作者： Zhang, Yi Liu, Yu Zhou, Junlong Sun, Jin Li, Keqin Nanjing Univ Sci & Technol Sch Comp Sci & Engn 200 Xiaolingwei St Nanjing 210094 Peoples R China Lian Yungang E Port Informat Dev Co Ltd Lian Yungang Peoples R China SUNY Coll New Paltz Dept Comp Sci New Paltz NY 12561 USA

Mobile edge computing (MEC) allows mobile devices to offload computation tasks to nearby MEC servers for achieving low latency and energy efficiency. This paper aims at scheduling security-critical tasks, which require data encryption and thus incur extra runtime and energy costs, in a MEC system consisting of multiple resource-limited MEC servers. The scheduling objective is to minimize task completion time as well as the mobile device's energy consumption. We propose two slow-movement particle swarm optimization algorithms to solve the resultant NP-hard problem. Specifically, we develop a position-based mapping scheme to map particles onto scheduling solutions. The mapping method relies on the current best solution and a position-based probability model to generate high-quality solutions that can inherit the good schemata from the current best solution. To prevent the significant change in particles' positions, we further propose a novel particle updating strategy to slow down particles' movements, in order to explore more high-quality solutions under the guide of personal best particle and global best particle. Experimental results demonstrate that, the proposed algorithms significantly outperform the conventional particle swarm optimization algorithm in terms of both effectiveness and efficiency. Performance of the mapping method and the particle updating strategy are also investigated. (C) 2020 Elsevier B.V. All rights reserved.

关键词： Mobile edge computing Security-critical tasks scheduling algorithms Particle swarm optimization

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MQDS: An energy saving scheduling strategy with diverse QoS constraints towards reconfigurable cloud storage systems

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2022年 129卷 252-268页

作者： You, Xindong Sun, Dawei Lv, Xueqiang Gao, Shang Buyya, Rajkumar Beijing Informat Sci & Technol Univ Beijing Key Lab Internet Culture & Digital Dissem Beijing 100101 Peoples R China China Univ Geosci Sch Informat Engn Beijing 100083 Peoples R China Deakin Univ Sch Informat Technol Waurn Ponds Vic 3216 Australia Univ Melbourne Sch Comp & Informat Syst Cloud Comp & Distributed Syst CLOUDS Lab Melbourne Vic Australia

Nowadays, cloud storage systems are usually constructed by heterogeneous disks with reconfigurable speed for energy efficiency. scheduling tasks with diverse QoS (Quality of Service) requirements to disks with different speeds is seldom considered in state-of-the-art mainstream disk scheduling algorithms. This paper proposes a multi-QoS disk scheduling strategy (MQDS), aiming to support energy-saving and diverse QoS constraints towards reconfigurable heterogeneous cloud storage systems. Three algorithms are designed in MQDS: Time Prior Disks Algorithm (TPDS) for time-sensitive tasks, Cost Prior Disks Algorithm (CPDS) for cost-sensitive tasks, and Benefit Function-based Disks Algorithm (BFDS) for tasks with time-varying QoS requirements. CloudSimDisk simulator is extended to evaluate the response time, energy consumption and cost expenditure performance of the proposed algorithms, for comparison with the extended Robin Round Disk scheduling algorithm (E-RRDS). Extensive experimental results demonstrate that the three proposed algorithms outperform E-RRDS. TPDS consumes shortest response time and CPDS has the least cost;and BFDS achieves balance between TPDS and CPDS, which provide more options to users. It is worth mentioning that all the algorithms in MQDS are more energy efficient than E-RRDS. As a whole, the proposed MQDS is energy efficient and able to accommodate diverse QoS constraints well. (C) 2021 Elsevier B.V. All rights reserved.

关键词： Reconfigurable disk Quality of Service Energy efficiency Cloud storage scheduling algorithms

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Quality-Oriented Task Allocation and scheduling in Transcoding Servers With Heterogeneous Processors

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2022年第3期32卷 1667-1680页

作者： Lee, Dayoung Song, Minseok Inha Univ Dept Comp Engn Incheon 22212 South Korea

Dynamically adaptive streaming over HTTP requires a large-scale server to transcode various bitrate versions in which different preset parameters can be used to provide different video qualities at each resolution. When transcoding servers contain a heterogeneous mix of CPUs and GPUs, the task scheduler must choose a processor and preset parameter for each transcoding task to meet the transcoding deadlines while achieving the best possible video quality. We apply regression analysis to sample variable-bit-rate videos to provide accurate (mean absolute percentage error values from 1.3% to 13.9%) model for predicting bitrate, transcoding time and video quality at each resolution on different processors. We build this into a greedy allocation and scheduling algorithm which first satisfies deadlines with low video quality, and then redistributes the workload to improve that quality while continuing to meet the deadlines. This scheme was both simulated and implemented on a testbed server. It satisfies all deadlines while outperforming standard algorithms by between 3.12% and 15.59% in terms of popularity-weighted video quality divided by bitrate.

关键词： Transcoding Task analysis Streaming media Servers Bit rate Video recording Quality assessment Multimedia systems transcoding scheduling algorithms

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Version Age of Information Minimization Over Fading Broadcast Channels

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2025年第2期24卷 1620-1634页

作者： Karevvanavar, Gangadhar Pable, Hrishikesh Patil, Om Bhat, Rajshekhar Vishweshwar Pappas, Nikolaos Indian Inst Technol Dharwad Dharwad 580011 Karnataka India Linkoping Univ Dept Comp & Informat Sci S-58183 Linkoping Sweden

We consider a base station (BS) that receives version update packets from multiple streams and broadcasts them using non-orthogonal multiple access (NOMA) over a fading broadcast channel. Sequentially indexed packets arrive randomly, rendering previous ones obsolete. The version age of information (VAoI) at a user is defined as the difference between the latest packet's version index at the BS and at the user. Our objective is to minimize the average VAoI across users, subject to an average power constraint at the BS, by optimally scheduling and transmitting packets with sufficient power for successful delivery. We consider channel-only stationary randomized policies (CO-SRP), making transmission decisions based on channel power gains, and obtain optimal CO-SRP, showing that VAoI achieved with CO-SRP is within twice the optimal VAoI. We also develop a Constrained Markov Decision Process (CMDP)-based solution, several heuristic benchmarks, and analyze CMDP policy properties. Simulations compare achievable VAoI and computational performance of various policies and reveal differences between optimizing AoI and VAoI. Notably, a scheme allowing transmission to at most one user at a time matches NOMA's performance under strict power constraints but is outperformed when constraints are relaxed. Additionally, AoI-optimized policies result in higher VAoI compared to VAoI-optimized policies and vice versa, when user arrival rates are mismatched.

关键词： NOMA Fading channels Streams Optimization Decoding Transmitters Minimization Information age Wireless communication Time division multiple access Version age of information non-orthogonal multiple access time division multiple access broadcast channel scheduling algorithms

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The Structure of Hypergraphs Arising in Cellular Mobile Communication Systems

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IEEE TRANSACTIONS ON MOBILE COMPUTING 2025年第1期24卷 150-164页

作者： Ganesan, Ashwin Atlas SkillTech Univ Mumbai 400070 Maharashtra India

An assumption that researchers have often used to model interference in a wireless network is the unit disk graph model. While many theoretical results and performance guarantees have been obtained under this model, an open research direction is to extend these results to hypergraph interference models. Motivated by recent results that the worst-case performance of the distributed maximal scheduling algorithm is characterized by the interference degree of the hypergraph, in the present work we investigate properties of the interference degree of the hypergraph and the structure of hypergraphs arising from physical constraints. We show that the problem of computing the interference degree of a hypergraph is NP-hard and we prove some properties and results concerning this hypergraph invariant. We investigate which hypergraphs are realizable, i.e. which hypergraphs arise in practice, based on physical constraints, as the interference model of a wireless network. In particular, a question that arises naturally is: what is the maximal value of r such that the hypergraph K-1,K-r is realizable? We determine this quantity for various integral and nonintegral values of the path loss exponent of signal propagation. We also investigate hypergraphs generated by line networks.

关键词： Interference scheduling algorithms Stars scheduling Signal to noise ratio Propagation losses Applications of hypergraph theory applied algorithms cellular systems distributed algorithms hypergraph models interference degree maximal scheduling unit disk graphs wireless networks wireless networks

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Visual Sensor Network Task scheduling Algorithm at Automated Container Terminal

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IEEE SENSORS JOURNAL 2022年第6期22卷 6042-6051页

作者： Mi, Chao Chen, Jian Zhang, Zhiwei Huang, Shifeng Postolache, Octavian Shanghai Maritime Univ Minist Educ Container Supply Chain Technol Engn Res Ctr Shanghai 201306 Peoples R China Shanghai Maritime Univ Logist Engn Sch Shanghai 201306 Peoples R China Shanghai SMUVis Smart Technol Ltd Shanghai 201306 Peoples R China Shanghai Maritime Univ Logist Sci & Engn Res Inst Sch Shanghai 201306 Peoples R China Inst Telecomunicacoes P-1049001 Lisbon Portugal Univ Lisbon ISCTE Inst P-1649026 Lisbon Portugal

The visual sensor network (VSN) is an important part of the automated container terminal. VSN present also a of problems such as the redundant number of visual sensors and limited computing resources. Different vision sensors are reported in literature when about computing resources (CR) reduced number of publications provides information about required CR as part of visual sensor network. In this context the paper propose solution that transforms the visual sensor network terminal task scheduling process into Markov Decision Process. Thus, a visual sensor network terminal task scheduling algorithm based on Deep-Q Learning is considered. In this algorithm, an innovative return value function is proposed to achieve better algorithm convergence. To verify the effectiveness of the model, several experiments were carried out under different conditions. The result shows that the recognition rate is improved by using the proposed algorithm. Based on considered method the number of visual sensors can be reduced, that conducts to a rational use of limited computing resources. At the same time cost reduction is also provided that is an important requirement of port operation optimization.

关键词： Task analysis Sensors Containers Visualization Vision sensors Wireless sensor networks scheduling algorithms Automated container terminal computing resources deep-Q learning visual sensor network

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