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Application scheduling With Multiplexed Sensing of Monitoring Points in Multi-Purpose IoT Wireless Sensor Networks

IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT 2024年第1期21卷 729-744页

作者： Cavdar, Mustafa Can Korpeoglu, Ibrahim Ulusoy, Ozgur Bilkent Univ Dept Comp Engn TR-06800 Ankara Turkiye

Wireless sensor networks (WSNs) play a crucial role in Internet-of-Things (IoT) systems serving a variety of applications. They gather data from specific sensor nodes and transmit it to remote units for processing. When multiple applications share a WSN infrastructure, efficient scheduling becomes vital. In our research, we address the problem of application scheduling in WSNs. Specifically, we focus on scenarios where applications request data from monitoring points within the coverage area of a WSN. We propose a shared-data approach that reduces the network's sensing and communication load by allowing multiple applications to use the same sensing data. To tackle the scheduling challenge, we introduce a genetic algorithm named GABAS and three greedy algorithms: LMPF, LMSF, and LTSF. These algorithms determine the order in which applications are admitted to the WSN infrastructure, considering various criteria. To assess the performance of our algorithms, we conducted extensive simulation experiments and compared them with standard scheduling methods. We also evaluated the performance of GABAS as compared to another genetic scheduling algorithm that has recently appeared in the literature. The overall experimental results show that the methods we propose outperform the compared approaches across various metrics, namely makespan, turnaround time, waiting time, and successful execution rate. In particular, our genetic algorithm proves to be highly effective in scheduling applications and optimizing the mentioned metrics.

关键词： Wireless sensor networks Monitoring Task analysis Sensors Measurement scheduling algorithms Genetic algorithms Internet of Things application scheduling algorithms

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Key Flow First Prioritized Flow scheduling Strategy in Multi-Tenant Data Centers

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IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT 2024年第3期21卷 3264-3277页

作者： Tao, Xudong Qian, Xiaoyan Han, Lei Fan, Weibei Shi, Yuzhou Zhu, Xinrui Li, Zhiyu Wei, Shuwen Xu, Rui Nanjing Univ Aeronaut & Astronaut Coll Civil Aviat Nanjing 211106 Peoples R China Nanjing Univ Posts & Telecommun Sch Comp Nanjing 210023 Peoples R China Nanjing Univ Aeronaut & Astronaut Nanjing 210016 Peoples R China

The mixed flow in multi-tenant data centers presents a challenge for priority flow scheduling due to the coexistence of various requirements such as latency and throughput. To address this issue, we propose Key Flow First (KFF), a balanced scheduling algorithm suitable for mixed flows in multi-tenant data centers. Firstly, KFF categorizes flows into Latency-Sensitive Flows (LS Flow) and Throughput-Demanding Flows (TD Flow) based on the Quality of Service (QoS) of their application sources. Secondly, it further differentiates flows into Mice Flows and Elephants Flows based on the amount of already sent bytes. Thirdly, KFF employs the Multi-Level Feedback Queue (MLFQ) threshold update algorithm and a priority-based strict forwarding mechanism. By avoiding reliance on complex flow priors, KFF consistently maintains reasonable scheduling of mixed flows under different load scenarios. Experimental results demonstrate that KFF effectively reduces the real-time load on the network and achieves good performance in terms of MAX (Shortest Job First (SJF), Earliest Deadline First (EDF)) performance under diverse load conditions. Compared to PIAS, KFF reduces the FCT slow down of deadline flows by nearly 60% under high TD loads;compared to Karuma and Time Deadline Aware pFabric (TDA-pFabric), KFF reduces the flow completion time (FCT) slow down of non-deadline Mice flows by over 90% under high LS loads and meanwhile guaranteeing nearly 0 deadline miss rate.

关键词： Computer networks Data centers scheduling algorithms Heuristic algorithms Communication system traffic scheduling Quality of service Data center networks traffic engineering flow scheduling fair queueing

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Scalable scheduling in Time-Sensitive Networking: An Efficient Stream Conflict Detection Method

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2025年第5期21卷 4105-4116页

作者： Xu, Lei Chen, Cailian Zhang, Yanzhou Li, Xin Wang, Shouliang Xu, Qimin Guan, Xinping Shanghai Jiao Tong Univ Sch Elect Informat & Elect Engn Shanghai 200240 Peoples R China Shanghai Key Lab Integrated Adm Technol Informat S Shanghai 200240 Peoples R China Minist Educ China Key Lab Syst Control & Informat Proc Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ SJTU Paris Elite Inst Technol Shanghai 200240 Peoples R China

As an emerging communication technology, time-sensitive networking (TSN) holds the potential to enable real-time and deterministic interactions for streams within the Industrial Internet of Things. However, effectively and promptly scheduling large-scale streams in the TSN network poses a significant challenge due to high computational complexity. In this article, we conduct a schedulability analysis to preprocess the stream set with given routing paths, avoiding invalid searches and providing optimized guidance for stream routing. To accelerate the feasibility validation of potential solutions, an efficient stream conflict detection approach is proposed leveraging stream grouping with correlation analysis to compress the detection space. Integrating the above preprocess and efficient conflict detection, we develop a scalable scheduling algorithm with an incremental schedule synthesis to enhance scalability while ensuring low slot occupancy for all links. Evaluation results demonstrate that the proposed algorithm significantly reduces synthesis time and achieves low slot occupancy of all links compared to existing scheduling methods.

关键词： Job shop scheduling Routing Switches Complexity theory Scalability Industrial Internet of Things scheduling algorithms Schedules Real-time systems Logic gates Efficient conflict detection scalable scheduling stream grouping time-sensitive networking (TSN)

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RIS-Assisted Transmission scheduling for Train-to-Train Communication System

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2024年第10期73卷 15020-15033页

作者： Li, Wenqing Ai, Bo Niu, Yong Han, Zhu Wang, Ning Zhong, Zhangdui He, Ruisi Beijing Jiaotong Univ Sch Elect & Informat Engn Beijing 100044 Peoples R China Univ Houston Dept Elect & Comp Engn Houston TX 77004 USA Kyung Hee Univ Dept Comp Sci & Engn Seoul 446701 South Korea Zhengzhou Univ Sch Informat Engn Zhengzhou 450001 Peoples R China

Millimeter wave (mmWave) has been considered as an enabler to alleviate the spectrum shortage problem while providing high data rates in high speed railway (HSR) communications. However, a mmWave channel has a larger path loss, and therefore is sensitive to blockage. In such a high speed mobile environment with fast-changing channels, considering the characteristics of mmWave, how to achieve reliable transmission scheduling in a train-to-train communication has become a critical issue, especially from the safety point of view. In this paper, we investigate a mmWave train-to-train communication system with the fixed frame structure, where two trains communicate with each other directly by mobile relays (MRs) deployed on top of cabin roofs. Due to the limited communication distance by MRs and the nature that mmWave is prone to blockage, reconfigurable intelligent surface (RIS) is placed between two trains to rebuild line of sight (LoS) link when original link is blocked or beyond the distance range. We aim to maximize the number of completely scheduled flows with different quality of service (QoS) requirements via optimizing the discrete phase shifts of RIS as well as flow scheduling. In particular, we consider multiple-frame scheduling to make use of the predictability of trains' trajectory. To solve this nonlinear integer programming problem, we decompose the joint scheduling problem into two subproblems. We first optimize the discrete phase shifts of RIS, and then build an interference-based graph of flows while transforming the transmission constraints into interference relationships. The goal of the problem can be realized through the proposed scheduling algorithm. Finally, simulation results show that the proposed algorithm outperforms three baseline schemes in the literature in terms of the number of the completely scheduled flows and system throughput.

关键词： Millimeter wave communication Reconfigurable intelligent surfaces Rail transportation Quality of service scheduling algorithms Optimization Job shop scheduling MmWave high speed railway (HSR) reconfigurable intelligent surface (RIS) train-to-train communication

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scheduling Coflows in Hybrid Optical-Circuit and Electrical-Packet Switches With Performance Guarantee

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IEEE-ACM TRANSACTIONS ON NETWORKING 2024年第3期32卷 2299-2314页

作者： Wang, Xin Shen, Hong Tian, Hui Sun Yat Sen Univ Sch Comp Sci & Engn Guangzhou 510275 Peoples R China Cent Queensland Univ Sch Engn & Technol Brisbane Qld 4000 Australia Griffith Univ Sch Informat & Commun Technol Nathan Qld 4111 Australia

scheduling of coflows, each a collection of parallel flows sharing the same objective, is an important task of data transmission that arises in the networks supporting data-intensive applications such as data center networks (DCNs). The hybrid switch design combining the optical circuit switch (OCS) and electrical packet switch (EPS) for transmitting high-volume and low-volume traffic separately has received considerable research attention. To support this design, efficient scheduling of coflows on hybrid network links is crucial for reducing the overall communication time. However, because it needs to consider both reconfiguration delay of circuit switching in the OCS and bandwidth limitation of packet switching in the EPS, coflow scheduling on hybrid network links is more challenging than on monotonic network links of either OCS or EPS. The existing coflow scheduling algorithms in hybrid switches are all heuristic and provide no performance guarantees. In this work, we first propose an approximation algorithm with a worst-case performance guarantee of 2 tau , where tau <= N is the maximum number of non-zero elements of each row and column of coflow's demand matrix, for single coflow scheduling in an NxN hybrid switch to minimize the coflow completion time (CCT). We then extend the algorithm for scheduling multiple coflows to minimize the total weighted CCT with a provable performance guarantee of mu tau(max) , where mu=4M & sdot;w(max)/w(min) , tau(max)=max(1) <= m <= M tau m <= N , w(max) and w(min) are respectively the maximum and minimum weights of the M coflows. Extensive simulations using Facebook data traces show that our algorithms outperform the state-of-the-art coflow scheduling schemes. Specifically, our algorithms transmit a single coflow up to 1.08 x faster than Solstice (hybrid switch) and 1.42 x faster than Reco-Sin (pure OCS), and multiple coflows u

关键词： Optical switches scheduling Approximation algorithms Optical packet switching scheduling algorithms Delays Bandwidth Coflow scheduling optical circuit switch electrical packet switch datacenter network approximation algorithm

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IRFS: A CQF scheduling Method Integrating Queue Resources and Flow Features in Time-Sensitive Networking

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2024年第10期73卷 14201-14211页

作者： Sun, Wenjing Zou, Yuan Guan, Nan Zhang, Xudong Fan, Jie Meng, Yihao Beijing Inst Technol Collaborat Innovat Ctr Elect Vehicles Beijing Sch Mech Engn Natl Engn Lab Elect Vehicles Beijing 100081 Peoples R China City Univ Hong Kong Dept Comp Sci Hong Kong Peoples R China

Time-sensitive networking (TSN) has revolutionized Ethernet with real-time and deterministic transmission capabilities, making it one of the most potential solutions for future vehicular and industrial networks. Compared to time-aware shaper (TAS), the cyclic queuing and forwarding (CQF) protocol simplifies the gate control list (GCL) configuration process, reducing the deployment difficulty of TSN in large-scale networks. Much research has proposed incremental scheduling approaches for the CQF. However, existing methods often inadequately consider and insufficiently integrate network and flow characteristics, limiting scheduling performance. This paper introduces a novel CQF scheduling method, IRFS, which integrates queue resources and flow features for efficient searching of scheduling priority, routing path, and start offset. A priority sorting function is proposed that deeply combines network and flow characteristics while considering both spatial and temporal resource allocation. IRFS achieves efficient scheduling and load balancing by constructing combinations of $(flow, path, offset)$, where the elements respectively represent flow features, the spatial distribution, and the temporal distribution of resources. The IRFS is validated in different network scenarios, including simple, complex, and In-Vehicle Networking (IVN) settings. It is compared against other state-of-the-art CQF scheduling algorithm. The IRFS demonstrates superior performance in scheduling success rate, load balancing, and computation time across these scenarios.

关键词： Job shop scheduling Sorting Logic gates Routing Switches scheduling algorithms Resource management Time-sensitive networking cyclic queuing and forwarding traffic scheduling resource mapping

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An evaluation of scheduling algorithms in LTE based 4G networks

An evaluation of scheduling algorithms in LTE based 4G netwo...

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International Conference on Emerging Technologies, ICET

作者： Qurat-ul-Ain Syed Riaz ul Hassnain Mudassir Shah Sahibzada Ali Mahmud Department of Electrical Engineering University of Engineering and Technology Peshawar Pakistan Department of Electronics Engineering University of Engineering and Technology Peshawar Abbottabad Campus Pakistan Department of Electrical Engineering Sarhad University of Science and IT Peshawar Pakistan

The intent of 4G technology is to converge high speed data application requirements and compete with other technologies. Different techniques i.e relaying, carrier aggregation, multiple input multiple output, and heterogeneous networks provide higher throughputs, low latency and enable LTE to become a Standard for Wireless broadband. Due to almost exponential increase in demand for high data rates it is expected that network will be occupied by more resource demanding applications. Therefore efficient scheduling of radio resources is required for better performance of LTE system. Proportional Fair scheduler is adopted to LTE system to achieve Orthogonal Frequency Division Multiple Access (OFDMA) potentiality in Time Domain systems (TDS) and Frequency Domain scheduling systems (FDS). This paper aims at enhancing the functionality of Proportional Fair algorithm by making future estimation of the channel quality index (CQI) to offer higher data rate among all users according to their running applications, at high mobility. Performance of proposed algorithm on the downlink is measured in terms of throughput and block error rate using a MATLAB-based system level simulator.

关键词： Throughput Long Term Evolution scheduling algorithms Indexes Resource management MIMO OFDM

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On fairness in LTE downlink MAC scheduling algorithms

On fairness in LTE downlink MAC scheduling algorithms

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International Conference on Information and Communication Technology Research (ICTRC)

作者： Ismael I. Al-Shiab Rana E. Ahmed Dept. of Computer Science and Engineering American University of Sharjah Sharjah UAE

A downlink MAC scheduler aims to improve the radio resources utilization in the Long Term Evolution (LTE) network. The MAC scheduler is responsible for sharing the available radio Resource Blocks (RBs) among different User Equipment (UEs) in time and frequency domains. Several downlink MAC schedulers have been proposed and implemented; however, providing fairness in terms of granting resources to different UEs with different QoS requirements remains a challenge. This paper presents the results of a comparative simulation study with respect to a fairness criterion for three well-known downlink schedulers.

关键词： Throughput Downlink Long Term Evolution Indexes Measurement Aggregates scheduling algorithms

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Decentralized scheduling for Concurrent Tasks in Mobile Edge Computing via Deep Reinforcement Learning

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IEEE TRANSACTIONS ON MOBILE COMPUTING 2024年第4期23卷 2765-2779页

作者： Fan, Ye Ge, Jidong Zhang, Sheng Wu, Jie Luo, Bin Nanjing Univ State Key Lab Novel Software Technol Nanjing 210008 Jiangsu Peoples R China Nanjing Univ Software Inst Nanjing 210008 Jiangsu Peoples R China Temple Univ Ctr Networked Comp Philadelphia PA 19122 USA

Mobile Edge Computing (MEC) is a promising solution to enhance the computing capability of resource-limited networks. A fundamental problem in MEC is efficiently offloading tasks from user devices to edge servers. However, there still exists a gap to deploy in real-world environments: 1) traditional centralized approaches needs complete information of edge network, ignoring the communication costs generated by synchronization, 2) previous works do not consider concurrent computation on edge servers, which may cause dynamic changes in the environment, and 3) the scheduling algorithm should deliver individualized decisions for different users independently and with high efficiency To solve this mismatch, we studied a multi-user task offloading problem where user devices make offloading decisions independently. We consider the concurrent execution of tasks and formulate a non-divisible and delay-aware task offloading problem to jointly minimize the dropped task ratio and long-term latency. We propose a decentralized task scheduling algorithm based on DRL that makes offloading decisions without knowing the information of other user devices. We employ Double-DQN, Dueling-DQN, Prioritized Replay Memory, and Recurrent Neural Network (RNN) techniques to improve the algorithm's performance. The results of simulation experiments show that our method can significantly reduce the long-term latency and dropped task ratio compared to the baseline algorithms.

关键词： Task analysis Servers Costs Heuristic algorithms Training scheduling algorithms Deep learning Deep reinforcement learning deep q-learning mobile edge computing resource allocation task offloading

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Spatial-Temporal Resource Utilization for Partially Connected Multi-AUV Broadcast scheduling

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IEEE WIRELESS COMMUNICATIONS LETTERS 2025年第5期14卷 1321-1325页

作者： He, Hongyi Du, Jun Jiang, Chunxiao Wang, Jintao Song, Jian Niyato, Dusit Tsinghua Univ Beijing Natl Res Ctr Informat Sci & Technol Dept Elect Engn Beijing Peoples R China Tsinghua Univ State Key Lab Space Network & Commun Beijing 100084 Peoples R China Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China Tsinghua Univ Beijing Natl Res Ctr Informat Sci & Technol Beijing 100084 Peoples R China Tsinghua Univ Beijing Natl Res Ctr Informat Sci & Technol Dept Elect Engn Beijing 100084 Peoples R China Tsinghua Univ Shenzhen Int Grad Sch Shenzhen 518055 Peoples R China Nanyang Technol Univ Coll Comp & Data Sci Singapore Singapore

The long propagation delays in underwater acoustic channels can be leveraged to improve communication efficiency using spatial-temporal reuse techniques. This letter focuses on a system of partially connected AUVs that continuously broadcast packets. A central controller gathers the location information of the AUVs and designs a broadcast sequence exploiting propagation delays to minimize the broadcast cycle. Since finding optimal solutions is time-consuming, we propose a scheduling algorithm that uses heuristics based on partial connections to reduce computational complexity. Additionally, we allow collision tolerance to shorten the broadcast cycle further and investigate the trade-off of the shorter broadcast cycle and collision probability, resulting in a scheduling algorithm exhibiting receiving-alignment properties. Simulations demonstrate the effectiveness of the proposed algorithm in reducing broadcast cycles while maintaining low computational complexity.

关键词： Bandwidth scheduling algorithms Media Access Control Electronic mail Protocols Propagation delay Underwater acoustics Linear programming Information science Heuristic algorithms Medium access control propagation delay underwater acoustic network broadcast scheduling algorithm

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