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21st IFAC World Congress on Automatic Control - Meeting Societal Challenges

作者： Bouhamed, Emna Marouane, Hend Trabelsi, Ala Zerai, Faouzi Sfax Univ Natl Sch Elect & Telecommun NTSCOM Lab Sfax Tunisia

5G promises very high throughput and low latency. It will be able to support the exchange of large amounts of data with a wide variety of communications, including Vehicle-to-Everything (V2X) services. Conventional resource allocation techniques based on orthogonal multiple access (OMA) appear to be unsuitable for a dense network due to limited resources available. This work presents a new planning algorithm called SAVCN (scheduling algorithm for V2X Communication based on NOMA), for the 5G network. The main feature of NOMA is the same resource can be shared by multiple users. The purpose of our algorithm is to improve network performance in terms of throughput, equity, the number of V2X users served and error rates. In fact, SAVCN efficiently allocates available resource blocks (Rbs) to maximize system throughput by taking into account a well-defined criterion on the minimum distance between transmitters and receivers. The simulation results indicate promising performance for SAVCN. Copyright (C) 2020 The Authors.

关键词： V2X NOMA scheduling algorithm throughput BER

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A MapReduce task scheduling algorithm for deadline constraints

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CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2013年第4期16卷 651-662页

作者： Tang, Zhuo Zhou, Junqing Li, Kenli Li, Ruixuan Hunan Univ Sch Informat Sci & Engn Changsha 410082 Hunan Peoples R China Huazhong Univ Sci & Technol Sch Comp Sci & Technol Wuhan 430074 Hubei Peoples R China

The current works about MapReduce task scheduling with deadline constraints neither take the differences of Map and Reduce task, nor the cluster's heterogeneity into account. This paper proposes an extensional MapReduce Task scheduling algorithm for Deadline constraints in Hadoop platform: MTSD. It allows user specify a job's deadline and tries to make the job be finished before the deadline. Through measuring the node's computing capacity, a node classification algorithm is proposed in MTSD. This algorithm classifies the nodes into several levels in heterogeneous clusters. Under this algorithm, we firstly illuminate a novel data distribution model which distributes data according to the node's capacity level respectively. The experiments show that the node classification algorithm can improved data locality observably to compare with default scheduler and it also can improve other scheduler's locality. Secondly, we calculate the task's average completion time which is based on the node level. It improves the precision of task's remaining time evaluation. Finally, MTSD provides a mechanism to decide which job's task should be scheduled by calculating the Map and Reduce task slot requirements.

关键词： MapReduce scheduling algorithm Data locality Deadline constraints Hadoop

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An on-demand data broadcasting scheduling algorithm based on dynamic index strategy

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WIRELESS COMMUNICATIONS & MOBILE COMPUTING 2015年第5期15卷 947-965页

作者： Hu, Wenbin Fan, Cunlian Luo, Jiajia Peng, Chao Du, Bo Wuhan Univ Sch Comp Wuhan 430072 Hubei Province Peoples R China Wuhan Univ State Key Lab Software Engn Wuhan 430072 Hubei Province Peoples R China Wuhan Univ Int Sch Software Wuhan 430072 Hubei Province Peoples R China

On-demand data broadcasting scheduling is an effective wireless data dissemination technique. Existing scheduling algorithms usually have two problems: (1) with the explosive growth of mobile users and real-time individual requirements, broadcasting systems present a shortage of scalability, dynamics and timeliness (request drop ratio);(2) with the growth of intelligent and entertained application, energy consumption of mobile client cannot be persistent (tuning time). This paper proposes an effective scheduling algorithm LxRxW. It takes into account the number of lost requests during next item broadcasting time, the number of requests and the waiting time. LxRxW can reduce the request drop ratio. At the same time, the algorithm employs a dynamic index strategy to put forward a dynamic adjusting method on the index cycle length (DAIL) to determine the proper index cycle. Extensive experimental results show that the LxRxW algorithm has better performance than other state-of-the-art scheduling algorithms and can significantly reduce the drop ratio of user requests by 40%-50%. The request drop ratio and accessing time of LxRxW with index increase by 1%-2% than LxRxW algorithm without index, but the tuning time decreases by 70%. The index strategy shows that when the index cycle length is less than 20units, it can significantly reduce the average tuning time but when the index cycle length continues increasing, the average tuning time will increase contrarily. DAIL can dynamically determine the length of index cycle. Moreover, it can reach optimal integrated performance of the request drop ratio, the average accessing time and the average tuning time. Copyright (c) 2013 John Wiley & Sons, Ltd.

关键词： on-demand data broadcasting scheduling algorithm dynamic index strategy deadline request drop ratio

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A fault recovery-based scheduling algorithm for cloud service reliability

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SECURITY AND COMMUNICATION NETWORKS 2015年第5期8卷 703-714页

作者： Qi, Ping Li, Longshu Anhui Univ Dept Comp Sci & Technol Hefei 230039 Anhui Peoples R China TongLing Univ Dept Math & Comp Sci Tongling Anhui Peoples R China

Because of the unreliable and dynamic characteristics, cloud service failures are inevitable. It has an adverse effect on task execution and scheduling. To improve cloud service reliability, we first analyze the fault recovery mechanism, and then, cloud service failures considered in this paper are classified into unrecoverable failures and recoverable failures. By extending the traditional dynamic level scheduling (DLS) algorithm, a novel scheduling algorithm based on fault recovery mechanism named fault recovery-based DLS algorithm is proposed to reduce the failure probability of task scheduling. The experimental results confirm that fault recovery mechanism can meet the reliability requirements of cloud computing infrastructures and the proposed algorithm can effectively ensure trustworthy execution of tasks. Copyright (c) 2014 John Wiley & Sons, Ltd.

关键词： cloud computing scheduling algorithm cognitive trust model trinomial distribution fault recovery

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AN ADAPTIVE scheduling algorithm FOR TDM SWITCHING SYSTEMS

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IEEE TRANSACTIONS ON COMMUNICATIONS 1995年第2-4期43卷 651-658页

作者： CHEN, WT LIU, HJ TELECOMMUN LABS SWITCH TECHNOL LABYANGMEI 32617TAIWAN NATL TSING HUA UNIV DEPT COMP SCIHSINCHU 30043TAIWAN

In this paper, we consider the scheduling problem in time-division multiplexed (TDM) switching systems. In previous works, the interdependence between traffic demands in two consecutive frames is neglected, and scheduling algorithms found up to now have time complexities O(N-5) or O(N-4.5), where N is the switch size. However, in many applications like voice or video communications, if a source transmits a packet to a destination in a frame, it is highly probable that it will also transmit a packet to the same destination in the next frame. So it is not necessary to schedule incoming packets for every frame it we can preserve all the switching patterns for the nearest scheduled frame and update the patterns appropriately according to the changes of traffic demands. The adaptive algorithm proposed in this paper assigns time slots to packets according to the changes of traffic demands. This algorithm has the worst case time complexity O(N-2 L), where L is the TDM frame length. Comparing the time complexity of the adaptive algorithm with those of previous scheduling algorithms, the adaptive algorithm can perform better than previous scheduling algorithms when N is large and/or L is small. Since traffic demands in consecutive frames are expected to be interdependent in many applications, the proposed algorithm may offer as an efficient alternative for scheduling time slots in these applications.

关键词： Adaptive scheduling scheduling algorithm Time division multiplexing Switching systems Adaptive algorithm Switches Communication switching Packet switching

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An efficient scheduling algorithm for real-time traffic on WDM passive star optical networks

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JOURNAL OF LIGHTWAVE TECHNOLOGY 2005年第11期23卷 3683-3695页

作者： Huang, XH Ma, MD Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore

One of the major challenges in the design of future-generation high-speed networks is the provision of quality-of-service (QoS) to real-time traffic. In this paper, we propose a novel scheduling scheme, namely differentiated dropping scheduling (DDS), which is designed to handle real-time traffic in passive star-coupled wavelength division multiplexing (WDM) optical networks. By taking channel and destination availability into account, DDS can dramatically improve network performance in terms of message loss rate. Moreover, this scheme has the capacity of preventing channel collision and destination conflict. In order to evaluate the proposed DDS algorithm, extensive discrete-event simulations and mathematical performance comparison are conducted by comparing its performance with Moore and Hodgson's algorithm and the earliest-due-date (EDD) algorithm. The results show that DDS can achieve the best performance among the three algorithms.

关键词： media-access-control (MAC) protocol optical network photonic switching real-time traffic scheduling algorithm wavelength division multiplexing (WDM)

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Finite State Machine-Based Load scheduling algorithm for Smart Home Energy Management

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IETE JOURNAL OF RESEARCH 2023年第10期69卷 7460-7475页

作者： Sajini, M. L. Merlin Suja, S. Raj, S. Merlin Gilbert Kowsalyadevi, S. Maria, Charisma Coimbatore Inst Technol Dept EEE Coimbatore Tamil Nadu India Karunya Inst Technol & Sci Dept ECE Coimbatore Tamil Nadu India Solliton Technol Coimbatore Tamil Nadu India

The problem of scheduling household appliances with the availability of renewable energy is the biggest challenge in the smart home energy management system. The components such as renewable energy resources, household appliances, utility grid, storage batteries are pooled into a nonlinear, time-varying, indefinite, and dynamic structure that is impossible to control and refine. For this, real-time pricing is applied in most nations to withstand the burden on the grid. This requires attention to utilize renewable energy effectively. In this paper, a load scheduling method to schedule the loads based on the availability of solar energy and customer preferences is presented. First, the availability of solar energy is forecasted ahead one day using Regression Analysis. Second, the finite state machine approach-based load scheduling algorithm is implemented and tested using MATLAB Simulink and Lab VIEW. LabVIEW-based GUI is developed to visualize the MATLAB schedule for loads. The problem is divided into several states with the availability of solar power, and if solar power is unavailable, grid power is utilized. The loads preferred by the consumers are scheduled in alignment with the production of solar power with the finite state machine scheduling algorithm. Also, the loads considered are able to consume instantaneous energy with the instantaneous production of energy, thereby reducing CO2 emission by not consuming power from the grid. Finally, the loads are scheduled accordingly, and it is concluded that coordination can be established between energy providers, and the system proposed can flatten out the load profile.

关键词： Energy management finite state machine load scheduling scheduling algorithm simulink model solar irradiance

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A Node-Oriented Discrete Event scheduling algorithm Based on Finite Resource Model

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JOURNAL OF ORGANIZATIONAL AND END USER COMPUTING 2019年第3期31卷 67-82页

作者： Huang, Yu Sheng, Wanxing Jin, Peipei Nie, Baicuan Qiu, Meikang Xu, Guangquan Peking Univ Beijing Peoples R China China Elect Power Res Inst Beijing Peoples R China Pace Univ New York NY 10038 USA Tianjin Univ Tianjin Peoples R China

Discrete event simulation is the most important and essential part in network simulation. The node-oriented model of discrete event scheduling is a model that allocates computing resources as nodes and makes the discrete event simulation as a simulation task on nodes. In this article the reason of low performance in large-scale network simulation is analyzed, and an ideal node-oriented model of discrete event scheduling is presented and a resource-limited node-oriented model of discrete event scheduling by adding some restrictions on network resources is proposed. Then, the authors complete contrast experiments of the resource-limited node-oriented model of discrete event scheduling and NS2. Finally, packet loss in resource-limited node-oriented model of discrete event scheduling is examined Also, NS2 is discussed in this article and the authors have proposed an improved method for the packet loss algorithm in a resource-limited node-oriented model of discrete event scheduling.

关键词： Computing Resources Discrete Event Simulation Network Simulation Node-Oriented NS2 Packet Loss algorithm scheduling algorithm Simulation Task

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A cost-efficient scheduling algorithm for streaming processing applications on cloud

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CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2022年第2期25卷 781-803页

作者： Li, Hongjian Fang, Hai Dai, Hongxi Zhou, Tao Shi, Wenhu Wang, Jingjing Xu, Chen Chongqing Univ Posts & Telecommun Dept Comp Sci & Technol Chongqing 400065 Peoples R China

Stream processing is a new memory computing paradigm that deals with dynamic data streams efficiently. Storm is one of the stream processing frameworks, but the default stream processing scheduler of storm also has some problems. For example, it does not consider reducing the cost in the cloud environment while ensuring the performance requirements. In this paper, a cost-efficient scheduling algorithm for Storm framework (CE-Storm) is proposed to reduce cost while satisfying deadline constrain. First, a new cost-efficient model (including resources usage cost, energy cost and communication cost) based on Storm framework is built. Then, based on the cost model, a cost-efficient scheduling algorithm which integrated resource monitoring module and communication detection module is designed. The nodes in the cluster are prioritized according to the cost-efficient information, and the nodes with higher priority are assigned tasks first to minimize the total cost of the cluster. Furthermore, this algorithm also reduces the communication cost between nodes and improves the cost effectiveness of the Storm cluster. We have performed extensive experiments on Storm clusters using Hibench's workloads in cloud environment. The result shows that the cost consumption of Storm clusters in cloud environment is reduced by 19.25% on average compared with the traditional scheduling algorithm. In others words, the proposed algorithms effectively improve the cost efficiency of Storm cluster in the cloud environment while satisfying the performance constrains.

关键词： Stream processing Storm cluster Cloud-deployed scheduling algorithm Cost-efficient

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Token Bucket Fair scheduling algorithm with Adaptive Rate Allocations for Heterogeneous Wireless Networks

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WIRELESS PERSONAL COMMUNICATIONS 2015年第2期84卷 801-819页

作者： AlQahtani, Salman A. King Saud Univ Coll Comp & Informat Sci Dept Comp Engn Riyadh Saudi Arabia

In this paper, we address the problem of uplink multi-traffic sources scheduling in heterogeneous wireless networks (HWNs) under real time traffics that requires fairness constraint and strict per-packet delay bounds and under non-real time traffics as well. The wide spread of HWNs, such as integrated of WiMax-WiFi-Relay wireless networks, enforces networks operators to design an efficient radio resource management (RRM) in order to tradeoff between network resource utilizations and user satisfactions. RRM concerns with traffic scheduling and admission control amongst different traffic sources to guarantee the Quality of Service. This paper participates to RRM developments by proposing and analyzing an efficient packet scheduling scheme with two modes of operations for the uplink channel of WiMax-WiFi-Relay station HWNs. These two modes of operations are known as Fixed Shared Flow and Adaptive Sharing Flow (ASF). The main aim of this scheduling is to allocate shared WiMax resources in a fair manner and to balance between maximizing the bandwidth utilization and users satisfactions. The performance bounds in terms of delay and throughout are presented. Then, the performance figures of the two modes of operations of the proposed scheduling scheme are compared. The results show that bounded delay can be provisioned for direct WiMax users, users via WiF and users via Relay Stations sharing the same WiMax bandwidth using both operations. Moreover, the simulation results show that the ASF scheduling scheme improves both system utilization and average delays.

关键词： Bandwidth reservation Heterogeneous wireless network scheduling algorithm Token bucket

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