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Cloudification of the Internet of Things (CIoT)

作者： Saleh Al Shamaa Wei Shi Georges Ankenmann School of Information Technology Carleton University Ottawa Ontario Canada

In order to meet the rising demand for cloud services and remain in compliance with Service Level Agreements (SLA), service providers require effective task scheduling solutions capable of adapting to cloud computing’s elastic and dynamic *** this paper, we propose a novel approach to optimize task scheduling in cloud computing called a ProbabilityBased Crossover Genetic Algorithm (PxGA) with a primary objective of minimizing the tasks execution makespan. PxGA is an improvement on the Genetic Algorithm (GA) achieved by introducing the concept of Virtual Machine (VM) fitness and applying it to implement an effective weighted probabilistic crossover technique. Using the CloudSim simulation toolkit, we conduct our analysis of PxGA and evaluate it against standard and more recent task scheduling algorithms. The results of the simulations show that our proposed task scheduling algorithm is superior to other task scheduling algorithms in terms of the makespan, the VMs energy consumption, and the degree of imbalance (DoI). Moreover, the computational time (CT) for the PxGA decreases when compared against the other evaluated algorithms, except for its base GA.

关键词： Cloud computing Energy consumption scheduling algorithms Computational modeling Dynamic scheduling Probabilistic logic Virtual machining

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Everything Matters in Programmable Packet scheduling

arXiv

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arXiv 2023年

作者： Alcoz, Albert Gran Vass, Balázs Rétvári, Gábor Vanbever, Laurent ETH Zürich Switzerland BME VIK TMIT Hungary

Programmable packet scheduling allows the deployment of scheduling algorithms into existing switches without need for hardware redesign. scheduling algorithms are programmed by tagging packets with ranks, indicating their desired priority. Programmable schedulers then execute these algorithms by serving packets in the order described in their ranks. The ideal programmable scheduler is a Push-In First-Out (PIFO) queue, which achieves perfect packet sorting by pushing packets into arbitrary positions in the queue, while only draining packets from the head. Unfortunately, implementing PIFO queues in hardware is challenging due to the need to arbitrarily sort packets at line rate based on their ranks. In the last years, various techniques have been proposed, approximating PIFO behaviors using the resources of existing data planes. While promising, approaches to date only approximate one of the two characteristic behaviors of a PIFO queue: either its scheduling behavior, or its admission control. We introduce PACKS, the first programmable scheduler that fully approximates PIFO queues on all their behaviors. PACKS does so by smartly using a set of strict-priority queues. It uses packet-rank information and queue-occupancy levels at enqueue to decide whether to admit packets to the scheduler, and how to map admitted packets to the different queues. We fully implement PACKS in P4 and evaluate it on real workloads. We show that PACKS better-approximates PIFO than state-of-the-art approaches and scales. We also show that PACKS runs at line rate on existing hardware (Intel Tofino). Copyright © 2023, The Authors. All rights reserved.

关键词： scheduling algorithms

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Mixed-Criticality with Integer Multiple WCETs and Dropping Relations: New scheduling Challenges

Mixed-Criticality with Integer Multiple WCETs and Dropping R...

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Asia and South Pacific Design Automation Conference

作者： Federico Reghenzani William Fornaciari Politecnico di Milano Milano Italy

scheduling Mixed-Criticality (MC) workload is a challenging problem in real-time computing. Earliest Deadline First Virtual Deadline (EDF-VD) is one of the most famous scheduling algorithm with optimal speedup bound properties. However, when EDF-VD is used to schedule task sets using a model with additional or relaxed constraints, its scheduling properties change. Inspired by an application of MC to the scheduling of fault tolerant tasks, in this article, we propose two models for multiple criticality levels: the first is a specialization of the MC model, and the second is a generalization of it. We then show, via formal proofs and numerical simulations, that the former considerably improves the speedup bound of EDF-VD. Finally, we provide the proofs related to the optimality of the two models, identifying the need of new scheduling algorithms.

关键词： Fault tolerance Schedules Design automation scheduling algorithms Computational modeling Fault tolerant systems Numerical simulation

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Device scheduling for Relay-assisted Over-the-Air Aggregation in Federated Learning

arXiv

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arXiv 2023年

作者： Zhang, Fan Chen, Jining Wang, Kunlun Chen, Wen Shanghai Key Laboratory of Multidimensional Information Processing East China Normal University Shanghai200241 China School of Communication and Electronic Engineering East China Normal University Shanghai200241 China Joint Innovation Laboratory of Digital GuangXi Smart Infrastructures Guangxi Information Center Nanning530000 China Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China

Federated learning (FL) leverages data distributed at the edge of the network to enable intelligent applications. The efficiency of FL can be improved by using over-the-air computation (AirComp) technology in the process of gradient aggregation. In this paper, we propose a relay-assisted large-scale FL framework, and investigate the device scheduling problem in relay-assisted FL systems under the constraints of power consumption and mean squared error (MSE). we formulate a joint device scheduling, and power allocation problem to maximize the number of scheduled devices. We solve the resultant non-convex optimization problem by transforming the optimization problem into multiple sparse optimization problems. By the proposed device scheduling algorithm, these sparse sub-problems are solved and the maximum number of federated learning edge devices is obtained. The simulation results demonstrate the effectiveness of the proposed scheme as compared with other benchmark schemes. Copyright © 2023, The Authors. All rights reserved.

关键词： scheduling algorithms

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Polynomial-Size Models to Minimize Total Completion Time in a Parallel Batching Environment 10th

Polynomial-Size Models to Minimize Total Completion Time in ...

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10th IFAC Triennial Conference on Manufacturing Modelling, Management and Control (MIM)

作者： Druetto, Alessandro Grosso, Andrea Univ Torino Dipartimento Informat Via Pessinetto 12 I-10149 Turin Italy

We present a new integer linear formulation for the problem of minimizing the total completion time on a single parallel-batching machine. The new formulation is strong, in the sense that it delivers a sharp lower bound, and compact, i.e. polynomial in size, contrasted to recent successful models for the same problem that have exponential size and require to be handled by column generation. The new model is promising: combined with a rounding procedure, it allows to deliver good solutions with small, certified optimality gaps for instances with up to 50 jobs, and we believe it is susceptible of further improvements. Copyright (C) 2022 The Authors.

关键词： Operations Research scheduling algorithms Parallel Batching Total Completion Time Arc-Flow Models

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Various job scheduling algorithms in cloud computing: A survey

Various job scheduling algorithms in cloud computing: A surv...

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International Conference on Information Communication and Embedded Systems (ICICES)

作者： Yash P. Dave Avani S. Shelat Dhara S. Patel Rutvij H. Jhaveri Department of Computer Science and Engineering Shri Sa'd Vidya Mandal Institute of Technology Bharuch India Department of Computer Science and Information Technology Shri Sa'd Vidya Mandal Institute of Technology Bharuch India

ISBN: (纸本)9781479936984

Cloud Computing provides a Computing environment where different resources, infrastructures, development platforms and software are delivered as a service to customers virtually on pay per time basis. Low cost, scalability, reliability, utility-based computing are important aspects of cloud computing. Job scheduling is an essential and most important part in any cloud environment. With increasing number of users, Job scheduling becomes a strenuous task. Ordering the jobs by scheduler while maintaining the balance between quality of services (QoS), efficiency and fairness of jobs is quite challenging. scheduling algorithms are implemented considering parameters such as throughput, resource utilization, latency, cost, priority, computational time, physical distances, performance, bandwidth, resource availability. Though there are different scheduling algorithms available in cloud computing, a very less comparative study has been done on performance of various scheduling algorithms with respect to above mentioned parameters. This paper aims at a comparative study of various types of job scheduling algorithms that provide efficient cloud services.

关键词： Cloud computing scheduling algorithms scheduling Algorithm design and analysis Classification algorithms Resource management

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Distributed Intelligent scheduling Algorithm for Wireless Communication Network Link Resources Based on Data Analysis

Distributed Intelligent Scheduling Algorithm for Wireless Co...

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Integrated Circuits and Communication Systems (ICICACS), IEEE International Conference on

作者： Yangjie Feng Information Science Research Institute of China Electronics Technology Corporation Beijing China

The construction of wireless network is the mainstream direction of future communication development, and link optimization provides a basis for information exchange between the next generation of intelligent mobile terminals and base stations. This paper studies the link scheduling problem based on data analysis. First, after deriving the traditional optimal power allocation strategy and improving the genetic algorithm to obtain a new model, this paper proposes an optimization scheme calculation that is suitable for resource sharing among nodes, and can also consider the impact of time utility and other factors on the global availability, network topology and quality of service to minimize the overhead, and applies it to the wireless communication network for example verification. The experimental results show that the distributed intelligent scheduling algorithm for wireless communication network link resources based on data analysis performs very well in terms of running time and system processing efficiency, which can reach more than 90% efficiency.

关键词： Performance evaluation Data analysis scheduling algorithms Wireless networks Quality of service scheduling Routing protocols

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Data Cloud Platform of Industrial Internet of Things based on TSN scheduling Algorithm

Data Cloud Platform of Industrial Internet of Things based o...

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Integrated Circuits and Communication Systems (ICICACS), IEEE International Conference on

作者： Guangfu Zhang Jiajing Cai Xiuyan Zheng College of Information Engineering Hainan Vocational University of Science and Technology Haikou China

With the rapid development of Industrial Science and technology, industrial scientific data has the characteristics of huge scale, wide range, diverse types and strong timeliness. The Industrial Internet of things (IIOT) data cloud platform came into being. Based on this, this paper studies and analyzes the application of TSN scheduling algorithm (SA) in the IIOT data cloud platform. Firstly, the architecture and key technologies of the Internet of things are introduced; Then the SA and cloud computing (CC) tasks in CC are analyzed, and the workflow system architecture under the data cloud platform of the IIOT and the workflow system architecture under the CC environment are discussed; The TSN SA is proposed and applied to the data cloud platform of the IIOT; Finally, the reliability of TSN SA is evaluated and tested. The test results show that the TSN resource SA proposed in this paper can basically achieve the packet loss rate of less than 1%, that is, the successful packet reception rate can basically reach more than 99%. It is verified that the TSN SA proposed in this paper can ensure the reliability and real-time of data transmission. The results show that the synchronization effect can fully meet the needs of industrial applications.

关键词： Cloud computing Job shop scheduling scheduling algorithms Systems architecture Real-time systems Reliability Synchronization

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Uplink scheduling in Federated Learning: an Importance-Aware Approach via Graph Representation Learning

arXiv

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arXiv 2023年

作者： Skocaj, Marco Rivera, Pedro Enrique Iturria Verdone, Roberto Erol-Kantarci, Melike University of Bologna DEI & WiLab - National Laboratory for Wireless Communications CNIT Italy University of Ottawa School of Electrical Engineering and Computer Science Canada

Federated Learning (FL) has emerged as a promising framework for distributed training of AI-based services, applications, and network procedures in 6G. One of the major challenges affecting the performance and efficiency of 6G wireless FL systems is the massive scheduling of user devices over resource-constrained channels. In this work, we argue that the uplink scheduling of FL client devices is a problem with a rich relational structure. To address this challenge, we propose a novel, energy-efficient, and importance-aware metric for client scheduling in FL applications by leveraging Unsupervised Graph Representation Learning (UGRL). Our proposed approach introduces a relational inductive bias in the scheduling process and does not require the collection of training feedback information from client devices, unlike state-of-the-art importance-aware mechanisms. We evaluate our proposed solution against baseline scheduling algorithms based on recently proposed metrics in the literature. Results show that, when considering scenarios of nodes exhibiting spatial relations, our approach can achieve an average gain of up to 10% in model accuracy and up to 17 times in energy efficiency compared to state-of-the-art importance-aware policies. © 2023, CC BY-NC-ND.

关键词： scheduling algorithms

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Fairness scheduling for Tasks with Different Real-time Level on Heterogeneous Systems

Fairness Scheduling for Tasks with Different Real-time Level...

引用

International Conference on Parallel and Distributed Systems (ICPADS)

作者： Shifan Shao Shouzhen Gu Biao Sun Edwin H.-M. Sha Qingfeng Zhuge East China Normal University

For a real-time task-intensive systems, the fairness of task execution in dynamic scheduling is an important research area. However, many exist scheduling algorithms are unable to guarantee that tasks can be completed by the deadline and executed with a fair priority. In this paper, we proposed an efficient Multi-DAG real-time scheduling algorithm, HSDFW, which employs a fair priority calculation method to enable tasks with different real-time levels can be completed by the deadline, and a rejection policy to improve the performance of schedule. We proposed an INLP model and an evaluation simulator to verify the efficiency of HSDFW algorithm. The evaluation results show that our proposed algorithm has excellent performance in terms of average scheduling length and resource utilization.

关键词： Schedules scheduling algorithms Heuristic algorithms Dynamic scheduling Real-time systems Resource management Task analysis

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