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Simpasio em Sistemas Computacionais (WSCAD-SSC)

作者： Alvaro H. Mamani-Aliaga Alfredo Goldman Yanik Ngoko Instituto de Matemática e Estatística Universidade de São Paulo Sao Paulo Sao Paulo Brazil

The large amount of data processing is growing fast. In many scenarios, both in industry and academia, high-performance computing (HPC) is a needed to process Big Data in short time. An important topic in HPC is task scheduling. In this context, several scheduling algorithms for grid computing have been proposed, but these algorithms have not been yet fully tested by taking into account different types of applications and platforms. This paper presents a comparative study designed to discover the behavior of scheduling algorithms exhibit under different settings. This was done through a methodology with four criteria: performance, scalability, workload distribution and adaptability. The scheduling algorithms compared in this paper are HEFT, CPOP and PCH. Our results show that the HEFT algorithm performs well in almost all cases, despite its simplicity. The PCH and CPOP algorithms perform well only in very specific cases, this is mainly due to the high dependence on the critical path for both algorithms.

关键词： scheduling algorithms Bills of materials Grid computing Algorithm design and analysis Genomics Bioinformatics Gold

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An improving strategy for LTE downlink scheduling algorithms based on QoS requirement

An improving strategy for LTE downlink scheduling algorithms...

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IEEE International Workshop Technical Committee on Communications Quality and Reliability, CQR

作者： Zhipeng Jiang Wei Zhang Suixiang Gao Lei Zhou School of Mathematics University of Chinese Academy of Sciences Central Research Institute of Huawei Corporation

ISBN: (纸本)9781467380812

LTE is an all IP network. The scheduling in its downlink channels is a key problem. Although many algorithms have been designed and analyzed, the QoS for the users in poor channel conditions are not enough to be ensured sometimes. We design a method to enhance the capacity of the system, which is a modifying strategy available for most existing algorithms. Our intuition is to allocate more resources to the users in poorer channel conditions without declining the QoS of the users in better channel. Simulations show that our strategy can satisfy the QoS for more users.

关键词： Quality of service Delays Downlink scheduling algorithms Algorithm design and analysis Throughput

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Research on Resource scheduling algorithms for Satellite Earth Stations

Research on Resource Scheduling Algorithms for Satellite Ear...

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IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)

作者： Chen Shaojun Liu Wansong 63782 People's Liberation Army troops Harbin China

ISBN: (数字)9781728180281

ISBN: (纸本)9781728180298

Resource scheduling has always been a hot and difficult problem in systems engineering and management at home and abroad, and it is also very important in the research of satellite earth station system. Due to the limited resources in the satellite earth station system, the rationality of resource allocation directly affects the overall performance of the multi-satellite system. The resource scheduling problem of satellite earth station is a combinatorial optimization problem based on *** paper summarizes the existing resource scheduling model and scheduling algorithm of satellite earth station system, and provides reference for the further research and development of this field.

关键词： Earth Satellites scheduling algorithms scheduling Resource management Modeling Space stations

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A theoretical comparison of job scheduling algorithms in cloud computing environment

A theoretical comparison of job scheduling algorithms in clo...

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International Conference on Next Generation Computing Technologies (NGCT)

作者： Abhishek Gupta H S Bhadauria Annapurna Singh Jagdish Chandra Patni Department of Computer Science and Engineering GBPEC Pauri India Deunspartment of CIT UPES Dehradun India

ISBN: (纸本)9781467368100

Cloud computing is a dynamic, scalable and payper-use distributed computing model empowering designers to convey applications amid job designation and storage distribution. Cloud computing encourages to impart a pool of virtualized computer resource empowering designers to convey applications amid job designation and storage distribution. The cloud computing mainly aims to give proficient access to remote and geographically distributed resources. As cloud technology is evolving day by day and confronts numerous challenges, one of them being uncovered is scheduling. scheduling is basically a set of constructs constructed to have a controlling hand over the order of work to be performed by a computer system. algorithms are vital to schedule the jobs for execution. Job scheduling algorithms is one of the most challenging hypothetical problems in the cloud computing domain area. Numerous deep investigations have been carried out in the domain of job scheduling of cloud computing. This paper intends to present the performance comparison analysis of various pre-existing job scheduling algorithms considering various parameters. This paper discusses about cloud computing and its constructs in section (i). In section (ii) job scheduling concept in cloud computing has been elaborated. In section (iii) existing algorithms for job scheduling are discussed, and are compared in a tabulated form with respect to various parameters and lastly section (iv) concludes the paper giving brief summary of the work.

关键词： Cloud computing scheduling algorithms Computational modeling Heuristic algorithms scheduling Computers

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Performance Analysis of Bio-Inspired scheduling algorithms for Cloud Environments

Performance Analysis of Bio-Inspired Scheduling Algorithms f...

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IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Ali Al Buhussain Robson E. De Grande Azzedine Boukerche PARADISE Research Lab University of Ottawa Ottawa ON Canada PARADISE Research Lab University of Ottawa Faculty of Medicine Ottawa ON CA

ISBN: (纸本)9781509036837

Cloud computing environments mainly focus on the delivery of resources, platforms, and applications as services to users over the Internet. Cloud promises users access to as many resources as they need, making use of an elastic provisioning of resources. The cloud technology has gained popularity in recent years as the new paradigm in the IT industry. The number of users of Cloud services has been increasing steadily, so the need for efficient task scheduling is crucial for maintaining performance. In this particular case, a scheduler is responsible for assigning tasks to virtual machines efficiently, it is expected to adapt to changes along with defined demand. In this paper, we present a comparative performance study on bio-inspired scheduling algorithms: Ant Colony Optimization (ACO) and Honey Bee Optimization (HBO). A networking scheduling algorithm, Random Biased Sampling, is also evaluated. Those algorithms show the ability of self-managing and adapting to changes in the environment. The experimental results have shown that ACO performs better when computation power is set as the objective, and HBO shows better scheduling when the objective mainly relies on costs.

关键词： Cloud computing scheduling algorithms Optimization Job shop scheduling Genetic algorithms

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Analysis of Round-Robin and Random scheduling algorithms on Sensor Node Activation Towards Latency of Wireless Sensor Network

Analysis of Round-Robin and Random Scheduling Algorithms on ...

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International Conference on Information and Communications Technology (ICOIACT)

作者： Ferry Wahyu Wibowo Andi Sunyoto Bayu Setiaji Wihayati Department of Informatics Universitas Amikom Yogyakarta Yogyakarta Indonesia Faculty of Information Technology Satya Wacana Christian University Salatiga Indonesia

ISBN: (数字)9798331536206

ISBN: (纸本)9798331536213

A Wireless Sensor Network (WSN) is a network system consisting of wireless sensor nodes that collect and transmit data. One crucial factor that affects WSN performance is latency, which is the time required to send data to the gateway. High latency can cause data delivery delays, resulting in data becoming irrelevant. At the same time, receiving real-time data quickly is the primary monitoring method. In addition, high latency can cause greater energy consumption because the sensor node device must be active longer. One way to overcome latency is to implement traffic management techniques such as scheduling data delivery or using priority delivery methods, which can reduce congestion and latency. This paper discusses the effect of latency on WSN using scheduling algorithms, namely Round-Robin and Random scheduling. The results were then taken 30 times to obtain a statistical comparison. The results obtained in the experiment received a Round-Robin scheduling algorithm that was superior to the random scheduling algorithm with a mean and standard deviation value of 12.68 and 2.33, respectively.

关键词： Wireless communication Wireless sensor networks scheduling algorithms Logic gates Real-time systems scheduling Delays Standards Monitoring Network systems

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Computational Complexity and Energy Consumption Analysis of Dynamic Resource scheduling algorithms for LTE

Computational Complexity and Energy Consumption Analysis of ...

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IEEE Vehicular Technology Conference

作者： Congzheng Han Simon Armour Office of Communications (Ofcom) London UK Centre for Communications Research University of Bristol Bristol UK

ISBN: (纸本)9781467309899

This paper presents a detailed analysis of computational complexity, RF and operational energy consumption of a number of radio resource management strategies. Those scheduling algorithms are evaluated within a LTE downlink simulator and the results show that the adaptive scheduling algorithm is able to achieve a significant energy saving-up to average operational energy reduction gain of 71.75% and 47.86% over a conventional nonenergy aware resource allocation scheme in the pessimistic and optimistic case, respectively. In addition, the computational complexity of the algorithm is estimated, and the trade-off between RF and DSP processing for power efficiency is evaluated.

关键词： Green Radio Energy Efficiency Radio Resource Management complexity classes Local thermodynamic equilibrium management of resources energy consumption analysis Long Term Evolution scheduling algorithms Pessimism radiofrequency dynamic efficiency Resource utilization operational energy consumption algorithms

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Study and analysis of task scheduling algorithms in clouds based on artificial bee colony

Study and analysis of task scheduling algorithms in clouds b...

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International Congress on Technology, Communication and Knowledge (ICTCK)

作者： Elaheh Hallaj Seyyed Reza Kamel Tabbakh Department of Software Engineering Islamic Azad University Neyshabur Iran Department of Software Engineering Islamic Azad University Mashhad Iran

ISBN: (纸本)9781467397636

Task scheduler plays a significant role in cloud computing, since it has a direct effect on cloud performance. As cloud scheduling is known to be an NP-hard problem, swarm intelligence-based techniques are widely used in this paradigm, due to their ability of searching for large scale problem solutions in an efficient manner. This paper, discusses some scheduling algorithms based on artificial bee colony. These algorithms exploit the smartness of bees' behavior to reach an optimal assignment of tasks to resources. An analytical comparison has also been done to briefly show the characteristics and applications of bee colony technique for scheduling in distributed computing area.

关键词： scheduling Virtual machining Cloud computing Algorithm design and analysis Heuristic algorithms scheduling algorithms Optimization

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Implementation of three scheduling algorithms in the smart grid communications over 4G networks

Implementation of three scheduling algorithms in the smart g...

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International Conference on Space Science and Communication (IconSpace)

作者： Ayman Hajjawi Mahamod Ismail Tito Yuwono Department of Electronic Electrical and System Engineering The National University of Malaysia (UKM) Selangor Malaysia Department of Electrical Engineering Universitas Islam Indonesia Yogyakarta Indonesia

The latest 4G wireless technology, Long Term Evolution (LTE), is expected to be a promising wireless network for smart grid communications due to its high data rate and low delay. The needs of real time communications in the smart grid require reliable, confident and well tested wireless networks. scheduling is one of the mechanisms which has a crucial role on the smart grid performance since it is in charge of the bandwidth resource allocation process. However, due to the fact that LTE has not been intended for smart grid communications, the performance of the scheduling algorithms must be optimized and properly tested. This paper aims at evaluating the performance of three scheduling algorithms, namely Frame Level Scheduler, Exponential Rule and Logarithmic Rule algorithms, in the smart grid communications. The evaluation process is based on their performance in the smart grid for three applications (VoIP, video surveillance and metering data) with specific data rate and delay requirements for each application. The results are evaluated in terms of throughput, delay and packet loss ratio.

关键词： Smart grids Delays Real-time systems scheduling algorithms Throughput Long Term Evolution Wireless networks

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Robustness comparison of scheduling algorithms in mapreduce framework

arXiv

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arXiv 2020年

作者： Daghighi, Amirali Chen, Jim Q. St. Cloud State University

Parallel computing is the fundamental base for MapReduce framework in Hadoop. A big data is split into small data chunks, where Map task is referred to processing a data chunk. Each data chunk is replicated over three servers in Hadoop for increasing the availability of data and decreasing the probability of data loss. As a result, the three servers that have the Map task stored on their disk are the fastest servers to process them, which are called local servers. All the servers in the same rack as local servers are called rack-local servers that are slower than local servers in processing Map tasks since the data chunk associated with the Map task should be fetched through the top of the rack switch. All the other servers are called remote servers that are the slowest servers for processing a Map task since they need to fetch data from a local server in another rack, so data should be transmitted through at least two top of the rack switches and a core switch. Note that the number of switches in the path of data transfer depends on the internal network structure of data centers. The First-In-First-Out (FIFO) and Hadoop Fair Scheduler (HFS) algorithms do not take the rack structure of data centers into account, so they are known to not be heavy-traffic delay optimal or even throughput optimal. The recent advances on scheduling for data centers considering the rack structure of them and the heterogeneity of servers resulted in the state-of-the-art Balanced-PANDAS algorithm that outperforms the classic MaxWeight algorithm and its derivation, JSQ-MaxWeight algorithm. In both Balanced-PANDAS and MaxWeight algorithms, the processing rate of local, rack-local, and remote servers are assumed to be known. However, with the change of traffic over time in addition to estimation errors of processing rates, it is not realistic to consider the processing rates to be known. In this work, we study the robustness of Balanced-PANDAS and MaxWeight algorithms in Copyright © 2020, The

关键词： scheduling algorithms

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