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Telecommunications Forum (TELFOR)

作者： Liljana Gavrilovska Dejan Talevski Faculty of Electrical Engineering and Information Technology Skopje Macedonia

Long Term Evolution (LTE) is the new standard specified by 3GPP on the way towards the fourth generation mobile network. The LTE introduces enhanced data link mechanisms to support successful implementation of new data services across the network. The incorporated scheduling mechanisms can significantly contribute to this goal. In this paper novel scheduling algorithms are presented and compared to the Max C/I Downlink scheduler for LTE, which is characterized by high data rates at cell level, but poor fairness. The newly developed algorithms allow fair distribution of available resources. Simulation results presented in the paper show that the implementation of these newly developed algorithms enables improvement of the overall system capacity and user level performances.

关键词： scheduling algorithms scheduling Downlink Throughput Channel models Mobile communication OFDM

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Dynamic scheduling algorithms for Serverless Computing Solutions in the Cloud

Dynamic Scheduling Algorithms for Serverless Computing Solut...

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E-mobility, Power Control and Smart Systems (ICEMPS), International Conference on

作者： Abdul Sajid Mohammed Venkata Ramana Saddi Santhosh Kumar Gopal Nasmin Jiwani J. Logeshwaran School of Computer and Information Sciences University of the Cumberlands Kentucky USA ACE American Insurance - Chubb Group Raleigh NC USA Sciences Charlotte NC USA Dept. of Information Technology University of The Cumberlands Williamsburg KY USA Department of Electronics and Communication Engineering Sri Eshwar College of Engineering Coimbatore INDIA

ISBN: (数字)9798350394399

ISBN: (纸本)9798350394405

Server less computing solutions within the cloud presentsan exceptional opportunity for corporations to gain progressed scalability, availability, and fee efficiency. To reap such blessings, establishments need to utilize the handiest dynamic scheduling algorithms that are tailor-made to their unique needs. These algorithms can include predictive scheduling, call for-driven scheduling, and application-conscious scheduling, among others. Predictive scheduling algorithms are looking for to expect capacity call for to prevent erratic performance. This study focuses on dynamic scheduling algorithms for serverless computing solutions in the cloud. The researchers explore the characteristics of serverless computing models and the challenges of dynamic scheduling. A comprehensive evaluation is conducted on various scheduling algorithms, taking into consideration performance metrics such as throughput, response time, and resource utilization. The results show that dynamic scheduling algorithms are effective in optimizing resource allocation and improving overall system performance. Specific values derived from the results include a significant reduction in resource wastage, improved scalability, and increased cost-effectiveness. These findings suggest that dynamic scheduling algorithms are crucial for efficient and scalable serverless computing solutions in the cloud. With the aid of applying the maximum suitable dynamic scheduling algorithms tailor-made to precise desires, corporations could be higher prepared to fulfill their formidable cloud-computing dreams.

关键词： scheduling algorithms Heuristic algorithms Scalability System performance Serverless computing Companies Dynamic scheduling

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Comparative Analysis of Various Task scheduling algorithms in Cloud Environment

Comparative Analysis of Various Task Scheduling Algorithms i...

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Information Technology (OCIT), OITS International Conference on

作者： Puspanjali Mallik Ajit Kumar Nayak Rabindra Kumar Dalei Shailabala Women's Autonomous College Cuttack Sikshya O Anusandhan University Bhubaneswar Silicon Institute of Technology Bhubaneswar

ISBN: (纸本)9781665416658

Internet is indispensable in all of the activities of today's society. Cloud computing emerges as a demanded recent technology to make the use of internet in a simplified, cost-affordable and timely available form to the user. The primary purpose of cloud computing is to utilize the resource efficiently, allocate the tasks to the resources, balance their load and satisfy the agreements of user without fail. This research paper includes a brief analysis and comparison of the traditional task scheduling algorithms like FCFS, RR, and MCT with recent algorithms such as IWD, TSCSA, LBMPSO. All of the recent time algorithms are satisfying multi-objective qualities and ensures economic feasibility.

关键词： Economics Cloud computing scheduling algorithms Task analysis Information technology

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A review energy-efficient task scheduling algorithms in cloud computing

A review energy-efficient task scheduling algorithms in clou...

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IEEE Long Island Systems, Applications and Technology Conference (LISAT)

作者： Saleh Atiewi Salman Yussof Mohd Ezanee Muder Almiani Tenaga National University Kajang Selangor Malaysia Al-Hussein Bin Talal University Ma'an Jordan

ISBN: (纸本)9781467384919

Cloud computing is a model for delivering information technology services, wherein resources are retrieved from the Internet through web-based tools and applications instead of a direct connection to a server. The capability to provision and release cloud computing resources with minimal management effort or service provider interaction led to the rapid increase of the use of cloud computing. Therefore, balancing cloud computing resources to provide better performance and services to end users is important. Load balancing in cloud computing means balancing three important stages through which a request is processed. The three stages are data center selection, virtual machine scheduling, and task scheduling at a selected data center. User task scheduling plays a significant role in improving the performance of cloud services. This paper presents a review of various energy-efficient task scheduling methods in a cloud environment. A brief analysis of various scheduling parameters considered in these methods is also presented. The results show that the best power-saving percentage level can be achieved by using both DVFS and DNS.

关键词： Cloud computing scheduling algorithms Servers Energy efficiency scheduling Energy consumption

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Improved Approximation Coflows scheduling algorithms for Minimizing the Total Weighted Completion Time and Makespan in Heterogeneous Parallel Networks

arXiv

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arXiv 2023年

作者： Chen, Chi-Yeh Department of Computer Science and Information Engineering National Cheng Kung University Taiwan

Coflow is a network abstraction used to represent communication patterns in data centers. The coflow scheduling problem encountered in large data centers is a challenging NP-hard problem. This paper tackles the scheduling problem of coflows with release times in heterogeneous parallel networks, which feature an architecture consisting of multiple network cores running in parallel. Two polynomial-time approximation algorithms are presented in this paper, designed to minimize the total weighted completion time and makespan in heterogeneous parallel networks, respectively. For any given ϵ > 0, our proposed approximation algorithm for minimizing the total weighted completion time achieves approximation ratios of 3 + ϵ and 2 + ϵ in the cases of arbitrary and zero release times, respectively. Additionally, we introduce an approximation algorithm for minimizing the makespan, achieving an approximation ratio of 2 + ϵ for ϵ > 0. Notably, these advancements surpass the previously best-known approximation ratio of O(log m/log log m) for both minimizing the total weighted completion time and makespan. This result also improves upon the previous approximation ratios of 6 − m2 and 5 − m2 for arbitrary and zero release times, respectively, in identical parallel networks. Copyright © 2023, The Authors. All rights reserved.

关键词： scheduling algorithms

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Research on IPTV scheduling algorithms Based on Patching Stream

Research on IPTV Scheduling Algorithms Based on Patching Str...

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IEEE International Conference on Computer and Communications

作者： Jun Tao Qi Jing Li Xiang Ma Hai Yang Chen Couer nd sof engineer deren Anhui Insiue of inforion echnoogyCoege of Eecric nd Eecronic Engineering Anhui Insiue of inforion echnoogyCoege of Eecric nd Eecronic Engineering Anhui Insiue of inforion echnoogyNework Services Deren H3C Counicion Technoogy Co. Ld.

ISBN: (数字)9781728147437

ISBN: (纸本)9781728147444

This paper describes the development status and key technologies of IPTV, and discusses the advantages of video multicast and the basic theory of multicast. Based on the analysis of the basic idea of stream scheduling strategy and the behavior characteristics of user on demand, the mathematical model of stream scheduling strategy is established, and the performance evaluation parameters of stream scheduling algorithm are proposed. The stream scheduling algorithm of patch stream is elaborated in detail. Two improved stream scheduling algorithms of patching stream are proposed, and their advantages are analyzed through experiments.

关键词： Streaming media IPTV scheduling algorithms Real-time systems Servers Protocols Heuristic algorithms

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A Simulation Framework to Evaluate Virtual CPU scheduling algorithms

A Simulation Framework to Evaluate Virtual CPU Scheduling Al...

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International Conference on Distributed Computing Systems Workshop

作者： Cuong Pham Qingkun Li Zachary Estrada Zbigniew Kalbarczyk Ravishankar Iyer University of Illinois at Urbana-Champaign

Virtual CPU (VCPU) scheduling algorithms that efficiently manage processing-resource at the machine virtualization layer are key to facilitate resource sharing and workload consolidation in Clouds. Such algorithms are mostly inherited from pre-virtualization designs, thus need to be revamped and re-evaluated. This paper presents a simulation framework based on SAN model to rapidly evaluate Virtual CPU scheduling algorithms. The paper also demonstrates an evaluation of three VCPU scheduling algorithms using this framework.

关键词： scheduling algorithms Synchronization Virtualization Storage area networks Virtual machine monitors Logic gates Load modeling

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Analysis of scheduling algorithms in data warehouse for query processing

Analysis of scheduling algorithms in data warehouse for quer...

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International Conference on Emerging Trends in Science, Engineering and Technology (INCOSET)

作者： S. Krishnaveni M. Hemalatha Dept. Computer Science Karpagam University Coimbatore Tamil Nadu India

ISBN: (纸本)9781467351416

The data warehouse is a centralized repository for analyzing and storing huge amounts of data. In distributed data warehouse, data can be shared across multiple data repositories which belong to one or more organizations. In general, clients expect short response times for their queries. The scheduling algorithms are used to resolve the issues and to accomplish the task with quick manner. In this paper, we are dealing grid based scheduling algorithms for query scheduling and resource management in distributed data warehouses. The algorithms are Optimal Resource Constraints (ORC), Grouping based Fine-grained Job scheduling (GFJS), Research on Novel Dynamic Resource Management (RNDRM) and New Resource Mechanism with Negotiate Solution (NRMNS). When we are combining both job and resource scheduling algorithms, the query processing time and memory size performances are lower than individual scheduling responses.

关键词： Data Warehouse Job scheduling (JS) Resource scheduling (RS) Optimal Resource Constraints (ORC) Grouping based Fine-grained Job scheduling (GFJS) Research on Novel Dynamic Resource Management (RNDRM) New Resource Mechanism with Negotiate Solution (NRMNS) Data warehousing scheduling algorithms management of resources Reaction Time query analysis jobs

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Efficient scheduling algorithms for On-demand Wireless Data Broadcast

Efficient Scheduling Algorithms for On-demand Wireless Data ...

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Annual IEEE International Conference on Computer Communications

作者： Zaixin Lu Weili Wu Wei Wayne Li Miao Pan Dept. of Mathematics and Computer Science Marywood University Scranton PA 18509 USA Dept. of Computer Science University of Texas at Dallas Richardson Texas 75080 USA Dept. of Computer Science Texas Southern University Houston Texas 77004 USA Dept. of Electrical & Computer Engineering University of Houston Houston Texas 77204 USA

ISBN: (纸本)9781467399548

On-demand wireless data broadcast is an efficient way to disseminate data to a large number of mobile users. In many applications, such as stock quotes and flight schedules, users may have to download multiple data items per request. However the multi-item request scheduling has not yet been thoroughly investigated for on-demand wireless data broadcasts. In this paper, we step-up on investigating this problem from viewpoint of theory and simulation. We develop a two-stage scheduling scheme to arrange the requested data items with the objective of minimizing the average access latency. The first stage is to select the data items to be broadcast in the next time period and the second stage is to schedule the broadcasting order for the data items selected in the first stage. We develop algorithms for the two stages respectively and analyze them both theoretically and practically. We also compare the proposed algorithms with other well known scheduling methods through simulation. The theoretical findings and simulation results reveal that significantly better access latency can be obtained by using our scheduling scheme rather than its competitors.

关键词： wireless data scheduling algorithms broadcasting Latency Consumers Competitors

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Hybrid Resource scheduling algorithms in Heterogeneous Distributed Computing: a Comparative Study and Further Enhancements

Hybrid Resource Scheduling Algorithms in Heterogeneous Distr...

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IT Innovation and Knowledge Discovery (ITIKD), International Conference on

作者： Mandicou Ba Ahmad Fall Bachar Salim Haggar Laboratoire LIMBI UCAD/ESPIDGI Dakar Senegal Laboratoire LIMBI ENASTIC Ndjamena Tchad

In the context of heterogeneous distributed systems like modern High-Performnace Computing (HPC) that must respond to unpredictable requests of variable complexity with variable resource requirements (processing power as well as storage capacity), a classical scheduling algorithm would not be suitable. Therefore, hybrid dynamic scheduling approaches have been adopted. These later have the ability to adapt over time based on the knowledge gained from the results of previous work. Several techniques are thus used to optimize these algorithms such as resources clustering. In this paper, we propose a comparative study of some of most popular algorithms in order to highlight the situations in which each algorithm is more suitable. We evaluate their performance and evolution in a realistic setting of CloudSim tool without neglecting load-balancing, and measure these performance metrics at runtime.

关键词： Measurement Technological innovation Runtime scheduling algorithms Heuristic algorithms Clustering algorithms Knowledge discovery

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