{"title":"实现最佳动态规模感知调度","authors":"Esa Hyytiä , Rhonda Righter","doi":"10.1016/j.peva.2024.102396","DOIUrl":null,"url":null,"abstract":"<div><p>In this paper, we study dispatching systems that appear in manufacturing, service, healthcare systems, as well as, in various information, communication and computer systems. Such systems comprise a dispatcher and a pool of parallel servers, to which jobs are assigned upon arrival. A common objective is to minimize the mean waiting or response time. In large systems, due to the state-space explosion and scalability reasons, it is impossible to utilize full state information of the system. We therefore consider systems with a small number of servers, and assume that the job sizes become known upon arrival. In such settings, it is plausible to carefully evaluate each server for every new job. First we study a system with a Poisson arrival process, and derive Bellman equations. Then we generalize to the case with general i.i.d. inter-arrival times. The Bellman equations are essentially functional equations that can be solved numerically via value iteration. From their solutions, the optimal dispatching policy and corresponding mean performance can be determined. Our solution framework is illustrated with examples, which show that significant performance gains compared to popular heuristic policies are available in our setting.</p></div>","PeriodicalId":19964,"journal":{"name":"Performance Evaluation","volume":"164 ","pages":"Article 102396"},"PeriodicalIF":1.0000,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Towards the optimal dynamic size-aware dispatching\",\"authors\":\"Esa Hyytiä , Rhonda Righter\",\"doi\":\"10.1016/j.peva.2024.102396\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In this paper, we study dispatching systems that appear in manufacturing, service, healthcare systems, as well as, in various information, communication and computer systems. Such systems comprise a dispatcher and a pool of parallel servers, to which jobs are assigned upon arrival. A common objective is to minimize the mean waiting or response time. In large systems, due to the state-space explosion and scalability reasons, it is impossible to utilize full state information of the system. We therefore consider systems with a small number of servers, and assume that the job sizes become known upon arrival. In such settings, it is plausible to carefully evaluate each server for every new job. First we study a system with a Poisson arrival process, and derive Bellman equations. Then we generalize to the case with general i.i.d. inter-arrival times. The Bellman equations are essentially functional equations that can be solved numerically via value iteration. From their solutions, the optimal dispatching policy and corresponding mean performance can be determined. Our solution framework is illustrated with examples, which show that significant performance gains compared to popular heuristic policies are available in our setting.</p></div>\",\"PeriodicalId\":19964,\"journal\":{\"name\":\"Performance Evaluation\",\"volume\":\"164 \",\"pages\":\"Article 102396\"},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2024-01-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Performance Evaluation\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0166531624000014\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Performance Evaluation","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0166531624000014","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
Towards the optimal dynamic size-aware dispatching
In this paper, we study dispatching systems that appear in manufacturing, service, healthcare systems, as well as, in various information, communication and computer systems. Such systems comprise a dispatcher and a pool of parallel servers, to which jobs are assigned upon arrival. A common objective is to minimize the mean waiting or response time. In large systems, due to the state-space explosion and scalability reasons, it is impossible to utilize full state information of the system. We therefore consider systems with a small number of servers, and assume that the job sizes become known upon arrival. In such settings, it is plausible to carefully evaluate each server for every new job. First we study a system with a Poisson arrival process, and derive Bellman equations. Then we generalize to the case with general i.i.d. inter-arrival times. The Bellman equations are essentially functional equations that can be solved numerically via value iteration. From their solutions, the optimal dispatching policy and corresponding mean performance can be determined. Our solution framework is illustrated with examples, which show that significant performance gains compared to popular heuristic policies are available in our setting.
期刊介绍:
Performance Evaluation functions as a leading journal in the area of modeling, measurement, and evaluation of performance aspects of computing and communication systems. As such, it aims to present a balanced and complete view of the entire Performance Evaluation profession. Hence, the journal is interested in papers that focus on one or more of the following dimensions:
-Define new performance evaluation tools, including measurement and monitoring tools as well as modeling and analytic techniques
-Provide new insights into the performance of computing and communication systems
-Introduce new application areas where performance evaluation tools can play an important role and creative new uses for performance evaluation tools.
More specifically, common application areas of interest include the performance of:
-Resource allocation and control methods and algorithms (e.g. routing and flow control in networks, bandwidth allocation, processor scheduling, memory management)
-System architecture, design and implementation
-Cognitive radio
-VANETs
-Social networks and media
-Energy efficient ICT
-Energy harvesting
-Data centers
-Data centric networks
-System reliability
-System tuning and capacity planning
-Wireless and sensor networks
-Autonomic and self-organizing systems
-Embedded systems
-Network science