Yiming Zeng, Jiarui Zhang, Zhenhua Liu, Yuanyuan Yang
{"title":"Entanglement Management through Swapping over Quantum Internets","authors":"Yiming Zeng, Jiarui Zhang, Zhenhua Liu, Yuanyuan Yang","doi":"10.1145/3626570.3626595","DOIUrl":"https://doi.org/10.1145/3626570.3626595","url":null,"abstract":"Quantum Internet has the potential to support a wide range of applications in quantum communication and quantum computing by generating, distributing, and processing quantum information. Generating a long-distance quantum entanglement is one of the most essential functions of a quantum Internet to facilitate these applications. However, entanglement is a probabilistic process, and its success rate drops significantly as distance increases. Entanglement swapping is an efficient technique used to address this challenge. How to efficiently manage the entanglement through swapping is a fundamental yet challenging problem. In this paper, we will consider two swapping methods: (1) BSM: a classic entanglement-swapping method based on Bell State measurements that fuse two successful quantum links, (2) nfusion: a more general and efficient swapping method based on Greenberger-Horne-Zeilinger measurements, capable of fusing n successful quantum links. Our goal is to maximize the entanglement rate for multiple quantum-user pairs over the quantum Internet with an arbitrary topology. We propose efficient entanglement management algorithms that utilized the unique properties of BSM and n-fusion. Evaluation results highlight that our approach outperforms existing routing protocols.","PeriodicalId":35745,"journal":{"name":"Performance Evaluation Review","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135426403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Special Issue on The Workshop on MAthematical performance Modeling and Analysis (MAMA 2023)","authors":"Mark S. Squillante","doi":"10.1145/3626570.3626572","DOIUrl":"https://doi.org/10.1145/3626570.3626572","url":null,"abstract":"The complexity of computer systems, networks and applications, as well as the advancements in computer technology, continue to grow at a rapid pace. Mathematical analysis, modeling and optimization have been playing, and continue to play, an important role in research studies to investigate fundamental issues and tradeoffs at the core of performance problems in the design and implementation of complex computer systems, networks and applications.","PeriodicalId":35745,"journal":{"name":"Performance Evaluation Review","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135426415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Making Decisions at Data Plane Speeds","authors":"Srinivas Narayana","doi":"10.1145/3626570.3626603","DOIUrl":"https://doi.org/10.1145/3626570.3626603","url":null,"abstract":"Feedback control loops to implement self-driving networks constitute data collection to sense the network, and control algorithms to make decisions driving the network. Highquality data is necessary for smart decisions. Yet, highquality data is hard to obtain from the network data plane, due to insufficient visibility and large data volumes stemming from high packet rates. This paper distills principles to collect high-quality data arising from our own research experience: (i) filter and aggregate data as close to the source as possible; (ii) identify broad families of statistics that are measurable with bounded inaccuracy; (iii) don't assume lowlevel data plane software is easy to instrument, but instead (iv) apportion software flexibility by the time scales of the computation; and (v) prefer in-band approaches where possible for timely and efficient reactivity. We call the community to act upon these principles to leverage emerging opportunities using safely-extensible network stacks.","PeriodicalId":35745,"journal":{"name":"Performance Evaluation Review","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135426567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Arpit Gupta, Ramakrishnan Durairajan, Walter Willinger
{"title":"Special Issue on The ACM SIGMETRICS Workshop on Measurements for Self-Driving Networks","authors":"Arpit Gupta, Ramakrishnan Durairajan, Walter Willinger","doi":"10.1145/3626570.3626601","DOIUrl":"https://doi.org/10.1145/3626570.3626601","url":null,"abstract":"The design and implementation of autonomous or \"selfdriving networks\" represent some of today's most significant challenges in networking research. The vision for these networks is that they will be able to make management and control decisions in real time, typically without human intervention. Recent technological advancements, like SDN and 5G networks, along with scientific innovations such as XAI and transformers, have paved the way for this vision. Key innovations include: (1) fully programmable, protocol-independent data planes and the languages to program them; (2) scalable platforms capable of processing distributed streaming data, bolstered by the latest tools and software for data analysis and machine learning (ML).","PeriodicalId":35745,"journal":{"name":"Performance Evaluation Review","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135426416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The stationary distribution of the redundancy-d model with random order of service","authors":"E. Anton, K. Gardner","doi":"10.1145/3626570.3626575","DOIUrl":"https://doi.org/10.1145/3626570.3626575","url":null,"abstract":"Redundancy has gained considerable attention as a dispatching paradigm that promises the potential for significant response time improvements, see [4, 6] and the references therein. The premise of redundancy is that upon a job's arrival, multiple copies of the job are dispatched to different servers. A job's class is defined by the set of servers to which its copies are dispatched, and there is a bipartite graph specifying the relationships between job classes and servers. A job is considered complete, and departs from the system, as soon as any one of its copies has completed service. The additional copies of a job are removed either (i) when the first copy enters service, known as the cancel-onstart (c.o.s.) model, or (ii) when the first copy completes service, known as the cancel-on-complete (c.o.c.) model. In both models, redundancy has the potential to significantly reduce response time by exploiting the variability of queue lengths and server capacities.","PeriodicalId":35745,"journal":{"name":"Performance Evaluation Review","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135426422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Performance of the Gittins Policy in the G/G/1 and G/G/k, With and Without Setup Times","authors":"Yige Hong, Ziv Scully","doi":"10.1145/3626570.3626583","DOIUrl":"https://doi.org/10.1145/3626570.3626583","url":null,"abstract":"We consider the classic problem of preemptively scheduling jobs of unknown size (a.k.a. service time) in a queue to minimize mean number-in-system, or equivalently mean response time (a.k.a. sojourn time). We know how to solve this problem in an M/G/1, provided the job size distribution is known to the scheduler. In this case, the optimal policy is the Gittins policy (a.k.a. Gittins index policy) [1].","PeriodicalId":35745,"journal":{"name":"Performance Evaluation Review","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135428152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Markov Decision Process Framework for Control-Based Reinforcement Learning","authors":"Yingdong Lu, Mark S. Squillante, Chai Wah Wu","doi":"10.1145/3626570.3626585","DOIUrl":"https://doi.org/10.1145/3626570.3626585","url":null,"abstract":"For many years, reinforcement learning (RL) has proven to be very successful in solving a wide variety of learning and decision making under uncertainty (DMuU) problems, including those related to game playing and robotic control. Many different RL approaches, with varying levels of success, have been developed to address these problems.","PeriodicalId":35745,"journal":{"name":"Performance Evaluation Review","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135426402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Quantum Switch Scheduling for Information Qubits","authors":"Panagiotis Promponas, V´ctor Valls, Leandros Tassiulas","doi":"10.1145/3626570.3626598","DOIUrl":"https://doi.org/10.1145/3626570.3626598","url":null,"abstract":"This paper studies the problem of designing a scheduling policy for a quantum switch that teleports information qubits. The problem is analogous to scheduling photons in highspeed optical switches, with the difference that an optical switch is modeled as a bipartite graph instead of a complete graph. The paper's contributions are to model the problem of designing a scheduling policy as decomposing a symmetric doubly stochastic matrix, and to show that we can use Birkhoff's algorithm to obtain such a decomposition.","PeriodicalId":35745,"journal":{"name":"Performance Evaluation Review","volume":"286 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135426404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xuchuang Wang, Yu-Zhen Janice Chen, Matheus Guedes de Andrade, Mohammad Hajiesmaili, John C.S. Lui, Don Towsley
{"title":"Quantum Best Arm Identification","authors":"Xuchuang Wang, Yu-Zhen Janice Chen, Matheus Guedes de Andrade, Mohammad Hajiesmaili, John C.S. Lui, Don Towsley","doi":"10.1145/3626570.3626596","DOIUrl":"https://doi.org/10.1145/3626570.3626596","url":null,"abstract":"Recent progress on building quantum computers [1] envisages wide applications of quantum algorithms in the near future. With the advantage of quantum computer, one can speed up not only fundamental algorithms, e.g., unstructured search [6] and factoring [11], but recent machine learning algorithms [3] as well. In this paper, we study the quantum speedup on a canonical task of reinforcement learning-best arm identification in multi-armed bandits.","PeriodicalId":35745,"journal":{"name":"Performance Evaluation Review","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135426406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Trade-off Analysis in Learning-augmented Algorithms with Societal Design Criteria","authors":"Mohammad H. Hajiesmaili","doi":"10.1145/3626570.3626590","DOIUrl":"https://doi.org/10.1145/3626570.3626590","url":null,"abstract":"Traditionally, computer systems are designed to optimize classic notions of performance such as flow completion time, cost, etc. The system performance is then typically evaluated by characterizing theoretical bounds in worst-case settings over a single performance metric. In the next generation of computer systems, societal design criteria, such as carbon awareness and fairness, becomes a first-class design goal. However, the classic performance metrics may conflict with societal criteria. Foundational understanding and performance evaluations of systems with these inherent trade-offs lead to novel research questions that could be considered new educational components for performance analysis courses. The classic techniques, e.g., worst-case analysis, for systems with conflicting objectives may lead to the impossibility of results. However, a foundational understanding of the impossibility of results calls for new techniques and tools. In traditional performance evaluation, to understand the foundational limits, typically, it is sufficient to derive lower-bound arguments in worst-case settings. In the new era of system design, lower bounds are inherently about trade-offs between different objectives. Characterizing these trade-offs in settings with multiple design criteria is closer to the notion of Pareto-optimality, which is drastically different from classic lower bounds. With the impossibility of results using classic paradigms, one possible direction is to (re)design systems following the emerging direction of learning-augmented algorithms. With this approach, it might be possible to remove/mitigate the foundational conflict between classic vs. societal metrics using the right predictions. However, the performance evaluation of learning-augmented algorithms calls for a new set of technical questions, which we highlight in this paper.","PeriodicalId":35745,"journal":{"name":"Performance Evaluation Review","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135426408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}