{"title":"Tackling Deployability Challenges in ML-Powered Networks","authors":"Noga H. Rotman","doi":"10.1145/3626570.3626605","DOIUrl":"https://doi.org/10.1145/3626570.3626605","url":null,"abstract":"Following the success of Machine Learning (ML) in various fields such as natural language processing, computer vision and computational biology, there has been a growing interest in incorporating ML into the networking domain [5, 6, 14, 4, 9]. Today, ML-based algorithms for prominent networking problems such as congestion control, resource management and routing, perform very well when their training environment is faithful to the operational environment, achieving state-of-the-art results when compared to traditional algorithms. However, the adaptation of these algorithms to function in production environments has not been straightforward, as real-world networks may differ greatly from the data used for training, leading to a drop in performance when unleashed into the wild.","PeriodicalId":35745,"journal":{"name":"Performance Evaluation Review","volume":"55 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":"135426271","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 First Workshop on Quantum Systems and Computations (2023)","authors":"David Elkouss, John C.S. Lui, Leandros Tassiulas","doi":"10.1145/3626570.3626593","DOIUrl":"https://doi.org/10.1145/3626570.3626593","url":null,"abstract":"It is of great pleasure to host the first Workshop on Quantum Systems and Computation, which was held on June 19, 2023 at Orlando, Florida.","PeriodicalId":35745,"journal":{"name":"Performance Evaluation Review","volume":"2017 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":"135426405","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":"Optimal Rate-Matrix Pruning For Heterogeneous Systems","authors":"Zhisheng Zhao, Debankur Mukherjee","doi":"10.1145/3626570.3626578","DOIUrl":"https://doi.org/10.1145/3626570.3626578","url":null,"abstract":"We consider large-scale load balancing systems where processing time distribution of tasks depend on both task and server types. We analyze the system in the asymptotic regime where both the number of task and server types tend proportionally to infinity. In such heterogeneous setting, popular policies like Join Fastest Idle Queue (JFIQ), Join Fastest Shortest Queue (JFSQ) are known to perform poorly and they even shrink the stability region. Moreover, to the best of our knowledge, in this setup, finding a scalable policy with provable performance guarantee has been an open question prior to this work. In this paper, we propose and analyze two asymptotically delay-optimal dynamic load balancing policies: (a) one that efficiently reserves the processing capacity of each server for \"good\" tasks and route tasks under the Join Idle Queue policy; and (b) a speed-priority policy that increases the probability of servers processing tasks at a high speed. Leveraging a framework inspired by the graphon literature and using the mean-field method and stochastic coupling arguments, we prove that both policies above achieve asymptotic zero queueing, whereby the probability that a typical task is assigned to an idle server tends to 1 as the system scales.","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":"135426407","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":"Engineering Autonomous Self-Driving Networks","authors":"Mariam Kiran","doi":"10.1145/3626570.3626606","DOIUrl":"https://doi.org/10.1145/3626570.3626606","url":null,"abstract":"Networking infrastructure, e.g. wide area networks (WAN) connecting data centers worldwide, or wireless 5G and beyond, are all witnessing unprecedented traffic demand, due to massive data-explosion in software applications involving text, image and video transfers and demand for high quality connectivity. The infrastructure itself is often limited by budget; and providing optimum performance with limited resources such as high bandwidth or low latency for user quality experience, is a challenge. Continually upgrading to expensive high-end switches and optical fibers is not a long-term feasible solution.","PeriodicalId":35745,"journal":{"name":"Performance Evaluation Review","volume":"38 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":"135426414","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":"Distributed Rate Scaling in Large-Scale Service Systems","authors":"Daan Rutten, Martin Zubeldia, Debankur Mukherjee","doi":"10.1145/3626570.3626579","DOIUrl":"https://doi.org/10.1145/3626570.3626579","url":null,"abstract":"We consider a large-scale parallel-server system, where each server dynamically chooses its processing speed in a completely distributed fashion. The goal is to minimize the global cost that is the sum of the average cost of maintaining the respective processing speeds of all servers and a certain non-decreasing function of the sojourn time of tasks. The key challenges arise from the facts that the arrival rate of tasks is unknown and that there is no centralized control or communication among the servers. Using insights from stochastic approximation, we develop a novel rate-scaling algorithm and prove that the cost of the processing rates under our algorithm converges to the globally optimum value as the system size becomes large. En route, we also analyze the performance of a fully heterogeneous parallel-server system (i.e, where each server has a different processing speed), which might be of independent interest.","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":"135426419","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":"Learning-based Optimal Quantum Switch Scheduling","authors":"Jiatai Huang, Longbo Huang","doi":"10.1145/3626570.3626597","DOIUrl":"https://doi.org/10.1145/3626570.3626597","url":null,"abstract":"In this paper, we consider the problem of optimal scheduling for quantum switches with dynamic demand and random entanglement successes. Different from prior results that often focus on (known) fixed entanglement success probabilities, we assume zero prior knowledge about the entanglement success probabilities and allow them to vary from time to time in an adversarial manner. We propose a learning-based algorithm QSSoftMW based on the framework developed in [1], which combines adversarial learning and Lyapunov queue analysis. We show that QSSoftMW is able to automatically adapt to the changing system statistics and ensure quantum switch stability.","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":"135426573","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}
Daan Rutten, Nicolas Christianson, Debankur Mukherjee, Adam Wierman
{"title":"Smoothed Online Optimization with Unreliable Predictions","authors":"Daan Rutten, Nicolas Christianson, Debankur Mukherjee, Adam Wierman","doi":"10.1145/3606376.3593570","DOIUrl":"https://doi.org/10.1145/3606376.3593570","url":null,"abstract":"We consider online optimization with switching costs in a normed vector space (X, ||·||) wherein, at each time t, a decision maker observes a non-convex hitting cost function ƒ : t X →[0, ∞] and must decide upon some xt∈X→, paying ƒt (xt) + || xt-xt-1||, where ||·|| characterizes the switching cost. Throughout, we assume that ƒt is globally α-polyhedral, i.e., ƒt has a unique minimizer υt ∈X, and, for all x ∈ X, ƒ t) (x) ≥ ƒt + α · ||x - υ t. Moreover, we assume that the decision maker has access to an untrusted prediction xt of the optimal decision during each round, such as the decision suggested by a black-box AI tool.","PeriodicalId":35745,"journal":{"name":"Performance Evaluation Review","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135657397","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}
Kailong Wang, Yuxi Ling, Yanjun Zhang, Zhou Yu, Haoyu Wang, Guangdong Bai, Beng Chin Ooi, Jin Song Dong
{"title":"Characterizing Cryptocurrency-themed Malicious Browser Extensions","authors":"Kailong Wang, Yuxi Ling, Yanjun Zhang, Zhou Yu, Haoyu Wang, Guangdong Bai, Beng Chin Ooi, Jin Song Dong","doi":"10.1145/3606376.3593529","DOIUrl":"https://doi.org/10.1145/3606376.3593529","url":null,"abstract":"Due to the surging popularity of various cryptocurrencies in recent years, a large number of browser extensions have been developed as portals to access relevant services, such as cryptocurrency exchanges and wallets. This has stimulated a wild growth of cryptocurrency-themed malicious extensions that cause heavy financial losses to the users and legitimate service providers. They have shown their capability of evading the stringent vetting processes of the extension stores, highlighting a lack of understanding of this emerging type of malware in our community. In this work, we conduct the first systematic study to identify and characterize cryptocurrency-themed malicious extensions. We monitor seven official and third-party extension distribution venues for 18 months (December 2020 to June 2022) and have collected around 3600 unique cryptocurrency-themed extensions. Leveraging a hybrid analysis, we have identified 186 malicious extensions that belong to five categories. We then characterize those extensions from various perspectives including their distribution channels, life cycles, developers, illicit behaviors, and illegal gains. Our work unveils the status quo of the cryptocurrency-themed malicious extensions and reveals their disguises and programmatic features on which detection techniques can be based. Our work serves as a warning to extension users, and an appeal to extension store operators to enact dedicated countermeasures. To facilitate future research in this area, we release our dataset of the identified malicious extensions and open-source our analyzer.","PeriodicalId":35745,"journal":{"name":"Performance Evaluation Review","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135657598","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}
Sushil Mahavir Varma, Francisco Castro, Siva Theja Maguluri
{"title":"Power-of-d Choices Load Balancing in the Sub-Halfin Whitt Regime","authors":"Sushil Mahavir Varma, Francisco Castro, Siva Theja Maguluri","doi":"10.1145/3606376.3593564","DOIUrl":"https://doi.org/10.1145/3606376.3593564","url":null,"abstract":"We characterize the steady-state queue length distribution for the Power-of-d choices routing algorithm for almost all values of d in the sub-Halfin Whitt asymptotic regime.","PeriodicalId":35745,"journal":{"name":"Performance Evaluation Review","volume":"285 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135657592","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}
Bo Sun, Lin Yang, Mohammad Hajiesmaili, Adam Wierman, John C.S. Lui, Don Towsley, Danny H.K. Tsang
{"title":"The Online Knapsack Problem with Departures","authors":"Bo Sun, Lin Yang, Mohammad Hajiesmaili, Adam Wierman, John C.S. Lui, Don Towsley, Danny H.K. Tsang","doi":"10.1145/3606376.3593576","DOIUrl":"https://doi.org/10.1145/3606376.3593576","url":null,"abstract":"The online knapsack problem is a classic online resource allocation problem in networking and operations research. Its basic version studies how to pack online arriving items of different sizes and values into a capacity-limited knapsack. In this paper, we study a general version that includes item departures, while also considering multiple knapsacks and multi-dimensional item sizes. We design a threshold-based online algorithm and prove that the algorithm can achieve order-optimal competitive ratios. Beyond worst-case optimized algorithms, we also propose a data-driven online algorithm that can achieve near-optimal average performance under typical instances while guaranteeing the worst-case performance.","PeriodicalId":35745,"journal":{"name":"Performance Evaluation Review","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135657591","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}
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