2022 20th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt)最新文献_第5页

Non-asymptotic near optimal algorithms for two sided matchings 双边匹配的非渐近近最优算法

2022 20th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt) Pub Date : 2022-07-24 DOI: 10.23919/WiOpt56218.2022.9930577

R. Vaze, J. Nair

引用次数: 2

Performance and EMF Exposure Trade-offs in Human-centric Cell-free Networks 以人为中心的无蜂窝网络的性能和EMF暴露权衡

2022 20th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt) Pub Date : 2022-07-13 DOI: 10.23919/WiOpt56218.2022.9930537

F. Malandrino, E. Chiaramello, M. Parazzini, C. Chiasserini

引用次数: 1

Differentially Private Linear Bandits with Partial Distributed Feedback 具有部分分布反馈的差分私有线性强盗

2022 20th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt) Pub Date : 2022-07-12 DOI: 10.23919/WiOpt56218.2022.9930524

Fengjiao Li, Xingyu Zhou, Bo Ji

{"title":"Differentially Private Linear Bandits with Partial Distributed Feedback","authors":"Fengjiao Li, Xingyu Zhou, Bo Ji","doi":"10.23919/WiOpt56218.2022.9930524","DOIUrl":"https://doi.org/10.23919/WiOpt56218.2022.9930524","url":null,"abstract":"In this paper, we study the problem of global reward maximization with only partial distributed feedback. This problem is motivated by several real-world applications (e.g., cellular network configuration, dynamic pricing, and policy selection) where an action taken by a central entity influences a large population that contributes to the global reward. However, collecting such reward feedback from the entire population not only incurs a prohibitively high cost, but often leads to privacy concerns. To tackle this problem, we consider differentially private distributed linear bandits, where only a subset of users from the population are selected (called clients) to participate in the learning process and the central server learns the global model from such partial feedback by iteratively aggregating these clients’ local feedback in a differentially private fashion. We then propose a unified algorithmic learning framework, called differentially private distributed phased elimination (DP-DPE), which can be naturally integrated with popular differential privacy (DP) models (including central DP, local DP, and shuffle DP). Furthermore, we prove that DP-DPE achieves both sublinear regret and sublinear communication cost. Interestingly, DP-DPE also achieves privacy protection “for free” in the sense that the additional cost due to privacy guarantees is a lower-order additive term. Finally, we conduct simulations to corroborate our theoretical results and demonstrate the effectiveness of DP-DPE.","PeriodicalId":228040,"journal":{"name":"2022 20th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116561510","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}

引用次数: 6

Unsupervised Crowdsourcing with Accuracy and Cost Guarantees 具有准确性和成本保证的无监督众包

2022 20th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt) Pub Date : 2022-07-05 DOI: 10.23919/WiOpt56218.2022.9930606

Yash Didwania, J. Nair, N. Hemachandra

引用次数: 0

Interference Constrained Beam Alignment for Time-Varying Channels via Kernelized Bandits 时变信道的干扰约束波束核束对准

2022 20th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt) Pub Date : 2022-07-02 DOI: 10.23919/WiOpt56218.2022.9930591

Yuntian Deng, Xingyu Zhou, A. Ghosh, Abhishek K. Gupta, N. Shroff

{"title":"Interference Constrained Beam Alignment for Time-Varying Channels via Kernelized Bandits","authors":"Yuntian Deng, Xingyu Zhou, A. Ghosh, Abhishek K. Gupta, N. Shroff","doi":"10.23919/WiOpt56218.2022.9930591","DOIUrl":"https://doi.org/10.23919/WiOpt56218.2022.9930591","url":null,"abstract":"To fully utilize the abundant spectrum resources in millimeter wave (mmWave), Beam Alignment (BA) is necessary for large antenna arrays to achieve large array gains. In practical dynamic wireless environments, channel modeling is challenging due to time-varying and multipath effects. In this paper, we formulate the beam alignment problem as a nonstationary online learning problem with the objective to maximize the received signal strength under interference constraint. In particular, we employ the non-stationary kernelized bandit to leverage the correlation among beams and model the complex beamforming and multipath channel functions. Furthermore, to mitigate interference to other user equipment, we leverage the primal-dual method to design a constrained UCB-type kernelized bandit algorithm. Our theoretical analysis indicates that the proposed algorithm can adaptively adjust the beam in time-varying environments, such that both the cumulative regret of the received signal and constraint violations have sublinear bounds with respect to time. This result is of independent interest for applications such as adaptive pricing and news ranking. In addition, the algorithm assumes the channel is a black-box function and does not require any prior knowledge for dynamic channel modeling, and thus is applicable in a variety of scenarios. We further show that if the information about the channel variation is known, the algorithm will have better theoretical guarantees and performance. Finally, we conduct simulations to highlight the effectiveness of the proposed algorithm.","PeriodicalId":228040,"journal":{"name":"2022 20th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124339098","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}

引用次数: 3

Optimal Congestion-aware Routing and Offloading in Collaborative Edge Computing 协同边缘计算中最优拥塞感知路由和卸载

2022 20th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt) Pub Date : 2022-05-15 DOI: 10.23919/WiOpt56218.2022.9930581

Jinkun Zhang, Yuezhou Liu, E. Yeh

{"title":"Optimal Congestion-aware Routing and Offloading in Collaborative Edge Computing","authors":"Jinkun Zhang, Yuezhou Liu, E. Yeh","doi":"10.23919/WiOpt56218.2022.9930581","DOIUrl":"https://doi.org/10.23919/WiOpt56218.2022.9930581","url":null,"abstract":"Collaborative edge computing (CEC) is an emerging paradigm where heterogeneous edge devices collaborate to fulfill computation tasks, such as model training or video processing, by sharing communication and computation resources. Nevertheless, when considering network congestion, the optimal data/result routing and computation offloading strategy of CEC still remains an open problem. In this paper, we formulate a flow model of partial-offloading and multi-hop routing in CEC network with arbitrarily topology and heterogeneous communication/computation capability. In contrast to most existing works, our model applies to tasks with non-negligible result size, and allows data sources to be distinct from the result destination. We propose a network-wide cost minimization problem with congestion-aware convex cost functions. Such convex cost covers various performance metrics and constraints, such as average queueing delay with limited processor capacity. Although the problem is non-convex, we provide necessary conditions and sufficient conditions for the global-optimal solution, and devise a fully distributed algorithm that converges to the optimum in polynomial time. Our proposed method allows asynchronous individual updating, and is adaptive to changes of network parameters. Numerical evaluation shows that our method significantly outperforms other baseline algorithms in multiple network instances, especially in congested scenarios.","PeriodicalId":228040,"journal":{"name":"2022 20th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132423145","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}

引用次数: 2

Scheduling for Multi-Phase Parallelizable Jobs 多阶段可并行作业的调度

2022 20th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt) Pub Date : 2022-05-01 DOI: 10.23919/WiOpt56218.2022.9930618

R. Vaze

引用次数: 0

Scheduling to Minimize Age of Information with Multiple Sources 调度以最小化多源信息的年龄

2022 20th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt) Pub Date : 2022-04-06 DOI: 10.23919/WiOpt56218.2022.9930540

K. Saurav, R. Vaze

引用次数: 7

Optimization of ARQ Distribution for HARQ Strategies in Delay-Bounded Networks 延迟有界网络中HARQ策略的ARQ分布优化

2022 20th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt) Pub Date : 2022-03-16 DOI: 10.23919/WiOpt56218.2022.9930612

Jaya Goel, J. Harshan

{"title":"Optimization of ARQ Distribution for HARQ Strategies in Delay-Bounded Networks","authors":"Jaya Goel, J. Harshan","doi":"10.23919/WiOpt56218.2022.9930612","DOIUrl":"https://doi.org/10.23919/WiOpt56218.2022.9930612","url":null,"abstract":"Inspired by several delay-bounded mission-critical applications, optimizing the end-to-end reliability of multi-hop networks is an important problem subject to end-to-end delay constraints on the packets. Towards that direction, Automatic Repeat Request (ARQ) based strategies have been recently proposed wherein the problem statement is to distribute a certain total number of ARQs (that capture end-to-end delay) across the nodes such that the end-to-end reliability is optimized. Although such strategies provide a fine control to trade end-to-end delay with end-to-end reliability, their performance degrades in slowly-varying channel conditions. Pointing at this drawback, in this work, we propose a Chase Combing Hybrid ARQ (CC-HARQ) based multi-hop network addressing a similar problem statement of how to distribute a certain total number of ARQs such that the end-to-end reliability is optimized. Towards solving the problem, first, we identify that the objective function of the optimization problem is intractable due to the presence of Marcum-Q functions in it. As a result, we propose an approximation on the objective function and then prove a set of necessary and sufficient conditions on the near-optimal ARQ distribution. Subsequently, we propose a low-complexity algorithm to solve the problem for any network size. We show that CC-HARQ based strategies are particularly appealing in slow-fading channels wherein the existing ARQ strategies fail.","PeriodicalId":228040,"journal":{"name":"2022 20th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134119567","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}

引用次数: 1

A New Design Framework for Heterogeneous Uncoded Storage Elastic Computing 异构非编码存储弹性计算的新设计框架

2022 20th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt) Pub Date : 2021-07-20 DOI: 10.23919/WiOpt56218.2022.9930566

Mingyue Ji, Xiang Zhang, Kai Wan

{"title":"A New Design Framework for Heterogeneous Uncoded Storage Elastic Computing","authors":"Mingyue Ji, Xiang Zhang, Kai Wan","doi":"10.23919/WiOpt56218.2022.9930566","DOIUrl":"https://doi.org/10.23919/WiOpt56218.2022.9930566","url":null,"abstract":"Elasticity is one important feature in modern cloud computing systems and can result in computation failure or significantly increase computing time. Such elasticity means that virtual machines over the cloud can be preempted under a short notice (e.g., hours or minutes) if a high-priority job appears; on the other hand, new virtual machines may become available over time to compensate the computing resources. Coded Storage Elastic Computing (CSEC) introduced by Yang et al. in 2018 is an effective and efficient approach to overcome the elasticity and it costs relatively less storage and computation load. However, one of the limitations of the CSEC is that it may only be applied to certain types of computations (e.g., linear) and may be challenging to be applied to more involved computations because the coded data storage and approximation are often needed. Hence, it may be preferred to use uncoded storage by directly copying data into the virtual machines. In addition, based on our own measurement, virtual machines on Amazon EC2 clusters often have heterogeneous computation speed even if they have exactly the same configurations (e.g., CPU, RAM, I/O cost). In this paper, we introduce a new optimization framework on Uncoded Storage Elastic Computing (USEC) systems with heterogeneous computing speed to minimize the overall computation time. Under this framework, we propose optimal solutions of USEC systems with or without straggler tolerance using different storage placements. Our proposed algorithms are evaluated using power iteration applications on Amazon EC2.","PeriodicalId":228040,"journal":{"name":"2022 20th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129176771","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}

引用次数: 2