2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton)最新文献_第7页

Pricing Multi-period Dispatch Under Uncertainty 不确定性下的多期调度定价

2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton) Pub Date : 2018-10-01 DOI: 10.1109/ALLERTON.2018.8635641

Ye Guo, L. Tong

{"title":"Pricing Multi-period Dispatch Under Uncertainty","authors":"Ye Guo, L. Tong","doi":"10.1109/ALLERTON.2018.8635641","DOIUrl":"https://doi.org/10.1109/ALLERTON.2018.8635641","url":null,"abstract":"Price formation in the context of multi-period dispatch of electricity under operational uncertainty is considered. General and partial equilibrium conditions for the locational marginal price (LMP) is examined. It is shown that, when the market participants are provided with limited forward prices, no uniform price exists for the partial equilibrium model in general. As a consequence, market participants have incentives to deviate from the optimal economic dispatch. Taking explicit accounts for ramping constraints, an extension of LMP, referred to as temporal locational marginal pricing (TLMP), is proposed that reflects both generation and opportunity costs of generators. Although discriminative, TLMP and the optimal economic dispatch satisfy both the general and partial equilibrium conditions for which, given the TLMP, dispatch schedules generated individually by profit-maximizing participants match the solution of the centralized social welfare maximization. TLMP is then extended for ex post pricing. The resulting incremental TLMP (iTLMP) is shown to provide revenue adequacy for the system operator and price supports for participants who offer sufficient ramping capability. Numerical simulations are used to demonstrate the performance of LMP, flexible ramping product (FRP), TLMP, and iTLMP.","PeriodicalId":299280,"journal":{"name":"2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122467417","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

Data Encoding for Byzantine-Resilient Distributed Gradient Descent 拜占庭弹性分布式梯度下降的数据编码

2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton) Pub Date : 2018-10-01 DOI: 10.1109/ALLERTON.2018.8636017

Deepesh Data, Linqi Song, S. Diggavi

{"title":"Data Encoding for Byzantine-Resilient Distributed Gradient Descent","authors":"Deepesh Data, Linqi Song, S. Diggavi","doi":"10.1109/ALLERTON.2018.8636017","DOIUrl":"https://doi.org/10.1109/ALLERTON.2018.8636017","url":null,"abstract":"We consider distributed gradient computation, where both data and computation are distributed among m worker machines, t of which can be Byzantine adversaries, and a designated (master) node computes the model/parameter vector, iteratively using gradient descent (GD). The Byzantine adversaries can (collaboratively) deviate arbitrarily from their gradient computation. To solve this, we propose a method based on data encoding and (real) error correction to combat the adversarial behavior. We can tolerate up to$tleq displaystyle lfloorfrac{m-1}{2}rfloor$ corrupt worker nodes, which is information-theoretically optimal. Our method does not assume any probability distribution on the data. We develop a sparse encoding scheme which enables computationally efficient data encoding. We demonstrate a trade-off between the number of adversaries tolerated and the resource requirement (storage and computational complexity). As an example, our scheme incurs a constant overhead (storage and computational complexity) over that required by the distributed GD algorithm, without adversaries, for$tleq displaystyle frac{m}{3}$.","PeriodicalId":299280,"journal":{"name":"2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114173718","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: 20

Stabilizing Phase-balanced or Phase-synchronized Trajectories of Van der Pol Oscillators in Uniform Electrical Networks 均匀电网络中稳定相平衡或相同步的Van der Pol振荡轨迹

2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton) Pub Date : 2018-10-01 DOI: 10.1109/ALLERTON.2018.8636079

Mohit Sinha, F. Dörfler, Brian B. Johnson, S. Dhople

引用次数: 6

Information Bottleneck Methods for Distributed Learning 分布式学习的信息瓶颈方法

2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton) Pub Date : 2018-10-01 DOI: 10.1109/ALLERTON.2018.8635884

Parinaz Farajiparvar, Ahmad Beirami, M. Nokleby

引用次数: 7

Decomposition Methods for Distributed Quadratic Programming with Application to Distributed Model Predictive Control 分布式二次规划的分解方法及其在分布式模型预测控制中的应用

2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton) Pub Date : 2018-10-01 DOI: 10.1109/ALLERTON.2018.8636067

Giuliano Costantini, Ramin Rostami, D. Görges

{"title":"Decomposition Methods for Distributed Quadratic Programming with Application to Distributed Model Predictive Control","authors":"Giuliano Costantini, Ramin Rostami, D. Görges","doi":"10.1109/ALLERTON.2018.8636067","DOIUrl":"https://doi.org/10.1109/ALLERTON.2018.8636067","url":null,"abstract":"This paper studies different decomposition techniques for coupled quadratic programming problems arising in Distributed Model Predictive Control (DMPC). Here the resulting global problem is not directly separable due to the dynamical coupling between the agents in the networked system. In the last decade, the Alternating Direction Method of Multipliers (ADMM) has been generally adopted as the standard optimization algorithm in the DMPC literature due to its fast convergence and robustness with respect to other algorithms as the dual decomposition method. The goal of this paper is to introduce a novel decomposition technique which with respect to ADMM can reduce the number of iterations required for convergence. A benchmark model is used at the end of the paper to numerically show these results under different coupling factors and network topologies. The proposed method is closely related to the Diagonal Quadratic Approximation (DQA) and its successor, the Accelerated Distributed Augmented Lagrangian (ADAL) method. In these algorithms the coupling constraint is relaxed by introducing an augmented Lagrangian and the resulting non-separable quadratic penalty term is approximated through a sequence of separable quadratic functions. This paper proposes a different separable approximation for the penalty term which leads to several advantages as a flexible communication scheme and an overall better convergence when the coupling is not excessively high.","PeriodicalId":299280,"journal":{"name":"2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127035712","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

The Geometry of Real Solutions to the Power Flow Equations 功率流方程实解的几何

2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton) Pub Date : 2018-10-01 DOI: 10.1109/ALLERTON.2018.8635895

J. Lindberg, Alisha Zachariah, N. Boston, B. Lesieutre

引用次数: 6

Scheduling and Estimation Strategies in a Sequential Networked Estimation Problem 序列网络估计问题中的调度与估计策略

2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton) Pub Date : 2018-10-01 DOI: 10.1109/ALLERTON.2018.8636085

Mukul Gagrani, M. Vasconcelos, A. Nayyar

引用次数: 4

Masterless Coded Computing: A Fully-Distributed Coded FFT Algorithm 无主编码计算:全分布式编码FFT算法

2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton) Pub Date : 2018-10-01 DOI: 10.1109/ALLERTON.2018.8636047

Haewon Jeong, Tze Meng Low, P. Grover

引用次数: 18

Coded Caching with Low Per-Request Complexity 低每请求复杂度的编码缓存

2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton) Pub Date : 2018-10-01 DOI: 10.1109/ALLERTON.2018.8636083

Barak Farbman, Yuval Cassuto, A. Sprintson

{"title":"Coded Caching with Low Per-Request Complexity","authors":"Barak Farbman, Yuval Cassuto, A. Sprintson","doi":"10.1109/ALLERTON.2018.8636083","DOIUrl":"https://doi.org/10.1109/ALLERTON.2018.8636083","url":null,"abstract":"The massive growth in high-rate streams (mostly video) over the Internet warranted the establishment of content distribution networks (CDNs), which bring the content closer to the consumer and hence reduce delays and congestion in the network. In this paper we address the setup of multiple Internet service providers (ISPs) sharing a federated cache. When multiple ISPs with different demands share a cache, storage cost can be reduced when the cache is coded. We address the problem of constructing the coded cache to fulfill all demands from all ISPs, where the constructions simultaneously optimize the cache's three main operational costs: storage, communication, and computation (to encode and decode requested objects). When only the storage needs to be minimized, the code-design problem can be formulated as an index coding problem, and solved by known tools in network coding. However, in practical setups the cache needs to respond efficiently (in communication and computation) to individual content-object requests, which renders known index/network-coding solutions non-applicable and non-scalable. We first show constructively that when the number of ISPs is less than or equal to 4, there is an efficient algorithm that achieves optimal storage with only bit-wise XOR operations, and with guaranteed low computation cost for serving requests. For larger numbers of ISPs, we present randomized algorithms that achieve optimal storage with XOR-only coding and low computation complexity per requested objects.","PeriodicalId":299280,"journal":{"name":"2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton)","volume":"314 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124462372","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

On Optimal Proactive Caching with Improving Predictions over Time 随着时间推移改进预测的最优主动缓存

2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton) Pub Date : 2018-10-01 DOI: 10.1109/ALLERTON.2018.8635960

John Tadrous, A. Eryilmaz

{"title":"On Optimal Proactive Caching with Improving Predictions over Time","authors":"John Tadrous, A. Eryilmaz","doi":"10.1109/ALLERTON.2018.8635960","DOIUrl":"https://doi.org/10.1109/ALLERTON.2018.8635960","url":null,"abstract":"This paper considers optimal proactive caching when future demand predictions improve over time as expected to happen in most prediction systems. In particular, our model captures the correlated demand pattern that is exhibited by end users as their current activity reveals progressively more information about their future demand. It is observed in previous work that, in a network where service costs grow superlinearly with the traffic load and static predictions, proactive caching can be harnessed to flatten the load over time and minimize the cost. Nevertheless, with time varying prediction quality, a tradeoff between load flattening and accurate proactive service emerges.In this work, we formulate and investigate the optimal proactive caching design under time-varying predictions. Our objective is to minimize the time average expected service cost given a finite proactive service window. We establish a lower bound on the minimal achievable cost by any proactive caching policy, then we develop a low complexity caching policy that strikes a balance between load flattening and accurate caching. We prove that our proposed policy is asymptotically optimal as the proactive service window grows. In addition, we characterize other non-asymptotic cases where the proposed policy remains optimal. We validate our analytical results with numerical simulation and highlight relevant insights.","PeriodicalId":299280,"journal":{"name":"2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton)","volume":"21 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120993985","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: 0