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Distributed Data Placement via Graph Partitioning  [PDF]
Lukasz Golab,Marios Hadjieleftheriou,Howard Karloff,Barna Saha
Computer Science , 2013,
Abstract: With the widespread use of shared-nothing clusters of servers, there has been a proliferation of distributed object stores that offer high availability, reliability and enhanced performance for MapReduce-style workloads. However, relational workloads cannot always be evaluated efficiently using MapReduce without extensive data migrations, which cause network congestion and reduced query throughput. We study the problem of computing data placement strategies that minimize the data communication costs incurred by typical relational query workloads in a distributed setting. Our main contribution is a reduction of the data placement problem to the well-studied problem of {\sc Graph Partitioning}, which is NP-Hard but for which efficient approximation algorithms exist. The novelty and significance of this result lie in representing the communication cost exactly and using standard graphs instead of hypergraphs, which were used in prior work on data placement that optimized for different objectives (not communication cost). We study several practical extensions of the problem: with load balancing, with replication, with materialized views, and with complex query plans consisting of sequences of intermediate operations that may be computed on different servers. We provide integer linear programs (IPs) that may be used with any IP solver to find an optimal data placement. For the no-replication case, we use publicly available graph partitioning libraries (e.g., METIS) to efficiently compute nearly-optimal solutions. For the versions with replication, we introduce two heuristics that utilize the {\sc Graph Partitioning} solution of the no-replication case. Using the TPC-DS workload, it may take an IP solver weeks to compute an optimal data placement, whereas our reduction produces nearly-optimal solutions in seconds.
The Waterfilling Game-Theoretical Framework for Distributed Wireless Network Information Flow  [cached]
He Gaoning,Cottatellucci Laura,Debbah Mérouane
EURASIP Journal on Wireless Communications and Networking , 2010,
Abstract: We present a general game-theoretical framework for power allocation in the downlink of distributed wireless small-cell networks, where multiple access points (APs) or small base stations send independent coded network information to multiple mobile terminals (MTs) through orthogonal channels. In such a game-theoretical study, a central question is whether a Nash equilibrium (NE) exists, and if so, whether the network operates efficiently at the NE. For independent continuous fading channels, we prove that the probability of a unique NE existing in the game is equal to 1. Furthermore, we show that this power allocation problem can be studied as a potential game, and hence efficiently solved. In order to reach the NE, we propose a distributed waterfilling-based algorithm requiring very limited feedback. The convergence behavior of the proposed algorithm is discussed. Finally, numerical results are provided to investigate the price of anarchy or inefficiency of the NE.
Dynamics at the Boundary of Game Theory and Distributed Computing  [PDF]
Aaron D. Jaggard,Neil Lutz,Michael Schapira,Rebecca N. Wright
Computer Science , 2015,
Abstract: We use ideas from distributed computing and game theory to study dynamic and decentralized environments in which computational nodes, or decision makers, interact strategically and with limited information. In such environments, which arise in many real-world settings, the participants act as both economic and computational entities. We exhibit a general non-convergence result for a broad class of dynamics in asynchronous settings. We consider implications of our result across a wide variety of interesting and timely applications: circuit design, social networks, Internet routing, and congestion control. We also study the computational and communication complexity of testing the convergence of asynchronous dynamics, as well as the effects of limited asynchrony. For uncoupled game dynamics, in which preferences are private inputs, we give new bounds on the recall necessary for self stabilization to an equilibrium. Our work opens a new avenue for research at the intersection of distributed computing and game theory.
Distributed Spectrum Access for Cognitive Small Cell Networks: A Robust Graphical Game Approach  [PDF]
Yuhua Xu,Yuli Zhang,Qihui Wu,Liang Shen,Jinlong Wang
Computer Science , 2015,
Abstract: This letter investigates the problem of distributed spectrum access for cognitive small cell networks. Compared with existing work, two inherent features are considered: i) the transmission of a cognitive small cell base station only interferes with its neighbors due to the low power, i.e., the interference is local, and ii) the channel state is time-varying due to fading. We formulate the problem as a robust graphical game, and prove that it is an ordinal potential game which has at least one pure strategy Nash equilibrium (NE). Also, the lower throughput bound of NE solutions is analytically obtained. To cope with the dynamic and incomplete information constraints, we propose a distribute spectrum access algorithm to converge to some stable results. Simulation results validate the effectiveness of the proposed game-theoretic distributed learning solution in time-varying spectrum environment.
Distributed Generation Placement Design and Contingency Analysis with Parallel Computing Technology  [cached]
Wenzhong Gao,Xi Chen
Journal of Computers , 2009, DOI: 10.4304/jcp.4.4.347-354
Abstract: Distributed Generation (DG) is a promising solution to many power system problems such as voltage regulation, power loss, etc. The location in the power system for DG placement is found to be very important. The additional DG placement strategy is also found to depend largely on the total capacity and location of DG already installed on the system. In this paper, a design strategy based on a proposed “critical bus tracking” method for Proton Exchange Membrane Fuel Cell (PEMFC) DG is tested on a modified IEEE 14 bus test case. Matlab Distributed Computing System (MDCS) is applied for a reduced computation time. Program for contingency analysis is also implemented in MDCS to test the design strategy. Tests are conducted in the modified IEEE 14 bus and 300 bus test cases to study the efficiency of the parallel algorithm for DG placement design and contingency analysis.
Spectrum allocation algorithm based on game theory in cognitive radio
认知无线电中基于博弈论的频谱分配算法*

TENG Zhi-jun,HAN Xue,YANG Xu,
滕志军
,韩雪,杨旭

计算机应用研究 , 2011,
Abstract: This paper proposed game theory for dynamic spectrum allocation in cognitive radio network. It proposed the spectrum allocation model in cognitive radio based on game theory and proposed a distributed spectrum assignment algorithms based on potential game
A New Placement Scheme of Distributed Generation in Power Grid  [PDF]
Zhipeng Jiang, Tiande Guo, Wei Pei
Energy and Power Engineering (EPE) , 2013, DOI: 10.4236/epe.2013.54B143
Abstract:

Smart grid gets more and more popular today. Distributed generation is one of the key technologies, and especially, the integration problem of the distributed generation is an important issue. Especially, the location and capacity of the distributed generation play an important role for the performance of the distribution network. In this paper, an optimization model to minimize the loss cost of the unsatisfied demand is given. This model is based on a reliability computing method which avoiding power flow calculation in a previous work. Then the model is used on the IEEE-123 nodes experiment network and a result of five distributed generation placement is got.

A Potential Game Approach for Information-Maximizing Cooperative Planning of Sensor Networks  [PDF]
Han-Lim Choi,Su-Jin Lee
Computer Science , 2014,
Abstract: This paper presents a potential game approach for distributed cooperative selection of informative sensors, when the goal is to maximize the mutual information between the measurement variables and the quantities of interest. It is proved that a local utility function defined by the conditional mutual information of an agent conditioned on the other agents' sensing decisions leads to a potential game with the global potential being the original mutual information of the cooperative planning problem. The joint strategy fictitious play method is then applied to obtain a distributed solution that provably converges to a pure strategy Nash equilibrium. Two numerical examples on simplified weather forecasting and range-only target tracking verify convergence and performance characteristics of the proposed game-theoretic approach.
Distributed Generation unit and Capacitor Placement for Multi-objective Optimization  [cached]
A. Sadighmanesh,K. Zare,M. Sabahi
International Journal of Electrical and Computer Engineering , 2012, DOI: 10.11591/ijece.v2i5.1590
Abstract: Distributed Generation (DG) and capacitor placement and the tap setting of ULTC transformers can be used individually to improve the voltage profile and loss reduction. In this article, the Genetic Algorithm (GA) is applied to optimize the multi-objective function for DG and capacitor placement with tap setting of ULTC. The objective function consists the loss reduction, voltage improvement and increasing the available transfer capability (ATC) of the distribution network. To show the effectiveness of the proposed method, it is applied to IEEE 41 bus radial distribution network. The results show that this method has a better effect on improving the objective functions.
Distributed Generation unit and Capacitor Placement for Loss, Voltage profile and ATC Optimization  [cached]
Abdolreza Sadighmanesh,Kazem Zare,Mehran Sabahi
International Journal of Electrical and Computer Engineering , 2012, DOI: 10.11591/ijece.v2i6.741
Abstract: Distributed Generation (DG) and capacitors placement and also the tap setting of ULTC transformers can be used individually to improve the voltage profile and loss reduction. In this article the Genetic Algorithm (GA) is applied to optimize the multi-objective function for of DG and capacitor placement with tap setting of ULTC. The objective function consists the loss reduction, voltage improvement and increasing the available transfer capability (ATC) of the distribution network. To show the effectiveness of the proposed method, it is applied to IEEE 41 bus radial distribution network. The results show that this method has a better effect on improving the objective functions.
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