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检索条件"主题词=Distributed algorithm"

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distributed Coordination Maximization over Networks: A Stochastic Approximation Approach 16

Distributed Coordination Maximization over Networks: A Stoch...

引用

17th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc)

作者： Jang, Hyeryung Yun, Se-Young Shin, Jinwoo Yi, Yung Korea Adv Inst Sci & Technol Dept Elect Engn Daejeon South Korea Los Alamos Natl Lab Los Alamos NM USA

ISBN: (纸本)9781450341844

In various online/offine networked environments, it is very popular that the system can benefit from coordinating actions of two interacting nodes, but incur some cost due to such coordination. Examples include a wireless sensor networks with duty cycling, where a sensor node consumes a certain amount of energy when it is awake, but a coordinated operation of sensors enables some meaningful tasks, e.g., sensed data forwarding, collaborative sensing of a phenomenon, or efficient decision of further sensing actions. In this paper, we formulate an optimization problem that captures the amount of coordination gain at the cost of node activation over networks. This problem is challenging since the target utility is a function of the long-term time portion of the inter-coupled activations of two adjacent nodes, and thus a standard Lagrange duality theory is hard to apply to obtain a distributed decomposition as in the standard NUM (Network Utility Maximization). We propose a fully-distributed algorithm that requires only one-hop message passing. Our approach is inspired by a control of Ising model in statistical physics, and the proposed algorithm is motivated by a stochastic approximation method that runs a Markov chain incompletely over time, but provably guarantees its convergence to the optimal solution. We validate our theoretical findings on convergence and optimality through extensive simulations under various scenarios.

关键词： CoordinationMaximization Stochastic Approximation distributed algorithm

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Energy-Aware Competitive Power distributed Allocation in Multi -cell Cellular Networks 4

Energy-Aware Competitive Power Distributed Allocation in Mul...

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4th IEEE International Conference on Progress in Informatics and Computing (IEEE PIC)

作者： Li, Ruisheng Ma, Wei Nanjing Univ Posts & Telecommun Nanjing Peoples R China

ISBN: (纸本)9781509034840

In this paper, we develop a distributed power allocation algorithm for maximizing the energy efficiency in the downlink of orthogonal frequency division multiple -access (OFDMA) based multi -cell cellular networks. Each small -cell allocates its available transmit power over the set of assigned sub -carriers to maximize its individual utility (defined as the small -cell's throughput per watt of transmit power) subject to a target rate requirement. In this framework, the relevant solution concept is that of Debreu equilibrium, a generalization of the concept of Nash equilibrium. Then we develop an non -cooperative game for energy efficient power control, and prove the existence of Debreu equilibrium. We also propose an algorithm based on an iterative water-filling best response process to achieve the equilibrium. Numerical simulations arc then performed assess the convergence of the proposed algorithm and the performance of its end -state as a function of the system parameters.

关键词： distributed algorithm downlink. power control energy efficiency multi-cell cellular networks

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Microgrid Cooperative distributed Energy Scheduling (CoDES) Considering Battery Degradation Cost 25

Microgrid Cooperative Distributed Energy Scheduling (CoDES) ...

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25th IEEE International Symposium on Industrial Electronics (ISIE)

作者： Zhang, Yuan Chow, Mo-Yuen North Carolina State Univ Dept Elect & Comp Engn Raleigh NC 27695 USA

ISBN: (纸本)9781509008735

Obtaining an optimal charging and discharging schedule of battery energy storage devices in a microgrid is essential to the economic and reliable operation of the system. The depth of discharge (DoD) is a key variable that affects the cycle life of a battery. In this paper, an energy scheduling problem is formulated for a microgrid considering battery degradation cost under different DoD scenarios. The formulated scheduling problem is solved by using the cooperative distributed energy scheduling (CoDES) algorithm in a distributed way. The operation of the CoDES algorithm is demonstrated and the economic benefit of using battery energy storage devices in a microgrid is analyzed under different DoD scenarios.

关键词： Battery degradation distributed algorithm energy scheduling economic analysis microgrid

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Experiments with Self-stabilizing distributed Data Fusion 35

Experiments with Self-stabilizing Distributed Data Fusion

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35th IEEE International Symposium on Reliable distributed Systems Workshops (SRDSW)

作者： Ducourthial, B. Cherfaoui, V. Univ Technol Compiegne Sorbonne Univ CNRS UMRUTC Heudiasyc 7253CS 60 319 F-60203 Compiegne France

ISBN: (纸本)9781509035137

The Theory of Belief Functions is a formal framework for reasoning with uncertainty that is well suited for representing unreliable information and weak states of knowledge. In a previous work, a distributed algorithm for computing data fusion on-the-fly has been introduced, avoiding gathering the data on a single node before computation. In this paper, we present an experimental study of its properties. This algorithm is self-stabilizing and runs on unreliable message passing networks. It converges in finite time whatever is the initialization of the system and for any unknown topology. First we explain the algorithm implementation on an unreliable message passing environment and we implement a simple use-case. Then, by experimenting with this distributed application on a realistic network emulator, we show its interest for enforcing local confidence using close nodes, saving bandwidth and warning dangers. Moreover, we focus on the interesting connections between the data fusion operator and the self-stabilizing properties and we highlight the importance of the discounting.

关键词： Airplug software distribution data fusion discounting distributed algorithm experimentation r-operator self-stabilization

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A distributed Frequent Itemset Mining algorithm Based on Spark 19

A Distributed Frequent Itemset Mining Algorithm Based on Spa...

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IEEE 19th International Conference on Computer Supported Cooperative Work in Design (CSCWD)

作者： Gui, Feng Ma, Yunlong Zhang, Feng Liu, Min Li, Fei Shen, Weiming Bai, Hua Tongji Univ Sch Elect & Infonnat Engn Shanghai 201804 Peoples R China

ISBN: (纸本)9781479920020

Frequent itemset mining is an important step of association rules mining. Traditional frequent itemset mining algorithms have certain limitations. For example Apriori algorithm has to scan the input data repeatedly, which leads to high I/O load and low performance, and the FP-Growth algorithm is limited by the capacity of computer's inner stores because it needs to build a FP-tree and mine frequent itemset on the basis of the FP-tree in memory. With the coming of the Big Data era, these limitations are becoming more prominent when confronted with mining large-scale data. In this paper, DPBM, a distributed matrix-based pruning algorithm based on Spark, is proposed to deal with frequent itemset mining. DPBM can greatly reduce the amount of candidate itemset by introducing a novel pruning technique for matrix-based frequent itemset minng algorithm, an improved Apriori algorithm which only needs to scan the input data once. In addition, each computer node reduces greatly the memory usage by implementing DPBM under a latest distributed environment-Spark, which is a lightning-fast distributed computing. The experimental results show that DPBM have better performance than MapReduce-based algorithms for frequent item set mining in terms of speed and scalability.

关键词： frequent itemset mining distributed algorithm matrix-pruning Spark MapReduce

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Near-Optimal Scheduling of distributed algorithms 15

Near-Optimal Scheduling of Distributed Algorithms

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34th Annual ACM Symposium on Principles of distributed Computing (PODC)

作者： Ghaffari, Mohsen MIT Cambridge MA 02139 USA

ISBN: (纸本)9781450336178

This paper studies the question of how to run many distributed algorithms, solving independent problems, together as fast as possible. Suppose that we want to run distributed algorithms A(1);A(2) ...;A(k) in the CONGEST model, each taking at most dilation rounds, and where for each network edge, at most congestion messages need to go through it, in total over all these algorithms. A celebrated work of Leighton, Maggs, and Rao [22] shows that in the special case where each of these algorithms is simply a packet routing |that is, sending a message from a source to a destination along a given path|there is an O(congestion + dilation) round schedule. Note that this bound is trivially optimal. Generalizing the framework of LMR [22], we study scheduling general distributed algorithms and present two results: (a) an existential schedule-length lower bound of Omega(congestion +dilation . log n/log log n) rounds, (b) a distributed algorithm that produces a near-optimal O (congestion+ *** n) round schedule, after O(dilation vertical bar log(2) n) rounds of pre-computation. A key challenge in the latter result is to solve the problem with only private randomness, as globally-shared randomness simplifies it significantly. The technique we use for this problem is in fact more general, and it can be used to remove the assumption of having shared randomness from a broad range of distributed algorithms, at the cost of a slow down factor of O(log(2) n).

关键词： distributed algorithm Scheduling Congestion Dilation Packet Routing Shared Randomness

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PTE: Enumerating Trillion Triangles On distributed Systems 16

PTE: Enumerating Trillion Triangles On Distributed Systems

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22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD)

作者： Park, Ha-Myung Myaeng, Sung-Hyon Kang, U. Korea Adv Inst Sci & Technol Daejeon South Korea Seoul Natl Univ Seoul South Korea

ISBN: (纸本)9781450342322

How can we enumerate triangles from an enormous graph with billions of vertices and edges? Triangle enumeration is an important task for graph data analysis with many applications including identifying suspicious users in social networks, detecting web spams, finding communities, etc. However, recent networks are so large that most of the previous algorithms fail to process them. Recently, several MapReduce algorithms have been proposed to address such large networks;however, they suffer from the massive shuffled data resulting in a very long processing time. In this paper, we propose PTE (Pre-partitioned Triangle Enumeration), a new distributed algorithm for enumerating triangles in enormous graphs by resolving the structural inefficiency of the previous MapReduce algorithms. PTE enumerates trillions of triangles in a billion scale graph by decreasing three factors: the amount of shuffled data, total work, and network read. Experimental results show that PTE provides up to 47x faster performance than recent distributed algorithms on real world graphs, and succeeds in enumerating more than 3 trillion triangles on the ClueWeb12 graph with 6.3 billion vertices and 72 billion edges, which any previous triangle computation algorithm fail to process.

关键词： triangle enumeration big data graph algorithm scalable algorithm distributed algorithm network analysis

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distributed Path Planning for Collective Transport Using Homogeneous Multi-robot Systems 1

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12th International Symposium on distributed Autonomous Robotic Systems (DARS)

作者： Habibi, Golnaz Xie, William Jellins, Mathew McLurkin, James Rice Univ Dept Comp Sci Houston TX USA Univ Texas Austin Dept Comp Sci Austin TX 78712 USA Purdue Univ W Lafayette IN 47907 USA

ISBN: (数字)9784431558798

ISBN: (纸本)9784431558798;9784431558774

We present a scalable distributed path planning algorithm for transporting a large object through an unknown environment using a group of homogeneous robots. The robots are randomly scattered across the terrain and collectively sample the obstacles in the environment in a distributed fashion. Given this sampling and the dimensions of the bounding box of the object, the robots construct a distributed configuration space. We then use a variant of the distributed Bellman-Ford algorithm to construct a shortest-path tree using a custom cost function from the goal location to all other connected robots. The cost function encompasses the work required to rotate and translate the object in addition to an extra control penalty to navigate close to obstacles. Our approach sets up a framework that allows the user to balance the trade-off between the safety of the path and the mechanical work required to move the object. The path is optimal given the sampling of the robots and user input parameters. We implemented our algorithm in both simulated and real-world environments. Our approach is robust to the size and shape of the object and adapts to dynamic environments.

关键词： Path planning distributed algorithm distributed bellman-ford algorithm Multi-robot system Collective transport

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distributed Matching and Resource Sharing for Space Division Multiplexing Assisted by D2D Cooperation

Distributed Matching and Resource Sharing for Space Division...

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7th International Conference on Information and Communication Technology Convergence (ICTC) - Towards Smarter Hyper-Connected World

作者： Jeong, Yeonjin Yoon, Jooheum Kim, Yun Hee Lee, Sang Hyun Kyung Hee Univ Dept Elect & Radio Engn Yongin 17104 South Korea Pusan Natl Univ Dept Elect Engn Busan 46241 South Korea

ISBN: (纸本)9781509013258

This paper considers the downlink of a cellular network with an as etric antenna confi. ation, where space division multiplexing with the transmit channel state information (CSI) is assisted by device-to-device (D2D) receive cooperation. For the network, a distributed algorithm following a message passing framework is applied for device matching and resource sharing to maximize the system throughput without sacrificing each device's rate and without reporting the D2D link qualities to the base station. We investigate the effect of the transmit CSI and D2D cooperation on the network operating with the distributed algorithm.

关键词： D2D cooperation distributed algorithm Space division multiplexing Transmit channel state information

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A distributed Polygon Retrieval algorithm using MapReduce 1

A Distributed Polygon Retrieval Algorithm using MapReduce

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ISPRS International Workshop on Spatiotemporal Computing

作者： Guo, Q. Palanisamy, B. Karimi, H. A. Univ Pittsburgh Sch Informat Sci Geoinformat Lab Pittsburgh PA 15260 USA

The burst of large-scale spatial terrain data due to the proliferation of data acquisition devices like 3D laser scanners poses challenges to spatial data analysis and computation. Among many spatial analyses and computations, polygon retrieval is a fundamental operation which is often performed under real-time constraints. However, existing sequential algorithms fail to meet this demand for larger sizes of terrain data. Motivated by the MapReduce programming model, a well-adopted large-scale parallel data processing technique, we present a MapReduce-based polygon retrieval algorithm designed with the objective of reducing the IO and CPU loads of spatial data processing. By indexing the data based on a quad-tree approach, a significant amount of unneeded data is filtered in the filtering stage and it reduces the IO overhead. The indexed data also facilitates querying the relationship between the terrain data and query area in shorter time. The results of the experiments performed in our Hadoop cluster demonstrate that our algorithm performs significantly better than the existing distributed algorithms.

关键词： Hadoop Polygon Retrieval distributed algorithm GIS

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