We propose a distributed parallel algorithm for inferring the hierarchical groups present in a large-scale text corpus. The algorithm is designed to deal with corpuses that typically do not fit into the main memory of...
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We propose a distributed parallel algorithm for inferring the hierarchical groups present in a large-scale text corpus. The algorithm is designed to deal with corpuses that typically do not fit into the main memory of a workstation computer. The key contribution of this paper lies in its proposal and verification of a parallel distributed algorithm that exploits the advantages of two complementary techniques based on (i) localized modularity optimization and (ii) spectral clustering. Based on our experimental observations, these are complementary in the sense that the former excels at finding coarse groups in a large-scale network, while the latter demands a heavy memory footprint but is effective in inferring tightly knit fine-grained groups. Empirical evaluation of the distributed implementation scheme shows that the algorithm exhibits a significant speed-up when compared to existing algorithms like Louvain and, at the same time, produces better quality clusters than either Louvain or spectral clustering algorithms in terms of the F-score and Rand index.
Recent advances in spacecraft technology allow a large number of smaller and cheaper satellites to fulfill useful Earth monitoring roles. An emerging challenge is to coordinate those satellites to monitor the Earth...
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Recent advances in spacecraft technology allow a large number of smaller and cheaper satellites to fulfill useful Earth monitoring roles. An emerging challenge is to coordinate those satellites to monitor the Earth's surface and atmosphere. In this paper, we study the satellite assignment problem for a large constellation of Earth observing satellites, where a set of satellites assign themselves to observe a set of locations. The objective is to maximize a global utility function that is associated with the assignment profile. Due to the communication constraints of the space system, we develop a distributed assignment algorithm where each satellite makes its choice based on local information and local communication. We show that the efficiency ratio of the distributed solution to the optimal one is lower bounded by 1/2. Moreover, this bound is proven to be tight in the sense that there exist scenarios where the bound 1/2 is approached as close as possible.
Aiming at the problem of the dynamic hydraulic balance regulation of chilled water pipe network in central air-conditioning system, a distributed iterative optimization algorithm is proposed based on the novel distrib...
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Aiming at the problem of the dynamic hydraulic balance regulation of chilled water pipe network in central air-conditioning system, a distributed iterative optimization algorithm is proposed based on the novel distributed control architecture and the alternating direction method of multipliers (ADMM) with regular term. Firstly, the total flow and the minimum water pressure difference between supply and return are calculated according to the flow demand of each air handling unit. Furthermore, based on the ADMM with regular term, the optimal operation of parallel pumps is accomplished. Finally, the dynamic hydraulic balance of chilled water pipe network is achieved with the minimum energy consumption, and the on-demand flow distribution is realized. After that, a central air-conditioning system is taken as an example to verify the performance of the proposed algorithm. Results show that the proposed algorithm is a distributed optimization algorithm with high precision, high stability and high energy saving. Compared with one strategy that is not optimized, the operation strategy optimized by the proposed algorithm can save energy about 28.54% while realizing the dynamic hydraulic balance of the pipe network. (c) 2021 Elsevier Ltd. All rights reserved.
To improve the energy efficiency and load-balance in large-scale multi-agent systems, a large-scale distributed cluster algorithm is proposed. At first, a parameter describing the spatial distribution of agents is des...
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To improve the energy efficiency and load-balance in large-scale multi-agent systems, a large-scale distributed cluster algorithm is proposed. At first, a parameter describing the spatial distribution of agents is designed to assess the information spreading capability of an agent. Besides, a competition resolution mechanism is proposed to tackle the competition problem in large-scale multiagent systems. Thus, the proposed algorithm can balance the load, adjust the system network locally and dynamically, reduce system energy consumption. Finally, simulations are presented to demonstrate the superiority of the proposed algorithm.
This paper proposes a decentralized algorithm to organize an ad hoc sensor network into clusters by using Fuzzy Logic. Each sensor uses a Fuzzy decision making process to find the best Cluster Head. Simulation shows t...
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This paper proposes a decentralized algorithm to organize an ad hoc sensor network into clusters by using Fuzzy Logic. Each sensor uses a Fuzzy decision making process to find the best Cluster Head. Simulation shows that this protocol is able to dynamically adapt to network mobility and also shows that with fuzzy logic we have stable clusters and so a cluster head have greater lifetime. Therefore respect to mobility, we have the minimum message exchange and so minimum energy consumption.
Node localization becomes an exciting research area for recently large emergence of ZigBee based wireless applications,where received signal strength indication is adopted as a coarse but simple method on range measur...
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Node localization becomes an exciting research area for recently large emergence of ZigBee based wireless applications,where received signal strength indication is adopted as a coarse but simple method on range measurement. Compared with the centralized approach,distributed algorithm that nodes locally calculate their own position coordinates can significantly reduce location-related network traffic;however,this is an intensive *** commercial digital- hardware-block based method used in CC2431,we propose a novel distributed algorithm that can be implemented based on common 8-bit *** this algorithm,instead of 'log-normal','piecewise linear' path loss model was established, which let only linear operation when estimating range from ***,min-max method,other than maximum likelihood estimation method,was used to simplify coordinate ***,ZigBee compatible sensor node modules were developed to carry out the contrast experiments,and results demonstrate the new method has close or even better precision compared with basic algorithm,but with lower cost.
The distributed Stochastic algorithm (DSA) is a distributed hill-climbing technique for solving large distributed Constraint Optimization Problems (DCOPs) such as distributed scheduling, resource allocation, and distr...
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ISBN:
(纸本)9780982657119
The distributed Stochastic algorithm (DSA) is a distributed hill-climbing technique for solving large distributed Constraint Optimization Problems (DCOPs) such as distributed scheduling, resource allocation, and distributed route planning. The best known version of DSA, DSA-B, works by having agents change their assignments with probability p when making that change will improve their solution (a hill-climbing move). To escape local minima, DSA-B performs a lateral escape move by switching to another equally good value with the same probability p. It is unclear why hill climbing and escape moves are chosen with the same probability. We investigate the performance effects of making these moves with different probabilities, pH and pL. Through empirical evaluation, we discover that the efficiency of DSA can not only be considerably improved, but can be more specifically tuned to a particular domain or user's needs when these two move types are considered separately. Our work also shows that DSA can outperform both DBA and DPP when it is properly tuned.
This work investigates distributed transmission scheduling in wireless networks. Due to interference constraints, "neighboring links" cannot be simultaneously activated, otherwise transmissions will fail. He...
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ISBN:
(纸本)9781450300384
This work investigates distributed transmission scheduling in wireless networks. Due to interference constraints, "neighboring links" cannot be simultaneously activated, otherwise transmissions will fail. Hereafter, we consider any binary model of interference. We follow the model described by Bui, Sanghavi, and Srikant in [3]. We assume. There are two phases during each slot: first the control phase which determines what links will be activated next, followed by a transmission phase during which data is transmitted. We assume random arrivals of data (packets) on each link during each slot, so that a buffer (queue) is associated to each link. It takes exactly one time slot to transmit a packet on a link. Since nodes do not have a global knowledge of the network, our aim (like in [3]) is to design for the control phase a distributed algorithm which identifies a set of non-interfering links.
We propose a new distributed delay-constrained unicast routing algorithm which can always find a delay-constrained path with small message complexity if such a path *** each network node,limited information about the ...
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ISBN:
(纸本)7800908275
We propose a new distributed delay-constrained unicast routing algorithm which can always find a delay-constrained path with small message complexity if such a path *** each network node,limited information about the network state is needed and only a small amount of computation is *** results show that the proposed algorithm has much better cost performance than the least delay path algorithm.
Traditional swarm robots mainly rely on a single GPS for *** environment or the failure of the GPS receiver may cause some robots cannot be located because their GPS signals lose,so co
Traditional swarm robots mainly rely on a single GPS for *** environment or the failure of the GPS receiver may cause some robots cannot be located because their GPS signals lose,so co
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