Proposal for Autonomous Decentralized Structure Formation Based on Local Interaction and Back-Diffusion Potential

Takano, Chisa; Aida, Masaki; Murata, Masayuki; Imase, Makoto

doi:10.1587/transcom.e95.b.1529

Cited by 13 publications

(27 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We first describe the difference between the MCMC-based c 2016 Information Processing Society of Japan ADCM [7] and ADCMs [3], [6] inspired by the physical universe. ADCMs [3], [6] can make a spatially structure used for network clustering and layering.…”

Section: Related Workmentioning

confidence: 99%

“…ADCMs [3], [6] can make a spatially structure used for network clustering and layering. However, they do not address other engineering problems (e.g., resource allocation) formulated by a system performance variable.…”

Section: Related Workmentioning

confidence: 99%

“…ADCMs would be scalable, but the problem of not depending on supervising nodes is that it is difficult to control the entire behavior of a large-scale and wide-area system in a desirable direction. Fortunately, the ADCMs [3], [6], [7] solved this problem with the inspiration from the physical universe.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Adaptive Function to Ensure Robustness of MCMC-based Autonomous Decentralized Control Mechanism against Changing Environment

Sato

Aida

Shimonishi³

2016

Journal of Information Processing

Self Cite

View full text Add to dashboard Cite

Abstract:In our previous work, we proposed an autonomous decentralized control mechanism (ADCM) to be able to control the probability distribution of a system performance variable on the Markov chain Monte Carlo method. As interesting features of our ADCM, we proved the probability distribution controlled by our ADCM is described by a few macro parameters, and discovered a law between the macro parameters and the external environment of the system in our ADCM. In this paper, on the basis of the law, we design an autonomous decentralized adaptive function to adapt to change in the external environment. This function ensures the robustness of our ADCM against changing environment. We apply our ADCM with the proposed adaptive function to a virtual machine placement problem in data center networks (DCNs). Simulation experiments confirm that the proposed adaptive function effectively deals with several DCN scenarios with changing environment.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Adaptive Function to Ensure Robustness of MCMC-based Autonomous Decentralized Control Mechanism against Changing Environment

Sato

Aida

Shimonishi³

2016

Journal of Information Processing

Self Cite

View full text Add to dashboard Cite

show abstract

“…Consequently, the back-diffusion method can yield clustering structures that reflect the characteristics of the network condition. [19] shows that the back-diffusion method (see [18]) can configure clusters faster than an existing method [15] by a factor of 10 or more. This means that communication can be recovered more quickly through the back-diffusion method.…”

Section: Copyright C 2014 the Institute Of Electronics Information Amentioning

confidence: 99%

“…This framework is founded on the interplay between local interaction and the solution provided by a partial differential equation. As a specific example, we proposed the autonomous decentralized formation of structures with finite spatial size and showed the applicability of our method to autonomous clustering in MANETs [18]. Our clustering method, the back-diffusion method, can configure clusters using only local information about neighboring nodes.…”

Section: Introductionmentioning

confidence: 99%

Power Consumption Characteristics of Autonomous Decentralized Clustering Based on Local Interaction

Hamamoto

Takano

Ishida

et al. 2014

IEICE Trans. Inf. & Syst.

Self Cite

View full text Add to dashboard Cite

Ryo HAMAMOTO†a) , Student Member, Chisa TAKANO †b) , Kenji ISHIDA †c) , and Masaki AIDA † †d) , Members SUMMARYMobile ad hoc networks (MANETs) consist of mobile terminals that directly connect with one another to communicate without a network infrastructure, such as base stations and/or access points of wireless local area networks (LANs) connected to wired backbone networks. Large-scale disasters such as tsunamis and earthquakes can cause serious damage to life, property as well as any network infrastructure. However, MANETs can function even after severe disasters have destroyed regular network infrastructure. We have proposed an autonomous decentralized structure formation technology based on local interaction, and have applied it to implement autonomous decentralized clustering on MANETs. This method is known to configure clusters that reflect the network condition, such as residual battery power and the degree of each node. However, the effect of clusters that reflect the network condition has not been evaluated. In this study, we configure clusters using our method, the back-diffusion method, and a bio-inspired method, which is a kind of autonomous decentralized clustering that cannot reflect the network condition. We also clarify the importance of clustering that reflects the network condition, with regard to power consumption and data transfer efficiency.

show abstract

Autonomous Decentralized Spectral Clustering for Hierarchical Routing of Multi-Hop Wireless Networks

2023

Self Cite

View full text Add to dashboard Cite

In multi-hop wireless networks (MWNs), hierarchical structures are important to achieve scalable routing control, as well as clustering algorithms for creating such structures and so have been extensively studied. Due to the constraints of MWNs as distributed systems, these clustering algorithms must be implemented in an autonomous and decentralized manner. In particular, ensuring transparency to network topology and node mobility is important. Spectral clustering is a technique for appropriately creating clusters regardless of the network topology. However, since this technique requires information on the entire network, it is difficult to implement it autonomously and in a decentralized manner. Therefore, autonomous and decentralized spectral clustering has only succeeded in simple grid networks. This paper proposes a spectral clustering algorithm that can be implemented in an autonomous and decentralized manner for any network topology. In this method, a certain spatial structure is generated in an autonomous and decentralized manner by using differential equation-based temporal evolution equations; clusters are then formed using the spatial structure yielded by the temporal evolution equations. We demonstrate that this method can realize spectral clustering in an autonomous and decentralized manner in a static network model and also can realize a stable cluster structure that responds to node movement in a dynamic network model. INDEX TERMSAutonomous decentralized clustering, spectral clustering, multi-hop wireless network, hierarchical routing, spectral graph theory.

show abstract

Proposal for Autonomous Decentralized Structure Formation Based on Local Interaction and Back-Diffusion Potential

Cited by 13 publications

References 14 publications

Adaptive Function to Ensure Robustness of MCMC-based Autonomous Decentralized Control Mechanism against Changing Environment

Adaptive Function to Ensure Robustness of MCMC-based Autonomous Decentralized Control Mechanism against Changing Environment

Power Consumption Characteristics of Autonomous Decentralized Clustering Based on Local Interaction

Autonomous Decentralized Spectral Clustering for Hierarchical Routing of Multi-Hop Wireless Networks

Contact Info

Product

Resources

About