Spherical representation and polyhedron routing for load balancing in wireless sensor networks

Yu, Xiaokang; Ban, Xiaomeng; Zeng, Wei; Sarkar, Rik; Gu, Xianfeng; Gao, Jie

doi:10.1109/infcom.2011.5935240

“…There is a long line of research in metric embeddingfor example, embedding discrete metrics into trees [18] and into vector spaces [19]. Optimization-based representation of networks has been used for routing and navigation in domains such as sensor networks and robotics [20], [21]. Representations in hyperbolic spaces have emerged as a technique to preserve richer network structures [22], [23], [24].…”

Section: Related Workmentioning

confidence: 99%

Gemsec

Rózemberczki

¹

,

Davies

²

,

Sarkar

³

et al. 2019

Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining

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Modern graph embedding procedures can efficiently process graphs with millions of nodes. In this paper, we propose GEMSEC -a graph embedding algorithm which learns a clustering of the nodes simultaneously with computing their embedding. GEMSEC is a general extension of earlier work in the domain of sequence-based graph embedding. GEMSEC places nodes in an abstract feature space where the vertex features minimize the negative log-likelihood of preserving sampled vertex neighborhoods, and it incorporates known social network properties through a machine learning regularization. We present two new social network datasets and show that by simultaneously considering the embedding and clustering problems with respect to social properties, GEMSEC extracts high-quality clusters competitive with or superior to other community detection algorithms. In experiments, the method is found to be computationally efficient and robust to the choice of hyperparameters.

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“…There is a long line of research in metric embeddingfor example, embedding discrete metrics into trees [18] and 1 https://github.com/benedekrozemberczki/GEMSEC into vector spaces [19]. Optimization-based representation of networks has been used for routing and navigation in domains such as sensor networks and robotics [20], [21]. Representations in hyperbolic spaces have emerged as a technique to preserve richer network structures [22], [23], [24].…”

Section: Related Workmentioning

confidence: 99%

GEMSEC: Graph Embedding with Self Clustering

Rozemberczki,

Davies,

Sarkar

et al. 2018

Preprint

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Modern graph embedding procedures can efficiently process graphs with millions of nodes. In this paper, we propose GEMSEC -a graph embedding algorithm which learns a clustering of the nodes simultaneously with computing their embedding. GEMSEC is a general extension of earlier work in the domain of sequence-based graph embedding. GEMSEC places nodes in an abstract feature space where the vertex features minimize the negative log-likelihood of preserving sampled vertex neighborhoods, and it incorporates known social network properties through a machine learning regularization. We present two new social network datasets and show that by simultaneously considering the embedding and clustering problems with respect to social properties, GEMSEC extracts high-quality clusters competitive with or superior to other community detection algorithms. In experiments, the method is found to be computationally efficient and robust to the choice of hyperparameters.

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“…Yu et al [23] examined a network inside a simply connected domain and used Ricci flow to generate Thurston's embedding as the skeleton of a convex polytope. The intuition is to map the network on a sphere (or half sphere) as routing on a sphere has no congestion due to perfect symmetry.…”

Section: Related Workmentioning

confidence: 99%

Load balanced short path routing in large-scale wireless networks using area-preserving maps

Goswami

¹

,

Ni

²

,

Ban

³

et al. 2014

Proceedings of the 15th ACM International Symposium on Mobile Ad Hoc Networking and Computing

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Load balanced routing in a network, i.e., minimizing the maximum traffic load any node carries for unsplittable flows, is a well known NP-hard problem. Finding practical algorithms remains a long standing challenge. In this paper we propose greedy routing using virtual coordinates that achieves both small path stretch ratio (compared to shortest path) and small load balancing ratio (compared to optimal load balanced routing), in a large scale wireless sensor network deployed densely inside a geometric domain with complex shape. We first provide a greedy routing scheme on a disk with a stretch ratio of at most 2, and under which the maximum load is a factor 4 √ 2 smaller than the maximum load under shortest path routing. This is the first simple routing scheme with a small stretch that has been proven to outperform shortest path routing in terms of load balancing. Then we transform a network of arbitrary shape to a disk by an area preserving map φ. We show that both the path length and the maximum traffic load in the original network only increases by an additional factor of d 2 , where d is the maximum length stretch of φ. Combined with the result on a disk we again achieve both bounded stretch and bounded load balancing ratio. Our simulation results evaluated the practical performance on both quality measures.

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Spherical representation and polyhedron routing for load balancing in wireless sensor networks

Cited by 11 publications

References 21 publications

Gemsec

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GEMSEC: Graph Embedding with Self Clustering

Load balanced short path routing in large-scale wireless networks using area-preserving maps

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