{"title":"具有地理因素的小世界分析增广图模型","authors":"V. Nguyen, C. Martel","doi":"10.1137/1.9781611972986.5","DOIUrl":null,"url":null,"abstract":"Small-world properties, such as small-diameter and clustering, and the power-law property are widely recognized as common features of large-scale real-world networks. Recent studies also notice two important geographical factors which play a significant role, particularly in Internet related setting. These two are the distance-bias tendency (links tend to connect to closer nodes) and the property of bounded growth in localities. However, existing formal models for real-world complex networks usually don't fully consider these geographical factors. \n \nWe describe a flexible approach using a standard augmented graph model (e.g. Watt and Strogatz's [33], and Kleinberg's [20] models) and present important initial results on a refined model where we focus on the small-diameter characteristic and the above two geographical factors. We start with a general model where an arbitrary initial node-weighted graph H is augmented with additional random links specified by a generic 'distribution rule' τ and the weights of nodes in H. We consider a refined setting where the initial graph H is associated with a growth-bounded metric, and τ has a distance-bias characteristic, specified by parameters as follows. The base graph H has neighborhood growth bounded from both below and above, specified by parameters β1, β2 > 0. (These parameters can be thought of as the dimension of the graph, e.g. β1 = 2 and β1 = 3 for a graph modeling a setting with nodes in both 2D and 3D settings.) That is 2β1 ≤ Nu(2r)/Nu(r) ≤ 2β2 where Nu(r) is the number of nodes v within metric distance r from u: d(u, v) ≤ r. When we add random links using distribution τ, this distribution is specified by parameter α > 0 such that the probability that a link from u goes to v ≠ u is ∝ 1/dα(u,v). We show which parameters produce a small-diameter graph and how the diameter changes depending on the relationship between the distance-bias parameter α and the two bounded growth parameters β1, β2 > 0. In particular, for most connected base graphs, the diameter of our augmented graph is logarithmic if α ≤ β1, and poly-log if β2 ≤ α 2β2. These results also suggest promising implications for applications in designing routing algorithms.","PeriodicalId":340112,"journal":{"name":"Workshop on Analytic Algorithmics and Combinatorics","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Augmented Graph Models for Small-World Analysis with Geographic Factors\",\"authors\":\"V. Nguyen, C. Martel\",\"doi\":\"10.1137/1.9781611972986.5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Small-world properties, such as small-diameter and clustering, and the power-law property are widely recognized as common features of large-scale real-world networks. Recent studies also notice two important geographical factors which play a significant role, particularly in Internet related setting. These two are the distance-bias tendency (links tend to connect to closer nodes) and the property of bounded growth in localities. However, existing formal models for real-world complex networks usually don't fully consider these geographical factors. \\n \\nWe describe a flexible approach using a standard augmented graph model (e.g. Watt and Strogatz's [33], and Kleinberg's [20] models) and present important initial results on a refined model where we focus on the small-diameter characteristic and the above two geographical factors. We start with a general model where an arbitrary initial node-weighted graph H is augmented with additional random links specified by a generic 'distribution rule' τ and the weights of nodes in H. We consider a refined setting where the initial graph H is associated with a growth-bounded metric, and τ has a distance-bias characteristic, specified by parameters as follows. The base graph H has neighborhood growth bounded from both below and above, specified by parameters β1, β2 > 0. (These parameters can be thought of as the dimension of the graph, e.g. β1 = 2 and β1 = 3 for a graph modeling a setting with nodes in both 2D and 3D settings.) That is 2β1 ≤ Nu(2r)/Nu(r) ≤ 2β2 where Nu(r) is the number of nodes v within metric distance r from u: d(u, v) ≤ r. When we add random links using distribution τ, this distribution is specified by parameter α > 0 such that the probability that a link from u goes to v ≠ u is ∝ 1/dα(u,v). We show which parameters produce a small-diameter graph and how the diameter changes depending on the relationship between the distance-bias parameter α and the two bounded growth parameters β1, β2 > 0. In particular, for most connected base graphs, the diameter of our augmented graph is logarithmic if α ≤ β1, and poly-log if β2 ≤ α 2β2. These results also suggest promising implications for applications in designing routing algorithms.\",\"PeriodicalId\":340112,\"journal\":{\"name\":\"Workshop on Analytic Algorithmics and Combinatorics\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-01-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Workshop on Analytic Algorithmics and Combinatorics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1137/1.9781611972986.5\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Workshop on Analytic Algorithmics and Combinatorics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1137/1.9781611972986.5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Augmented Graph Models for Small-World Analysis with Geographic Factors
Small-world properties, such as small-diameter and clustering, and the power-law property are widely recognized as common features of large-scale real-world networks. Recent studies also notice two important geographical factors which play a significant role, particularly in Internet related setting. These two are the distance-bias tendency (links tend to connect to closer nodes) and the property of bounded growth in localities. However, existing formal models for real-world complex networks usually don't fully consider these geographical factors.
We describe a flexible approach using a standard augmented graph model (e.g. Watt and Strogatz's [33], and Kleinberg's [20] models) and present important initial results on a refined model where we focus on the small-diameter characteristic and the above two geographical factors. We start with a general model where an arbitrary initial node-weighted graph H is augmented with additional random links specified by a generic 'distribution rule' τ and the weights of nodes in H. We consider a refined setting where the initial graph H is associated with a growth-bounded metric, and τ has a distance-bias characteristic, specified by parameters as follows. The base graph H has neighborhood growth bounded from both below and above, specified by parameters β1, β2 > 0. (These parameters can be thought of as the dimension of the graph, e.g. β1 = 2 and β1 = 3 for a graph modeling a setting with nodes in both 2D and 3D settings.) That is 2β1 ≤ Nu(2r)/Nu(r) ≤ 2β2 where Nu(r) is the number of nodes v within metric distance r from u: d(u, v) ≤ r. When we add random links using distribution τ, this distribution is specified by parameter α > 0 such that the probability that a link from u goes to v ≠ u is ∝ 1/dα(u,v). We show which parameters produce a small-diameter graph and how the diameter changes depending on the relationship between the distance-bias parameter α and the two bounded growth parameters β1, β2 > 0. In particular, for most connected base graphs, the diameter of our augmented graph is logarithmic if α ≤ β1, and poly-log if β2 ≤ α 2β2. These results also suggest promising implications for applications in designing routing algorithms.