{"id":246266,"date":"2016-06-30T11:12:08","date_gmt":"2016-06-30T18:12:08","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&#038;p=246266"},"modified":"2018-10-16T20:11:59","modified_gmt":"2018-10-17T03:11:59","slug":"routing-complex-contagion-kleinbergs-small-world-networks","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/routing-complex-contagion-kleinbergs-small-world-networks\/","title":{"rendered":"The Routing of Complex Contagion in Kleinberg&#8217;s Small-world Networks"},"content":{"rendered":"<p>In Kleinberg\u2019s small-world network model, strong ties are modeled as deterministic edges in the underlying base grid and weak ties are modeled as random edges connecting remote nodes. The probability of connecting a node u with node v through a weak tie is proportional to 1\/|uv|^\u03b1, where |uv| is the grid distance between u and v and \u03b1 \u2265 0 is the parameter of the model. Complex contagion refers to the propagation mechanism in a network where each node is activated only after k \u2265 2 neighbors of the node are activated. In this paper, we propose the concept of routing of complex contagion (or complex routing), where at each time step we can select one eligible node (nodes already having two active neighbors) to activate, with the goal of activating the pre-selected target node in the end. We consider decentralized routing scheme where only the links connected to already activated nodes are known to the selection strategy. We study the routing time of complex contagion and compare the result with simple routing and complex di\ufb00usion (the di\ufb00usion of complex contagion, where all eligible nodes are activated immediately in the same step with the goal of activating all nodes in the end). We show that for decentralized complex routing, the routing time is lower bounded by a polynomial in n (the number of nodes in the network) for all range of \u03b1 both in expectation and with high probability (in particular, \u2126(n^{1\/(\u03b1+2)}) for \u03b1 \u2264 2 and \u2126(n^{\u03b1\/(2\u03b1+4)}) for \u03b1 > 2 in expectation). Our results indicate that complex routing is exponentially harder than both simple routing and complex di\ufb00usion at the sweetspot of \u03b1 = 2.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In Kleinberg\u2019s small-world network model, strong ties are modeled as deterministic edges in the underlying base grid and weak ties are modeled as random edges connecting remote nodes. The probability of connecting a node u with node v through a weak tie is proportional to 1\/|uv|^\u03b1, where |uv| is the grid distance between u and [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":null,"msr_publishername":"","msr_publisher_other":"","msr_booktitle":"Proceedings of the 22nd International Computing and Combinatorics Conference (COCOON'2016)","msr_chapter":"","msr_edition":"Proceedings of the 22nd International Computing and Combinatorics Conference (COCOON'2016), Ho Chi Minh City, Vietnam, August, 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