NDLI: Capacity Scaling of Wireless Social Networks

Content Provider	IEEE Xplore Digital Library
Author	Cheng Wang Lu Shao Zhong Li Lei Yang Xiang-Yang Li Changjun Jiang
Copyright Year	1990
Abstract	In this paper, we investigate capacity scaling laws of wireless social networks under the social-based session formation. We model a wireless social network as a three-layered structure, consisting of the physical layer, social layer, and session layer; and we introduce a cross-layer distance & density-aware model, called the population-based formation model, under which: 1) for each node v_k, the number of its friends/followers, denoted by q_k, follows a Zipf's distribution with degree clustering exponent g; 2) q_k anchor points are independently chosen according to a probability distribution with density function proportional to (E_k,X)^-β, where E_k;X is the expected number of nodes (population) within the distance \|v_k-X\| to v_k, and β is the clustering exponent of friendship formation; 3) finally, q_k nodes respectively nearest to those q_k anchor points are selected as the friends of v_k. We present the general density function of social relationship distribution, with general distribution of physical layer, serving as the basis for studying general capacity of wireless social networks. As the first step of addressing this issue, for the homogeneous physical layer, we derive the social-broadcast capacity under both generalized physical and protocol interference models, taking into account general clustering exponents of both friendship degree and friendship formation in a 2-dimensional parameter space, i.e., (γ,β) ϵ[0,∞)². Importantly, we notice that the adopted model with homogenous physical layer does not sufficiently reflect the advantages of the population-based formation model in terms of realistic validity and practicability. Accordingly, we introduce a random network model, called the center-clustering random model (CCRM) with node distribution exponent δ ϵ [0, ∞), highlighting the clustering and inhomogeneity property in real-life networks, and discuss how to further derive more general network capacity over 3-dimensional parameter space (δ,γ,β) ϵ [0, ∞)³ based on our results over (γ,β) ϵ [0, ∞)².
Sponsorship	IEEE Computer Society
Starting Page	1839
Ending Page	1850
Page Count	12
File Size	854814
File Format	PDF
ISSN	10459219
Volume Number	26
Issue Number	7
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Social network services Wireless communication Physical layer Density functional theory Wireless sensor networks Analytical models Nonhomogeneous media network capacity Scaling laws social networks wireless networks
Content Type	Text
Resource Type	Article
Subject	Signal Processing Computational Theory and Mathematics Hardware and Architecture

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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