Social interaction increases capacity of wireless networks

Abstract-In this paper, we study the effects of social interactions among nodes on the capacity of wireless networks. We consider three scenarios. In the first scenario, the size of the social group for all nodes is fixed while the frequency of communication within members of a social group follows power law distribution. In the second scenario, scale free networks are studied where the size of the social group differs from node to node, and the destination in each group is selected uniformly among the members of that group. Further investigation in the second scenario reveals that traditional transport capacity definition provides misleading conclusions for such network models. We show that nodes with different social status impact the capacity differently. By separating nodes with different social status and allocating separate bandwidth to them, it is shown that majority of nodes scale in this network. In the third scenario, both the size of the social groups and the destination in each group are selected according to power law distributions. Our simulation results corroborate the analytical results. Further, we observe consistently that social interaction improves the capacity of wireless networks which implies that the Gupta-Kumar results were pessimistic for practical networks.

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“…Proof: The proof can be found in [20]. Proof of theorem 1: This theorem is a direct result of lemmas 2 and 3.…”

Section: Proof: Define the Random Variablesmentioning

confidence: 97%

Effect of Social Groups on the Capacity of Wireless Networks

Kiskani

Azimdoost

Sadjadpour

2016

IEEE Trans. Wireless Commun.

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“…For social wireless networks, Sadjadpour et al studied the capacity of a scale-free wireless network in which nodes communicate with each other in the context of social groups [47]. Particularly, it was discovered that the maximum capacity can be improved in the social scale-free networks compared with the classical conclusion drawn by Gupta and Kumar [23], [48]. In addition, they studied the capacity of composite networks, namely, the combination of social and wireless adhoc networks [49].…”

Section: A Related Workmentioning

confidence: 99%

“…It has been explained in [23] that the relay nodes will never cause traffic bottleneck, so the underlaying propagation network will not change the capacity of the overlaying social network. Please note that this kind of multi-hop data relaying is complying with the same approach as widely used in [23], [46], [47], [48].…”

Section: Network Modelmentioning

confidence: 99%

On the Capacity of Fractal D2D Social Networks with Hierarchical Communications

Chen¹,

Li²,

Zhao³

et al. 2020

Preprint

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The maximum capacity of fractal D2D (device-todevice) social networks with both direct and hierarchical communications is studied in this paper. Specifically, the fractal networks are characterized by the direct social connection and the selfsimilarity. Firstly, for a fractal D2D social network with direct social communications, it is proved that the maximum capacity is Θif a user communicates with one of his/her direct contacts randomly, where n denotes the total number of users in the network, and it can reach up to Θ 1 log n if any pair of social contacts with distance d communicate according to the probability in proportion to d −β . Secondly, since users might get in touch with others without direct social connections through the inter-connected multiple users, the fractal D2D social network with these hierarchical communications is studied as well, and the related capacity is further derived. Our results show that this capacity is mainly affected by the correlation exponent ǫ of the fractal structure. The capacity is reduced in proportional to 1 log n if 2 < ǫ < 3, while the reduction coefficient is 1 n if ǫ > 3.

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“…For social wireless networks, Sadjadpour et al studied the capacity of a scale-free wireless network in which nodes communicate with each other in the context of social groups [26]. Particularly, it was discovered that the maximum capacity can be improved in the social scale-free networks compared with the classical conclusion drawn by Gupta and Kumar [27], [28]. In addition, they studied the capacity of composite networks, namely, the combination of social and wireless adhoc networks [29].…”

Section: A Related Workmentioning

confidence: 99%

On the Capacity of Fractal D2D Social Networks With Hierarchical Communications

Chen¹,

Li²,

Zhang³

et al. 2017

Preprint

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The maximum capacity of fractal D2D (deviceto-device) social networks with both direct and hierarchical communications is studied in this paper. Specifically, the fractal networks are characterized by the direct social connection and the self-similarity. Firstly, for a fractal D2D social network with direct social communications, it is proved that the maximumif a user communicates with one of his/her direct contacts randomly, where n denotes the total number of users in the network, and it can reach up to Θ 1 log n if any pair of social contacts with distance d communicate according to the probability in proportion to d −β . Secondly, since users might get in touch with others without direct social connections through the inter-connected multiple users, the fractal D2D social network with these hierarchical communications is studied as well, and the related capacity is further derived. Our results show that this capacity is mainly affected by the correlation exponent of the fractal structure. The capacity is reduced in proportional to 1 log n if 2 < < 3, while the reduction coefficient is 1 n if = 3.

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Social interaction increases capacity of wireless networks

Cited by 13 publications

References 8 publications

Effect of Social Groups on the Capacity of Wireless Networks

Effect of Social Groups on the Capacity of Wireless Networks

On the Capacity of Fractal D2D Social Networks with Hierarchical Communications

On the Capacity of Fractal D2D Social Networks With Hierarchical Communications

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