Impact of Social Interaction on the Capacity of Hybrid Wireless Networks
Qiuming Liu, He Xiao, Xiaohong Qiu, Li Chen Yu · IEEE Access · 2018
In this paper, we jointly consider the optimal max-$L$-hops routing policy and social features for the throughput capacity of a hybrid wireless network, which is different from the existing works that ignored the network traffic model. For the social feature, each node’s social group is determined by a probability related to the distance from the source node. To embody the features of social behavior, we propose a traffic model within a social group. Under the max-$L$-hops routing policy in the hybrid wireless network, we analyze the effects of physical distance, clustering property, and a number of base station on throughput capacity. We also study the influence of different social group sizes on the throughput capacity. Our results demonstrate that: 1) the optimal$L$is not only related to social group size, but also the selection of destination nodes; 2) when the social contact factors$\alpha$and$\beta$increase, the throughput capacity trends to be independent of the number of base station and routing parameter$L$. Particularly, our results show that the wireless network is scalable with the number of node, if the social contact factor is large enough; and 3) the results demonstrate that the base station and social interaction improve the throughput capacity of hybrid wireless networks.