Performance evaluation of referral selection algorithms in human centric communication networks

Human centric communication network (HCCN) is a communication network offering human centric mobile Internet services. In such a network, the relationship among users depends on their social behavior and the available network infrastructure. Advertisement and narrowcasting are two main important services in human centric communication networks. In [8], a viral-marketing-based approach was proposed to disseminate advertisement information in HCCN. Heuristic degree-based referral selection algorithms were presented to selected referrals under the given budget and time constraints. In this paper, key factors that may affect the referral selection algorithms are addressed and two referral selection algorithms are presented. Simulation results showed the proposed referral selection algorithms can achieve a better influence rate in different application scenarios.