PROJECT TITLE :

BEEINFO: Interest-Based Forwarding Using Artificial Bee Colony for Socially Aware Networking

ABSTRACT:

Socially aware networking (SAN) provides a promising paradigm for routing and forwarding data packets by exploiting social properties of involved entities, for example, in vehicular social networks (VSNs). The mobility of people usually options some regularity in location and time, significantly in vehicular environments. However, people' learning capability and awareness to the dynamic environments haven't been well explored within the literature. Inspired by the synthetic bee colony, we gift BEEINFO, that may be a set of interest-primarily based forwarding schemes for SAN, that consists of BEEINFO-D, BEEINFO-S, and BEEINFO-D&S. BEEINFO adopts the food foraging behavior of bees to detect the atmosphere data and to optimize the forwarding procedure. BEEINFO takes advantage of people' perceiving and learning capability to assemble information of density and social ties. BEEINFO-D, BEEINFO-S, and BEEINFO-D&S are distinct from every alternative per different utilization of density and social ties. This enhances the adaptability to dynamic environments. Additionally, BEEINFO performs message scheduling and buffer management to boost the forwarding performance. Intensive simulations are conducted to compare BEEINFO with 2 representative protocols, i.e., PRoPHET and Epidemic. The results illustrate that BEEINFO outperforms PRoPHET and Epidemic with higher message delivery ratio, less overhead, and fewer hop counts.


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