  Socially-aware networking is an emerging paradigm for intermittently
connected networks consisting of mobile users with social relationships and
characteristics. In this setting, humans are the main carriers of mobile
devices. Hence, their connections, social features, and behaviors can be
exploited to improve the performance of data forwarding protocols. In this
paper, we first explore the impact of three social features, namely physical
proximity, user interests, and social relationship on users' daily routines.
Then, we propose a multi-dimensional routing protocol called
Proximity-Interest-Social (PIS) protocol in which the three different social
dimensions are integrated into a unified distance function in order to select
optimal intermediate data carriers. PIS protocol utilizes a time slot
management mechanism to discover users' movement similarities in different time
periods during a day. We compare the performance of PIS to Epidemic, PROPHET,
and SimBet routing protocols using SIGCOMM09 and INFOCOM06 data sets. The
experiment results show that PIS outperforms other benchmark routing protocols
with the highest data delivery ratio with a low communication overhead.
