On Exploiting Hotspot and Entropy for Data Forwarding in Delay Tolerant   Networks
  Performance of data forwarding in Delay Tolerant Networks (DTNs) benefits considerably if one can make use of human mobility in terms of social structures. However, it is difficult and time-consuming to calculate the centrality and similarity of nodes by using solutions for traditional social networks, this is mainly because of the transient node contact and the intermittently connected environment. In this work, we are interested in the following question: Can we explore some other stable social attributes to quantify the centrality and similarity of nodes? Taking GPS traces of human walks from the real world, we find that there exist two known phenomena. One is public hotspot, the other is personal hotspot. Motivated by this observation, we present Hoten (hotspot and entropy), a novel routing metric to improve routing performance in DTNs. First, we use the relative entropy between the public hotspots and the personal hotspots to compute the centrality of nodes. Then we utilize the inverse symmetrized entropy of the personal hotspots between two nodes to compute the similarity between them. Third, we exploit the entropy of personal hotspots of a node to estimate its personality. Besides, we propose a method to ascertain the optimized size of hotspot. Finally, we compare our routing strategy with other state-of-the-art routing schemes through extensive trace-driven simulations, the results show that Hoten largely outperforms other solutions, especially in terms of combined overhead/packet delivery ratio and the average number of hops per message. 
Peiyan Yuan, Huadong Ma, Shaojie Tang
cs.DC