Community-Aware Opportunistic Routing in Mobile Social Networks Mingjun Xiao, Member, IEEE, Jie Wu, Fellow, IEEE, and Liusheng Huang, Member, IEEE Abstract—Mobile social networks (MSNs) are a kind of delay tolerant network that consists of lots of mobile nodes with social characteristics. Recently, many social-aware algorithms have been proposed to address routing problems in MSNs. However, these algorithms tend to forward messages to the nodes with locally optimal social characteristics, and thus cannot achieve the optimal performance. In this paper, we propose a distributed optimal Community-Aware Opportunistic Routing (CAOR) algorithm. Our main contributions are that we propose a home-aware community model, whereby we turn an MSN into a network that only includes community homes. We prove that, in the network of community homes, we can still compute the minimum expected delivery delays of nodes through a reverse Dijkstra algorithm and achieve the optimal opportunistic routing performance. Since the number of communities is far less than the number of nodes in magnitude, the computational cost and maintenance cost of contact information are greatly reduced. We demonstrate how our algorithm significantly outperforms the previous ones through extensive simulations, based on a real MSN trace and a synthetic MSN trace. Index Terms—Community, delay tolerant networks, mobile social networks, opportunistic routing 1 INTRODUCTION M OBILE social networks (MSNs) are a special kind of delay tolerant network (DTN), in which mobile users move around and communicate with each other via their carried short-distance wireless communication devices. Typical MSNs include pocket switch networks, mobile vehicular net- works, mobile sensor networks, etc. [1]. As more users exploit portable short-distance wireless communication devices (such as smart phones, iPads, mobile PCs, and sensors in vehicles) to contact and share data between each other in a cheap way, MSNs attract more attention. Since MSNs experi- ence intermittent connectivity incurred by the mobility of users, routing is a mainly concerning and challenging problem. Recently, some social-aware routing algorithms that are based on social network analysis have been proposed, such as Bubble Rap [2], SimBet [3], and algorithms in [4]–[7], etc. Two key concepts in social network analysis are: (i) community, which is a group of people with social relations; (ii) centrality, which indicates the social relations between a node and other nodes in a community. Based on the two concepts, these algorithms detect the communities and compute the centrali- ty value for each node. Messages are delivered via the nodes with good centralities. Since social relations of mobile users generally have long-term characteristics and are less volatile than node mobility, social-aware algorithms outperform tra- ditional DTN algorithms, such as flooding-based algorithms [8], [9] and probability-based algorithms [10]–[14]. Despite this, these algorithms tend to forward messages to the nodes with locally best centralities. In this paper, we focus on the single-copy routing problem in MSNs. In many real MSNs, mobile users that have a common interest generally will visit some (real or virtual) location that is related to this interest. For instance in Fig. 1, students with a common study interest will visit the same classrooms to take part in the same courses; customers with the same shopping interests often visit the same shops; friends generally share some resources through facebook, and so on. Based on this basic social characteristic, we propose a home- aware community model. Mobile users with a common inter- est autonomously form a community, in which the frequently visited location is their common “home.” Moreover, like [1], we assume that each home supports a real or virtual throwbox [15], a local device that can temporarily store and transmit messages. Under the home-aware community model, we propose a distributed optimal Community-Aware Opportunistic Rout- ing algorithm (CAOR). We first turn the routing between lots of nodes to the routing between a few community homes. Then, we adopt the optimal opportunistic routing scheme by maintaining an optimal relay set for each home. Each home only forwards its message to the node in its optimal relay set, and ignores other relays. Since this scheme solves the problem of whether a home should select a visited node as the relay of message delivery or ignore this visited node to wait for those better relays, it can achieve the optimal performance. More specifically, our major contributions are summarized as follows: 1. We present a home-aware community model and extend the centrality concept from a single node to a group of nodes. Unlike existing community models, each • M. Xiao and L. Huang are with the School of Computer Science and Technology, Suzhou Institute for Advanced Study, University of Science and Technology of China, Hefei, 230027, China. E-mail: {xiaomj, lshuang}@ustc.edu.cn. • J. Wu is with the Department of Computer and Information Sciences, Temple University, Philadelphia, PA 19122. E-mail: jiewu@temple.edu. Manuscript received 02 Oct. 2012; revised 13 Feb. 2013; accepted 25 Feb. 2013. Date of publication 19 Mar. 2013; date of current version 27 June 2014. Recommended for acceptance by K. Li. For information on obtaining reprints of this article, please send e-mail to: reprints@ieee.org, and reference the Digital Object Identifier below. Digital Object Identifier no. 10.1109/TC.2013.55 1682 IEEE TRANSACTIONS ON COMPUTERS, VOL. 63, NO. 7, JULY 2014 0018-9340 © 2013 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.