Abstract—The recent popularization of hand-held mobile devices, such as smartphones, enables the inter-connectivity among mobile users without the support of Internet infrastructure. When mobile users move and contact each other opportunistically, they form a Delay Tolerant Network (DTN), which can be exploited to share data among them. Data replication is one of the common techniques for such data sharing. However, the unstable network topology and limited contact duration in DTNs make it difficult to directly apply traditional data replication schemes. Although there are a few existing studies on data replication in DTNs, they generally ignore the contact duration limits. In this paper, we recognize the deficiency of existing data replication schemes which treat the complete data item as the replication unit, and propose to replicate data at the packet level. We analytically formulate the contact duration aware data replication problem and give a centralized solution to better utilize the limited storage buffers and the contact opportunities. We further propose a practical contact Duration Aware Replication Algorithm (DARA) which operates in a fully distributed manner and reduces the computational complexity. Extensive simulations on both synthetic and realistic traces show that our distributed scheme achieves close-to-optimal performance, and outperforms other existing replication schemes. I.

Recently, there has been a tremendous increase in mobile data usage with the wide-spread proliferation of smartphone like devices. However, this increased demand from users has caused severe traffic overloading in cellular networks. Offloading the traffic through several other devices (femtocells, WiFi access points) have been considered to be immediate remedy for such a problem. Thus, in this paper, we study the deployment of WiFi access points (AP) in a metropolitan area for efficient offloading of mobile data traffic. We analyze a large scale real user mobility traces and propose a deployment algorithm based on the density of user data request frequency. In simulations, we present offloading ratio that our algorithm can accomplish with different number of APs. The results demonstrate that our algorithm can achieve close to optimal offloading ratio that is higher than offloading ratios that existing algorithms can achieve with the same number of APs.

Abstract—Cellular networks (e.g., 3G) are currently facing severe traffic overload problems caused by excessive traffic demands. Offloading part of the cellular traffic through other forms of networks, such as Delay Tolerant Networks (DTNs) and WiFi hotspots, is a promising solution. However, since these networks can only provide intermittent connectivity to mobile users, utilizing them for cellular traffic offloading may result in a non-negligible delay. As the delay increases, the users ’ satisfaction decreases. In this paper, we investigate the tradeoff between the amount of traffic being offloaded and the users ’ satisfaction. We provide a novel incentive framework to motivate users to leverage their delay tolerance for cellular traffic offloading. To minimize the incentive cost given an offloading target, users with high delay tolerance and large offloading potential should be prioritized for traffic offloading. To effectively capture the dynamic characteristics of users ’ delay tolerance, our incentive framework is based on reverse auction to let users proactively express their delay tolerance by submitting bids. We further illustrate how to predict the offloading potential of the users by using stochastic analysis for both DTN and WiFi cases. Extensive trace-driven simulations verify the efficiency of our incentive framework for cellular traffic offloading.