Towards Efficient File Sharing and Packet Routing in Mobile Opportunistic Networks

With the increasing popularity of portable digital devices (e.g., smartphones, laptops, and tablets), mobile opportunistic networks (MONs) [40, 90] consisting of portable devices have attracted much attention recently. MONs are also known as pocket switched networks (PSNs) [52]. MONs can be regarded as a special form of mobile ad hoc networks (MANETs) [7] or delay tolerant networks (DTNs) [35, 56]. In such networks, mobile nodes (devices) move continuously and meet opportunistically. Two mobile nodes can communicate with each other only when they are within the communication range of each other in a peer-to-peer (P2P) manner (i.e., without the need of infrastructures). Therefore, such a network structure can potentially provide file sharing or packet routing services among portable devices without the support of network infrastructures. On the other hand, mobile opportunistic networks often experience frequent network partition, and no end-to-end contemporaneous path can be ensured in the network. These distinctive properties make traditional file sharing or packet routing algorithms in Internet or mobile networks a formidable challenge in MONs. In summary, it is essential and important to achieve efficient file sharing and packet routing algorithms in MONs, which are the key for providing practical and novel services and applications over such networks. In this Dissertation, we develop several methods to resolve the aforementioned challenges. Firstly, we propose two methods to enhance file sharing efficiency in MONs by creating replicas and by leveraging social network properties, respectively. In the first method, we investigate how to create file replicas to optimize file availability for file sharing in MONs. We introduce a new concept of resource for file replication, which considers both node storage and meeting frequency with other nodes. We theoretically study the influence of resource allocation on the average file access delay and derive a resource allocation rule to minimize the average file access delay. We also propose a distributed file replication protocol to realize the deduced optimal file replication rule. In the second method, we leverage social network properties to improve the file searching efficiency in MONs. This method groups common-interest nodes that frequently meet with each other into a community. It takes advantage of node mobility by designating stable nodes, which have the most frequent contact with community members, as community coordinators for intra-community file request forwarding, and highly-mobile nodes that visit other communities frequently as community ambassadors for inter-community file request forwarding. Based on such a community structure, an interest-oriented file searching scheme is proposed to first search local community and then search the community that is most likely to contain the requested file, leading to highly efficient file sharing in MONs. Secondly, we propose two methods to realize efficient packet routing among mobile nodes and among different landmarks in MONs, respectively. The first method utilizes distributed social map to route packets to mobile nodes efficiently with a low-cost in MONs. Each node builds its own social map consisting of nodes it has met and their frequently encountered nodes in a distributed manner. Based on both encountering frequency and social closeness of two linked nodes in the social map, we decide the weight of each link to reflect the packet delivery ability between the two nodes. The social map enables more accurate forwarder selection through a broader view and reduces the cost on information exchange. The second method realizes high-throughput packet routing among different landmarks in MONs. It selects popular places that nodes visit frequently as landmarks and divides the entire MON area into sub-areas represented by landmarks. Nodes transiting between two landmarks relay packets between the two landmarks. The frequency of node transits between two landmarks is measured to represent the forwarding capacity between them, based on which routing tables are built on each landmark to guide packet routing. Finally, packets are routed landmark by landmark to reach their destination landmarks. Extensive analysis and real-trace based experiments are conducted to support the designs in this Dissertation and demonstrate the effectiveness of the proposed methods in comparison with the state-of-art methods. In the future, we plan to further enhance the file sharing and packet routing efficiency by considering more realistic scenarios or including more useful information. We will also investigate the security and privacy issues in the proposed methods

Simplifying Wireless Social Caching

Social groups give the opportunity for a new form of caching. In this paper, we investigate how a social group of users can jointly optimize bandwidth usage, by each caching parts of the data demand, and then opportunistically share these parts among themselves upon meeting. We formulate this problem as a Linear Program (LP) with exponential complexity. Based on the optimal solution, we propose a simple heuristic inspired by the bipartite set-cover problem that operates in polynomial time. Furthermore, we prove a worst case gap between the heuristic and the LP solutions. Finally, we assess the performance of our algorithm using real-world mobility traces from the MIT Reality Mining project dataset and two mobility traces that were synthesized using the SWIM model. Our heuristic performs closely to the optimal in most cases, showing a better performance with respect to alternative solutions.Comment: Parts of this work were accepted for publication in ISIT 2016. A complete version is submitted to Transactions on Mobile Computin

When Queueing Meets Coding: Optimal-Latency Data Retrieving Scheme in Storage Clouds

In this paper, we study the problem of reducing the delay of downloading data from cloud storage systems by leveraging multiple parallel threads, assuming that the data has been encoded and stored in the clouds using fixed rate forward error correction (FEC) codes with parameters (n, k). That is, each file is divided into k equal-sized chunks, which are then expanded into n chunks such that any k chunks out of the n are sufficient to successfully restore the original file. The model can be depicted as a multiple-server queue with arrivals of data retrieving requests and a server corresponding to a thread. However, this is not a typical queueing model because a server can terminate its operation, depending on when other servers complete their service (due to the redundancy that is spread across the threads). Hence, to the best of our knowledge, the analysis of this queueing model remains quite uncharted. Recent traces from Amazon S3 show that the time to retrieve a fixed size chunk is random and can be approximated as a constant delay plus an i.i.d. exponentially distributed random variable. For the tractability of the theoretical analysis, we assume that the chunk downloading time is i.i.d. exponentially distributed. Under this assumption, we show that any work-conserving scheme is delay-optimal among all on-line scheduling schemes when k = 1. When k > 1, we find that a simple greedy scheme, which allocates all available threads to the head of line request, is delay optimal among all on-line scheduling schemes. We also provide some numerical results that point to the limitations of the exponential assumption, and suggest further research directions.Comment: Original accepted by IEEE Infocom 2014, 9 pages. Some statements in the Infocom paper are correcte