Christina Dunning

Bio: Christina Dunning is an academic researcher from University of Montana. The author has contributed to research in topics: Routing protocol & Equal-cost multi-path routing. The author has an hindex of 1, co-authored 1 publications receiving 20 citations.

Social-similarity-based routing algorithm in Delay Tolerant Networks

Abstract: A Delay Tolerant Network (DTN) is a type of wireless mobile network that does not guarantee continuous network connectivity. One application can be found in the social communication networks that are becoming ever more ubiquitous with the development of more portable, affordable, and powerful mobile devices. In such a network, people move around and contact each other based on their common interests. Recently, some social-feature-based routing protocols that take advantage of recorded social features to steer the routing in the right direction have been proposed. In such protocols, every node finds its differences in social features with the destination. The routing hence becomes a process to resolve the social feature differences between a source and a destination. However, we believe that merely distinguishing nodes by “same” or “different” social features is insufficient in reflecting nodes' dynamic behavior. Therefore, we put forward SOSIM, a novel routing algorithm that uses similarity metrics from data mining on nodes' contact history to more accurately evaluate social similarities between nodes. To improve efficiency, we apply delegation forwarding in our algorithm. Analysis indicates that our algorithm can improve routing performance with a low implementation cost. The simulation results using real trace also show that our algorithm outperforms the existing ones.

A Survey of Mobile Social Networks: Applications, Social Characteristics, and Challenges

Abstract: With the popularity of mobile devices and the development of the wireless technologies, humans can be connected ubiquitously. Because of the mobility of the devices, it is a hard task to maintain the end-to-end path between source node and destination node. Researchers have introduced analysis of nodes’ social behavior to solve the problem of data dissemination in the networks, which leads to the emersion of the Mobile Social Networks (MSNs). They increase the performance of data forwarding by the social relationships and interactions among nodes. Many schemes and algorithms have been proposed to enhance data forwarding performance and provide humanized service by introducing social features and digging social properties. In this paper, first, we investigate the architectures and evolutionary process of the MSNs. Then, the social features of nodes existing in the MSNs and main social properties of MSNs are described. In term of the state-of-the-art works, data forwarding strategies in the MSNs are divided into four categories, including only encounter history-based strategies, social-based strategies, incentive mechanisms, and forwarding methods that take social selfishness into consideration of this paper. Finally, the major issues and challenges are discussed.

A Unified Routing Framework for Integrated Space/Air Information Networks

Abstract: The aerospace-based communications can be managed more efficiently through the construction of an integrated space/air information network by the convergence of satellite (space) and unmanned aerial vehicle (air) networks. Such an integrated network would best fit the advent of delay- and disruption-tolerant networking, in which the data transmission can tolerate long delay and disruption under a store-carry-forward mechanism. Such a network, however, has some challenging research needs due to the network’s high mobility of nodes and time-varying topology that may result in high error bit rate and long delay. In this paper, we propose a unified routing framework for this integrated network, where a Hybrid time-space Graph supporting Hierarchical Routing (HGHR) algorithm is achieved. More specifically, the HGHR performs on a hybrid time-space graph, including two subgraphs: a deterministic graph for the space network and a semi-deterministic one for the air network. This latter graph is based on a discrete time homogeneous semi-Markov prediction model. The hybrid time-space graph is then transformed into a state-space graph, based on which, a message forwarding rule under the store-carry-forward mechanism is adopted. Simulation results show that the proposed HGHR algorithm has good performance in terms of message delivery ratio, end-to-end delay, and power consumption.

Social-Similarity-based Multicast Algorithm in impromptu mobile social networks

Abstract: Mobile social networks (MSNs) where people contact each other through mobile devices have become increasingly popular. In this paper, we study a special kind of MSNs formed impromptu when people gather together at conferences, social events, etc. Multicast is an important routing service which supports the dissemination of messages to a group of users. Most of the existing related multicast algorithms are designed for general Delay Tolerant Networks (DTNs) where social factors are neglected. Recently, a social-profile-based multicast (SPM) protocol that utilizes the static social features in user profiles has been proposed. We believe that in a dynamic environment such as the IMSN, static social features may not reflect people's dynamic behavior. Therefore, in this paper, we propose a novel Social-Similarity-based Multicast Algorithm (Multi-Sosim) using nodes' dynamic social features and a compare-split scheme to improve multicast efficiency in IMSNs. Simulation results using a real trace show that our algorithm outperforms its variations and the existing one using static social features.

Trajectory Data Mining-Based Routing in DTN-Enabled Vehicular Ad Hoc Networks

Abstract: A delay/disruption tolerant network (DTN) architecture where a “store-carry-forward” strategy is adopted for data transmissions can be utilized in vehicular ad hoc networks (VANETs). The key point of routing in DTN-enabled VANETs is to choose the best node and determine the best time to forward messages. Time-space graph models provide an idea of converting the dynamic routing problems into static ones in deterministic DTNs. But it is a challenge to predict vehicles’ future positions in order to obtain the time-space graph. In this paper, to achieve the cost-efficient and reliable routing in DTN-enabled VANETs, a novel timeliness-aware trajectory data mining algorithm is proposed to predict nodes’ future positions. A sparse time-space graph is then obtained, based on which, two routing heuristics are proposed. Simulation results demonstrate that our proposed routing algorithms ensure low cost and high reliability over time.