@article{xing_wang_2011, title={Toward robust multi-hop data forwarding in large scale wireless networks}, volume={55}, ISSN={["1872-7069"]}, DOI={10.1016/j.comnet.2011.04.014}, abstractNote={Design of robust network topology is an essential issue in large-scale multi-hop wireless networks since data packets are forwarded through intermediate nodes between source and destination, especially in the presence of non-cooperative nodes. Traditionally, topology design aims at generating network topology with high node degree, maximum throughput, and mitigation of malicious attacks. In this paper, we formulate a novel topology control problem as achieving optimal topology which maximizes network robustness against data forwarding distortion (DFD) in which a relay node may be compliant in route discovery, but drop or delay packets as non-cooperative nodes. Such node misbehavior can degrade network performance dramatically, without being detected by routing protocols and countermeasures. Therefore, we propose to design a network topology and data forwarding algorithms, namely PROACtive, in order to distribute data packets among cooperative nodes only, subject to k-connectivity constraint. Through analysis and simulations, we show that there exists a trade-off between achieving network robustness and k-connected with high probability (w.h.p.). By using distributed measurement schemes, data packets can be forwarded with low message complexity Θ(N), and improves network goodput significantly in different network scenarios.}, number={11}, journal={COMPUTER NETWORKS}, author={Xing, Fei and Wang, Wenye}, year={2011}, month={Aug}, pages={2608–2621} }
 @article{xing_wang_2008, title={On the devolution of large-scale sensor networks in the presence of random failures}, ISBN={["978-1-4244-2074-2"]}, ISSN={["1550-3607"]}, DOI={10.1109/icc.2008.439}, abstractNote={In battery-constrained large-scale sensor networks, nodes are prone to random failures due to various reasons, such as energy depletion and hostile environment. Random failures can substantially impact the communication connectivity, which in turn impairs the sensing coverage. Redeploying additional sensors is one effective way to maintain the connectivity; however, it may be infeasible and costly to replace failed sensors one by one. When should a redeployment be conducted is an interesting and important question in designing resilient sensor networks. In this paper, we tackle this problem by investigating the devolution process of large-scale sensor networks. We first define a new metric called the first partition time, which is the first time that a network starts to discomposes to multiple isolated small components. Then we analyze the devolution process in a geometric random graph from a percolation-based connectivity perspective and obtain the condition under which the graph is not percolated. Finally, we find out that the lower bound of the first partition time depends on the node lifetime distribution and should be of the order between log (log n) and (log n)1/rho for rho > 1. This result provides a theoretical upper bound of the latest time that a redeployment has to be carried out.}, journal={2008 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS, PROCEEDINGS, VOLS 1-13}, author={Xing, Fei and Wang, Wenye}, year={2008}, pages={2304–2308} }
 @inproceedings{xing_wang_2006, title={Modeling and analysis of connectivity in mobile ad hoc networks with misbehaving nodes}, DOI={10.1109/icc.2006.254994}, abstractNote={Mobile ad hoc networks are vulnerable to malicious attacks and failures due to their unique features, such as node mobility and dynamic network topology. The design and evaluation of routing protocols and topology control require sound analysis on network connectivity and node behaviors. However, little work has been done on how node misbehaviors affect network connectivity. Modeling and analysis of node misbehavior involves many challenges such as multiple failures caused by selfishness, mobility, and potential Denial of Service attacks. Thus, we propose a novel model to characterize node misbehaviors based on a semi-Markov process. In particular, we analyze the impact of node misbehavior on network connectivity in a mobile ad hoc network stochastically. Numerical results based on analysis and simulations are provided to demonstrate the effectiveness of our approach and results.}, booktitle={2006 ieee international conference on communications, vols 1-12}, author={Xing, F. and Wang, Wenye}, year={2006}, pages={1879–1884} }