@article{zhao_holder_chen_xie_cao_chi_xia_2019, title={Facile Synthesis of Pt Icosahedral Nanocrystals with Controllable Sizes for the Evaluation of Size-Dependent Activity toward Oxygen Reduction}, volume={11}, ISSN={["1867-3899"]}, DOI={10.1002/cctc.201900239}, abstractNote={Abstract}, number={10}, journal={CHEMCATCHEM}, author={Zhao, Ming and Holder, Joseph and Chen, Zitao and Xie, Minghao and Cao, Zhenming and Chi, Miaofang and Xia, Younan}, year={2019}, month={May}, pages={2458–2463} }
 @article{li_zhao_wang_2013, title={Internode Mobility Correlation for Group Detection and Analysis in VANETs}, volume={62}, ISSN={["1939-9359"]}, DOI={10.1109/tvt.2013.2264689}, abstractNote={Recent studies on mobility-assisted schemes for routing and topology control and on mobility-induced link dynamics have presented significant findings on the properties of a pair of nodes (e.g., the intermeeting time and link life time) or a group of nodes (e.g., network connectivity and partitions). In contrast to the study on the properties of a set of nodes rather than individuals, many works share a common ground with respect to node mobility, i.e., independent mobility in multihop wireless networks. Nonetheless, in vehicular ad hoc networks (VANETs), mobile devices installed on vehicles or held by humans are not isolated; however, they are dependent on each other. For example, the speed of a vehicle is influenced by its close-by vehicles, and vehicles on the same road move at similar speeds. Therefore, the gap between our understanding of the impact of independent mobility and our interest in the properties of correlated mobility in VANETs, along with the real systems altogether, declare an interesting question. How can we measure the internode mobility correlation, such as to uncover the node groups and network components, and explore their impact on link dynamics and network connectivity? Bearing this question in mind, we first examine several traces and find that node mobility exhibits spatial locality and temporal locality correlations, which are closely related to node grouping. To study the properties of these groups on the fly, we introduce a new metric, i.e., dual-locality ratio (DLR), which quantifies mobility correlation of nodes. In light of taking spatial and temporal locality dimensions into account, the DLR can be used to effectively identify stable user groups, which in turn can be used for network performance enhancement.}, number={9}, journal={IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY}, author={Li, Yujin and Zhao, Ming and Wang, Wenye}, year={2013}, month={Nov}, pages={4590–4601} }
 @inproceedings{li_zhao_wang_2011, title={Intermittently connected vehicle-to-vehicle networks: Detection and analysis}, DOI={10.1109/glocom.2011.6134395}, abstractNote={Vehicular Adhoc Networks (VANETs) are dedicated to improve the safety and efficiency of transportation systems through vehicle to vehicle or vehicle to road side communications. VANETs exhibit dynamic topology and intermittent connectivity due to high vehicle mobility. These distinguished features declare a challenging question: how to detect on the fly vehicular networks such that we can explore mobility-assisted message dissemination and topology control in VANETs. As being closely related to network dynamics, vehicle mobility could be explored to uncover network structure. In this paper, we have observed that mobility of vehicle, rather than being random, shows \emph{temporal locality} (i.e., frequently visiting several communities like home and office), and \emph{spatial locality} (i.e., velocity constrained by road layout and nearby vehicles). We first examine temporal locality using a campus trace, then measure temporal locality similarity between two vehicles based on the relative entropy of their location preferences. By further incorporating spatial locality similarity, we introduce a new metric, namely \emph{dual locality ratio} (DLR), which represents the mobility correlation of vehicles. Simulation results show that DLR can effectively identify dynamic vehicular network structures. We also demonstrate applications of DLR for improving performances of data forwarding and clustering in vehicle-to-vehicle networks.}, booktitle={2011 ieee global telecommunications conference (globecom 2011)}, author={Li, Y. J. and Zhao, M. and Wang, Wenye}, year={2011} }
 @article{zhao_wang_2009, title={A unified mobility model for analysis and simulation of mobile wireless networks}, volume={15}, ISSN={["1572-8196"]}, DOI={10.1007/s11276-007-0055-4}, number={3}, journal={WIRELESS NETWORKS}, author={Zhao, Ming and Wang, Wenye}, year={2009}, month={Apr}, pages={365–389} }
 @inproceedings{zhao_wang_2006, title={A novel semi-Markov smooth mobility model for mobile ad hoc networks.}, DOI={10.1109/glocom.2006.940}, abstractNote={Existing random mobility models have their limitations such as speed decay and sharp turn which have been demonstrated by the previous studies. More importantly, mobility models need to mimic the movements that abide by the physical law for accurate analysis and simulations of mobile networks. Therefore, in this paper, we propose a novel mobility model, semi-Markov smooth (SMS) model. Each SMS movement includes three consecutive phases: speed up phase, middle smooth phase, and slow down phase. Thus, the entire motion in the SMS model is smooth and consistent with the moving behaviors in real environment. Through steady state analysis, we demonstrate that SMS model has no average speed decay problem and always maintains a uniform spatial node distribution. The analytical results are validated by extensive simulation experiments. In addition, we compare the simulation results on link lifetime and percentage of node degree with random waypoint model, Gauss-Markov model and the proposed SMS model.}, booktitle={Globecom 2006 - 2006 ieee global telecommunications conference}, author={Zhao, M. and Wang, Wenye}, year={2006} }
 @inproceedings{wang_zhao, title={Joint effects of radio channels and node mobility on link dynamics in wireless networks}, booktitle={27th ieee conference on computer communications (infocom), vols 1-5}, author={Wang, W. Y. and Zhao, M.}, pages={1606–1614} }