Mobile Ad hoc Networks(MANETs) play an important role in emergency communications where network needs to be constructed temporarily and quickly.Since the nodes move randomly,routing protocols must be highly effective ...Mobile Ad hoc Networks(MANETs) play an important role in emergency communications where network needs to be constructed temporarily and quickly.Since the nodes move randomly,routing protocols must be highly effective and reliable to guarantee successful packet delivery.Based on the data delivery structure,most of the existing multicast routing protocols can be classified into two folders:tree-based and mesh-based.We observe that tree-based ones have high forwarding efficiency and low consumptions of bandwidth,and they may have poor robustness because only one link exists between two nodes.As a treebased multicast routing protocol,MAODV(Multicast Ad hoc On-demand Vector) shows an excellent performance in lightweight ad hoc networks.As the load of network increases,QoS(Quality of Service) is degraded obviously.In this paper,we analyze the impact of network load on MAODV protocol,and propose an optimized protocol MAODV-BB(Multicast Ad hoc On-demand Vector with Backup Branches),which improves robustness of the MAODV protocol by combining advantages of the tree structure and the mesh structure.It not only can update shorter tree branches but also construct a multicast tree with backup branches.Mathematical analysis and simulation results both demonstrate that the MAODV-BB protocol improves the network performance over conventional MAODV in heavy load ad hoc networks.展开更多
Gene co-expression networks provide an important tool for systems biology studies. Using microarray data from the Array Express database, we constructed an Arabidopsis gene co-expression network, termed At GGM2014, ba...Gene co-expression networks provide an important tool for systems biology studies. Using microarray data from the Array Express database, we constructed an Arabidopsis gene co-expression network, termed At GGM2014, based on the graphical Gaussian model, which contains 102,644 co-expression gene pairs among 18,068 genes. The network was grouped into 622 gene co-expression modules. These modules function in diverse house-keeping, cell cycle, development, hormone response, metabolism, and stress response pathways. We developed a tool to facilitate easy visualization of the expression patterns of these modules either in a tissue context or their regulation under different treatment conditions. The results indicate that at least six modules with tissue-specific expression pattern failed to record modular regulation under various stress conditions. This discrepancy could be best explained by the fact that experiments to study plant stress responses focused mainly on leaves and less on roots, and thus failed to recover specific regulation pattern in other tissues. Overall, the modular structures revealed by our network provide extensive information to generate testable hypotheses about diverse plant signaling pathways. At GGM2014 offers a constructive tool for plant systems biology studies.展开更多
基金This work is supported by the NSFC （National Natural Science Foundation of China） No. 61371068 and No. 61172130, the National 863 program No.2011AA11A102-04-02 and Shenzhen Technology Research and Development Program No. CXZZ20120830100839333.
文摘Mobile Ad hoc Networks(MANETs) play an important role in emergency communications where network needs to be constructed temporarily and quickly.Since the nodes move randomly,routing protocols must be highly effective and reliable to guarantee successful packet delivery.Based on the data delivery structure,most of the existing multicast routing protocols can be classified into two folders:tree-based and mesh-based.We observe that tree-based ones have high forwarding efficiency and low consumptions of bandwidth,and they may have poor robustness because only one link exists between two nodes.As a treebased multicast routing protocol,MAODV(Multicast Ad hoc On-demand Vector) shows an excellent performance in lightweight ad hoc networks.As the load of network increases,QoS(Quality of Service) is degraded obviously.In this paper,we analyze the impact of network load on MAODV protocol,and propose an optimized protocol MAODV-BB(Multicast Ad hoc On-demand Vector with Backup Branches),which improves robustness of the MAODV protocol by combining advantages of the tree structure and the mesh structure.It not only can update shorter tree branches but also construct a multicast tree with backup branches.Mathematical analysis and simulation results both demonstrate that the MAODV-BB protocol improves the network performance over conventional MAODV in heavy load ad hoc networks.
基金supported by US National Science Foundation grants DBI-0723722 and DBI-1042344 to SPDKUC Davis funds to SPDK
文摘Gene co-expression networks provide an important tool for systems biology studies. Using microarray data from the Array Express database, we constructed an Arabidopsis gene co-expression network, termed At GGM2014, based on the graphical Gaussian model, which contains 102,644 co-expression gene pairs among 18,068 genes. The network was grouped into 622 gene co-expression modules. These modules function in diverse house-keeping, cell cycle, development, hormone response, metabolism, and stress response pathways. We developed a tool to facilitate easy visualization of the expression patterns of these modules either in a tissue context or their regulation under different treatment conditions. The results indicate that at least six modules with tissue-specific expression pattern failed to record modular regulation under various stress conditions. This discrepancy could be best explained by the fact that experiments to study plant stress responses focused mainly on leaves and less on roots, and thus failed to recover specific regulation pattern in other tissues. Overall, the modular structures revealed by our network provide extensive information to generate testable hypotheses about diverse plant signaling pathways. At GGM2014 offers a constructive tool for plant systems biology studies.
