Individual Node Level Research Articles

SideKnot: Edge bundling for uncovering relation patterns in graphs

The node-link diagram is an intuitive way to depict a graph and present relationships between entities. Addressing the visual clutter induced by edge crossing and node-edge overlapping is a challenging task as the size of graph outgrows the visualization space. Many edge bundling methods are proposed to disclose high-level edge patterns. Though previous methods can successfully reveal the skeleton graph structure, the relation patterns at the individual node level can be overlooked. In addition, most edge bundling algorithms are computationally complex, which prevents them from scaling up for extremely large graphs. In this article, we extend SideKnot, an efficient edge bundling method to cluster and knot edges at the node side. Our proposed method is light, runs faster than most existing algorithms, and can reveal the relation patterns at the individual node level. Our results show that SideKnot can disclose a node's standing in the graph as well as the directional connection patterns to its peers.

Stability in flux: community structure in dynamic networks

The structure of many biological, social and technological systems can usefully be described in terms of complex networks. Although often portrayed as fixed in time, such networks are inherently dynamic, as the edges that join nodes are cut and rewired, and nodes themselves update their states. Understanding the structure of these networks requires us to understand the dynamic processes that create, maintain and modify them. Here, we build upon existing models of coevolving networks to characterize how dynamic behaviour at the level of individual nodes generates stable aggregate behaviours. We focus particularly on the dynamics of groups of nodes formed endogenously by nodes that share similar properties (represented as node state) and demonstrate that, under certain conditions, network modularity based on state compares well with network modularity based on topology. We show that if nodes rewire their edges based on fixed node states, the network modularity reaches a stable equilibrium which we quantify analytically. Furthermore, if node state is not fixed, but can be adopted from neighbouring nodes, the distribution of group sizes reaches a dynamic equilibrium, which remains stable even as the composition and identity of the groups change. These results show that dynamic networks can maintain the stable community structure that has been observed in many social and biological systems.

Navigating networks with limited information

We study navigation with limited information in networks and demonstrate that many real-world networks have a structure which can be described as favoring communication at short distance at the cost of constraining communication at long distance. This feature, which is robust and more evident with limited than with complete information, reflects both topological and possibly functional design characteristics. For example, the characteristics of the networks studied derived from a city and from the Internet are manifested through modular network designs. We also observe that directed navigation in typical networks requires remarkably little information on the level of individual nodes. By studying navigation or specific signaling, we take a complementary approach to the common studies of information transfer devoted to broadcasting of information in studies of virus spreading and the like.

Tasking Distributed Sensor Networks

Distributed wireless sensor networks provide significant new capabilities for automatically collecting and analyzing data from physical environments. Such sensor networks gather and analyze data in response to queries posed by users of the network. By using more sensor nodes than is strictly necessary to cover an area, these sensor networks can provide reliable information, tolerate many types of faults, and have a long effective lifetime. Like most wireless systems, however, these sensor networks must effectively manage power consumption to achieve a satisfactory system lifetime. Power management at the node level, including low power hardware and power aware operating systems, can provide significant savings in power consumption. In this paper, we present algorithms for managing power at the distributed system level, rather than just at the individual node level. These distributed algorithms determine which set of sensor nodes will be tasked with a given user query and which sensor nodes will remain in an idle state conserving power. The goal of the algorithms is to extend the effective service time of the entire network. In this paper, we give a theoretical analysis of these algorithms along with extensive simulation results.

Characteristics of Reproductive Abortion in Soybean1

The abortion of reproductive plant parts is an important, but not well understood, part of the yield production process in many crop plants. The objective of this research was to characterize the effects of growth stage and timing on the abortion process of soybean [Glycine max (L.) Merr.] flowers exhibiting variation in abortion. Soybean plants were grown in a greenhouse (cv. McCall) and for 3 yrs in the field (cv. Kent). The soil types were a Donerail silt loam (Typic Arguidofl), Maury silt loam (Typic Paleudalf), and a Lanton silt loam (Cumulic Haplaquolls). Fully‐opened flowers located on nodes from the middle of the main stem were marked during early (R1) and late (R3) flowering and then observed for 2 or 3 weeks to determine the extent and timing of flower abortion. Defoliation and three different depodding treatments were used to alter abortion. Nineteen percent of the early flowers aborted (failed to produce seed bearing pod) in the greenhouse, but 31 to 48% aborted over yrs in the field. Abortion of late flowers varied from 76 to 92% in two greenhouse experiments and from 69 to 90% in the three field experiments. The abortion process occurred more rapidly in the greenhouse where much of the abortion was apparent by 6 days after flower opening (DAFO), compared with the field where less than 50% of the abortion was apparent by 10 DAFO. The three depodding treatments decreased and defoliation increased flower abortion. Removing all pods from a plant except those at one node, reduced late flower abortion at that node from 69 to 54%. However, removing all pods from only one node of the plant reduced abortion at that node from 69 to 36%. The results of these experiments suggest that the processes controlling abortion operate at the individual node level and that the whole plant source‐sink ratio is of secondary importance.