Reconstruction of Network Evolutionary History from Extant Network Topology and Duplication History

Genome-wide protein-protein interaction (PPI) data are readily available thanks to recent breakthroughs in biotechnology. However, PPI networks of extant organisms are only snapshots of the network evolution. How to infer the whole evolution history becomes a challenging problem in computational biology. In this paper, we present a likelihood-based approach to inferring network evolution history from the topology of PPI networks and the duplication relationship among the paralogs. Simulations show that our approach outperforms the existing ones in terms of the accuracy of reconstruction. Moreover, the growth parameters of several real PPI networks estimated by our method are more consistent with the ones predicted in literature.Comment: 15 pages, 5 figures, submitted to ISBRA 201

Energy-aware Dual-path Geographic Routing to Bypass Routing Holes in Wireless Sensor Networks

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this record.Geographic routing has been considered as an attractive approach for resource-constrained wireless sensor networks (WSNs) since it exploits local location information instead of global topology information to route data. However, this routing approach often suffers from the routing hole (i.e., an area free of nodes in the direction closer to destination) in various environments such as buildings and obstacles during data delivery, resulting in route failure. Currently, existing geographic routing protocols tend to walk along only one side of the routing holes to recover the route, thus achieving suboptimal network performance such as longer delivery delay and lower delivery ratio. Furthermore, these protocols cannot guarantee that all packets are delivered in an energy-efficient manner once encountering routing holes. In this paper, we focus on addressing these issues and propose an energy-aware dual-path geographic routing (EDGR) protocol for better route recovery from routing holes. EDGR adaptively utilizes the location information, residual energy, and the characteristics of energy consumption to make routing decisions, and dynamically exploits two node-disjoint anchor lists, passing through two sides of the routing holes, to shift routing path for load balance. Moreover, we extend EDGR into three-dimensional (3D) sensor networks to provide energy-aware routing for routing hole detour. Simulation results demonstrate that EDGR exhibits higher energy efficiency, and has moderate performance improvements on network lifetime, packet delivery ratio, and delivery delay, compared to other geographic routing protocols in WSNs over a variety of communication scenarios passing through routing holes. The proposed EDGR is much applicable to resource-constrained WSNs with routing holes.This work has been partially supported by the National Natural Science Foundation of China (No. 61402343, No. 61672318, No. U1504614, No. 61631013, and No. 61303241), the National Key Research and Development Program (No. 2016YFB1000102), the Natural Science Foundation of Suzhou/Jiangsu Province (No. BK20160385), the EU FP7 QUICK Project (No. PIRSESGA- 2013-612652), and the projects of Tsinghua National Laboratory for Information Science and Technology (TNList)

Energy efficient geographic routing for wireless sensor networks.

A wireless sensor network consists of a large number of low-power nodes equipped with wireless radio. For two nodes not in mutual transmission range, message exchanges need to be relayed through a series of intermediate nodes, which is a process known as multi-hop routing. The design of efficient routing protocols for dynamic network topologies is a crucial for scalable sensor networks. Geographic routing is a recently developed technique that uses locally available position information of nodes to make packet forwarding decisions. This dissertation develops a framework for energy efficient geographic routing. This framework includes a path pruning strategy by exploiting the channel listening capability, an anchor-based routing protocol using anchors to act as relay nodes between source and destination, a geographic multicast algorithm clustering destinations that can share the same next hop, and a lifetime-aware routing algorithm to prolong the lifetime of wireless sensor networks by considering four important factors: PRR (Packet Reception Rate), forwarding history, progress and remaining energy. This dissertation discusses the system design, theoretic analysis, simulation and testbed implementation involved in the aforementioned framework. It is shown that the proposed design significantly improves the routing efficiency in sensor networks over existing geographic routing protocols. The routing methods developed in this dissertation are also applicable to other location-based wireless networks

Enabling SAML for dynamic identity federation management

Proceedings of: The Second IFIP WG 6.8 Joint Conference, WMNC 2009, Gdansk, Poland, September 9-11, 2009Federation in identity management has emerged as a key concept for reducing complexity in the companies and offering an improved user experience when accessing services. In this sense, the process of trust establishment is fundamental to allow rapid and seamless interaction between different trust domains. However, the problem of establishing identity federations in dynamic and open environments that form part of Next Generation Networks (NGNs), where it is desirable to speed up the processes of service provisioning and deprovisioning, has not been fully addressed. This paper analyzes the underlying trust mechanisms of the existing frameworks for federated identity management and its suitability to be applied in the mentioned environments. This analysis is mainly focused on the Single Sign On (SSO) profile. We propose a generic extension for the SAML standard in order to facilitate the creation of federation relationships in a dynamic way between prior unknown parties. Finally, we give some details of implementation and compatibility issues

A Nearly Optimal Algorithm for the Geodesic Voronoi Diagram of Points in a Simple Polygon

The geodesic Voronoi diagram of m point sites inside a simple polygon of n vertices is a subdivision of the polygon into m cells, one to each site, such that all points in a cell share the same nearest site under the geodesic distance. The best known lower bound for the construction time is Omega(n+m log m), and a matching upper bound is a long-standing open question. The state-of-the-art construction algorithms achieve O((n+m)log (n+m)) and O(n+m log m log^2n) time, which are optimal for m=Omega(n) and m=O(n/(log^3n)), respectively. In this paper, we give a construction algorithm with O(n+m(log m+log^2 n)) time, and it is nearly optimal in the sense that if a single Voronoi vertex can be computed in O(log n) time, then the construction time will become the optimal O(n+m log m). In other words, we reduce the problem of constructing the diagram in the optimal time to the problem of computing a single Voronoi vertex in O(log n) time

Robotic Wireless Energy Transfer in Dynamic Environments: System Design and Experimental Validation

Wireless energy transfer (WET) is a ground-breaking technology for cutting the last wire between mobile sensors and power grids in smart cities. However, WET only offers effective transmission of energy over a short distance. Robotic WET is an emerging paradigm that mounts the energy transmitter on a mobile robot and navigates the robot through different regions in a large area to charge remote energy harvesters. However, it is challenging to determine the robotic charging strategy in an unknown and dynamic environment due to the uncertainty of obstacles. This article proposes a hardware-in-the-loop joint optimization framework that offers three distinctive features: efficient model updates and re-optimization based on the last-round experimental data; iterative refinement of the anchor list for adaptation to different environments; and verification of algorithms in a high-fidelity Gazebo simulator and a multi-robot testbed. Experimental results show that the proposed framework significantly saves WET mission completion time while satisfying energy harvesting and collision avoidance constraints