Adaptive Monitor Placement for Near Real-time Node Failure Localisation in Wireless Sensor Networks

As sensor-based networks become more prevalent, scaling to unmanageable numbers or deployed in difficult to reach areas, real-time failure localisation is becoming essential for continued operation. Network tomography, a system and application-independent approach, has been successful in localising complex failures (i.e., observable by end-to-end global analysis) in traditional networks. Applying network tomography to wireless sensor networks (WSNs), however, is challenging. First, WSN topology changes due to environmental interactions (e.g., interference). Additionally, the selection of devices for running network monitoring processes (monitors) is an NP-hard problem. Monitors observe end-to-end in-network properties to identify failures, with their placement impacting the number of identifiable failures. Since monitoring consumes more in-node resources, it is essential to minimise their number while maintaining network tomography’s effectiveness. Unfortunately, state-of-the-art solutions solve this optimisation problem using time-consuming greedy heuristics. In this article, we propose two solutions for efficiently applying Network Tomography in WSNs: a graph compression scheme, enabling faster monitor placement by reducing the number of edges in the network, and an adaptive monitor placement algorithm for recovering the monitor placement given topology changes. The experiments show that our solution is at least 1,000× faster than the state-of-the-art approaches and efficiently copes with topology variations in large-scale WSNs.

Spectroscopic Characterization of Mitochondrial G-Quadruplexes

Guanine quadruplexes (G4s) are highly polymorphic four-stranded structures formed within guanine-rich DNA and RNA sequences that play a crucial role in biological processes. The recent discovery of the first G4 structures within mitochondrial DNA has led to a small revolution in the field. In particular, the G-rich conserved sequence block II (CSB II) can form different types of G4s that are thought to play a crucial role in replication. In this study, we decipher the most relevant G4 structures that can be formed within CSB II: RNA G4 at the RNA transcript, DNA G4 within the non-transcribed strand and DNA:RNA hybrid between the RNA transcript and the non-transcribed strand. We show that the more abundant, but unexplored, G6AG7 (37%) and G6AG8 (35%) sequences in CSB II yield more stable G4s than the less profuse G5AG7 sequence. Moreover, the existence of a guanine located 1 bp upstream promotes G4 formation. In all cases, parallel G4s are formed, but their topology changes from a less ordered to a highly ordered G4 when adding small amounts of potassium or sodium cations. Circular dichroism was used due to discriminate different conformations and topologies of nucleic acids and was complemented with gel electrophoresis and fluorescence spectroscopy studies.

Identification of topology changes in power grids via reduced admittance matrix

Frequent changes in power grid topology bring risks to the stable operation of power systems. It is essential to identify changes in the power grid topology quickly and accurately. This paper presents a novel method named network reduction-based topology change identification (NR-TCI) algorithm to identify topology changes in multi-machine power systems. The proposed algorithm can quickly identify power grid topology changes using only phasor measurement unit (PMU) data sampled during the system’s transient process. The NR-TCI algorithm uses the network order reduction method to reduce the order of a bus admittance matrix and then uses PMU measurement data to estimate the reduced admittance matrix by least square method. Finally, the reduced admittance matrix is adopted to find topological information, and the Sherman–Morrison formula is utilized to identify the topology changes. The effectiveness of the proposed NR-TCI algorithm is verified with a case study of a 3 machine 9 bus system in Matlab. In addition, the influence of PMU sampling frequency on the effectiveness of the proposed algorithm is also studied.

Non-uniform ergodic properties of Hamiltonian flows with impacts

The ergodic properties of two uncoupled oscillators, one horizontal and one vertical, residing in a class of non-rectangular star-shaped polygons with only vertical and horizontal boundaries and impacting elastically from its boundaries are studied. We prove that the iso-energy level sets topology changes non-trivially; the flow on level sets is always conjugated to a translation flow on a translation surface, yet, for some segments of partial energies the genus of the surface is strictly greater than $1$ . When at least one of the oscillators is unharmonic, or when both are harmonic and non-resonant, we prove that for almost all partial energies, including the impacting ones, the flow on level sets is uniquely ergodic. When both oscillators are harmonic and resonant, we prove that there exist intervals of partial energies on which periodic ribbons and additional ergodic components coexist. We prove that for almost all partial energies in such segments the motion is uniquely ergodic on the part of the level set that is not occupied by the periodic ribbons. This implies that ergodic averages project to piecewise smooth weighted averages in the configuration space.

ASR-FANET: An adaptive SDN-based routing framework for FANET

Flying ad hoc network (FANET) is widely used in many military, commercial and civilian applications. Compared with mobile adhoc network (MANET) and vehicular ad hoc network (VANET), FANET holds unique characteristics such as high mobility, intermittent links and frequent topology changes, which cause a challenging task in the design of routing protocols. A novel adaptive software defined networking (SDN)-based routing framework for FANET called ASR-FANET is proposed in this article to solve the above challenges. The ASR-FANET framework is mainly composed of three important parts, which are the topology discovery mechanism, statistics gathering mechanism and route computation mechanism. In topology discovery mechanism, the periodic information about network topology is collected, including nodes and links. In statistics gathering mechanism, the status of the wireless network connection and flight statistics are collected. In route computation mechanism, the optimal path is calculated based on link costs. The performance of ASR-FANET framework is also has been evaluated by comprehensive simulations. The simulation results show that proposed framework is much better than other traditional protocols in packet delivery fraction, average end to end delay, normalized routing load, packet loss and throughput.

Disaster Management Using VANET

Disaster management is management of tasks involving responses to emergencies and methods of devising recovery strategies from havocs caused by nature. It assumes paramount importance now as the human surrounding has enormously become unpredictable owing to natural or man-made disasters. Consequence of disaster can be reduced by broadcasting of disaster alert to a defined radius that could be affected by the disaster. The objective of disaster management is to ensure energy economical and reliable communication that is resilient to network topology changes within the area. Vehicular ad hoc network (VANET) is efficiently utilized to transfer the disaster alert information. Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication is used for disseminating the disaster alert message. This study proposes an effective data acquisition from the disaster location, data dissemination to the neighbouring zones and disaster management using VANET technology.

A Topology Identification Method to Enhance the Linear Estimation of Generator Rotor Speeds

<div>This paper proposes a methodology to avoid biased estimations of generator rotor speeds under network topology changes. The algorithm is based on deep neural networks and executes topology processing considering the relevant branches for rotor speed estimations. The proposed technique uses the measurements from the same phasor measurement units (PMUs) needed to carry out generator rotor speed estimations; thus, it does not imply an additional cost for the transmission system operator. The proposed methodology is demonstrated with a centralized and distributed approach, using a modified version of the New England test system and the IEEE 118-bus test system, respectively. The numerical results on both test systems demonstrate the reliability and the low computational burden of the proposed algorithm.</div>

A Topology Identification Method to Enhance the Linear Estimation of Generator Rotor Speeds

<div>This paper proposes a methodology to avoid biased estimations of generator rotor speeds under network topology changes. The algorithm is based on deep neural networks and executes topology processing considering the relevant branches for rotor speed estimations. The proposed technique uses the measurements from the same phasor measurement units (PMUs) needed to carry out generator rotor speed estimations; thus, it does not imply an additional cost for the transmission system operator. The proposed methodology is demonstrated with a centralized and distributed approach, using a modified version of the New England test system and the IEEE 118-bus test system, respectively. The numerical results on both test systems demonstrate the reliability and the low computational burden of the proposed algorithm.</div>