A self-adaptive deployment model of UAV cluster for emergency communication network

Equipped with micro wireless sensor nodes, a unmanned aerial vehicle) cluster can form an emergency communication network, which can have several applications such as environmental monitoring, disaster relief, military operations and so on. However, situations where there is excessive aggregation and small amount of dispersion of the unmanned aerial vehicle cluster may occur when the network is formed. To mitigate these, a solution based on a 3D virtual force driven by self-adaptive deployment (named as 3DVFSD) is proposed. As a result, the three virtual forces of central gravity, uniform force, and boundary constraint force are combined to act on each node of the communication network. By coordinating the distance between the nodes, especially the threshold of the distance between the boundary node and the boundary, the centralized nodes can be relatively dispersed. Meanwhile, the nodes can be prevented from being too scattered by constraining the distance from the boundary node to the end. The simulation results show that the 3DVFSD algorithm is superior to the traditional virtual force-driven deployment strategy in terms of convergence speed, coverage, and uniformity.

Sliding Dynamics and Bifurcations in the Extended Nonsmooth Filippov Ecosystem

We propose a nonsmooth Filippov refuge ecosystem with a piecewise saturating response function and analyze its dynamics. We first investigate some key elements to our model which include the sliding segment, the sliding mode dynamics and the existence of equilibria which are classified into regular/virtual equilibrium, pseudo-equilibrium, boundary equilibrium and tangent point. In particular, we consider how the existence of the regular equilibrium and the pseudo-equilibrium are related. Then we study the stability of the standard periodic solution (limit cycle), the sliding periodic solutions (grazing or touching cycle) and the dynamics of the pseudo equilibrium, using quantitative analysis techniques related to nonsmooth Filippov systems. Furthermore, as the threshold value is varied, the model exhibits several complex bifurcations which are classified into equilibria, sliding mode, local sliding (boundary node and focus) and global bifurcations (grazing or touching). In conclusion, we discuss the importance of the refuge strategy in a biological setting.

Event boundary detection using autonomous agents in a sensor network

We propose a novel approach to event boundary detection, where autonomous agents are deployed in order to minimize the number of transmissions required to discover an event boundary. The goal of our algorithm is to reduce the number of non-boundary node transmissions (i.e. nodes within the event area and not within transmission distance to the boundary), since the sensory data from these nodes are not required for event boundary detection. The algorithm works by first randomly generating a fraction of agents within the event nodes, then discovering and mapping the boundary, and finally reporting the aggregated results to the user. Simulations demonstrate that the algorithm exhibits O(n) efficiency relationship with the event area, which is an improvement over existing methods that show O(n²) relationships. Furthermore, we demonstrate that the boundary of an event may be successfully mapped using the proposed algorithm.

Event boundary detection using autonomous agents in a sensor network

We propose a novel approach to event boundary detection, where autonomous agents are deployed in order to minimize the number of transmissions required to discover an event boundary. The goal of our algorithm is to reduce the number of non-boundary node transmissions (i.e. nodes within the event area and not within transmission distance to the boundary), since the sensory data from these nodes are not required for event boundary detection. The algorithm works by first randomly generating a fraction of agents within the event nodes, then discovering and mapping the boundary, and finally reporting the aggregated results to the user. Simulations demonstrate that the algorithm exhibits O(n) efficiency relationship with the event area, which is an improvement over existing methods that show O(n²) relationships. Furthermore, we demonstrate that the boundary of an event may be successfully mapped using the proposed algorithm.

Non-smooth Dynamics Emerging from Predator-driven Discontinuous Prey Dispersal

In ecology, the refuge protection of the prey plays a significant role in the dynamics of the interactions between prey and predator. In this paper, we investigate the dynamics of a non-smooth prey-predator mathematical model characterized by density-dependent intermittent refuge protection of the prey. The model assumes the population density of the predator as an index for the prey to decide on when to avail or discontinue refuge protection, representing the level of apprehension of the prey by the predators. We apply Filippov's regularization approach to study the model and obtain the sliding segment of the system. We obtain the criterion for the existence of the regular or virtual equilibria, boundary equilibrium, tangent points, and pseudo-equilibria of the Filippov system. The conditions for the visibility (or invisibility) of the tangent points are derived. We investigate the regular or virtual equilibrium bifurcation, boundary-node bifurcation and pseudo-saddle-node bifurcation. Further, we examine the effects of dispersal delay on the Filippov system associated with prey vigilance in identifying the predator population density. We observe that the hysteresis in the Filippov system produces stable limit cycles around the predator population density threshold in some bounded region in the phase plane. Moreover, we find that the level of apprehension and vigilance of the prey play a significant role in their refuge-dispersion dynamics.

Detecting overlapping communities using ensemble-based distributed neighbourhood threshold method in social networks

In this paper, we have proposed a novel overlapping community detection algorithm based on an ensemble approach with a distributed neighbourhood threshold method (EnDNTM). EnDNTM uses pre-partitioned disjoint communities generated by the ensemble mechanism and then analyzes the neighbourhood distribution of boundary nodes in disjoint communities to detect overlapping communities. It is a form of seed-based global method since boundary nodes are considered as seeds and become the starting point for detecting overlapping communities. A threshold value for each boundary node is used as the minimum influence by the neighbours of a node in order to determine its belongingness to any community. The effectiveness of the EnDNTM algorithm has been demonstrated by testing with five synthetic benchmark datasets and fifteen real-world datasets. The performance of the EnDNTM algorithm was compared with seven overlapping community detection algorithms. The F1-score, normalized mutual information ONMI and extended modularity Qo⁢v metrics were used to measure the quality of the detected communities. EnDNTM outperforms comparable algorithms on 4 out of 5 synthetic benchmarks datasets, 11 out of 15 real world datasets and gives comparable results with the remaining datasets. Experiments on various synthetic and real world datasets reveal that for a majority of datasets, the proposed ensemble-based distributed neighbourhood threshold method is able to select the best disjoint clusters produced by a disjoint method from a collection of methods for detecting overlapping communities.

The Theory and New Unified Formulas of Displacement-Type Local Absorbing Boundary Conditions

ABSTRACT A series of classical absorbing boundary conditions (ABCs), including paraxial-approximation ABCs, Liao’s multi-transmitting formula (MTF), Higdon ABCs, and some other related techniques, have the common feature that the motion of an arbitrary artificial boundary node at each timestep is directly predicted from the motions of some adjacent nodes at several previous timesteps. They are expressed in somewhat equivalent forms, contain similar control parameters, and have comparable accuracy and stability in numerical simulations. This study develops a theoretical framework called displacement-type (a more exact name would be “prediction-type” or “extrapolation-type”) local ABCs to merge these boundary conditions. The idea of this theory mainly originates from the versatility of MTF, which uses a unified formula to approximate the propagation of outgoing waves through each boundary node. This idea can be generalized to other displacement-type local ABCs to unify their expressions and to optimize their applications. These ABCs have two basic control parameters; one is the boundary order, and the other is adjustable computational wave velocities. Considering the poor performance of paraxial ABCs and the slight imperfections in MTF and Higdon ABCs, we propose two new unified formulas to be the starting points of expressing, evaluating, and applying displacement-type local ABCs. One formula is an optimized MTF by introducing various computational wave velocities. The other formula is a generalized Higdon boundary formula, which is established in a unified local coordinate and uses the adjustable computational wave velocities. The rule of choosing boundary parameters for the absorption of acoustic and elastic waves is discussed in detail. Numerical tests validate the proposed theory and formulas. Issues on numerical stability are briefly reviewed and tested in simulation examples. This is still an active research topic related to displacement-type local ABCs.

Distributed Extended Kalman Filtering Based Techniques for 3-D UAV Jamming Localization

Wireless networks are vulnerable to jamming attacks. Jamming in wireless communication becomes a major research problem due to ease in Unmanned Aerial Vehicle (UAV) launching and blocking of communication channels. Jamming is a subset of Denial of Service Attack (DoS) and an intentional interference where the malicious node disrupts the wireless communication by increasing the noise at the receiver node through transmission interference signal towards the target channel. In this work, the considered jammer is a UAV hovering around the target area to block the communication channel between two transceivers. We proposed a three-dimensional (3-D) UAV jamming localization scheme to track and detect the jammer position at each time step by employing a single boundary node observer. For this purpose, we developed two distributed Extended Kalman Filter (EKF) based schemes: (1) the Distributed EKF (DEKF) scheme using the information of the received power from the jammer at a single nearby boundary node only and (2) Distance Ratio aided Distributed EKF (DEKF-DR) based scheme utilizing an edge node in addition to a single boundary node. Extensive simulations are conducted in order to evaluate the performance of the proposed distributed algorithms for a 3-D trajectory and compared with that of the conventional Centralized EKF (EKF-Centr) based method (which is also modified for the 3-D scenario). The results show the clear supremacy of the proposed distributed algorithms with much lesser complexity in contrast to the conventional EKF-Centr technique.