Diagnosability is often considered as an important factor for measuring the self-diagnostic ability of network systems. However, classic system-level diagnosis focuses only on processor faults and ignores the objective reality of communication faults. Under real circumstances, missing edges and node failures usually occur simultaneously in multiprocessor systems (called hybrid fault circumstances). Therefore, it is important to study the diagnosability of multiprocessor systems under hybrid fault circumstances. In this paper, we propose several diagnosabilities of interconnection networks with missing edges and faulty nodes. By exploring some important relationships between diagnosability and the minimum degree of a network under hybrid fault circumstances, we present and prove the diagnosability of several classic interconnection networks, including BC (bijective connection) networks, star graphs, folded hypercubes, exchanged hypercubes, exchanged crossed cubes, k-ary n-cubes, bubble-sort star graphs and balanced hypercubes, with missing edges and broken-down nodes under the PMC (Preparata, Metze and Chien) and MM^* (Maeng and Malek) models.

In this paper, we jointly consider the inhomogeneity and spatial dimension in large scale wireless networks. We study the effects of topology on the throughput capacity. This problem is inherently difficult since it is complex to handle the interference caused by simultaneous transmission. To solve this problem, we, according to the inhomogeneity of topology, divide the transmission into intra-cluster transmission and inter-cluster transmission. For the intra-cluster transmission, a spheroidal percolation model is constructed. The spheroidal percolation model guarantees a constant rate when a power control strategy is adopted. We also propose a cube percolation mode for the inter-cluster transmission. Different from the spheroidal percolation model, a constant transmission rate can be achieved without power control. For both transmissions, we propose a routing scheme with five phases. By comparing the achievable rate of each phase, we get the rate bottleneck, which is the throughput capacity of the network.

Unmanned aerial vehicles (UAV) can capture multiview images of large-scale scenes, and then using aerial light field (ALF)-rendering technology, they can render high-quality, large-scale 3D scenes. However, the reconstruction of large-scale scenes poses challenges, such as rendering distortion and high memory consumption. In this article, we study the multiview image-capturing and novel view-rendering method of UAV sampling to address these issues. First, we present an ALF sampling model using the spectral analysis of light field and obtain an exact spectrum expression of the ALF. Through the spectral support of ALF, we determine the bandwidth and calculate the minimum required UAV sampling rate. Finally, we demonstrate that our sampling and rendering methods can improve the rendering quality of UAV 3D reconstruction and reduce the minimum sampling rate.

We consider a wireless multi-hops networks in which each node desires to secure transmit message. To guarantee secure transmission, we employ an independent randomization encoding strategy to encode the confidential message. We formulate the problem as network utility maximization. Based on the secure communication strategy, we firstly propose a simple and provable dynamic control algorithm for the case that the length of secrecy codewords is infinite. The control algorithm not only satisfies end-to-end perfect secrecy constraint, but also keeps the network stability. Next, we further consider the case that a finite length of secrecy codewords is performed, in which the possibility of perfect secrecy is eliminated. For this case, we develop an improved control algorithm, subject to network stability and secrecy outage requirement. On the basis of Lyapunov optimization method, we obtain the optimal algorithm, which is decomposed into end-to-end secrecy encoding, flow control and routing scheduling. The simulation results show that both of the proposed algorithms can achieve an utility result, arbitrarily close to optimal value. Finally, the performance of the proposed control policies are validated with various network conditions.

We investigate the secrecy throughput of inhomogeneous wireless network, especially in cases of independent and uniform eavesdropper with single antenna and multiple antennas. Towards the inhomogeneous distribution of legitimate nodes, we novelly construct a circular percolation model under the idea of transforming “inhomogeneous” to “homogeneous.” Correspondingly, the information is transmitted by two ways: intracluster transmission and intercluster transmission. For intracluster transmission, a per-node secrecy throughput of $\mathrm{\Omega }(\sqrt{\mathit{1}/n^{\mathit{1}-v}(\mathit{1}-v)\text{log}n})$ is derived by circular percolation model, where n and $n^v$ represent the number of nodes and clusters in the network, respectively. As for intercluster case, a connection called “information pipelines” is built. Then the per-node secrecy throughput of $\mathrm{\Omega }\left(\sqrt{\underset{\_}{\mathrm{\Phi }}}/\sqrt{n}\right)$ can be obtained, where $\underset{\_}{\mathrm{\Phi }}$ denotes the minimum node density in the network. Moreover, when the eavesdropper is equipped with $\mathrm{\Psi }(n)$ antennas, the per-node secrecy throughput of $\mathrm{\Omega }(\sqrt{\mathit{1}/n^{\mathit{1}-v}(\mathit{1}-v)\text{log}n}{\mathrm{\Psi }}^{-\mathit{2}/\alpha }(n))$ and $\mathrm{\Omega }((\sqrt{\underset{\_}{\mathrm{\Phi }}}/\sqrt{n}){\mathrm{\Psi }}^{-\mathit{2}/\alpha }(n))$ is achieved for intracluster and intercluster transmission, respectively.