Secrecy rate analysis of UAV-enabled mmWave networks using matern hardcore point processes

IEEE Communications aided by low-altitude unmanned aerial vehicles (UAVs) have emerged as an effective solution to provide large coverage and dynamic capacity for both military and civilian applications, especially in unexpected scenarios. However, because of their broad coverage, UAV communications are prone to passive eavesdropping attacks. This paper analyzes the secrecy performance of UAVs networks at the millimeter wave (mmWave) band and takes into account unique features of air-toground channels and practical constraints of UAV deployment. To be specific, it explores the 3D antenna gain in the air-toground links and uses the Matérn hardcore point process to guarantee the safety distance between the randomly deployed UAV base stations. In addition, we propose the transmit jamming strategy to improve the secrecy performance in which part of UAVs send jamming signals to confound the eavesdroppers. Simulation results verify our analysis and demonstrate the impact of different system parameters on the achievable secrecy rate. It is also revealed that optimizing the density of jamming UAVs will significantly improve security of UAV-enabled networks

Blockchain-empowered decentralized storage in air-to-ground industrial networks

Blockchain has created a revolution in digital networking by using distributed storage, cryptographic algorithms, and smart contracts. Many areas are benefiting from this technology, including data integrity and security, as well as authentication and authorization. Internet of Things (IoTs) networks often suffers from such security issues, which is slowing down wide-scale adoption. In this paper, we describe the employing of blockchain technology to construct a decentralized platform for storing and trading information in the air-to-ground IoT heterogeneous network. To allow both air and ground sensors to participate in the decentralized network, we design a mutual-benefit consensus process to create uneven equilibrium distributions of resources among the participants. We use a Cournot model to optimize the active density factor set in the heterogeneous air network and then employ a Nash equilibrium to balance the number of ground sensors, which is influenced by the achievable average downlink rate between the air sensors and the ground supporters. Finally, we provide numerical results to demonstrate the beneficial properties of the proposed consensus process for air-to-ground networks and show the maximum active sensor's density utilization of air networks to achieve a high quality of service

A efficient mapping algorithm with novel node-ranking approach for embedding virtual networks

Virtual network embedding (VNE) problem has been widely accepted as an important aspect in network virtualization (NV) area: how to efficiently embed virtual networks, with node and link resource demands, onto the shared substrate network that has finite network resources. Previous VNE heuristic algorithms, only considering single network topology attribute and local resources of each node, may lead to inefficient resource utilization of the substrate network in the long term. To address this issue, a topology attribute and global resource-driven VNE algorithm (VNE-TAGRD), adopting a novel node-ranking approach, is proposed in this paper. The novel node-ranking approach, developed from the well-known Google PageRank algorithm, considers three essential topology attributes and global network resources information before conducting the embedding of given virtual network request (VNR). Numerical simulation results reveal that the VNE-TAGRD algorithm outperforms five typical and latest heuristic algorithms that only consider single network topology attribute and local resources of each node, such as long-term average VNR acceptance ratio and average revenue to cost ratio

Performance analysis of cache-enabled millimeter wave small cell networks

CCBY Millimeter wave (mmWave) small-cell networks can provide high regional throughput, but the backhaul requirement has become a performance bottleneck. This paper proposes a hybrid system that combines traditional backhaul-connected small base stations (SBSs) and cache-enabled SBSs to achieve the maximum area spectral efficiency (ASE) while saving backhaul consumption in mmWave small cell networks. We derive and compare the ASE results for both the traditional and hybrid networks, and also show that the optimal content placement to maximize ASE is to cache the most popular contents. Numerical results demonstrate the performance improvement of deploying cache-enabled SBSs. Furthermore, given a total caching capacity, it is revealed that there is a tradeoff between the cache-enabled SBSs density and individual cache size to maximize the ASE

A novel optimal mapping algorithm with less computational complexity for virtual network embedding

IEEE Network Virtualization (NV) is widely accepted as one enabling technology for future network, which enables multiple Virtual Networks (VNs) with different paradigms and protocols to coexist on the shared Substrate Network (SN). One key challenge in network virtualization is Virtual Network Embedding (VNE), which maps a virtual network onto the shared SN. Since VNE is NP-hard, existing efforts mainly focus on proposing heuristic algorithms that try to achieve feasible VN embedding in reasonable time, consequently the resulted embedding is not optimal. To tackle this difficulty, we propose a candidate assisted (CAN-A) optimal VNE algorithm with lower computational complexity. The key idea of the CAN-A algorithm lies in constructing the candidate substrate node subset and the candidate substrate path subset before embedding. This reduces the mapping execution time substantially without performance loss. In the following embedding, four types of node and link constraints are considered in the CAN-A algorithm, making it more applicable to realistic networks. Simulation results show that the execution time of CAN-A is hugely cut down compared with pure VNE-MIP algorithm. CAN-A also outperforms the typical heuristic algorithms in terms of other performance indices, such as the average virtual network request (VNR) acceptance ratio and the average virtual link propagation delay