Airborne Directional Networking: Topology Control Protocol Design

This research identifies and evaluates the impact of several architectural design choices in relation to airborne networking in contested environments related to autonomous topology control. Using simulation, we evaluate topology reconfiguration effectiveness using classical performance metrics for different point-to-point communication architectures. Our attention is focused on the design choices which have the greatest impact on reliability, scalability, and performance. In this work, we discuss the impact of several practical considerations of airborne networking in contested environments related to autonomous topology control modeling. Using simulation, we derive multiple classical performance metrics to evaluate topology reconfiguration effectiveness for different point-to-point communication architecture attributes for the purpose of qualifying protocol design elements

Intelligent detection of black hole attacks for secure communication in autonomous and connected vehicles

Detection of Black Hole attacks is one of the most challenging and critical routing security issues in vehicular ad hoc networks (VANETs) and autonomous and connected vehicles (ACVs). Malicious vehicles or nodes may exist in the cyber-physical path on which the data and control packets have to be routed converting a secure and reliable route into a compromised one. However, instead of passing packets to a neighbouring node, malicious nodes bypass them and drop any data packets that could contain emergency alarms. We introduce an intelligent black hole attack detection scheme (IDBA) tailored to ACV. We consider four key parameters in the design of the scheme, namely, Hop Count, Destination Sequence Number, Packet Delivery Ratio (PDR), and End-to-End delay (E2E). We tested the performance of our IDBA against AODV with Black Hole (BAODV), Intrusion Detection System (IdsAODV), and EAODV algorithms. Extensive simulation results show that our IDBA outperforms existing approaches in terms of PDR, E2E, Routing Overhead, Packet Loss Rate, and Throughput

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Wireless social networks: a survey of recent advances, applications and challenges

With the ubiquitous use of smartphones and other connected pieces of equipment, the number of devices connected to the Internet is exponentially growing. This will test the efficiency of the envisioned 5G network architectures for data acquisition and its storage. It is a common observation that the communication between smart devices is typically influenced by their social relationship. This suggests that the theory of social networks can be leveraged to improve the quality of service for such communication links. In fact, the social networking concepts of centrality and community have been investigated for an efficient realization of novel wireless network architectures. This work provides a comprehensive introduction to social networks and reviews the recent literature on the application of social networks in wireless communications. The potential challenges in communication network design are also highlighted, for a successful implementation of social networking strategies. Finally, some future directions are discussed for the application of social networking strategies to emerging wireless technologies such as non-orthogonal multiple access and visible light communications

A Study of Routing Protocols for Ad-Hoc Network Based on Named Data Networking

電気通信大学202

Efficient Spectrum Management for Mobile Ad Hoc Networks

The successful deployment of advanced wireless network applications for defense, homeland security, and public safety depends on the availability of relatively interference-free spectrum. Setup and maintenance of mobile networks for military and civilian first-response units often requires temporary allocation of spectrum resources for operations of finite, but uncertain, duration. As currently practiced, this is a very labor-intensive process with direct parallels to project management. Given the wide range of real-time local variation in propagation conditions, spatial distribution of nodes, and evolving technical and mission priorities current human-in-the loop conflict resolution approaches seem untenable. If the conventional radio regulatory structure is strictly adhered to, demand for spectrum will soon exceed supply. Software defined radio is one technology with potential to exploit local inefficiencies in spectrum usage, but questions regarding the management of such network have persisted for years. This dissertation examines a real-time spectrum distribution approach that is based on principles of economic utility and equilibrium among multiple competitors for limited goods in a free market. The spectrum distribution problem may be viewed as a special case of multi-objective optimization of a constrained resource. A computer simulation was developed to create hundreds of cases of local spectrum crowding, to which simultaneous perturbation simulated annealing (SPSA) was applied as a nominal optimization algorithm. Two control architectures were modeled for comparison, one requiring a local monitoring infrastructure and coordination ("top down") the other more market based ("bottom up"). The analysis described herein indicates that in both cases "hands-off" local spectrum management by trusted algorithms is not only feasible, but that conditions of entry for new networks may be determined a priori, with a degree of confidence described by relatively simple algebraic formulas