Betweenness centrality in dense random geometric networks

Random geometric networks consist of 1) a set of nodes embedded randomly in a bounded domain $\mathcal{V} \subseteq \mathbb{R}^d$ and 2) links formed probabilistically according to a function of mutual Euclidean separation. We quantify how often all paths in the network characterisable as topologically `shortest' contain a given node (betweenness centrality), deriving an expression in terms of a known integral whenever 1) the network boundary is the perimeter of a disk and 2) the network is extremely dense. Our method shows how similar formulas can be obtained for any convex geometry. Numerical corroboration is provided, as well as a discussion of our formula's potential use for cluster head election and boundary detection in densely deployed wireless ad hoc networks.Comment: 6 pages, 3 figure

Free Space Optical Communications: An Overview

Bridging the so-called “last mile” in communication networks has revived keen interest in free-Space Optics (FSO), also known as fiber-free or fiberless optics, which is a technology that transports data via laser technology. It is a line-of-sight technology that currently enables optical transmission up to 2.5 Gbps of data, voice and video through the air at long distances (4km), allowing optical connectivity without deploying fiber-optic cable or securing spectrum licenses. It is moving closer to being a realistic alternative to laying fiber in access networks. This paper presents an introduction to FSO and the current state of its technology

Predictive Analytics Lead to Smarter Self-Organizing Directional Wireless Backbone Networks

Directional wireless systems are becoming a cost-effective approach towards providing a high-speed, reliable, broadband connection for the ubiquitous mobile wireless devices in use today. The most common of these systems consists of narrow-beam radio frequency (RF) and free-space-optical (FSO) links, which offer speeds between 100Mbps and 100Gbps while offering bit-error-rates comparable to fixed fiber optic installations. In addition, spatial and spectral efficiencies are accessible with directional wireless systems that cannot be matched with broadcast systems. The added benefits of compact designs permit the installation of directional antennas on-board unmanned autonomous systems (UAS) to provide network availability to regions prone to natural disasters, in maritime situations, and in war-torn countries that lack infrastructure security. In addition, through the use of intelligent network-centric algorithms, a flexible airborne backbone network can be established to dodge the scalability limitations of traditional omnidirectional wireless networks. Assuring end-to-end connectivity and coverage is the main challenge in the design of directional wireless backbone (DWB) networks. Conflating the duality of these objectives with the dynamical nature of the environment in which DWB networks are deployed, in addition to the standardized network metrics such as latency-minimization and throughput maximization, demands a rigorous control process that encompasses all aspects of the system. This includes the mechanical steering of the directional point-to-point link and the monitoring of aggregate network performance (e.g. dropped packets). The inclusion of processes for topology control, mobility management, pointing, acquisition, and tracking of the directional antennas, alongside traditional protocols (e.g. IPv6) provides a rigorous framework for next-generation mobile directional communication networks. This dissertation provides a novel approach to increase reliability in reconfigurable beam-steered directional wireless backbone networks by predicating optimal network reconfigurations wherein the network is modeled as a giant molecule in which the point-to-point links between two UASs are able to grow and retract analogously to the bonds between atoms in a molecule. This cross-disciplinary methodology explores the application of potential energy surfaces and normal mode analysis as an extension to the topology control optimization. Each of these methodologies provides a new and unique ability for predicting unstable configurations of DWB networks through an understanding of second-order principle dynamics inherent within the aggregate configuration of the system. This insight is not available through monitoring individual link performance. Together, the techniques used to model the DWB network through molecular dynamics are referred to as predictive analytics and provide reliable results that lead to smarter self-organizing reconfigurable beam-steered DWB networks. Furthermore, a comprehensive control architecture is proposed that complements traditional network science (e.g. Internet protocol) and the unique design aspects of DWB networks. The distinct ability of a beam-steered DWB network to adjust the direction of its antennas (i.e. reconfigure) in response to degraded effects within the atmosphere or due to an increased separation of nodes, is not incorporated in traditional network processes such re-routing mechanism, and therefore, processes for reconfiguration can be abstracted which both optimize the physical interconnections while maintaining interoperability with existing protocols. This control framework is validated using network metrics for latency and throughput and compared to existing architectures which use only standard re-routing mechanisms. Results are shown that validate both the analogous molecular modeling of a reconfigurable beam-steered directional wireless backbone network and a comprehensive control architecture which coalesces the unique capabilities of reconfiguration and mobility of mobile wireless backbone networks with existing protocols for networks such as IPv6

Exploring Wireless Data Center Networks: Can They Reduce Energy Consumption While Providing Secure Connections?

Data centers have become the digital backbone of the modern world. To support the growing demands on bandwidth, Data Centers consume an increasing amount of power. A significant portion of that power is consumed by information technology (IT) equipment, including servers and networking components. Additionally, the complex cabling in traditional data centers poses design and maintenance challenges and increases the energy cost of the cooling infrastructure by obstructing the flow of chilled air. Hence, to reduce the power consumption of the data centers, we proposed a wireless server-to-server data center network architecture using millimeter-wave links to eliminate the need for power-hungry switching fabric of traditional fat-tree-based data center networks. The server-to-server wireless data center network (S2S-WiDCN) architecture requires Line-of-Sight (LoS) between servers to establish direct communication links. However, in the presence of interference from internal or external sources, or an obstruction, such as an IT technician, the LoS may be blocked. To address this issue, we also propose a novel obstruction-aware adaptive routing algorithm for S2S-WiDCN. S2S-WiDCN can reduce the power consumption of the data center network portion while not affecting the power consumption of the servers in the data center, which contributes significantly towards the total power consumption of the data center. Moreover, servers in data centers are almost always underutilized due to over-provisioning, which contributes heavily toward the high-power consumption of the data centers. To address the high power consumption of the servers, we proposed a network-aware bandwidth-constrained server consolidation algorithm called Network-Aware Server Consolidation (NASCon) for wireless data centers that can reduce the power consumption up to 37% while improving the network performance. However, due to the arrival of new tasks and the completion of existing tasks, the consolidated utilization profile of servers change, which may have an adverse effect on overall power consumption over time. To overcome this, NASCon algorithm needs to be executed periodically. We have proposed a mathematical model to estimate the optimal inter-consolidation time, which can be used by the data center resource management unit for scheduling NASCon consolidation operation in real-time and leverage the benefits of server consolidation. However, in any data center environment ensuring security is one of the highest design priorities. Hence, for S2S-WiDCN to become a practical and viable solution for data center network design, the security of the network has to be ensured. S2S-WiDCN data center can be vulnerable to a variety of different attacks as it uses wireless links over an unguided channel for communication. As being a wireless system, the network has to be secured against common threats associated with any wireless networks such as eavesdropping attack, denial of services attack, and jamming attack. In parallel, other security threats such as the attack on the control plane, side-channel attack through traffic analysis are also possible. We have done an extensive study to elaborate the scope of these attacks as well as explore probable solutions against these issues. We also proposed viable solutions for the attack against eavesdropping, denial of services, jamming, and control-plane attack. To address the traffic analysis attack, we proposed a simulated annealing-based random routing mechanism which can be adopted instead of default routing in the wireless data center

UAV Based 5G Network: A Practical Survey Study

Unmanned aerial vehicles (UAVs) are anticipated to significantly contribute to the development of new wireless networks that could handle high-speed transmissions and enable wireless broadcasts. When compared to communications that rely on permanent infrastructure, UAVs offer a number of advantages, including flexible deployment, dependable line-of-sight (LoS) connection links, and more design degrees of freedom because of controlled mobility. Unmanned aerial vehicles (UAVs) combined with 5G networks and Internet of Things (IoT) components have the potential to completely transform a variety of industries. UAVs may transfer massive volumes of data in real-time by utilizing the low latency and high-speed abilities of 5G networks, opening up a variety of applications like remote sensing, precision farming, and disaster response. This study of UAV communication with regard to 5G/B5G WLANs is presented in this research. The three UAV-assisted MEC network scenarios also include the specifics for the allocation of resources and optimization. We also concentrate on the case where a UAV does task computation in addition to serving as a MEC server to examine wind farm turbines. This paper covers the key implementation difficulties of UAV-assisted MEC, such as optimum UAV deployment, wind models, and coupled trajectory-computation performance optimization, in order to promote widespread implementations of UAV-assisted MEC in practice. The primary problem for 5G and beyond 5G (B5G) is delivering broadband access to various device kinds. Prior to discussing associated research issues faced by the developing integrated network design, we first provide a brief overview of the background information as well as the networks that integrate space, aviation, and land