Self-Organizing Directional Wireless Backbone Networks

Directional wireless communications is emerging as a viable, cost-effective technology for rapidly deployable broadband wireless communication infrastructures. This technology provides extremely high data rates through the use of narrow-beam free space optical (FSO) and/or radio-frequency (RF) point-to-point links. The use of directional wireless communications to form flexible backbone networks, which provide broadband connectivity to capacity-limited wireless networks or hosts, promises to circumvent the scalability limitations of traditional wireless networks. The main challenge in the design of directional wireless backbone (DWB) networks is to assure robustness and survivability in a dynamic wireless environment. DWB networks must assure highly available broadband connectivity and be able to regain connectivity in the face of loss or degradation. This dissertation considers the use of topology control to provide assured connectivity in dynamic environments. Topology control is defined as the autonomous network capability to dynamically reconfigure its physical topology. In the case of DWB networks, the physical topology can be reconfigured through 1) redirection of point-to-point links and/or 2) reposition of backbone nodes. Coverage and connectivity are presented as the two most important issues in DWB-based networks. The aim of this dissertation is to provide initial designs for scalable self-organized DWB networks, which could autonomously adapt their physical topology to maximize coverage to terminals or hosts while maintaining robust backbone connectivity. This dissertation provides a novel approach to the topology control problem by modeling communication networks as physical systems where network robustness is characterized in terms of the system's potential energy. In our model, communication links define physical interactions between network nodes. Topology control mechanisms are designed to mimic physical systems' natural reaction to external excitations which drive the network topology to energy minimizing configurations based on local forces exerted on network nodes. The potential energy of a communications network is defined as the total communications energy usage for a given target performance. Accurate link physics models that take into account the variation of the wireless channel due to atmospheric attenuation, turbulence-induced fading, node mobility, and different antenna patterns have been developed in order to characterize the behavior of the potential energy stored at each wireless link in the network. The net force at each backbone node is computed as the negative gradient of the potential energy function at the node's location. Mobility control algorithms are designed to reposition backbone nodes in the direction of the net force. The algorithms developed are completely distributed, show constant time complexity and produce optimal solutions from local interactions, thus proving the system's self-organizing capability

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

Achieving Small World Properties using Bio-Inspired Techniques in Wireless Networks

It is highly desirable and challenging for a wireless ad hoc network to have self-organization properties in order to achieve network wide characteristics. Studies have shown that Small World properties, primarily low average path length and high clustering coefficient, are desired properties for networks in general. However, due to the spatial nature of the wireless networks, achieving small world properties remains highly challenging. Studies also show that, wireless ad hoc networks with small world properties show a degree distribution that lies between geometric and power law. In this paper, we show that in a wireless ad hoc network with non-uniform node density with only local information, we can significantly reduce the average path length and retain the clustering coefficient. To achieve our goal, our algorithm first identifies logical regions using Lateral Inhibition technique, then identifies the nodes that beamform and finally the beam properties using Flocking. We use Lateral Inhibition and Flocking because they enable us to use local state information as opposed to other techniques. We support our work with simulation results and analysis, which show that a reduction of up to 40% can be achieved for a high-density network. We also show the effect of hopcount used to create regions on average path length, clustering coefficient and connectivity.Comment: Accepted for publication: Special Issue on Security and Performance of Networks and Clouds (The Computer Journal

Self-organization of Nodes using Bio-Inspired Techniques for Achieving Small World Properties

In an autonomous wireless sensor network, self-organization of the nodes is essential to achieve network wide characteristics. We believe that connectivity in wireless autonomous networks can be increased and overall average path length can be reduced by using beamforming and bio-inspired algorithms. Recent works on the use of beamforming in wireless networks mostly assume the knowledge of the network in aggregation to either heterogeneous or hybrid deployment. We propose that without the global knowledge or the introduction of any special feature, the average path length can be reduced with the help of inspirations from the nature and simple interactions between neighboring nodes. Our algorithm also reduces the number of disconnected components within the network. Our results show that reduction in the average path length and the number of disconnected components can be achieved using very simple local rules and without the full network knowledge.Comment: Accepted to Joint workshop on complex networks and pervasive group communication (CCNet/PerGroup), in conjunction with IEEE Globecom 201

Enhancing Cooperation in MANET Using the Backbone Group Model (An Application of Maximum Coverage Problem)

AbstractMANET is a cooperative network in which every node is responsible for routing and forwarding as a result consumes more battery power and bandwidth. In order to save itself in terms of battery power and bandwidth noncooperation is genuine. Cooperation can be enhanced on the basis of reduction in resource consumption by involving a limited number of nodes in routing activities rather than all. To get accurate selection of nodes to define a backbone several works have been proposed in the literature. These works define a backbone with impractical assumptions that is not feasible for MANET. In this paper we have presented the Backbone Group (BG) model, which involve the minimum number of nodes called BG in routing activities instead of all. A BG is a minimal set of nodes that efficiently connects the network. We have divided a MANET in terms of the single hop neighborhood called locality group (LG). In a LG we have a cluster head (CH), a set of regular nodes (RNs) and one or more border nodes (BNs). The CHs are responsible for the creation and management of LG and BG. The CHs use a BG for a threshold time then switches to another BG, to involve all nodes in network participation. The proposed model shows its effectiveness in terms of reduction in routing overhead up to a ratio (n2: n2/k) where k is the number of LGs

A Self-Organization Framework for Wireless Ad Hoc Networks as Small Worlds

Motivated by the benefits of small world networks, we propose a self-organization framework for wireless ad hoc networks. We investigate the use of directional beamforming for creating long-range short cuts between nodes. Using simulation results for randomized beamforming as a guideline, we identify crucial design issues for algorithm design. Our results show that, while significant path length reduction is achievable, this is accompanied by the problem of asymmetric paths between nodes. Subsequently, we propose a distributed algorithm for small world creation that achieves path length reduction while maintaining connectivity. We define a new centrality measure that estimates the structural importance of nodes based on traffic flow in the network, which is used to identify the optimum nodes for beamforming. We show, using simulations, that this leads to significant reduction in path length while maintaining connectivity.Comment: Submitted to IEEE Transactions on Vehicular Technolog

INTERFACE MODE ASSIGNMENT METHOD FOR SELF-RECONSTRUCTION OF WIRELESS MESH NETWORKS

The key features of computer networks available for disaster situation is reliable, fault tolerance and self-configurable. Therefore, using wireless mesh network for disaster prevention and recover system has gain much attention from the research community in last decades. In addition, from the practical aspects of the network infrastructures of the disaster system, we should assume the core capabilities such as wireless connectivity in wide range, ease of use, and low cost so on. In this paper, we propose an interface mode assignment method for reconstructing a route from an isolated router to a gateway (GW) router in a wireless mesh network based on IEEE 802.11 infrastructure mode after a disaster occurrance. The proposed method assigns an adequate mode to each interface in an isolated router to recover the network reachability in distributed manner. Simulation results show the effectiveness of the proposed method via two different scenarios