Directional wireless networks using FSO and RF transmissions provide wireless backbone support for mobile
communications in dynamic environments. The heterogeneous and dynamic nature of such networks challenges their
robustness and requires self-organization mechanisms to assure end-to-end broadband connectivity. We developed a
framework based on the definition of a potential energy function to characterize robustness in communication networks
and the study of first and second order variations of the potential energy to provide prediction and control strategies for
network performance optimization. In this paper, we present non-convex molecular potentials such as the Morse
Potential, used to describe the potential energy of bonds within molecules, for the characterization of communication
links in the presence of physical constraints such as the power available at the network nodes. The inclusion of the
Morse Potential translates into adaptive control strategies where forces on network nodes drive the release, retention or
reconfiguration of communication links for network performance optimization. Simulation results show the effectiveness
of our self-organized control mechanism, where the physical topology reorganizes to maximize the number of source to
destination communicating pairs. Molecular Normal Mode Analysis (NMA) techniques for assessing network
performance degradation in dynamic networks are also presented. Preliminary results show correlation between peaks in
the eigenvalues of the Hessian of the network potential and network degradation.
Next generation communication networks are becoming increasingly complex systems. Previously, we presented a novel
physics-based approach to model dynamic wireless networks as physical systems which react to local forces exerted on
network nodes. We showed that under clear atmospheric conditions the network communication energy can be modeled
as the potential energy of an analogous spring system and presented a distributed mobility control algorithm where nodes
react to local forces driving the network to energy minimizing configurations. This paper extends our previous work by
including the effects of atmospheric attenuation and transmitted power constraints in the optimization problem. We show
how our new formulation still results in a convex energy minimization problem. Accordingly, an updated force-driven
mobility control algorithm is presented. Forces on mobile backbone nodes are computed as the negative gradient of the
new energy function. Results show how in the presence of atmospheric obscuration stronger forces are exerted on
network nodes that make them move closer to each other, avoiding loss of connectivity. We show results in terms of
network coverage and backbone connectivity and compare the developed algorithms for different scenarios.
Next generation wireless networks are increasingly complex in terms of their heterogeneity (terminal, edge and backbone
nodes; directional and omnidirectional wireless links) and dynamic behavior (node mobility, atmospheric obscuration,
fading). Modeling such complex systems is becoming a very challenging and cumbersome mathematical problem. This
paper proposes a novel physics-based approach to the modeling, characterization and control of complex wireless
networks. Heterogeneous wireless networks are modeled as physical systems where nodes are represented as particles
and communication links as attraction forces between them. Forces are defined based on network connectivity and
include the effects of link distance, link directivity and atmospheric obscuration. The network energy usage is used as a
cost function that is shown to be related to the potential energy of the analogous physical system. We formulate the joint
coverage-connectivity optimization problem in backbone-based wireless networks as an energy minimization problem
and present a mobility control algorithm that mimics the natural reaction of a physical system to minimize potential
energy driven by local forces exerted on network nodes. Our mobility control algorithm is shown to be completely
distributed, scalable and self-organized. Initial results show the efficiency of our mobility control approach to
autonomously adjust the position of controlled backbone nodes in order to optimize coverage and connectivity in
Recent developments in pointing, acquisition, and tracking have enabled the formation of point-to-point FSO or narrow
beam directional wireless networks that are capable of dynamic changes in their topology. Autonomous changes to
topology in response to varying available link capacities and load demands of various nodes is called topology control.
Topology control consists of computing new topologies to dynamically optimize the network under changing traffic
conditions, and then carrying out the reconfiguration process to achieve the target topology. Our current work in this area
studies the process of topology reconfiguration by using the packet drops that happen during this process as a cost
metric. It is shown that the reconfiguration cost can be minimized when the target topology is reached by implementing
the topology reconfiguration as a series of smaller steps (successive approximations). It is also shown that a topology
computation algorithm that results in lower overall packet drops can be obtained by including the reconfiguration cost in
the objective function along with the typical objective of congestion minimization. Simulations are used to evaluate and
compare the performance of topology computation heuristics when the objective function includes reconfiguration cost.
Establishing and initially configuring a Free Space Optical (FSO) backbone is a challenging problem, especially when nodes only have local connectivity information and a limited number of transceivers. The problem of configuring an initial connected topology or bootstrapping a directional FSO network can be formulated as a Minimum Degree Spanning Tree (MDST) problem, which is known to be NP-Complete. Recently, we developed a distributed approximation algorithm, which constructs a spanning tree with maximal node degree at most one larger than that in the optimal solution . In such a distributed approach, nodes need to coordinate their local decisions to collectively set up a connected topology. For that purpose, algorithms and protocols for local information exchange/dissemination and synchronization are required. This paper presents the design, implementation and evaluation of a complete bootstrapping process model for FSO networks. Our model integrates the algorithm presented in  with the required communication and synchronization mechanisms to guarantee the efficient emergence of overall network connectivity from local interactions between individual nodes. Time performance results for the overall bootstrapping process are presented. Our scheme allows the network to form a connected topology whenever one exists and shows linear time complexity.
Hybrid Free Space Optical (FSO) and Radio Frequency (RF) networks promise highly available wireless broadband connectivity and quality of service (QoS), particularly suitable for emerging network applications involving extremely high data rate transmissions such as high quality video-on-demand and real-time surveillance. FSO links are prone to atmospheric obscuration (fog, clouds, snow, etc) and are difficult to align over long distances due the use of narrow laser beams and the effect of atmospheric turbulence. These problems can be mitigated by using adjunct directional RF links, which provide backup connectivity. In this paper, methodologies for modeling and simulation of hybrid FSO/RF networks are described. Individual link propagation models are derived using scattering theory, as well as experimental measurements. MATLAB is used to generate realistic atmospheric obscuration scenarios, including moving cloud layers at different altitudes. These scenarios are then imported into a network simulator (OPNET) to emulate mobile hybrid FSO/RF networks. This framework allows accurate analysis of the effects of node mobility, atmospheric obscuration and traffic demands on network performance, and precise evaluation of topology reconfiguration algorithms as they react to dynamic changes in the network. Results show how topology reconfiguration algorithms, together with enhancements to TCP/IP protocols which reduce the network response time, enable the network to rapidly detect and act upon link state changes in highly dynamic environments, ensuring optimized network performance and availability.
Hybrid free space optical/radio frequency (FSO/RF) networks promise broadband connectivity, high availability and quality of service (QoS), together with the capability of autonomous reconfigurability to deal with changing atmospheric and traffic conditions in dynamic environments. Nodes with n-connectedness (multiple transceivers) offer great flexibility in constructing new network topologies. Moreover, topologies using hybrid links are more effective in changing atmospheric conditions than those, using either communication modality alone. While FSO links can be expected to be available >99% of the time on links up to 1km in length, high performance RF provides backup connectivity in heavily obscured conditions. We have designed and implemented gimbal-mounted, hybrid FSO/RF nodes with combined apertures for joint pointing, acquisition, and tracking (PAT) operation. These nodes incorporate directional RF antennas for PAT network setup and management, and FSO links for very high data rate transmission. We describe these hybrid nodes and their performance, our hybrid network simulations, and our re-configurable network testbed for high data rate video transmission. Our simulations include realistic modeling of obscuration, traffic management, and topology control to deal with link non-availability and optimization of network performance. Hybrid, directional networks are scalable and provide low probability of intercept/detection (LPI/LPD) operation, especially in FSO mode.
Optical wireless networks are emerging as a viable, cost effective technology for rapidly deployable broadband sensor communication infrastructures. The use of directional, narrow beam, optical wireless links provides great promise for secure, extremely high data rate communication between fixed or mobile nodes, very suitable for sensor networks in civil and military contexts. The main challenge is to maintain the quality of such networks, as changing atmospheric
and platform conditions critically affect their performance. Topology control is used as the means to achieve survivable optical wireless networking under adverse conditions, based on dynamic and autonomous topology reconfiguration. The topology control process involves tracking and acquisition of nodes, assessment of link-state information, collection and distribution of topology data, and the algorithmic solution of an optimal topology. This paper focuses on
the analysis, implementation and evaluation of algorithms and heuristics for selecting the best possible topology in order to optimize a given performance objective while satisfying connectivity constraints. The work done at the physical layer is based on link cost information. A cost measure is defined in terms of bit-error-rate and the heuristics developed seek to form a bi-connected topology which minimizes total network cost. At the network layer a key factor is the traffic matrix, and heuristics were developed in order to minimize congestion, flow-rate or end-to-end delay.