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.
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. This thesis considers the process of topology reconfiguration and use the packet drops that happen during this process as a cost metric for this process. It is shown that by implementing the topology reconfiguration as a series of smaller steps (successive approximation), the number of packets that are dropped during the reconfiguration are reduced. Using this knowledge, the topology computation algorithm can be refined to also minimize the reconfiguration cost along with the typical objective of minimizing congestion.
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.
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