TY - CHAP
T1 - Topology information control in feedback based reconfiguration processes
AU - Murgu, Alexandru
AU - Postlethwaite, Ian
AU - Gu, Da-Wei
AU - Edwards, Christopher
PY - 2010
Y1 - 2010
N2 - In this paper, we describe an information control and coding framework devoted to reconfiguration processes based on a modified perspective on the Shannon information where the information flows are regarded as network commodities. This interpretation is suitable for independent multipoint-to-multipoint channels in group communication, such as the multiple-access or broadcast channels, and allows the flow control class of techniques to implement the information coding by invoking the multi-layered protocol stack. Iterative parametric dynamic programming is a good modeling candidate for describing the reconfiguration process as multi-objective relational optimization in a multilevel fashion. At the lower processing level, an auxiliary weighted power Lagrangian problem is solved using dynamic programming associated to the topology control. The upper processing level adjusts the value of the weighting vector in a weighted power Lagrangian formulation which is responsible for the information control monitoring. The low level solution process is repeated until the optimal solution of the nonseparable optimization problem is attained by the optimal solution of an auxiliary weighted power Lagrangian problem. The application of this information control framework is to the management traffic in self-healing networks of UAV surveillance missions.
AB - In this paper, we describe an information control and coding framework devoted to reconfiguration processes based on a modified perspective on the Shannon information where the information flows are regarded as network commodities. This interpretation is suitable for independent multipoint-to-multipoint channels in group communication, such as the multiple-access or broadcast channels, and allows the flow control class of techniques to implement the information coding by invoking the multi-layered protocol stack. Iterative parametric dynamic programming is a good modeling candidate for describing the reconfiguration process as multi-objective relational optimization in a multilevel fashion. At the lower processing level, an auxiliary weighted power Lagrangian problem is solved using dynamic programming associated to the topology control. The upper processing level adjusts the value of the weighting vector in a weighted power Lagrangian formulation which is responsible for the information control monitoring. The low level solution process is repeated until the optimal solution of the nonseparable optimization problem is attained by the optimal solution of an auxiliary weighted power Lagrangian problem. The application of this information control framework is to the management traffic in self-healing networks of UAV surveillance missions.
U2 - 10.1007/978-1-4419-5689-7_5
DO - 10.1007/978-1-4419-5689-7_5
M3 - Chapter
SN - 978-1441956880
VL - 40
T3 - Springer Optimization and Its Applications
SP - 101
EP - 124
BT - Dynamics of Information Systems
PB - Springer
CY - London
ER -