Self-organization Based Control For New Generation Networks
PI: Douglas Sicker, Department of Computer Science, University of Colorado at Boulder
Self-Organization (SO) of network components and operating parameters offers promising ways to achieve higher scalability, robustness, and adaptability in future generation networks. In a self-organizing based network architecture, the globally integrated behavior of the whole system emerges through mutual interaction among networks and nodes operating on local information. As guiding principles of self-organization, networking researchers have adapted models and algorithms of self-organization found in mathematics, chemistry, physics and biology. There is a growing body of literature on this topic, particularly relating to biologically inspired algorithms (BIA); however, there is little work that compares these algorithms against established approaches or against the overall complexity of network control, and there is an absence of work that describes the classes of algorithms as they relate to various network challenges.
This work proposes to examine this area by considering a general design methodology of BIA-based control to answer such questions as: What kind of BIA can be applied to which network control problems? How well do these algorithms and problems conform to the notion of distributed or local control? How well can we expect these algorithms to operate – both in terms of solving the given problem and in terms of computational overhead? How do these algorithms perform when implemented in actual wireless networks. The fundamental goal of this work is to provide a rigorous structure for assessing the general applicability of BIA for wireless network control problems. An additional goal is to provide a structure for reproducing the experiments by other researchers.