Uncertainties in Next Generation Networks: Using Bayesian Models And Stochastic Analysis
A conceptual approach to reduce the basic uncertainty in worldwide networks, this exciting new text presents a deterministic solution to the key uncertainties, amongst the four-pronged problem of aggregation, switching, scheduling and information transport. The relation between these four functions can be understood as the progressive uncertainty in networks– the primary uncertainty being that of time dependent procedures.
The text presents a quantification of the uncertainties involved and shows that industry and academia have unknowingly and subconsciously developed heuristic solutions without focusing on the problem from a conceptual perspective, then seeks to solve the problem by creating conceptual theories from well-known and emerging innovations. It maps the solutions to each of the problems onto a comprehensive solution to the emerging problems in next generation networks (such as next generation multi-layered platforms for providing multiple services).
- Focuses on the conceptual understanding of how networks behave.
- Discusses the 6 basic areas of networking (switching, routing, aggregation, management, scheduling, transport), thereby identifying constant, fundamental uncertainties and shows how these uncertainties hang together.
- Presents technology independent concepts that bridge the gap between the application domain and the algorithm world.
- Provides a top-down approach to show the true uncertainty equilibrium existing in worldwide networks.
- Suggests plausible, unified solutions that save resources, cost, and meet the challenges of next generation Internet.
- Provides a series of analytical models illustrated with real-world examples and a conceptual proof of its theory.