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Network management is the continuous process of monitoring a network to detect and diagnose problems, and tuning the configuration of the underlying protocols and mechanisms to fix them. However, today's network architectures were not designed with these tasks in mind. As a result, managing data networks is, at best, a black art practiced by an increasingly overwhelmed community of network administrators. In recent years, a variety of theoretical techniques (e.g., anomaly detection, streaming algorithms, tomography, and optimization theory) have helped network administrators run their networks more effectively.
Much research on network management has (understandably) worked within the limitations of the existing networking technology. However, today's measurement data, network protocols, and router mechanisms often induce management problems that are unnecessarily difficult (or even impossible) to solve. Rather than creating new ways to retrofit network management on the existing infrastructure, this workshop focuses on the clean-slate design of network architectures with management challenges in mind from the beginning. The workshop aims to understand the limitations of supporting network management on top of today's technology, to identify the algorithmic challenges in network management, and propose new designs that induce management problems that have better, and computationally easier, solutions.
Important open questions include:
To start answering these questions, this workshop will bring together experts from theoretical computer science and electrical engineering, networking and distributed systems, and network management and operations.