Agent Organization in the Knowledge Plane

In designing and building a network like the Internet, we continue to face the problems of scale and distribution. With the dramatic expansion in scale and heterogeneity of the Internet, network management has become an increasingly difficult task. Furthermore, network applications often need to maintain efficient organization among the participants by collecting information from the underlying networks. Such individual information collection activities lead to duplicate efforts and contention for network resources. The Knowledge Plane (KP) is a new common construct that provides knowledge and expertise to meet the functional, policy and scaling requirements of network management, as well as to create synergy and exploit commonality among many network applications. To achieve these goals, we face many challenging problems, including widely distributed data collection, efficient processing of that data, wide availability of the expertise, etc. In this thesis, to provide better support for network management and large-scale network applications, I propose a knowledge plane architecture that consists of a network knowledge plane (NetKP) at the network layer, and on top of it, multiple specialized KPs (spec-KPs). The NetKP organizes agents to provide valuable knowledge and facilities about the Internet to the spec-KPs. Each spec-KP is specialized in its own area of interest. In both the NetKP and the spec-KPs, agents are organized into regions based on different sets of constraints. I focus on two key design issues in the NetKP: (1) a regionbased architecture for agent organization, in which I design an efficient and non-intrusive organization among regions that combines network topology and a distributed hash table; (2) request and knowledge dissemination, in which I design a robust and efficient broadcast and aggregation mechanism using a tree structure among regions. In the spec-KPs, I build two examples: experiment management on the PlanetLab testbed and distributed intrusion detection on the DETER testbed. The experiment results suggest a common approach driven by the design principles of the Internet and more specialized constraints can derive productive organization for network management and applications. Thesis Supervisor: Karen R. Sollins Title: Principal Research Scientist, Computer Science and Artificial Intelligence Laboratory