Flexible enterprise network management on commodity switches

Enterprise networks interconnect heterogeneous hosts, requiring careful management to provide secure, reliable and high-performance network communication. Today, the operators have to manually configure individual network devices, while considering the host address assignments and devices constraints (e.g., limited memory). These approaches are too complicated and inefficient for enterprise networks with growing numbers of hosts and devices.;The rise of Software Defined Networks (SDN) offers opportunities to simplify the management of enterprise networks. Leveraging the logically-centralized control plane and the programmable switch rule-tables in SDN, we design a novel network management system that supports flexible policies and reduces configuration complexity. We argue that the operators should focus on defining network-wide policies rather than grappling with low-level details, such as switch memory sizes, individual switch configurations and host addresses. It is the controller's job to compile the high-level policies into rules for individual switches while staying within the rule-table sizes.;In this thesis, we present a flexible enterprise network management system that assigns addresses based on host attributes, distributes network-wide policies across multiple switches and computes switch rules to achieve high-level load balancing policies. Specifically, (1) We propose the "Attribute-Carrying IPs" (ACIPs) abstraction, where the attributes of a host are encoded in the IP addresses to enable flexible policy specification. We present Alpaca, algorithms for realizing ACIPs under practical constraints of limited-length IP addresses and constraint switch rule-tables. (2) We propose the "One Big Switch" abstraction, which consists of an endpoint policy that views all hosts connected to a single switch, a hop-by-hop routing policy that defines paths between endpoints and a compiler that synthesizes switch rules that obey policies and adhere to the resource constraints. We present efficient algorithms that distribute policies across networks while managing rule-space constraints. (3) We propose the "One Big Server" abstraction, where a switch load balances incoming service requests to multiple equivalent servers based on their capacities. We present Niagara, an SDN-based traffic-splitting scheme that achieves accurate traffic splits while being extremely efficient in using the rule-table space.