Toward Synthesis of Network Updates

Updates to network configurations are notoriously difficult to implement correctly. Even if the old and new configurations are correct, the update process can introduce transient errors such as forwarding loops, dropped packets, and access control violations. The key factor that makes updates difficult to implement is that networks are distributed systems with hundreds or even thousands of nodes, but updates must be rolled out one node at a time. In networks today, the task of determining a correct sequence of updates is usually done manually -- a tedious and error-prone process for network operators. This paper presents a new tool for synthesizing network updates automatically. The tool generates efficient updates that are guaranteed to respect invariants specified by the operator. It works by navigating through the (restricted) space of possible solutions, learning from counterexamples to improve scalability and optimize performance. We have implemented our tool in OCaml, and conducted experiments showing that it scales to networks with a thousand switches and tens of switches updating.Comment: In Proceedings SYNT 2013, arXiv:1403.726

Tight and simple Web graph compression

Analysing Web graphs has applications in determining page ranks, fighting Web spam, detecting communities and mirror sites, and more. This study is however hampered by the necessity of storing a major part of huge graphs in the external memory, which prevents efficient random access to edge (hyperlink) lists. A number of algorithms involving compression techniques have thus been presented, to represent Web graphs succinctly but also providing random access. Those techniques are usually based on differential encodings of the adjacency lists, finding repeating nodes or node regions in the successive lists, more general grammar-based transformations or 2-dimensional representations of the binary matrix of the graph. In this paper we present two Web graph compression algorithms. The first can be seen as engineering of the Boldi and Vigna (2004) method. We extend the notion of similarity between link lists, and use a more compact encoding of residuals. The algorithm works on blocks of varying size (in the number of input lines) and sacrifices access time for better compression ratio, achieving more succinct graph representation than other algorithms reported in the literature. The second algorithm works on blocks of the same size, in the number of input lines, and its key mechanism is merging the block into a single ordered list. This method achieves much more attractive space-time tradeoffs.Comment: 15 page