Exploiting locality for data management in systems of limited bandwidth

This paper deals with data management in computer systems in which the computing nodes are connected by a relatively sparse network. We consider the problem of placing and accessing a set of shared objects that are read and written from the nodes in the network. These objects are, e.g., global variables in a parallel program, pages or cache lines in a virtual shared memory system, shared files in a distributed file system, or pages in the World Wide Web. A data management strategy consists of a placement strategy that maps the objects (possibly dynamically and with redundancy) to the nodes, and an access strategy that describes how reads and writes are handled by the system (including the routing). We investigate static and dynamic data management strategies. In the static model, we assume that we are given an application for which the rates of read and write acesses for all node-object pairs are known. The goal is to calculate a static placement of the objects to the nodes in the network and to specify the routing such that the network congestion is minimized. We introduce efficient algorithms that calculate optimal or close-to-optimal solutions for tree-connected networks, meshes of arbitrary dimension, and internet-like clustered networks. These algorithms take time only linear in the input size. In the dynamic model, we assume no knowledge about the access pattern. An adversary specifies accesses at runtime. Here we develop dynamic caching strategies that also aim to minimize the congestion on trees, meshes, and clustered networks. These strategies are investigated in a competitive model. For example, we achieve competitive ratio 3 for tree-connected networks and competitive ratio O(d.log n) for d-dimensional meshes of size n. Further, we present an Omega(log n/d) lower bound for the competitive ratio for on-line routing in meshes, which implies that the achieved upper bound on the competive ratio for meshes of constant dimension is optimal.