Users of large scale network testbeds often execute experiments that require a set of nodes that behave and communicate among themselves in a reasonably stable pattern. In this work we call such a set of nodes a stable clique, and introduce a monitoring strategy that allows their detection in PlanetLab, a non-trivial task for such a large scale dynamic network. Nodes monitor each other by sampling the RTT (Round-Trip-Time) and computing its variation. Based on this data and a threshold, pairs of nodes are classified as stable or unstable. A set of graphs is generated, on which maximum sized cliques are computed. Three experiments were conducted in which hundreds of nodes were monitored for several days. Results show the unexpected behavior of some nodes, and the size of the maximum stable clique for different time windows and different thresholds.

Query optimization that involves expensive predicates has received considerable attention in the database community. Typically, the output to a database query is a set of tuples that satisfy certain conditions, and, with expensive predicates, these conditions may be computationally costly to verify. In the simplest case, when the query looks for the set of tuples that simultaneously satisfy k expensive predicates, the problem reduces to ordering the evaluation of the predicates so as to minimize the time to output the set of tuples comprising the answer to the query. We study different cases of the problem: the sequential case, in which a single processor is available to evaluate the predicates, and the distributed case, in which there are k processors available, each dedicated to a different attribute (column) of the database, and there is no communication cost between the processors.