  Peer to peer (P2P) systems are moving from application specific architectures
to a generic service oriented design philosophy. This raises interesting
problems in connection with providing useful P2P middleware services capable of
dealing with resource assignment and management in a large-scale, heterogeneous
and unreliable environment. The slicing service, has been proposed to allow for
an automatic partitioning of P2P networks into groups (slices) that represent a
controllable amount of some resource and that are also relatively homogeneous
with respect to that resource. In this paper we propose two gossip-based
algorithms to solve the distributed slicing problem. The first algorithm speeds
up an existing algorithm sorting a set of uniform random numbers. The second
algorithm statistically approximates the rank of nodes in the ordering. The
scalability, efficiency and resilience to dynamics of both algorithms rely on
their gossip-based models. These algorithms are proved viable theoretically and
experimentally.
