A Self-organizing Approach to Tuple Distribution in Large-Scale Tuple-Space Systems

A system is said to be self-organizing if its execution yields temporal global structures out of simple and local interactions amongst its constituents (e.g agents, processes). In nature, one can find many natural systems that achieve organization at the global level without a reference to the status of the global organization; real examples include ants, bees, and bacteria. The future of tuple-space systems such as Linda lies on (i) their ability to handle non-trivial coordination constructs common in complex applications, and (ii) their scalability to environments where hundreds and maybe thousands of nodes exist. The Achilles heel of scalability in current tuple-space systems is tuple organization. Legacy solutions based on antiquated approaches such as hashing are (unfortunately) commonplace. This paper gets inspiration from self-organization to improve the status quo of tuple organization in tuple-space systems. We present a solution that organizes tuples in large networks while requiring virtually no global knowledge about the system.