Autonomous data consistency technique through fair evaluation among heterogeneous systems

By integrating heterogeneous systems with different individual requirements, it becomes possible for application systems to use the various data generated in the heterogeneous systems. Integrated systems also make it possible to process the applications from different points of view and to obtain higher assurance levels. The important requirements for the integration of application systems are not to halt the entire systems, not to violate individual system missions and to derive a synergetic effect. The autonomous decentralized system (ADS), by its online property, enables the integration of systems without stopping any system and without violating any system's mission. To collect consistent data combinations from different systems each subsystem needs to determine the combination independently and autonomously. This paper proposes a new concept, the data alliance, to determine consistent data combination from heterogeneous systems. In addition, the fairness must be maintained between the subsystems to achieve the consistency to satisfy the nature of the autonomous coordinability. This paper defines the fairness among systems in terms of the cost of the data freshness and the alliance waiting time. The data freshness value expresses the degree of how recent the data combination is for the subsystem, and the alliance waiting time expresses how long the subsystem must wait to get agreement among cooperating applications. The last part of the paper shows by simulation that the proposed technique is effective in different system topologies.