A Self-Scheduling Model Using Agent-Base, Peer-to-Peer Negotiation, and Open Common Schema

Research has shown that market-style selfscheduling is a promising approach to achieving real-time online resources allocation. However, the field still lacks sufficient results in areas such as control, inter-operation of heterogeneous data semantics, and qualitative performance measurement, to satisfy large scale distributed operations, especially today’s information enterprises. We propose a new agent-based, peer-to-peer publish and subscribe model for enterprise resource allocation under the above conditions. We use the proven industrial exchange technology to develop a full-fledged artificial market to self-schedule information tasks (resources offerings and requests) across a potentially extended enterprise, with a comprehensive performance-feedback-reallocation mechanism. New results also include an Agent-Base for creating and managing large number of custom agents online, a peer-to-peer negotiation method, and an open common schema design, to enable the model. It also provides an implementation scheme for developing the basic architecture, the pricing model, and the data interchange required of the