Functionally Accurate, Cooperative Distributed Systems

TLDR

The FA/C approach is inspired by knowledge‑based AI techniques for handling uncertainty from noisy data and approximate knowledge. The paper proposes the functionally accurate, cooperative (FA/C) approach for structuring distributed processing systems and outlines future research directions. FA/C structures distributed systems by having nodes cooperatively exchange partial tentative results at multiple abstraction levels, treating distribution‑induced uncertainty and errors as integral to problem solving, and is suited to tasks where data cannot be partitioned without inter‑node state visibility. The FA/C approach is evaluated in distributed interpretation, network traffic‑light control, and planning, and its relation to management organization structures is also examined.

Abstract

A new approach for structuring distributed processing systems, called functionally accurate, cooperative (FA/C), is proposed. The approach differs from conventional ones in its emphasis on handling distribution-caused uncertainty and errors as an integral part of the network problem-solving process. In this approach nodes cooperatively problem-solve by exchanging partial tentative results (at various levels of abstraction) within the context of common goals. The approach is especially suited to applications in which the data necessary to achieve a solution cannot be partitioned in such a way that a node can complete a task without seeing the intermediate state of task processing at other nodes. Much of the inspiration for the FA/C approach comes from the mechanisms used in knowledge-based artificial intelligence (Al) systems for resolving uncertainty caused by noisy input data and the use of approximate knowledge. The appropriateness of the FA/C approach is explored in three application domains: distributed interpretation, distributed network traffic-light control, and distributed planning. Additionally, the relationship between the approach and the structure of management organizations is developed. Finally, a number of current research directions necessary to more fully develop the FA/C approach are outlined. These research directions include distributed search, the integration of implicit and explicit forms of control, and distributed planning and organizational self-design.