具有计算域的可预测自组织

J. Beal, Mirko Viroli
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引用次数: 0

摘要

近年来,许多关于自组织系统的不同研究方向汇集在一起,为分布式系统的工程创造了一种新的“聚合编程”方法。聚合编程的动机是为了避免臭名昭著的棘手的“局部到全局”问题,即系统设计者必须预测如何控制单个设备以实现集体目标。相反,设计人员编写了一个集体抽象的程序,从已经解决了局部到全局问题的特殊情况库中组合“构建块”原语。将许多提议的聚合编程方法统一起来的是“计算域”的概念,它将域域中的每个设备映射到其范围内的局部值。这个概念最初是为空间计算机开发的,其中通信和几何位置紧密相连,但也可以支持许多非空间网络的有效聚合编程。最近,这种方法的数学基础已经被形式化了,一个最小的“场演算”似乎是一个有效的统一模型,涵盖了广泛的聚合规划模型,包括连续的(例如,基于几何的)和离散的(例如,基于图的)。在此基础上,受限语言可以确保各种理想的特性,如可伸缩性、自稳定性和对扰动的鲁棒性。通过构建一个足够广泛的可组合“构建块”分布式算法集合,可以简单快速地开发具有隐式可伸缩和弹性的复杂分布式系统。这条研究路线的最终目标是使健壮的分布式系统的编程像单处理器编程一样简单和广泛,从而使我们的技术基础设施的可靠性、效率和民主得到广泛的提高。
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Predictable Self-Organization with Computational Fields
In recent years, a number of different strands of research on self-organizing systems have come together to create a new "aggregate programming" approach to the engineering of distributed systems. Aggregate programming is motivated by a desire to avoid the notoriously intractable "local to global" problem, where the system designer must predict how to control individual devices to achieve a collective goal. Instead, the designer programs an abstraction of the collective, composing "building block" primitives from a library of special cases where the local-to-global problem is already solved. Unifying a number of the proposed aggregate programming approaches is the notion of a "computational field" that maps each device in the field's domain to a local value in its range. This concept was originally developed for spatial computers, in which communication and geometric position are closely linked, but can support effective aggregate programming of many non-spatial networks as well. A mathematical foundation for such approaches has been formalized recently with a minimal "field calculus" that appears to be an effective unifying model, covering a wide range of aggregate programming models, both continuous (e.g., geometry-based) and discrete (e.g., graph-based). On this foundation, restricted languages can ensure various desirable properties such as scalability, self-stabilization, and robustness to perturbation. By building up a sufficiently broad collection of composable "building block" distributed algorithms, it is possible to enable simple and rapid development of complex distributed systems that are implicitly scalable and resilient. The ultimate aim of this line of research is to make the programming of robust distributed systems as simple and widespread as single-processor programming, thereby enabling widespread increases in the reliability, efficiency, and democracy of our technological infrastructure.
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