Large-scale decentralized systems of autonomous agents interacting via asynchronous communication often experience the following self-healing dilemma: fault detection inherits network uncertainties making a remote faulty process indistinguishable from a slow process. In the case of a slow process without fault, fault correction is undesirable as it can trigger new faults that could be prevented with fault tolerance that is a more proactive system maintenance. But in the case of an actual faulty process, fault tolerance alone without eventually correcting persistent faults can make systems underperforming. Measuring, understanding and resolving such self-healing dilemmas is a timely challenge and critical requirement given the rise of distributed ledgers, edge computing, the Internet of Things in several energy, transport and health applications. This paper contributes a novel and general-purpose modeling of fault scenarios during system runtime. They are used to accurately measure and predict inconsistencies generated by the undesirable outcomes of fault correction and fault tolerance as the means to improve self-healing of large-scale decentralized systems at the design phase. A rigorous experimental methodology is designed that evaluates 696 experimental settings of different fault scales, fault profiles and fault detection thresholds in a prototyped decentralized network of 3000 nodes. Almost 9 million measurements of inconsistencies were collected in a network, where each node monitors the health status of another node, while both can defect. The prediction performance of the modeled fault scenarios is validated in a challenging application scenario of decentralized and dynamic in-network data aggregation using real-world data from a Smart Grid pilot project. Findings confirm the origin of inconsistencies at design phase.
翻译:通过非同步通信互动的自治代理人大规模分散系统往往经历以下自我愈合的两难困境:错误的发现继承了网络的不确定性,使远程错误过程与缓慢过程无法区别于缓慢过程。在无过失的缓慢过程的情况下,错误的纠正是不可取的,因为它可能引发新的错误,而这种错误容忍可以防止新的错误,而这种系统维护更积极主动。但是,在实际的错误过程的情况下,仅仅过错容忍而不最终纠正长期存在的缺陷,会使系统在设计阶段表现不佳。衡量、理解和解决这种自愈合困境是一个及时的挑战和关键的要求,因为分布式分类账、边缘计算、若干能源、运输和健康应用中各种事物的互联网的上升,使得一个全新的错误过程与一般目的的模型在系统运行期间对故障情况进行模型化和通用的建模。在设计阶段,使用错误校正的错误校正和错误容忍作为改进大规模分散化系统自我愈合的手段,在设计阶段,在设计阶段衡量不同错误程度的模型、错误剖析和错错错错错的互联网应用方面没有评估69个试验级的实验性环境,而在动态网络上,在10万个阶段进行原型的精确的模型的模型状态上没有评估。