Autonomous Distributed Local Computing Models using Self-Stabilization

在许多应用领域中，大量的分布式计算需要在地理上分布和自治的参与者之间进行动态和自适应的协调。虽然分布式计算的基础已经得到了相当大的发展，但是诸如部分知识、初始化或部分协调等资源的价值问题仍然没有得到解决。在许多当前的分布式系统中，参与者（如客户端、设备或任何粒度级别的传感器）被集成到不断变化的网络拓扑中以实现全局目标，尽管每个参与者可用的知识是本地的、不完整的、不完美的和不对称的。基于状态的计算?比如在自稳定协议中使用的那种？是一个令人兴奋的计算范式，它提供了一个保护伞，覆盖了局部可计算性和全局目标。

A large class of distributed computations in many application domains requires dynamic and adaptive coordination among geographically distributed and autonomous participants.While the foundations of distributed computing have been considerably developed, the question of the value of resources such as partial knowledge, initialization or partial coordination remains unresolved. In many current distributed systems, participants, such as clients, devices, or sensors at any level of granularity, are integrated into a changing network topology to accomplish a global objective despite the fact that the knowledge available at each participant is local, incomplete, imperfect and asymmetric. State-based computation?such as that employed in self-stabilizing protocols?is an exciting computing paradigm that provides an umbrella covering such local computability towards global objectives.