Decentralized applications rely on non-centralized technical infrastructures and coordination principles. Without trusted third parties, their execution is not controlled by entities exercising centralized coordination but is instead realized through technologies supporting distribution such as blockchains and serverless computing. Executing decentralized applications with these technologies, however, is challenging due to the limited transparency and insight in the execution, especially when involving centralized cloud platforms. This paper extends an approach for execution and instance tracking on blockchains and cloud platforms permitting distributed parties to observe the instances and states of executable models. The approach is extended with (1.) a metamodel describing the concepts for instance tracking on cloud platforms independent of concrete models or implementation, (2.) a multidimensional data model realizing the concepts accordingly, permitting the verifiable storage, tracking, and analysis of execution states for distributed parties, and (3.) an implementation on the Ethereum blockchain and Amazon Web Services (AWS) using state machine models. Towards supporting decentralized applications with high scalability and distribution requirements, the approach establishes a consistent view on instances for distributed parties to track and analyze the execution along multiple dimensions such as specific clients and execution engines.
翻译:面向区块链和云平台的去中心化应用程序依赖于非中心化的技术基础设施和协调原则。未经受信任第三方的控制下,它们的执行不是由行使集中协调的实体控制,而是通过支持分布式的技术实现的,例如区块链和无服务器计算。然而,使用这些技术执行去中心化应用程序具有挑战性,因为在涉及集中的云平台时,执行的透明度和洞察力有限。本文扩展了一种面向区块链和云平台的执行和实例追踪方法,该方法允许分布式各方观察可执行模型的实例和状态。该方法扩展了(1.)描述云平台上实例追踪概念的元模型,独立于具体的模型或实现。(2.)实现相应概念的多维数据模型,以允许分布式各方对执行状态进行可验证的存储、跟踪和分析。(3.)使用状态机模型在以太坊区块链和亚马逊网络服务(AWS)上进行实现。为了支持具有高可扩展性和分布式要求的去中心化应用程序,该方法建立了一种对于分布式各方来追踪和分析执行的实例的一致性视图,例如特定的客户端和执行引擎。