Edge computing provides resources for IoT workloads at the network edge. Monitoring systems are vital for efficiently managing resources and application workloads by collecting, storing, and providing relevant information about the state of the resources. However, traditional monitoring systems have a centralized architecture for both data plane and control plane, which increases latency, creates a failure bottleneck, and faces challenges in providing quick and trustworthy data in volatile edge environments, especially where infrastructures are often built upon failure-prone, unsophisticated computing and network resources. Thus, we propose DEMon, a decentralized, self-adaptive monitoring system for edge. DEMon leverages the stochastic gossip communication protocol at its core. It develops efficient protocols for information dissemination, communication, and retrieval, avoiding a single point of failure and ensuring fast and trustworthy data access. Its decentralized control enables self-adaptive management of monitoring parameters, addressing the trade-offs between the quality of service of monitoring and resource consumption. We implement the proposed system as a lightweight and portable container-based system and evaluate it through experiments. We also present a use case demonstrating its feasibility. The results show that DEMon efficiently disseminates and retrieves the monitoring information, addressing the challenges of edge monitoring.

翻译：边缘计算在网络边缘为物联网工作负载提供资源。监测系统通过收集、存储并提供有关资源状态的相关信息，对于高效管理资源和应用程序工作负载至关重要。然而，传统监测系统在数据平面和控制平面均采用集中式架构，这会增加延迟、造成故障瓶颈，并且在易变的边缘环境中难以提供快速可靠的数据，尤其是在基础设施通常由易故障、低端计算和网络资源构建的情况下。为此，我们提出DEMon——一种去中心化、自适应的边缘监测系统。DEMon的核心采用随机流言通信协议，并开发了高效的信息传播、通信和检索协议，避免了单点故障，确保了快速可靠的数据访问。其去中心化控制能够实现监测参数的自适应管理，从而在监测服务质量与资源消耗之间取得平衡。我们将所提出的系统实现为轻量级、可移植的基于容器的系统，并通过实验对其进行评估。我们还展示了一个用例以证明其可行性。结果表明，DEMon能够高效地传播和检索监测信息，有效应对边缘监测面临的挑战。