A Decentralized and Self-Adaptive Approach for Monitoring Volatile Edge Environments
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...
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Main Authors | , , , |
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Format | Journal Article |
Language | English |
Published |
13.05.2024
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Subjects | |
Online Access | Get full text |
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Summary: | 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. |
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DOI: | 10.48550/arxiv.2405.07806 |