Adaptive Context-Aware Replication Mechanismfor Distributed IoT Environments

Abstract

The rapid evolution of the Internet of Things (IoT), supported by the convergence of cloud, edge and mistcomputing layers, opens new avenues for delivering reliable and responsive services to distributed smart devices.However, ensuring efficient and adaptive service replication in such resource-constrained and dynamically changing IoTenvironments remains a significant challenge. To tackle this, we introduce Elastic Context-Aware Replication (ECAR),an intelligent replication strategy tailored for IoT systems. ECAR dynamically redistributes services across the IoTcontinuum by leveraging both physical and logical contextual information. Unlike traditional replication schemes, ECARcontinuously adapts to real-time workload fluctuations and network conditions, ensuring low latency and efficientresource usage. ECAR’s effectiveness is demonstrated through a comparative evaluation involving diverse IoTdeployment scenarios, including Cloud-Intensive Replication (CIR), Cloud-Edge-Intensive Replication (CEIR) andCloud-Edge-Access-Intensive Replication (CEAIR), alongside two existing replication strategies, Group-Delay-AwareReplication (GDAR) and Combined Context-Aware Replication (CCA). The evaluation shows ECAR achieving up to 18%reduction in service drop rates, 82% improvement in allocation efficiency and 82% better resource utilization. Theseresults underline ECAR’s effectiveness in supporting scalable, reliable and latency-aware service delivery for IoTdeployments.