Supporting Real-Time Mobile Applications in the Cloud-to-Things Continuum through Dynamic Resource Allocation

The increasing adoption of Internet of Things (IoT) devices and growing demand for real-time applications have driven a shift in the computation paradigm from Cloud computing toward Edge computing, giving rise to the Cloud-to-Things Continuum (C2TC). Many real-time IoT applications involve Mobile Nodes (MNs), such as mobile robots or autonomous vehicles, which may join or leave the system dynamically. In addition, future reconfigurable IoT systems will be characterized by multiple applications with heterogeneous requirements dynamically deployed or removed on the same infrastructure. To support such environment, dynamic management mechanisms are needed to ensure that the requirements of different real-time applications are guaranteed despite frequent system reconfigurations (e.g., application deployment and removal). This paper proposes DJ-NECORA, an online algorithm for joint allocation of networking and computing resources in C2TC, capable of guaranteeing the requirements of real-time applications while efficiently managing system reconfigurations and a varying number of MNs. DJ-NECORA is evaluated via simulations in a realistic scenario against two state-of-the-art solutions and an Ideal algorithm. Results show that DJ-NECORA manages system reconfigurations efficiently, provides better Quality of Service (QoS), and performs close to the Ideal algorithm.