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Low-Latency IoT applications such as autonomous vehicles, augmented/virtualreality devices and security applications require high computation resources tomake decisions on the fly. However, these kinds of applications cannot tolerateoffloading their tasks to be processed on a cloud infrastructure due to theexperienced latency. Therefore, edge computing is introduced to enable lowlatency by moving the tasks processing closer to the users at the edge of thenetwork. The edge of the network is characterized by the heterogeneity of edgedevices forming it; thus, it is crucial to devise novel solutions that takeinto account the different physical resources of each edge device. In thispaper, we propose a resource representation scheme, allowing each edge deviceto expose its resource information to the supervisor of the edge node throughthe mobile edge computing application programming interfaces proposed byEuropean Telecommunications Standards Institute. The information about the edgedevice resource is exposed to the supervisor of the EN each time a resourceallocation is required. To this end, we leverage a Lyapunov optimizationframework to dynamically allocate resources at the edge devices. To test ourproposed model, we performed intensive theoretical and experimental simulationson a testbed to validate the proposed scheme and its impact on differentsystem's parameters. The simulations have shown that our proposed approachoutperforms other benchmark approaches and provides low latency and optimalresource consumption.

Resource Provisioning in Edge Computing for Latency Sensitive Applications