Image Download and Rate Allocation of Internet-of-Things Analytics at Gateways in Smart Cities

Internet-of-Things (IoT) devices are connected to the Internet through a gateway, which can host IoT analytics encapsulated in containers to convert raw sensor data into more condensed processed data. In this paper, we study two research problems to maximize the overall Quality-of-Service (QoS) level of all IoT analytics that run on both data center servers and gateways. The first problem is to select additional IoT analytics to deploy on a gateway to save upload bandwidth due to transmitting raw sensor data. The second problem is to allocate the residue upload bandwidth among all IoT analytics to maximize the overall QoS level. We propose several algorithms to solve these two research problems. We have implemented real testbeds to evaluate our proposed system and algorithms. Our experiment results reveal that the proposed algorithms: (i) capitalize the download bandwidth and storage space of the gateway for saving the upload bandwidth consumption and (ii) achieve high QoS levels without overloading the network and gateway.