APOLLO: A platform for experimental analysis of time sensitive multimedia IoT applications

The Internet of Things (IoT) is growing fast and is gaining significant adoption in areas such as smart cities and manufacturing. The variety and low-cost of IoT devices with excellent audio/visual sensors is fueling the growth of multimedia IoT applications, many of which are bandwidth-hungry and time-sensitive (i.e., must produce their results within an application specific time-sensitive requirement). While a large body of related work has studied distribution of such Time Sensitive Multimedia IoT (TS-MIoT) applications in simulated environments, there is lack of a platform that can be used to experiment with techniques for meeting their time-sensitive and computing resource requirements on real-world IoT infrastructure, i.e., a combination of IoT devices, close by computers and a cloud data centre connected by a variety of networks. This paper proposes APOLLO, a platform for experimental analysis of TS-MIoT applications. APOLLO provides mechanisms to load TS-MIoT application execution plans and execute the plans on available IoT infrastructure. We describe a proof-of-concept implementation using Orleans and present experimental evaluations to validate APOLLO's ability to support the experimental analysis of TS-MIoT applications.