Ontology Based Power Profiling for Internet of Things Deployed with Software Defined Data Center

Abstract

Cost effective, secure and environment friendly data centers are crucial for the success of embracing the adoption of Internet of Things (IoT). Regardless of the potential benefits of IoT, there are still many hurdles to be overcome to leverage the wide growth of the IoT technology. One challenging vector is the efficient power profiling of the entities involved in an IoT ecosystem. Software-Defined Data Center (SDDC) virtualizes the key data center infrastructure such as compute, storage and network. IoT fabric with SDDC, due to virtualization and the reduction in the hardware footprint, an extent of reduced power consumption is achieved when compared to a non-virtualized traditional data center. Today, in the end-to-end IoT and IT fabric, deficiency of intelligent power profiling techniques merits the need to supervise power in such an ecosystem, especially from an OT/IT convergence point of view where SDDC represents IT (Information Technology) and IoT forms OT (Operational Technology). To that end, this paper looks at power profiling for IoT fabric with SDDC by modeling the IoT ecosystem using semantic approaches. Thus, we bring in a notion of power awareness to the software defined IoT fabric. Specifically, this paper models a power profile ontology for the IoT fabric with SDDC and monitor such an ecosystem at run time and derive useful value by bridging the OT/IT convergence gap with respect to end-to-end power profiling.