The digital universe is growing at significant rates in recent years. One of the main responsible for this sentence is the Internet of Things, or IoT, which requires a middleware that should be capable to handle this increase of data volume at real-time. Particularly, data can arrive in the middleware in parallel as in terms of input data from Radio-Frequency Identification (RFID) readers as request-reply query operations from the users side. Solutions modeled at software, hardware and/or architecture levels present limitations to handle such load, facing the problem of scalability in the IoT scope. In this context, this arti- cle presents a model denoted Eliot - Elasticity-driven Internet of Things - which combines both cloud and high performance computing to address the IoT scal- ability problem in a novel EPCglobal-compliant architecture. Particularly, we keep the same API but offer an elastic EPCIS component in the cloud, which is designed as a collection of virtual machines (VMs) that are allocated and deallocated on-the-fly in accordance with the system load. Based on the Eliot model, we developed a prototype that could run over any black-box EPCglobal- compliant middleware. We selected the Fosstrak for this role, which is currently one of the most used IoT middlewares. Thus, the prototype acts as an upper layer over the Fosstrak to offer a better throughput and latency performances in an effortless way. The results are encouraging, presenting significant performance gains in terms of response time and request throughput when comparing both elastic (Eliot) and non-elastic (standard Fosstrak) executions.