| Title | Identifying Metrics for an IoT Performance Estimation Framework |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Alexopoulos, Ilias, Neophytou, Stelios, Kyriakides, Ioannis |
| Conference Name | 2021 10th Mediterranean Conference on Embedded Computing (MECO) |
| Date Published | jun |
| Keywords | Computational modeling, Embedded computing, Estimation, Hardware, Memory management, performance evaluation, Power demand, pubcrawl, Resiliency, Scalability, work factor metrics |
| Abstract | In this work we introduce a framework to support design decisions for heterogeneous IoT platforms and devices. The framework methodology as well as the development of software and hardware models are outlined. Specific factors that affect the performance of device are identified and formulated in a metric form. The performance aspects are embedded in a flexible and scalable framework for decision support. An indicative experimental setup investigates the applicability of the framework for a specific functional block. The experimental results are used to assess the significance of the framework under development. |
| DOI | 10.1109/MECO52532.2021.9460212 |
| Citation Key | alexopoulos_identifying_2021 |
Identifying Metrics for an IoT Performance Estimation Framework