Abstract
Dynamic selection of services and by extension of service providers are vital in today’s liberalized market of energy. On the other hand it is equally important for Service Providers to spot the one QoS Module that offers the best QoS level in a given cost. Type of service, response time, throughput, availability and cost, consist a basic set of attributes that should be taken into consideration when building a concrete Grid network. In the proposed QoS architecture Prosumers request services based on the aforementioned set of attributes. The Prosumer requests the service through the QoS Module. It is then the QoS Module that seeks the Service Provider that best fits the needs of the client. The aforementioned approach is well supplemented with a data analytics/machine learning architecture to further enrich the provisioning aspect this work is bringing to the Smart Grid market of energy.
| Original language | English |
|---|---|
| Pages (from-to) | 77-86 |
| Number of pages | 10 |
| Journal | Journal of Communications Software and Systems |
| DOIs | |
| Publication status | Published - 1 Jun 2017 |
| Externally published | Yes |
Keywords
- Data Mining
- Service Oriented Architecture
- QoS
- Machine Learning
- 1005 Communications Technologies
- Smart Grid
