|ZANELLA MICHELE||Cycle: XXXIII |
Section: Computer Science and Engineering
Tutor: SILVANO CRISTINA
Advisor: FORNACIARI WILLIAM Major Research topic
:Post-Cloud Computing: Addressing Resource Management in Resource ContinuumAbstract:
Due to the huge amount of data generated by very pervasive IoT and mobile devices combined with a high transfer rate and real-time requirements of emerging scenarios, Cloud computing is showing some limitations.
In this sense, post-cloud computing solutions (e.g., Edge and Fog computing) move part (or all) of the computation closer to the data source, making them a very hot research topic.
Even if there are some tentative frameworks and standardization proposals, there are no homogeneous architectural models to integrate the various paradigms or, in many cases, they are based on proprietary solutions.
Moreover, current solutions implement in part (or not at all) fine-grained resource management techniques, which are necessary to deal with energy-constrained devices.
For these reasons, part of my work is devoted to propose a cooperative approach to the statement of integrating different run-time managed levels of resources from Cloud to Edge.
However, dealing with the aforementioned distributed and multi-level systems, means having different kinds of resource heterogeneity:
a) inter-level, i.e., computing resources with very different capabilities;
b) intra-level, i.e., different devices or computing resources in the same level;
c) intra-node, i.e., heterogeneous resource available on the same device/node.
In this sense, and especially for the inter-node heterogeneity, my research aim at offering the opportunity to extend the outcome of European projects (i.e., MANGO and RECIPE) also for the aforementioned scenario.
In particular, a first goal is the extension of the Barbeque Run-Time Resource manager framework with a Data Communication Interface to enable the coordination between difference instances of the resource manager.
Secondly, a novel resource-aware and task-based programming model is proposed in order to overcome the current state-of-the-art limitations.
Thus, since the correlation between heterogeneity and post-cloud scenarios, part of this work focuses on extending the programming model also for developing and integrate distributed applications.
Finally, in the Fog scenario, mobile devices become part of the computing system in the sense that they can be exploited by lower-level or nearby devices to perform part of the computation.
On the other hand, mobile devices are increasing their computational power still being affected by their energy budget limitation.
At this regard, the rest of my research work aims at enabling an efficient integration of mobile devices in the Fog level.
This can be achieved through the run-time management of the application’s execution, device’s resources allocation and energy consumption, while taking into account application’s performance and requirements.
The aformenetioned solution requires to provide a set of API to make Android applications reconfigurable combined with a prototype mobile version of the BarbequeRTRM that can enforce the decision of a novel management strategy.