Toward a Unified Characterization of Mapping Algorithms in Cloud and MPSoC Environments Using a Literature-Based Approach

Abstract

To address the growing demand for high-quality multimedia applications on mobile devices, stronger smartphones based on multicore processors are becoming the mainstream. However, processing power is still behind the required resources for some multimedia applications such as new video coding standards. Mobile cloud computing is a solution for this concern. In order to efficiently distribute tasks onto an infrastructure of devices, a mapping algorithm is required. This algorithm should determine the suitable device in the cloud and should also allocate the corresponding core in the selected multicore device. Providing a suitable algorithm considering the two domains of cloud and Multiprocessor System on Chip (MPSoC) simultaneously is a challenge. Describing the mapping algorithms with a set of descriptive elements makes differentiation among them easier. Unification of these features on both domains results in simpler mapping algorithms. In this paper, we present a generic representation for the mapping algorithms in the MPSoC and cloud environments. Grounded Theory has been applied to identify the main features of the mapping algorithms. The obtained features are organized in more abstract categories based on their similarities. In order to evaluate the results, a few sample mapping algorithms from each of the cloud and MPSoC domains have been successfully characterized with the obtained features.