GenACO a multi-objective cached data offloading optimization based on genetic algorithm and ant colony optimization.

ABSTRACT:

Background

Data exchange and management have been observed to be improving with the rapid growth of 5G technology, edge computing, and the Internet of Things (IoT). Moreover, edge computing is expected to quickly serve extensive and massive data requests despite its limited storage capacity. Such a situation needs data caching and offloading capabilities for proper distribution to users. These capabilities also need to be optimized due to the experience constraints, such as data priority determination, limited storage, and execution time.

Methods

We proposed a novel framework called Genetic and Ant Colony Optimization (GenACO) to improve the performance of the cached data optimization implemented in previous research by providing a more optimum objective function value. GenA

SUBMITTER: Indana Zulfa M 

PROVIDER: S-EPMC8507473 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature