Research Article
Adaptive Replica Selection in Mobile Edge Environments
@INPROCEEDINGS{10.1007/978-3-030-94822-1_14, author={Jo\"{a}o Dias and Jo\"{a}o A. Silva and Herv\^{e} Paulino}, title={Adaptive Replica Selection in Mobile Edge Environments}, proceedings={Mobile and Ubiquitous Systems: Computing, Networking and Services. 18th EAI International Conference, MobiQuitous 2021, Virtual Event, November 8-11, 2021, Proceedings}, proceedings_a={MOBIQUITOUS}, year={2022}, month={2}, keywords={Replica selection Replica ranking Mobile edge computing Replication}, doi={10.1007/978-3-030-94822-1_14} }- João Dias
João A. Silva
Hervé Paulino
Year: 2022
Adaptive Replica Selection in Mobile Edge Environments
MOBIQUITOUS
Springer
DOI: 10.1007/978-3-030-94822-1_14
Abstract
Mobile Edge Computing (MEC) is a paradigm that aims to bring cloud services closer to mobile clients, effectively reducing latency and saving backbone bandwidth. As in cloud environments, many applications make use of replication to enhance their quality of service. However, here, data generated by the mobile devices is usually kept near its source, and can have multiple replicas scattered through the network (e.g., on the mobile devices or on edge servers). When requesting data, replica selection can have a significant impact in multiple aspects of a system, e.g., load balancing, throughput, or energy efficiency. Thus, the possible herd behavior combined with the unreliable wireless communication channels can cause systems to under-perform. In this paper, we proposeMecerra, a replica ranking algorithm tailored for the characteristics of MEC environments. Additionally, we detailWasabi, a flexible replica ranking framework that also handles the management of system metrics. We implementMecerrainWasabi, and integrate it into a data storage system for edge networks, building an adaptive replica selection scheme. We use the resulting system to evaluate our proposal and compare it against related work. Results show thatMecerrais able to greatly increase the probability of finding the best replica, andWasabiprovides low overhead.
