Abstract
Edge computing, as a new computing paradigm, brings cloud computing’s computing and storage capacities to network edge for providing low latency services for users. The networked edge servers in a specific area constitute <i>edge storage systems</i> (ESSs), where popular data can be stored to serve the users in the area. The novel ESSs raise many new opportunities as well as unprecedented challenges. Most existing studies of ESSs focus on the storage of data replicas in the system to ensure low data retrieval latency for users. However, replica-based edge storage strategies can easily incur high storage costs. It is not cost-effective to store massive replicas of large-size data, especially those that do not require real-time access at the edge, e.g., system upgrade files, popular app installation files, videos in online games. It may not even be possible due to the constrained storage resources on edge servers. In this article, we make the first attempt to investigate the use of erasure codes in cost-effective data storage at the edge. The focus is to find the optimal strategy for placing coded data blocks on the edge servers in an ESS, aiming to minimize the storage cost while serving all the users in the system. We first model this novel <i>Erasure Coding based Edge Data Placement</i> (EC-EDP) problem as an integer linear programming problem and prove its <inline-formula><tex-math notation="LaTeX">$\mathcal {NP}$</tex-math></inline-formula> -hardness. Then, we propose an optimal approach named EC-EDP-O based on integer programming. Another approximation algorithm named EC-EDP-V is proposed to address the high computation complexity of large-scale EC-EDP scenarios efficiently. The extensive experimental results demonstrate that EC-EDP-O and EC-EDP-V can save an average of 68.58% (and up to 81.16% in large-scale scenarios) storage cost compared with replica-based storage approaches.
Highlights
I N recent years, the world has witnessed the explosive growth of smart devices and mobile users
This illustrates the importance of leveraging the ability of edge servers to cost-effectively utilize the constrained and expensive storage resources in the edge storage systems (ESSs)
The experimental results show that Erasure Coding based Edge Data Placement (EC-EDP)-O is a clear winner in small-scale EC-EDP scenarios, while EC-EDPV is the best option for solving large-scale EC-EDP problems
Summary
I N recent years, the world has witnessed the explosive growth of smart devices and mobile users. Even if it is feasible, caching massive data replicas on dense edge servers in an ESS - is often not cost-effective because the storage resources on edge servers are expensive [19] This issue is especially critical when app vendors need to store largesize data that do not require real-time access, e.g., system upgrade files, popular app installation files, videos in online games, in ESSs mainly to save on the expenses incurred by transmitting data out of the cloud for every user. From the perspective of app vendors, the coded blocks of data stored in an ESS must be able to serve all the users at minimum storage cost while fulfilling the proximity, coverage, and transmission constraints. This problem is referred to as the erasure coding based edge data placement (EC-EDP) problem. We evaluate the performance of EC-EDP-O and EC-EDP-V against five representative approaches through extensive experiments conducted on a widely-used EUA dataset
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