R&D: Degraded Read Coding Scheme in Heterogeneous Distributed Cloud Storage System for IoT Data

IEEE Xplore has published, in  2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring) proceedings, an article written by Xianfan Sun, Shushi Gu, Ye Wang, Kaiyu Liu, Harbin Institute of Technology (Shenzhen), Communication Engineering Research Center, Shenzhen, China,518055, Ning Zhang, Texas A&M University-Corpus Christi, Department of Computing Sciences, TX, USA,78412, and Qinyu Zhang, Harbin Institute of Technology (Shenzhen), Communication Engineering Research Center, Shenzhen, China, 518055.

Abstract: “The Internet of Things (IoT) is creating billions of connected devices and generating enormous amounts of data. Data needs to be stored efficiently so that it can be retrieved easily on demand. Cloud storage is an inevitable choice for data management for IoT. Because of application diversity, limited bandwidth of end devices and the demand for real time, it is necessary to decrease the cost of data access in Heterogeneous Distributed Cloud Storage System (HDCSS). According to the point that applications always access the partial data, this paper combining the data access rate, proposes a degraded read scheme based Local Reconstruction Code (LRC) to improve the local max throughput in HDCSS. Simulation results show that our proposed scheme can achieve about a 50% increase in local throughput of hot data blocks without adding additional access load compared with commonly used LRC.“