Migration Algorithm for Big Marine Data in Hybrid Cloud Storage
Huang Dongmei, Du Yanling, and He Qi
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Marine data is a typical big data. As the diversified marine data acquisition methods develop rapidly (remote sensing, GPS sensing, buoy monitoring, seabed monitoring, research ships and so on), the marine data grows explosively. However, the management of big data is a sophisticated problem currently. Cloud storage is an effective way to manage the big data. As the big marine data is characterized by massive, multisource, uncertain and especially the sensitive, the conventional architecture of cloud storage is not suitable for it. The big marine data is managed on hybrid cloud storage platform based on its characteristics and applications. Then, how to take advantage of hybrid cloud storage to manage the big marine data becomes a challenge. Data migration is the key question in the hybrid cloud storage. To resolve it, the lifecycle of big marine data is put forward, and based on it, the migration algorithm for the hybrid cloud storage is proposed. In the migration algorithm, the marine data sensitivity, data access frequency, data time length, data size and so on, are provided as the migration factors. Migration algorithm considers the capacity of data storage, attributes characteristics of marine data as well as the dynamic changes in the process of data access. The experimental results show that hybrid cloud storage pattern reduces the costs of managing big marine data greatly. Meanwhile, the access speed of big marine data is ensured by the presented migration algorithm.