A Bit String Content Aware Chunking Strategy for Reduced CPU Energy on Cloud Storage

Abstract

In order to achieve energy saving and reduce the total cost of ownership, green storage has become the first priority for data center. Detecting and deleting the redundant data are the key factors to the reduction of the energy consumption of CPU, while high performance stable chunking strategy provides the groundwork for detecting redundant data. The existing chunking algorithm greatly reduces the system performance when confronted with big data and it wastes a lot of energy. Factors affecting the chunking performance are analyzed and discussed in the paper and a new fingerprint signature calculation is implemented. Furthermore, a Bit String Content Aware Chunking Strategy (BCCS) is put forward. This strategy reduces the cost of signature computation in chunking process to improve the system performance and cuts down the energy consumption of the cloud storage data center. On the basis of relevant test scenarios and test data of this paper, the advantages of the chunking strategy are verified.

Blockchain‐based data deduplication using novel content‐defined chunking algorithm in cloud environment

“…34,35 Researchers primarily concentrate on enhancing data chunking methods to raise the deduplication ratio. According to Zhou et al, 36 the chunking stage of most modern chunking algorithms uses the Rabin method sliding window, which uses a lot of CPU resources and affects performance. The authors subsequently proposed a novel chunking technique known as the bit string content-aware chunking strategy (BCCS), which determines the chunks fingerprint via a simple shift operation in order to reduce resource usage.…”