Orchestrating Image Retrieval and Storage over A Cloud System
IEEE Transactions on Cloud Computing
; 2022.
Article
in English
| Scopus | ID: covidwho-1788784
ABSTRACT
Since massive numbers of images are now being communicated from, and stored in different cloud systems, faster retrieval has become extremely important. This is more relevant, especially after COVID-19 in bandwidth-constrained environments. However, to the best of our knowledge, a coherent solution to overcome this problem is yet to be investigated in the literature. In this paper, by customizing the Progressive JPEG method, we propose a new Scan Script to ensure Faster Image Retrieval. Furthermore, we also propose a new lossy PJPEG architecture to reduce the file size as a solution to overcome our Scan Script's drawback. In order to achieve an orchestration between them, we improve the scanning of Progressive JPEG's picture payloads to ensure Faster Image Retrieval using the change in bit pixels of distinct Luma and Chroma components (Y, C<sub>b</sub>, and C<sub>r</sub>). The orchestration improves user experience even in bandwidth-constrained cases. We evaluate our proposed orchestration in a real-world setting across two continents encompassing a private cloud. Compared to existing alternatives, our proposed orchestration can improve user waiting time by up to 54% and decrease image size by up to 27%. Our proposed work is tested in cutting-edge cloud apps, ensuring up to 69% quicker loading time. IEEE
Cloud computing; Discrete Cosine Transform; Discrete cosine transforms; Encoding; Faster Image Retrieval; Image coding; Image Compression; Loading; Progressive JPEG (PJPEG); Quantization (signal); Scan Script; Transform coding; Bandwidth; Cosine transforms; Image enhancement; Image retrieval; Search engines; Vector quantization; Bandwidth-constrained; Cloud systems; Cloud-computing; Encodings; Fast image retrieval; Images compression; Progressive JPEG
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
IEEE Transactions on Cloud Computing
Year:
2022
Document Type:
Article
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