An enhanced scheme for image deduplication in iot environment

Abstract

The unprecedented growth of digital data in Internet of Things (IoT) and newlinecloud ecosystem is exerting an extra load on storage systems due to duplicate newlinedata in geographical distributed locations of users. Deduplication as a data newlinecompression technique has gained attention in large distributed storage newlinesystems. Deduplication solves data redundancy problem, reduces storage newlinecost, improves storage efficiency and provides fast data availability in newlinetoday s data intensive real-life applications. newlineIt efficiently improves data storage by reducing storage and maintenance newlineof unnecessary data. However, storage optimization still remains a challenge newlinein resource-constrained IoT environment, where data intensive real life IoT newlineapplications are producing an enormous amount of data. Thus, detection and newlineelimination of duplicate data in IoT environments in timely manner becomes newlinecrucial. Data deduplication/ redundancy elimination techniques significantly newlinereduce the impact of duplicate data generated, on low-resource constrained newlineend devices in IoT environment. Most of the existing solutions have not been newlineable to achieve the desired requirements of duplicate detection for newlineunannotated data generated by geographical varying locations of users in IoT newlineenvironment with less computation overhead. In existing schemes most of newlinethe work has been performed at cloud level for normal and secure newlinededuplication. Less attention has been given to latency issues being faced by newlineuser applications at edge level in IoT environment, the main cause of newlinebringing deduplication schemes near the edge level. Hence, computationally newlineefficient data duplicate detection schemes for deduplication in IoT newlineenvironment are needed. newlineAddressing the issue of deduplication newline