Authors: Dr. M.M. Janeela Therasa, Gayathri CL
Abstract: Mobile Edge Computing (MEC) enables low-latency data processing by bringing computation closer to users. However, it faces critical challenges such as limited storage capacity, unpredictable data patterns, network instability, and increasing volumes of duplicate data. These factors lead to performance degradation, increased retrieval latency, and inefficient resource utilization. To tackle these issues, a robust optimization-based deduplication framework is proposed. This system leverages two algorithms: UEDDE-C (Uncertainty-based Edge Data Deduplication with Column and Constraint Generation), which provides high accuracy in detecting exact duplicates, and UEDDE-A (Approximation-based), which is computationally lightweight and effective for identifying near duplicates. Furthermore, since data security is a pressing concern in edge environments, the proposed system integrates AES encryption to safeguard sensitive information before the deduplication process. This ensures not only confidentiality and integrity but also standardizes data into consistent formats for more efficient handling. The proposed framework significantly reduces redundant storage, lowers network traffic, speeds up data access, ensures security compliance, and enhances overall MEC system reliability under uncertain and dynamic conditions.
DOI: https://doi.org/10.5281/zenodo.15834266
