Abstract
One of the use cases of mobile networks that can be considered for use in Beyond 5G is a massive IoT environment where many IoT (Internet of Things) terminals with low power consumption and computing power are connected. In order to efficiently use network resources in this environment, it is necessary to compress and reduce the amount of data uploaded by a large number of IoT terminals. In this study, we consider data compression in a Massive IoT environment using edge servers, assuming a Multi-access Edge Computing (MEC) scenario. In particular, we consider the application of “Generalized Deduplication (GD)", a stream data compression method based on duplicate deletion, which has been attracting attention in recent years for its lightweight and efficient compression of IoT sensing data. The basic GD algorithm assumes one-to-one stream transmission and reception. In this report, we propose an extension of the GD algorithm that is suitable for one-to-multi (edge server and IoT terminals) MEC environments and has more efficient performance. Specifically, we investigate dictionary construction for the GD utilization in a one-to-multi environment and show a basic evaluation of the efficiency of the proposed algorithm.
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