Abstract
As of today, the amount of information generated is beyond imagination as transactions are taking place in millions and trillions by people and the sensors connected over the internet. A comparable volume of data is generated just by people on daily basis. Large-scale applications have become part of our life because of the revolutionary paradigm, known as the Internet of Things (IoT). Intelligence equipped millions of devices are deployed in complex networks in order to provide functions such as communication, monitoring and control of critical infrastructure. Henceforth, this tremendous growth of IoT devices and the resulting massive amount of information that was generated at network edge has further strained the highly developed intrinsic cloud computing paradigm because of occupancy of bandwidth and resource constraints. Thus, Multi-access edge computing (MEC) has emerged as an upheaval methodology to bring storage and computation in the proximity of end user, leading to the so-called MEC-enabled IoT Multi-access edge computing. It is a sort of network-based design that hypothesizes IT service deployments in affiliation with cloud computing capabilities at the network edge. The goal of MEC is to diminish latency and at the same time to ensure efficient network operations and service delivery, along with enhanced customer experience. Multi-access edge computing (also known as mobile edge computing) anchorage mobility, cloud services, and edge computing to proffer and relocate application hosts from central data centers to the network edge. This brings dual benefit of applications closer to end users and compute services closer to application data. European Telecommunications Standards Institute (ETSI) is pioneer in creating the specialized standards both in terms of technical and architectural perspective for multi-access edge computing.
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Kavali, L.M., Kalpana, P., Srinivasa Naveen Kumar, G., Jagannadha Rao, D.B. (2023). Perlustration into Multi-access Edge Computing: A Prospective Approach. In: Reddy, V.S., Prasad, V.K., Wang, J., Rao Dasari, N.M. (eds) Intelligent Systems and Sustainable Computing. ICISSC 2022. Smart Innovation, Systems and Technologies, vol 363. Springer, Singapore. https://doi.org/10.1007/978-981-99-4717-1_47
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