• ETRI Journal
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• v.44 no.6
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• pp.936-944
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• 2022

The mobile network allows redundant transmission via disjoint paths to support high-reliability communication (e.g., ultrareliable and low-latency communications [URLLC]). Although redundant transmission can improve communication reliability, it also increases network costs (e.g., traffic and control overhead). In this study, we propose a reliability-guaranteed multipath allocation algorithm (RG-MAA) that allocates appropriate paths by considering the path setup time and dynamicity of the reliability paths. We develop an optimization problem using a constrained Markov decision process (CMDP) to minimize network costs while ensuring the required communication reliability. The evaluation results show that RG-MAA can reduce network costs by up to 30% compared with the scheme that uses all possible paths while ensuring the required communication reliability.

• Journal of Internet Computing and Services
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• v.20 no.5
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• pp.113-119
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• 2019

The key features of 5G mobile communications recently commercialized can be represented by High Data Rate, Connection Density and Low Latency, of which the features most distinct from the existing 4G will be low Latency, which will be the foundation for various new service offerings. AR and self-driving technologies are being considered as services that utilize these features, and 5G Network Latency is also being discussed in related standards. However, it is true that the discussion of E2E Latency from a service perspective is much lacking. The final goal to achieve low Latency at 5G is to achieve 1ms of air interface based on RTD, which can be done through Ultra-reliable Low Latency Communications (URLLC) through Rel-16 in early 20 years, and further network parity through Mobile Edge Computing (MEC) is also being studied. In addition to 5G network-related factors, the overall 5G E2E Latency also includes link/equipment Latency on the path between the 5G network and the IDC server for service delivery, and the Processing Latency for service processing within the mobile app and server. Meanwhile, it is also necessary to study detailed service requirements by separating Latency for initial setup of service and Latency for continuous service. In this paper, the following three factors were reviewed for initial setup of service. First, the experiment and analysis presented the impact on Latency on the Latency in the case of 1 Data Lake Setup, 2 CRDX On/Off for efficient power, and finally 3H/O on Latency. Through this, we expect Low Latency to contribute to the service requirements and planning associated with Latency in the initial setup of the required services.