增强现实在移动周边计算中的超低延迟通信技术

Bharathiraja Nagu, Thiruneelakandan Arjunan, M. Bangare, Pradeepa Karuppaiah, Gaganpreet Kaur, Mohammed Wasim Bhatt
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引用次数: 3

摘要

增强现实(AR)技术在提高可靠性和低延迟通信(IRLC)方面已成为当今世界的一项新兴技术。为了尽量减少AR中客户设备(CE)的附件适配,将AR工作负载卸载到板载设备上可能是可行的。移动边缘计算(MEC)将提高CE的吞吐量。MEC在无线媒体上造成了巨大的开销或通信遗漏,使得选择最佳的有效载荷命题变得困难。该系统探索了协同工作以实现AR目标的车载设备。代码分割是一种贝叶斯网络,用于检查工作的整体相互依赖性。从寿命和耐久性的角度来看,它用于降低支持mec的AR环境中的供应商故障概率(PSF)。加权粒子群算法(WPSO)是在强调平衡问题的基础上提出的。因此,基于启发式的WPSO有助于改进性能度量。与现有通信技术相比,混合方法可以显着增加在各种网络场景中预测PSF的断言。初步的迭代方法适用于AR操作和IRLC场景来概括属性。
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Ultra-low latency communication technology for Augmented Reality application in mobile periphery computing
Abstract Improved Reliability and Low Latency Communication (IRLC) with Augmented Reality (AR) has become an emerging technology in today’s world. To minimize an accessory adaptation for Customer Equipment (CE) in AR, it may be feasible to offload the AR workload onto the onboard devices. Mobile-Edge Computation (MEC) will improve the throughput of a CE. MEC has caused enormous overhead or communication omissions on wireless media, making it difficult to choose the optimal payload proposition. The proposed system explores on-board devices that work together to achieve an AR goal. Code splitting is a Bayesian network used to examine the overall interdependence of efforts. From a longevity and endurance perspective, it is used to reduce the Probability of Supplier Failure (PSF) of an MEC-enabled AR environment. Weighed Particle Swarm Optimization (WPSO) was proposed despite the reality based on the emphasis on balancing the issue. As a result, a heuristic-based WPSO facilitates to improve the performance measures. A hybrid method could significantly increase the assertion of a predicted PSF in various network scenarios compared to the existing communication technologies. A preliminary iterative approach is suitable for AR operations and IRLC scenarios to generalize the attributes.
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