Abstract

The Tactile Internet promises new applications and services that harness real-time human-machine interactions to revolutionize our everyday life. Its realization however, necessitates a complete rethink of the underlying communications infrastructure as these applications/services necessitate carrier-grade reliability, ultra-high security, and ultra-low latency (∼1 ms). To meet stringent latency targets, control/steering servers are anticipated to be placed at a short distance of only a few kilometers to the tactile edge. Therefore, in addition to the significant on-going research in the wireless tactile edge, there is an urgent need to focus on the local area network (LAN) segment to support the vision of Tactile Internet. Rising to this challenge, we report on the first initiative in designing LANs to facilitate the converged delivery of latency-sensitive Tactile Internet traffic and bandwidth-intensive applications. Specifically, our solution combines the time and wavelength division multiplexing technology on a passive optical LAN, with a predictive resource allocation algorithm termed Tactile Internet capable dynamic wavelength and bandwidth allocation algorithm (TI-DWBA). TI-DWBA is designed to estimate the average bandwidth of Tactile Internet (TI) and non-TI traffic at each integrated optical network terminal/wireless access point (ONT/WAP), exploit prediction mechanisms at the central office to predict and allocate bandwidth and wavelengths to accumulated traffic at each ONT/WAP, dynamically vary the number of active wavelengths in the network such that network congestion is alleviated to satisfy end-to-end latency constraints. In this paper, the effectiveness of TI-DWBA in constraining end-to-end latency of Tactile Internet traffic is tested under various network configurations, traffic distributions, traffic proportions, and traffic loads, with results indicating that ultra-low end-to-end latencies in the order of 100 μs are achievable.

© 2017 IEEE

Resource Management in Cloud and Tactile-Capable Next-Generation Optical Access Networks

Joelle Neaime and Ahmad R. Dhaini
J. Opt. Commun. Netw. 10(11) 902-914 (2018)

Medium Access Control Protocol and Resource Allocation for Passive Optical Interconnects

Xiaoman Shen, Sailing He, and Jiajia Chen
J. Opt. Commun. Netw. 9(7) 555-562 (2017)

Machine-Learning-Based Prediction for Resource (Re)allocation in Optical Data Center Networks

Sandeep Kumar Singh and Admela Jukan
J. Opt. Commun. Netw. 10(10) D12-D28 (2018)

Towards Immersive Tactile Internet Experiences: Low-Latency FiWi Enhanced Mobile Networks With Edge Intelligence [Invited]

Martin Maier and Amin Ebrahimzadeh
J. Opt. Commun. Netw. 11(4) B10-B25 (2019)

Optimal and near-optimal alpha-fair resource allocation algorithms based on traffic demand predictions for optical network planning

Tania Panayiotou and Georgios Ellinas
J. Opt. Commun. Netw. 13(3) 53-68 (2021)