What are the latest trends and innovations in traffic engineering research and development?

2 Machine learning

Another emerging trend in traffic engineering is the application of machine learning (ML) techniques to analyze, predict, and optimize network traffic. ML can help traffic engineers to understand the patterns, behaviors, and anomalies of network traffic, and to identify the factors that affect its quality of service (QoS) and quality of experience (QoE). ML can also help traffic engineers to design and implement adaptive and intelligent traffic control mechanisms, such as load balancing, congestion control, routing optimization, and traffic shaping. ML can also enable traffic engineers to automate and improve network operations, such as fault detection, diagnosis, and recovery, and security and privacy protection.

3 Multi-domain and multi-layer traffic engineering

A third trend in traffic engineering is the development of multi-domain and multi-layer traffic engineering solutions, which aim to coordinate and optimize traffic across different network segments, domains, and layers. Multi-domain traffic engineering involves the interoperability and collaboration of different network operators, service providers, and end-users, who may have different objectives, policies, and constraints. Multi-layer traffic engineering involves the integration and coordination of different network layers, such as optical, IP, MPLS, and wireless, which may have different characteristics, capabilities, and limitations. Multi-domain and multi-layer traffic engineering solutions require advanced techniques and tools, such as network slicing, segment routing, cross-layer optimization, and distributed coordination.

4 Edge and fog computing

A fourth trend in traffic engineering is the integration of edge and fog computing, which aim to bring computing and storage resources closer to the network edge, where the data sources and consumers are located. Edge and fog computing can help traffic engineers to reduce network latency, bandwidth consumption, and energy consumption, and to improve network scalability, reliability, and security. Edge and fog computing can also enable traffic engineers to support new applications and services that require low latency, high bandwidth, and real-time processing, such as augmented reality, virtual reality, smart cities, and autonomous vehicles.

5 Green and sustainable traffic engineering

A fifth trend in traffic engineering is the adoption of green and sustainable traffic engineering practices, which aim to minimize the environmental impact and energy consumption of network traffic. Green and sustainable traffic engineering involves designing, implementing, and managing network traffic in a way that reduces carbon emissions, waste generation, and resource depletion. Green and sustainable traffic engineering also involves exploiting renewable energy sources, such as solar, wind, and hydro, to power network devices and equipment. Green and sustainable traffic engineering also involves promoting social and ethical values, such as fairness, inclusiveness, and transparency, in network traffic management.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?