About Muhammad Sarwar

Working as a key contributor to Fujitsu’s network solutions strategy, architecture and portfolio, Muhammad Sarwar applies his extensive expertise in multiple areas. These include future product and roadmap planning; product and partnership management; idea and product incubation; and innovation in digital transformation. His particular areas of interest include data center networking; network management, abstraction, and security; automation and analytics; SDN/NFV; and emerging technologies in areas such as augmented reality, autonomous/connected vehicles, and blockchain.

These Four Tenets are the Secrets of Hyperscale Optical Transport

The ever-expanding demands of data center interconnect were never going to be easy to address. Data center operators facing constant pressure for better cost metrics in terms of bandwidth and rack space density know that when the chips are down, it’s all about economics of scale—or more accurately, scalability.

With the new 1FINITY T600 optical transport blade, the quest to deliver the maximum amount of traffic and the highest performance at the minimum possible cost is suddenly much more reasonable and achievable. In addition to being the first compact modular blade to offer ultra-high speed transmission up to 600G, the T600 delivers the highest spectral efficiency in the industry: up to 76.8 Tbps per single fiber, enabling maximum performance and capacity for both data center interconnect (DCI) and 5G applications.

The T600’s value for data center operators can be broken down into four tenets that were uppermost in our minds as we designed the platform. These four tenets represent the cornerstones of hyperscale optical transport for next-generation DCI as well as 5G:

  • Flexibility – Designed to support all DCI applications, the T600 offers a wide range of configuration options and is engineered to scale progressively while controlling cost per bit per km.
  • Capacity – To enable extreme optical transport use cases, the T600 supports 600G transmission with both C- and L-band spectrum on the line side, as well as providing client ports that are upgradeable to 400 GbE, further boosting capacity; the blade will soon offer 6 × 400 GbE client ports as an option in place of the existing 24 × 100 GbE ports.
  • Automation – Starting with the feature-rich system software on the blade, Fujitsu has embraced the open-source model and laid the foundations for automation that simplifies operations and enhances adoption of network-level automation.
  • Security – From management to control to data plane, the T600 incorporates security measures to protect critical data from intrusion, including Layer 1 encryption and compliance with Federal Information Processing Standard (FIPS) 140-2 as well as built-in physical design defenses.

Hyperscale optical transport will require extreme but flexible fiber capacity and reach capabilities that can be scaled for various DCI applications. Fujitsu addresses these needs with the 1FINITY T600 Transport blade, enabling data centers and cloud providers to equip their networks for the demands of the hyperconnected digital economy.

Find out more about the four tenets of hyperscale optical transport on the 1FINITY T600 blade—watch our video intro and check out the hyperscale transport technology brief.

Networks and Vehicles Follow Similar Journey to Automation

Autonomous vehicles (let’s call them AVs) and Autonomous Networks (ANs) are road-mates; they’ve essentially traveled the same route in the quest for full automation. They share the overarching Holy Grail objective of zero-touch operation, undisturbed by human hand as they go about the full range of their respective operations.

The Society of Automotive Engineers (SAE) has defined a six-degree taxonomy that classifies the level and type of automation capabilities in a given vehicle. This is summarized on Wikipedia’s Self-Driving Car page and illustrated in Figure 1.

Figure 1: SAE levels of vehicle automation

Both AVs and ANs have already arrived at their third level of automation, i.e. partial automation, where most of what they do is automated—but human supervision, monitoring, and even interaction is still needed. And just as AVs have relied upon an evolving set of building blocks over decades, ANs have also employed and built upon a number of tools along the way. Figure 2 illustrates this cumulative evolution.

Figure 2: Building blocks of network evolution

There are many examples of these building blocks in the network world. For instance, we have the availability and growing adoption of zero-touch provisioning (ZTP); YANG model-based open interfaces (NETCONF, REST APIs, gNMI/gNOI); gRPC-based deep-streaming telemetry; extensive, detailed logging and monitoring; and streaming for rapid fault isolation and prediction.

Perhaps the most critical characteristic that AVs and ANs share is that in order for their potential to be fulfilled, diverse stakeholders need to come together and coordinate. In the AV world, massive efforts are underway at every level (governments, cities and towns, car companies, insurance companies, and technology vendors) to standardize and streamline end-to-end operations based on key principles of interoperation, openness and reliability.

For ANs, there is a similar and pressing need by networking community for collaborative, coordinated development of an open, generic framework for a fully autonomous optical network, which could be used for setting up reference use cases that can be extended to various network architectures. This framework should be driven by the primary requirement of ZERO human intervention in network operations after initial deployment—including configuration, monitoring, fault isolation, and fault resolution. The framework should leverage currently available tools and technologies for full-featured and automation-ready software, such as Fujitsu System Software version 2 (FSS2) for network element management, in conjunction with Fujitsu Virtuora®, an open network control solution for network element and network management.

Efforts to achieve autonomous networks and autonomous vehicles show strong similarities in terms of both pace and trends.  These similarities are driven by common objectives to, primarily, address scale and the need for a growing number of applications, while tackling the human error element, and enabled by an intertwined and cross-dependent set of technology advancements and adaptations.