“Australia’s strategic environment has deteriorated more rapidly than anticipated” was the frank admission in the government’s Defence Strategic Update released last year. This confronting assessment was accompanied by an acknowledgement that Australia needed to sharply step up its capability if we are to sustain an edge on the battlefield.
For Defence Minister Peter Dutton the focus is clear. In his first speech as Minister he said:
“We must do everything we can to put the ADF in the strongest possible position in what is a very, very uncertain time. We owe it to the men and women of the ADF to give them the tools and resources they need to get on with their job, and to keep both themselves and our country safe.”
In previous eras, addressing this directive might involve sourcing a better weapon, or a more resilient uniform. Today, these things still matter, but edge computing and the resulting information superiority it delivers is where our frontline land forces stand to make the greatest gains against our adversaries.
Achieving land force information superiority requires a radical departure from old ways of doing things.
Foremost, it relies on the ability to have an enterprise-wide view of data from all sources and making sense of that data to deliver real time decision advantage of the battlespace.
Getting to this end state is not without its challenges, but it is essential to maintain our edge. Communication stovepipes, data silos and processing capabilities across poorly integrated ICT estates make any analysis of fast and big data challenging. Often ICT estates have evolved over time, in complex political and departmental decision-making processes, that will not deliver the strategic transformation needed to win in future wars.
The introduction of edge computing within a hybrid cloud operating model is what will move us from the current mess to a transformative ability for land forces to improve real time decision making across the battlespace.
How will it do this? Fundamentally, it delivers mission outcomes by serving those closest to the action, the warfighter. Rather than bulk transferring of large data sets from the field to a central processing data centre (an enormous challenge in many battlefield environments), edge computing allows for distributed processing to be performed in deployed hybrid cloud environments leveraging cloud services in a ruggedized form to provide compute, block and object storage exactly where soldiers need it most: the battlefield. Typical cloud services - such as containerisation, deployable images, infrastructure as code, clustering, Artificial Intelligence (AI), Machine Learning (ML), IoT, streaming analytics and exploitation of 5G for operational uses - facilitate faster response times while reducing latency and perishability of raw data for intelligence means in support of land forces.
Of course, land forces don’t operate in isolation. The fusion of intelligence within military domains assists in enhancing the quality of intelligence preparation of the battlefield. As an example, the fusion of Passive Collection Airborne ISR (AISR) assets forms an integral part in battlespace situational awareness for land forces across SIGINT, COMINT, ELINT and IMINT for early Indicators & Warning (I&W) of enemy force posture. But at present fusion and processing of Full Motion Video (FMV), EO/IR imaging, Foliage Penetration Radar, and other sensor suites are challenged by existing fitted systems. Often software processing and applications are tightly coupled to the operating systems and hardware, making system changes and upgrades more difficult and time consuming. Differing sensor systems also have differing deployment and maintenance models with limited onboard processing capabilities that can leverage AI and ML to rapidly support early detection of time-sensitive signals. All this is further compounded by constrained bandwidth limitations that impact on the ability to process raw feeds in real time.
Extending beyond passive collection, once returned to a Forward Operating Base (FOB) or HQ, post analysis and processing of collected multi-intelligence data, video, image recognition, and audio analysis is not easy using the old ways of doing things. It is performed with constraints on raw data size, and perishability issues of raw data and ability to synchronise to core processing data centres back home for further enrichment and analysis: often some large datasets are flown back due to cost and network issues. These sub-systems have been delivered in isolation and not fully integrated and with the inability to evolve naturally across platform changes. Outdated systems and hardware often with high customisation and skill sets impact mission performance. These systems also often sit outside the IT modernisation strategies of many militaries for cloud native approach from core to edge, thus not fully capturing the advantages gained by DevSecOps.
End-to-end core to edge systems across the ecosystem are not fully integrated and have been developed and deployed in isolation from a broader IT architecture strategy. Edge computing across a hybrid cloud model will evolve to remove many of the current challenges highlighted above, and deal with the reality that new platforms will continually be deployed in isolation. For instance, the ability to deploy Roving Edge Devices (RED) in nodes or clusters for processing and data storage in deployed environments, provides for enhanced real/near-real time multi-intelligence decision support for land forces when it really counts. RED has the ability to facilitate cloud services, cloud functionality of containerisation, functions, images, AI, ML, IoT and leverag the power of GPUs to process at mission speed. The ability to support DevSecOps, deliver elasticity and scalability through ML model deployment, and hybrid cloud flexibility and choice while fully capturing the operational advantages of 5G will be a powerful game changer.
In summary, imagine an Australian soldier able to seamlessly achieve information superiority by making sense in real-time of the myriad data streams currently available, but which currently are unusable on the spot. Imagine the ability to use edge computing to leverage the power of AI on AISR coupled with automated FMV with video analytics, and the ability to apply voice biometrics in real time to support land force operations. Oracle RED provides the flexibility to support edge cloud services in congested and constrained environments to enhance land force battlespace situational awareness, operational planning, targeting and execution more effectively. The geopolitical environment is changing, and time is no longer on our side. It’s time Australia lifted its game!