Asperitas Microdatacenter

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A microdatacenter is a small, self contained data center consisting of computing, storage, networking, power and cooling. Micro data centers may employ water cooling to achieve compactness, low component count, low cost and high energy efficiency. Its small size allows decentralised deployment in places where traditional data centers cannot go, for instance edge computing for Internet of things.

The Internet of Things (IoT) is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers (UIDs) and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction.

Distributed Micro Edge Data centers

Micro edge data centers (10-200 kW) function as forward locations of the core data centers. The edge nodes are continuously connected and/or replicated with the core datacenters and several strategic other edge nodes. This provides constant availability through geo-redundancy. [1]

By making information available in multiple locations at the same time, it becomes easy to exchange between different physical structures when interacting with the information. The capacity of overhead installations can be minimised to allow only for normal operation and a shutdown phase in case of emergency while active data processes are moved to a different facility.

The micro edge nodes are small locations with minimised overhead installations. They will have simplified configurations which consists of a small data floor, switchboard and energy delivery. Often without redundancy in power or cooling infrastructure (there is a significant thermal buffer with Immersed Computing®), but with sufficient sustainable Li-ion battery power (i.e. Tesla Powerpack) to allow for replication and shutdown. The facilities are optimally equipped with liquid cooling technologies to reduce overhead installations. This allows these facilities to become enclosed air environments which prevents environmental impact like noise or exterior installations. The liquid infrastructure is cooled with any present external cooling strategy which is available.

Edge management

The management of the distributed datacenter model, is possible through the emergence of software platforms providing ubiquitous management of data, network and computation capacities. These kind of platforms already exists for traditional centralised infrastructure, but new challenges emerge from this hybrid and distributed architecture. Closer to the end users, edge nodes in urban areas have new constraints in terms of energy consumption and heat production. Containerisation, through technologies like Docker [2] or Singularity, [3] opens great opportunities to make applications more scalable, flexible and less dependent on the infrastructure. Many frameworks appeared recently (Swarm, Kubernetes [4] ) to manage decentralised clusters. Some of them also integrate energy and heat management by design like “Q.ware [5] ” developed by Qarnot computing. [6] This positive dynamic in the software industry is an essential pillar to enabling core datacenters and edge nodes with an integrated architecture.

Network optimization

The use of core data centers and edge nodes allows for network optimisation by preventing long distance transport of raw (large) data and allowing the processing of data close to the source. By bringing data which is in high demand closer to the end user (caching), high volume data transmission across long distance backbones is greatly reduced, as well as latency which is a critical factor for delivering good end user experience.

Energy grid balancing

One of the limitations for datacenter growth is the capacity of the existing power grid. In most areas in the world, the power grid was designed and implemented long before data centers even existed. There are numerous areas where the power grid will reach its maximum capacity within the next 3–5 years. The traditional datacenter approach causes high loads on very specific parts of the grid. By applying the distributed data center model, the power grid is more balanced and the impact of expansion greatly reduced.

Energy production

By focusing on the reuse of energy, each edge node can reject its thermal energy directly into a reusable heat infrastructure (district heating/heat storage), building heating (hospitals/industry), water heating (hospitals/zoos) or other heat users. The core data centers become large suppliers of district heating networks or will be connected to 24/7 industries which require constant heating within a large scale industrial process.

See also

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References

  1. ↑ mmacy. "Data replication in Azure Storage". docs.microsoft.com. Retrieved 2017-07-25.
  2. ↑ "Docker". Docker. Retrieved 2017-07-25.
  3. ↑ "Singularity | Singularity". singularity.lbl.gov. Retrieved 2017-07-25.
  4. ↑ "Kubernetes". Kubernetes. Retrieved 2017-07-25.
  5. ↑ "Qarnot - The first computing heater for smart buildings". www.qarnot.com. Retrieved 2017-07-25.
  6. ↑ Computing, Qarnot. "Qarnot Computing". compute.qarnot.com. Retrieved 2017-07-25.
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