New compute paradigm: edgy

Phil Marshall / Tolaga Research

The debate continues: when should compute resources be centralized and when should they be decentralized? Historically, compute architectures have vacillated between the two, depending on the underlying systems and services being supported.

Currently, cloud computing favors centralization, particularly for services that are supported with public infrastructure. In response, web-scale providers have deployed massive data centers in key strategic locations across the globe.

Amazon, Microsoft and Google each have 14-15 major data centers to support their global services. Centralized cloud architectures enable efficiencies and economies of scale that have helped propel the profitability of web-scale providers, and fuel the destruction of the traditional telecom industry by driving value away from networks.

See Also

Telecom Asia December 2016/January 2017
5G starts to find traction
LPWA IoT gains traction
AI boost for operators worldwide

Living on the edge

Although centralized cloud architectures will prevail for the foreseeable future, there is a growing need for decentralized solutions with edge computing. Edge computing is a young technology that suits a variety of services, particularly latency sensitive ones (AR/VR), services with specific security or connectivity demands, and high-bandwidth media applications. Many of the services promised for advanced 4G and 5G also depend on edge compute architectures, as do next-gen network functions such as cloud-RAN.

Network operators can capitalize on edge computing’s ability to bring value closer to the network. But there’s competition from companies like Amazon and Microsoft-both these behemoths now promote proprietary enterprise edge compute solutions which are tightly coupled with their respective cloud platforms and targeted specifically for the IoT.

Standards, anyone?

The edge compute initiatives being pursued by network operators are tied to several industry standards, including:

Multi-Access Edge Computing (MEC), spearheaded by the 3GPP.

CORD (Central Office Re-Architected as a Data Center), which was initially pioneered by AT&T to apply data center technology in central office locations.

CUPS (Control User Plane Separation), an important 3GPP initiative to simplify mobile edge compute architectures and operations.

The edge compute strategies of network operators are in stark contrast to the IoT-centric strategies being pursued by Amazon and Microsoft.

In many cases, network operators are focusing edge compute primarily towards cloud-network initiatives such as NFV and cloud-RAN. While both NFV and cloud-RAN are important, we believe they potentially obscure the opportunities that Amazon and Microsoft now target. These opportunities address digitization activities across many sectors including retail, manufacturing, smart cities, and healthcare.

For the most part, wide area network coverage and mobility is not required. Instead, solutions are more campus or regionally oriented. Many of the applications are well supported by mid-tier integrated edge compute platforms, rather than the high-end platforms needed for NFV and cloud-RAN. 

Survival of the fittest

The business cases for edge compute are challenging and will determine the use-cases that thrive, and those that don’t. Campus or regionally orientated edge compute architectures are appealing since they target the infrastructure where it is needed. When wide area network implementations are deployed, network operators must pay attention to the number of edge compute sites they implement, and the compute functionality provisioned. Since high-end edge compute platforms are needed to support NFV and cloud-RAN capabilities, it is currently prohibitively expensive to deploy these capabilities across the central office footprint of a typical network, as is intended with CORD. However, CORD based implementations are currently viable for end-user services that can be supported with less expensive edge compute infrastructure.

Although edge compute is nascent, it’s already in demand for enterprise-led implementations, particularly for IoT applications. We believe it’s important for network operators to broaden their edge compute initiatives to capitalize on this demand. We also believe that if network operators don’t align their edge compute strategies with tangible end-user demands, they might fall into a similar trap that the industry experienced with Internet Multimedia Subsystems (IMS) in past. 

This article first appeared on Telecom Asia December 2017 / January 2018



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