Distributed Computing

Distributed Computing

The information technology industry can be very cyclical. By way of example, IT has cycled between emphasizing centralized computing (such as mainframe computing model) and distributed computing (PC, laptop, smartphone, tablet).

Recently, telecom and computing network operations are moving quickly to take advantage of Cloud Computing, which entails elements of both centralized and distributed computing.

The ICT industry is realizing many benefits from centralized computing in a Cloud Computing infrastructure approach and the “as a Service” model. However, there are also instances in which a non-centralized (e.g. distributed computing) approach improves the efficiency and effectiveness of operations.

Distributed Computing

Distributed Computing represents computing at the edge of networks and is often referred to simply as Edge Computing.

There will be many opportunities within ICT for capture and processing of real-time data at the edge. Some data may remain static and/or archived in the centralized Cloud whereas data-in-motion may be dynamic and processed in real-time with corresponding real-time decision making. Artificial Intelligence (AI) can be an important component of the overall sub-system as decisions are made using AI, Big Data technologies, and intelligent predictive algorithms.

From a business perspective, edge computing is driven by certain growing market needs such as the value of processing some data locally. From a technical perspective, distributed computing is enabled by many factors including microprocessor improvements that make computing at the edge of networks more practical in terms of speed, energy efficiency, and heat output. This will be particularly important in the case of IoT Chipsets as the Internet of Things will necessitate a multitude of devices operating continuously with little or no direct human operational support.

Mobile Edge Computing

Mobile Edge Computing (MEC) is a concept developed by the European Telecommunications Standards Institute (ETSI) that aims to bring computational power into Mobile RAN to promote virtualization of software at the radio edge. MEC brings virtualized applications much closer to mobile users ensuring network flexibility, economy and scalability for improved user experience.

MEC will complement both LTE and 5G networks as processing occurs closer to the source of data capture rather than relying on back-haul to centralized resources. This will provide the dual benefit of both reducing data transport needs as well as decreasing latency, which is very important for certain real-time data intensive applications such as Haptic Internet, Augmented and Virtual Reality.

Distributed Computing in IoT: Fog Computing

IoT is going to be a big driver for distributed (Fog) computing as it is inefficient to transport all IoT data collected to centralized storage and/or to rely upon communications centrally for processing, especially for real-time analytics.  With distributed computing, Big Data Analytics can be performed at the edge of the network and results will be acted upon in real-time, as appropriate, and/or sent to the core network (e.g. centralized Cloud).

It is also important to note that IoT Data Management is a two-part system consisting of online/real-time front-end (e.g. distributed nodes) and off-line back-end (centralized Cloud storage). The online/real-time portion of the system is concerned with data management associated with distributed objects/assets/devices and their associated sensors.

Cisco Systems, ARM Holdings, Dell, Intel, Microsoft, and Princeton University, founded the OpenFog Consortium in 2015 to promote interests and development in fog computing. It is widely held understanding that Cisco originally coined the term “Fog Computing”.

The Future of MEC and Fog Computing

Both MEC and Fog Computing have the aim to create a platform that offers storage, computing power, and services at the edge of the Cloud instead of at the core Cloud. This does not mean that centralized cloud infrastructure goes away. Quite the contrary, Mind Commerce sees a centralized topology as necessary for many ICT use cases such as the many “as a service” models.

However, edge computing will become increasingly important for many wireless applications as a means of gaining greater efficiency. Applications will include both human-oriented services as well as those autonomous machine-to-machine instances associated with IoT.

Accordingly, Mind Commerce sees a bright future for edge computing in general, as well as MEC and Fog Computing in particular, as both cellular and non-cellular networks expand to support the rapidly growing Data Economy.

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