The explosive amplitude of IoT, spanning virtually every sphere, has a pivotal role to play in the expansion of fog computing market. Still considered a plausible tech sub-space by mere mortals, this business domain, an inherent extension of the cloud computing industry, is likely to actually emerge as a viable niche vertical, starting 2018, as per the predictions of The US office of National Institute of Standards and Technology (NIST). Subject to its extraordinary ability to support latency-sensitive and vertically-isolated applications by means of providing a scalable, ubiquitous, distributed, and layered network connectivity, storage, and computing, fog aims to simplify processing and IoT infrastructure. In consequence, there has been an increasing surge in exploiting the unused IT infrastructure for fog computing applications that need to compute resources in a global network. Subsequently, this has led to fog computing market gaining heavy momentum, reinforcing the buzzword of ‘fog technology’ across myriad domains.
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The far-reaching application spectrum of fog computing industry is quite evident from the numerous instances of companies tapping the fog space making headlines. A recent precedence is that of Storj Labs and SONM teaming up to enable fog computing through blockchain technology. Elaborating further, Storj Labs, a software provider has joined hands with Supercomputer Organized by Network Mining (SONM) in order to bring about distributed instances of persistent storage implemented by Storj Labs available to organizations incorporating SONM’s blockchain. Accordingly, SONM plans to build a peer-to-peer blockchain network – effectively a fog computing instance that would deal with the computing and storage of resources on the edge of a global network. The partnership marks substantial importance in fog computing marketing, having established the fact that blockchain technology and fog computing are two strongly intertwined mechanisms.
The end-use landscape of fog computing market is rather humongous and versatile, though this does not exactly come as a surprise, given how minutely IoT has brought every object under the umbrella of the Internet. As per reliable estimates, the data analyzed on devices functioning on IoT will soon approach a mammoth 40%. It has also been speculated that by the year 2020, 10% of global data will be generated by edge devices. This would fuel the demand for highly efficient fog computing solutions that simultaneously deliver holistic intelligence and low latency, subsequently driving fog computing industry size, slated to cross USD 700 million by 2024. Numerous real-time instances of the benefits of this technology have already made inroads in fog computing market – recently, the IoT company Plat One made headlines for having tapped into fog computing for improving data processing management in its 1 million sensors.
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It is pivotal to mention that mainstream hardware component developers, such as Intel, Cisco, and Dell have been making a headway in fog computing industry, as is evidenced from their interest in joining forces with vendors dealing in machine learning and IoT analytics. Through the proposed dealerships, these companies would be able to deliver IoT gateways that support fog computing. Recently in fact, Cisco took a dive in fog computing market with the acquisitions of Jasper, an IoT platform provider and ParStream, a reputed company specializing in IoT analytics. Unrefutably, these buyouts would help the electronics giant to incorporate its networking component infrastructure with highly efficient computing capabilities, which would subsequently reinforce its position in the fog computing market. Following Cisco’s lead, numerous analytics software companies have also been attempting to develop new tools for fog computing – Apache’s Spark for instance is apt for real-time processing of fog-generated data. In effect, it would be diplomatic to state that fog computing market indeed would emerge as one of most remunerative business spaces of the next decade, traversing a highly profitable growth path over 2017-2024.
Chapter 3. Fog Computing Industry Insights
3.2. Industry segmentation
3.3. Industry landscape, 2015 - 2024
3.4. Industry ecosystem analysis
3.5. Fog computing architecture analysis
3.6. Fog computing processing features
3.7. Technology & innovation landscape
3.8. Regulatory landscape
3.9. Industry impact forces
3.9.1. Growth drivers
22.214.171.124. Increasing adoption of IoT and M2M devices
126.96.36.199. Growing penetration of cloud computing
188.8.131.52. Enhanced data security & real-time operation by fog computing
3.9.2. Industry pitfalls & challenges
184.108.40.206. Security, reliability, and fault tolerance issues associated with fog computing
220.127.116.11. Complex architecture of decentralized computing
3.10. Growth potential analysis
3.11. Porter's analysis
3.12. PESTEL analysis
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