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chariotadmin  
#1 Posted : 21 August 2019 10:24:12(UTC)
chariotadmin

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Cloud Computing
We’ve already got used to the technical term cloud, which is a network of multiple devices, computers and servers connected to each other over the Internet.
Such a computing system can be figuratively divided into two parts:
  • The frontend — consists of client devices (computers, tablets, mobile phones).

  • The backend — consists of data storage and processing systems (servers) that can be located far away from the client devices and make up the cloud itself.

These two layers communicate with each other directly by means of wireless connections.

Cloud computing technology provides various types of services that are categorized into three groups:
  • IaaS (Infrastructure as a Service) — a remote data center with resources such as data storage capacity, processing power and networking.

  • PaaS (Platform as a Service) — a development platform with tools and components for creating, testing and launching applications.

  • SaaS (Software as a Service) — ready-made software tailored to a variety of business needs.


Pros of Cloud for IoT
Since connected devices have limited storage capacity and processing power, the integration with cloud computing comes to assistance:
  • Improved performance (the communication between IoT sensors and data processing systems is faster)

  • Storage capacities (highly scalable and unlimited storage space are able to integrate, aggregate and share the enormous amount of data)

  • Processing capabilities (remote data centers provide unlimited virtual processing capabilities on-demand)

  • Reduced costs (license fees are lower than the cost of the on-premise equipment and its continuous maintenance)


Cons of Cloud for IoT
Unfortunately, there is nothing immaculate, and cloud technology has some downsides, especially for the Internet of Things services.
High latency (more and more IoT apps require very low latency, but cloud can’t guarantee it because of the distance between client devices and data processing centers)
Downtime (technical issues and interruptions in networks may occur for any reason in any Internet-based system and make customers suffer from an outage; many companies use multiple connection channels with automated failover to avoid problems)
Security and privacy (your private data is transferred through globally connected channels alongside thousands of gigabytes of other users’ information; no surprise that the system is vulnerable to cyberattacks or data loss; the problem can be partially solved with the help of hybrid or private clouds)

Fog Computing
The term fog computing (or fogging) was coined by Cisco in 2014, so it is new for the general public. Fog and cloud computing are interconnected. In nature, fog is closer to the earth than clouds; in the technological world, it is just the same, fog is closer to end-users, bringing cloud capabilities down to the ground.
The definition may sound like this: fog is the extension of cloud computing that consists of multiple edge nodes directly connected to physical devices.

Pros of Fog Computing
The fogging approach has many benefits for the Internet of Things, Big Data and real-time analytics. Here are the main advantages of fog computing over cloud computing:
  • Low latency (fog is geographically closer to users and is able to provide instant responses)

  • No problems with bandwidth (pieces of information are aggregated at different points instead of sending them together to one center via one channel)

  • Loss of connection is impossible (due to multiple interconnected channels)

  • High security (because data is processed by a huge number of nodes in a complex distributed system)

  • Improved user experience (instant responses and no downtimes satisfy users)

  • Power-efficiency (edge nodes run power-efficient protocols such as Bluetooth, Zigbee or Z-Wave)


Cons of Fog Computing
The technology doesn’t have any apparent disadvantages, but some shortcomings can be named:
  • A more complicated system (fog is an additional layer in the data processing and storage system)

  • Additional expenses (companies should buy edge devices: routers, hubs, gateways)

  • Limited scalability (fog is not as scalable as cloud)


Fog Computing vs. Cloud Computing: Key Differences
Cloud vs. fog concepts are very similar to each other. But still, there is a difference between cloud and fog computing on some parameters. Here is a point-by-point comparison of fog computing and cloud computing:
  • Cloud architecture is centralized and consists of large data centers that can be located around the globe, a thousand miles away from client devices. Fog architecture is distributed and consists of millions of small nodes located as close to client devices as possible.

  • Fog acts as a mediator between data centers and hardware, and hence it is closer to end-users. If there is no fog layer, the cloud communicates with devices directly, which is time-consuming.

  • In cloud computing, data processing takes place in remote data centers. Fog processing and storage are done on the edge of the network close to the source of information, which is crucial for real-time control.

  • Cloud is more powerful than fog regarding computing capabilities and storage capacity.

  • The cloud consists of a few large server nodes. Fog includes millions of small nodes.

  • Fog performs short-term edge analysis due to instant responsiveness, while the cloud aims for long-term deep analysis due to slower responsiveness.

  • Fog provides low latency; cloud — high latency.

  • A cloud system collapses without an Internet connection. Fog computing uses various protocols and standards, so the risk of failure is much lower.

  • Fog is a more secure system than the cloud due to its distributed architecture.



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