Why IoT Needs Fog Computing?


Source: vector

The Internet of Things (IoT) is one of the hottest mega-trends in technology – and for good reason , IoT deals with all the components of what we consider web 3.0 including Big Data Analytics, Cloud Computing and Mobile Computing .

The Challenge

The IoT promises to bring the connectivity to an earthly level, permeating every home, vehicle, and workplace with smart, Internet-connected devices. But as dependence on our newly connected devices increases along with the benefits and uses of a maturing technology, the reliability of the gateways that make the IoT a functional reality must increase and make uptime a near guarantee. As every appliance, light, door, piece of clothing, and every other object in your home and office become potentially Internet-enabled; The Internet of Things is poised to apply major stresses to the current internet and data center infrastructure. Gartner predicts that the IoT may include 26 billion connected units by 2020.


The popular current approach is to centralize cloud data processing in a single site, resulting in lower costs and strong application security. But with the sheer amount of input data that will be received from globally distributed sources, this central processing structure will require backup. Also most enterprise data is pushed up to the cloud, stored and analyzed, after which a decision is made and action taken. But this system isn’t efficient, to make it efficient, there is a need to process some data or some big data in IoT case in a smart way, especially if it’s sensitive data and need quick action.

To illustrate the need for smart processing of some kind of data, IDC estimates that the amount of data analyzed on devices that are physically close to the Internet of Things is approaching 40 percent, which supports the urgent need for a different approach to this need.


Source: Cisco

The Solution

To deal with this challenge, Fog Computing is the champion.

Fog computing allows computing, decision-making and action-taking to happen via IoT devices and only pushes relevant data to the cloud, Cisco coined the term “Fog computing “and gave a brilliant definition for Fog Computing: “The fog extends the cloud to be closer to the things that produce and act on IoT data. These devices, called fog nodes, can be deployed anywhere with a network connection: on a factory floor, on top of a power pole, alongside a railway track, in a vehicle, or on an oil rig. Any device with computing, storage, and network connectivity can be a fog node. Examples include industrial controllers, switches, routers, embedded servers, and video surveillance cameras.”


Source : Cisco

To understand Fog computing concept, the following actions define fog computing:

  • Analyzes the most time-sensitive data at the network edge, close to where it is generated instead of sending vast amounts of IoT data to the cloud.
  • Acts on IoT data in milliseconds, based on policy.
  • Sends selected data to the cloud for historical analysis and longer-term storage.

Benefits of using Fog Computing

  • Minimize latency
  • Conserve network bandwidth
  • Address security concerns at all level of the network
  • Operate reliably with quick decisions
  • Collect and secure wide range of data
  • Move data to the best place for processing
  • Lower expenses of using high computing power only when needed and less bandwidth
  • Better analysis and insights of local data

Keep in mind that fog computing is not a replacement of cloud computing by any measure, it works in conjunction with cloud computing, optimizing the use of available resources. But it was the product of a need to address two challenges, real-time process and action of incoming data, and limitation of resources like bandwidth and computing power, another factor helping fog computing is the fact that it takes advantage of the distributed nature of today’s virtualized IT resources.  This improvement to the data-path hierarchy is enabled by the increased compute functionality that manufacturers are building into their edge routers and switches.

Real-Life Example:

A traffic light system in a major city is equipped with smart sensors. It is the day after the local team won a championship game and it’s the morning of the day of the big parade. A surge of traffic into the city is expected as revelers come to celebrate their team’s win. As the traffic builds, data are collected from individual traffic lights. The application developed by the city to adjust light patterns and timing is running on each edge device. The app automatically makes adjustments to light patterns in real time, at the edge, working around traffic impediments as they arise and diminish. Traffic delays are kept to a minimum, and fans spend less time in their cars and have more time to enjoy their big day.

After the parade is over, all the data collected from the traffic light system would be sent up to the cloud and analyzed, supporting predictive analysis and allowing the city to adjust and improve its traffic application’s response to future traffic anomalies. There is little value in sending a live steady stream of everyday traffic sensor data to the cloud for storage and analysis. The civic engineers have a good handle on normal traffic patterns. The relevant data is sensor information that diverges from the norm, such as the data from parade day.

The Dynamics of Fog Computing

Fog computing, thought of as a “low to the ground” extension of the cloud to nearby gateways, and proficiently provides for this need. As Gartner’s Networking Analyst, Joe Skorupa puts it: “The enormous number of devices, coupled with the sheer volume, velocity and structure of IoT data, creates challenges, particularly in the areas of security, data, storage management, servers and the data center network with real-time business processes at stake. Data center managers will need to deploy more forward-looking capacity management in these areas to be able to proactively meet the business priorities associated with IoT.”

For data handling and back-haul issues that shadow the IoT’s future, fog computing offers a functional solution. Networking equipment vendors proposing such a framework, envisions the use of routers with industrial-strength reliability, running a combination of open Linux and JVM platforms embedded with vendor’s own proprietary OS. By using open platforms, applications could be ported to IT infrastructure using a programming environment that’s familiar and supported by multiple vendors. In this way, smart edge gateways can either handle or intelligently redirect the millions of tasks coming from the myriad sensors and monitors of the IoT, transmitting only summary and exception data to the cloud proper.

Source: Cisco

Fog Computing and Smart Gateways

The success of fog computing, hinges directly on the resilience of those smart gateways directing countless tasks on an internet teeming with IoT devices. IT resilience will be a necessity for the business continuity of IoT operations, with the following task to insure that success:

  • Redundancy
  • Security
  • Monitoring of power and cooling
  • Failover solutions in place to ensure maximum uptime

According to Gartner, every hour of downtime can cost an organization up to $300,000. Speed of deployment, cost-effective scalability, and ease of management with limited resources are also chief concerns.


Moving the intelligent processing of data to the edge only raises the stakes for maintaining the availability of these smart gateways and their communication path to the cloud. When the IoT provides methods that allow people to manage their daily lives, from locking their homes to checking their schedules to cooking their meals, gateway downtime in the fog computing world becomes a critical issue. Additionally, resilience and failover solutions that safeguard those processes will become even more essential.









10 Predictions for the Future of IoT


A Google search for “Internet of Things” term reveals over 280,000,000 results, thanks to the media making the connection between the smart home wearable devices, and the connected automobile, IoT has begun to become part of the popular parlance. But that’s not the complete picture, according to Gartner’s Nick Jones, vice president and distinguished analyst “The IoT demands an extensive range of new technologies and skills that many organizations have yet to master,” he  added “A recurring theme in the IoT space is the immaturity of technologies and services and of the vendors providing them. Architecting for this immaturity and managing the risk it creates will be a key challenge for organizations exploiting the IoT. In many technology areas, lack of skills will also pose significant challenges.”

In the coming years, IoT will look completely different than it does today. IoT is a greenfield market. New players, with new business models, approaches, and solutions, can appear out of nowhere and overtake incumbents. But business is the key market. While there is talk about wearables and connected homes, the real value and immediate market for IoT is with businesses and enterprises. The adoption of IoT will be much more similar to the traditional IT diffusion model (from businesses to consumers) than the consumer-led adoption of social media and personal mobility.


The top 10 trends of IoT according to Gartner:

1.Platforms. The platform is the key to success. The “things” will get increasingly inexpensive, applications will multiply, and connectivity will cost pennies.  Keeping in mind that IoT platforms bundle many of the infrastructure components of an IoT system into a single product. The services provided by such platforms fall into three main categories:

    • Low-level device control and operations such as communications, device monitoring and management, security, and firmware updates.
    • IoT data acquisition, transformation and management.
    • IoT application development, including event-driven logic, application programming, visualization, analytics and adapters to connect to enterprise systems.

2.Standards and Ecosystems. Gartner noted that as IoT devices proliferate, new ecosystems will emerge, and there will be “commercial and technical battles between these ecosystems” that “will dominate areas such as the smart home, the smart city and healthcare. Organizations creating products may have to develop variants to support multiple standards or ecosystems and be prepared to update products during their life span as the standards evolve and new standards and related APIs emerge,” according to Gartner. There will be a battle for IoT application mindshare. With billions of devices projected to be spewing out petabytes of data, application developers will have a field day launching thousands, or even millions, of new and cool apps. But, similar to the smartphone world, all of these apps will be fighting for mindshare, and only a few will rise to the top to be valued by businesses and consumers.


3.Event Stream Processing. According to Gartner: “Some IoT applications will generate extremely high data rates that must be analyzed in real time. Systems creating tens of thousands of events per second are common, and millions of events per second can occur in some telecom and telemetry situations. To address such requirements, distributed stream computing platforms (DSCPs) have emerged. They typically use parallel architectures to process very high-rate data streams to perform tasks such as real-time analytics and pattern identification.”

4.Operating Systems. There’s a wide range of systems out there that have been designed for specific purposes.

5.Processors and Architecture. Designing devices with an understanding of those devices’ needs will require “deep technical skills.”

6.Low-Power, Wide-Area Networks. Current solutions are proprietary, but standards will come to dominate. According to Gartner: “Traditional cellular networks don’t deliver a good combination of technical features and operational cost for those IoT applications that need wide-area coverage combined with relatively low bandwidth, good battery life, low hardware and operating cost, and high connection density. The long-term goal of a wide-area IoT network is to deliver data rates from hundreds of bits per second (bps) to tens of kilobits per second (Kbps) with nationwide coverage, a battery life of up to 10 years, an endpoint hardware cost of around $5, and support for hundreds of thousands of devices connected to a base station or its equivalent. The first low-power wide-area networks (LPWANs) were based on proprietary technologies, but in the long term emerging standards such as Narrowband IoT (NB-IoT) will likely dominate this space.”

7.Low-Power, Short-Range IoT Networks. Short-range networks connecting IT devices will be convoluted. There will not be a single common infrastructure connecting devices.

8.Device (Thing) Management. IoT things that are not ephemeral — that will be around for a while — will require management like every other device (firmware updates, software updates, etc.), and that introduces problems of scale.

9.Analytics. According to Gartner, IoT will require a new approach to analytics. “New analytic tools and algorithms are needed now, but as data volumes increase through 2021, the needs of the IoT may diverge further from traditional analytics,” according to Gartner. The currency of IoT will be “data.” But, this new currency only has value if the masses of data can be translated into insights and information which can be converted into concrete actions that will transform businesses, change people’s lives, and effect social change.


10.Security. According to Gartner, threats extend well beyond denial of sleep attacks: Those are attacks using malicious code, propagated through the Internet of Things, aimed at draining the batteries of your devices by keeping them awake. According to Gartner “The IoT introduces a wide range of new security risks and challenges to the IoT devices themselves, their platforms and operating systems, their communications, and even the systems to which they’re connected. Security technologies will be required to protect IoT devices and platforms from both information attacks and physical tampering, to encrypt their communications, and to address new challenges such as impersonating ‘things’ or denial-of-sleep attacks that drain batteries. IoT security will be complicated by the fact that many ‘things’ use simple processors and operating systems that may not support sophisticated security approaches.”


What is next?

The market is endless. It’s exciting but you need to build great software and hardware with a sophisticated backend with multiple security levels and to bring order and sophistication to data and understanding that security is an art that involves cryptography. Most companies don’t have the talent they need to develop secure products.