Keeping Your IoT Data Closer with Edge Computing

Implementing edge computing for IoT enables us to keep data closer to the edge instead of sharing it over long distances to data centers or the cloud. It helps minimize the major challenges faced by IoT devices by providing a more secure framework to maximize security and faster data transfer.

The world is moving towards an IoT-driven future. It is seeing a tremendous increase in applications on business as well as consumer levels. But like with any other technology, IoT also comes with its own set of difficulties which prove a threat to businesses as well as consumers alike. Most of these threats concern data privacy. The major issues of user data privacy, latency, bandwidth costs, and high data processing time can be minimized, if not eliminated by incorporating edge computing for IoT networks. IoT relies on a cloud computing framework which is not sufficient for an efficient IoT networks. There is a need to adopt a better framework to overcome the drawbacks of cloud computing for IoT devices and cloud computing can prove beneficial in improving the IoT structure.

Challenges Faced by IoT Devices

The adoption of IoT devices is increasing at a rapid rate, with 127 new IoT devices being added every second. With such a large number of devices being connected to the internet, the challenges faced by the IoT framework cannot be ignored. The following are the major challenges faced by an IoT network.

High Latency and Low Responsiveness

IoT devices need to receive and transfer data amongst themselves at a very high speeds. The information needs to be received, processed, and the resulting data needs to be sent back. All these operations must be completed at a fast pace without any data loss for an efficient working environment. Also, when it comes to consumer IoT devices, the data needs to be transferred over the internet on the service provider’s servers instead of a local network. The IoT devices can become unresponsive or slow in processing user requests if the devices suffer from connectivity issues. High latency results in a higher time for the devices to respond to the user request. This delay can become frustrating and may result in financial losses for businesses. The effectiveness of the IoT device is reduced due to high latency issues. The IoT devices become a liability instead of an asset if they suffer from latency issues which is not desirable.

Botnet attacks

Cybercriminals are always on the lookout to target corporations through online attacks. As the IoT framework depends completely on the devices being connected to the internet, the IoT devices become highly susceptible to become compromised through such instances of cyber-attacks. Cybercriminals can bring together a huge number of infected devices into networks called botnets. Botnet attacks are one of the most preferred methods of cyber-attacks adopted by cybercriminals. Botnet attacks are majorly caused in the form of a DDoS attacks. A DDoS attack sends a large number of requests simultaneously over the network. This causes the devices to crash as the network can’t handle such a large number of requests at the same time. The IoT devices crash and become unusable to the user or can carry out requests without the user’s consent. One such major botnet attack was carried out in 2016 on DNS provider Dyn which left many users from accessing major sites like Twitter, Netflix, and Amazon.

Data Security and Privacy Concerns

IoT devices gather a large amount of user data. The data contains sensitive information that can be exploited, if not appropriately handled. Businesses lose the risk of losing their confidential data if the data gets compromised. This can have a substantial negative impact on the company’s financial prospects. When it comes to consumers, IoT devices gather a wide array of user information like facial details to voices as well as passwords and biometric data. For businesses, the unethical use of this data can cause financial as well as reputational damage. Cybercriminals can sabotage these devices to make them unusable to the user. Data sharing also proves to be a major issue as some companies share their user data with other companies without the consent of the user.

High Costs

Data storage leads to enormous costs for the companies to store and process the data over the network. Server maintenance adds to the operating costs of the company. The data storage is mostly sourced to third-party businesses which increases the data storage costs. This can prove costly for small businesses and raises the need for an economical solution.

Benefits of Edge Computing for IoT

Edge computing helps overcome the major risks faced by IoT networks. The implementation of edge computing in IoT allows devices to have high responsiveness with low latency. With edge computing, the data centers are located closer to the endpoints. There is a significant reduction in latency and an increase in the responsiveness of the devices as the data moves between a distributed and decentralized data system. When incorporating edge computing for IoT frameworks, the devices are required to handle the data only from the few endpoints they are linked to. This results in a higher bandwidth network ensuring fast flow of data. Since IoT systems rely on high-speed information transfer, edge computing can significantly boost the performance of the business as well as the typical consumer. Companies are even turning to other advanced technologies to be used in conjunction with edge computing for improving the IoT framework adopted. Amazon is reportedly working on its own AI chips for its smart home solution, Alexa. With a local processing chip, the smart device has to rely less on the cloud. This means an increase in the responsiveness of the device as the work is done locally instead of relying on the cloud.

Edge computing provides a higher level of security for IoT devices. With the implementation of edge computing for IoT devices, the number of sensors or devices connected to the internet is significantly reduced. This reduces the instances of potential cyberattacks on the system. The amount of sensitive and private information passing through the network can also be filtered through an edge computing system. Overall, the security of the organization is vastly improved by adopting edge computing for IoT devices. An excellent example of using edge computing for IoT devices to improve their security is the Apple iPhone. All the biometric information of the user is encrypted and stored on the device rather than a centralized cloud. This drastically reduces the amount of user data available on a centralized system, thereby reducing the chances of the data getting compromised.

Edge computing for IoT delivers better computing power at reduced financial costs. Edge computing reduces the cost of data transmission as most of the data is filtered and processed before it is sent to the cloud. Only the required data is allowed to pass through the system, whereas most of the data is stored on local servers. These cost-effective measures are vital to the success of organizations, whether large or small, to cut down on unnecessary expenses. The cost of maintaining high capacity and a distant centralized data server is reduced significantly by implementing an edge computing solution.

Edge computing can redefine the way data is stored, accessed, and processed by IoT devices. It can also significantly improve the way IoT devices function and interact with each other. Edge computing for IoT combined with other technologies like 5G, artificial intelligence and machine learning can rapidly push us towards a fast, secure, and reliable IoT-driven future. The challenges faced by IoT devices can be substantially reduced by improving data transfer speeds between devices and ensuring the privacy of the user data. Businesses, as well as the typical consumer, can benefit hugely by incorporating advanced technologies like edge computing in their IoT framework.