As time goes by, we will need faster and faster data communication in order to drive technological development in all fields. Edge computing does just that. What is edge computing, what are its advantages and disadvantages?

What is Edge Computing?

Edge computing is a distributed information technology architecture, where client data is processed at the edge of the network, as close as possible to its source of origin. Data is an important factor in modern business because it is able to provide real-time business support control. 

Businesses are now filled with data routinely collected from sensors and IoT devices operating in real-time from remote locations, almost anywhere around the world. Edge computing is able to move some of the storage and computing resources out of the data center and closer to the data source itself.

Why is Edge Computing Important?

Computing tasks require an architecture that suits one type of computing task. Edge computing is emerging as a viable and important architecture in supporting distributed computing to deploy computing resources and storage closer to the data source.

In general, distributed computing models are not new. The concepts of remote offices, branch offices, and cloud computing have a long and proven track record. But decentralization can be very complicated as it requires high network monitoring. That’s why edge computing is more relevant as it offers an effective solution to network problems. 

Edge computing will be especially useful for moving large amounts of data. Even large data can be moved in a short period of time. Edge computing eases the process of transferring heavy data. 

Advantages of Edge Computing

Edge computing is largely capable of overcoming various problems in the network. For example, bandwidth limitations, improving latency conditions, and also network fraud. In addition, there are several advantages of edge competing that need to be known. Among them are:

1. Autonomy

Edge computing will be very useful when connectivity is unreliable or when bandwidth is limited due to the characteristics of the surrounding environment. For example, networks used on ships sailing at sea, oil platforms, farms in remote areas, rainforests, deserts, and various other hard-to-reach locations. 

Edge computing performs computing tasks at that location, sometimes on the edge device itself. For example, water quality sensors on water purifiers in remote villages. From here it can store data to be sent to a central point only when connectivity is available. By processing the data locally, the amount of data sent can be significantly reduced, so much less bandwidth and connectivity time is required. 

2. Data Sovereignty

Transferring large amounts of data is not just a technical issue. The journey of the data being moved will cross national and regional boundaries. This is where additional problems can arise, especially in terms of data security, privacy, and legal issues. Edge computing can be used to keep data close to its source and stay within the bounds of applicable data sovereignty laws. 

Data sovereignty is capable of processing raw data locally, obscuring and securing any sensitive data before finally sending any documents to the cloud and primary data centers. The cloud and primary data center may be located in another jurisdiction. 

3. Edge Security

Finally, edge computing offers additional opportunities to implement and ensure data security. Even though cloud providers have IoT services and specialize in analyzing complex data, companies generally remain concerned about the security of their data once it leaves the edge and returns to the cloud or data center. 

By implementing computing at the edge, all data that is returning to the cloud or data center can be secured with encryption. Edge deployments can also be strengthened to counter hackers and other malicious activity on the network. 

Challenges of Edge Computing

Edge computing does have great potential to bring the various advantages above, even so there are still challenges in its use. In addition to the limited network, there are several things that need to be considered regarding its implementation. Among them are:

1. Limited Capability

One of the attractions of cloud computing when compared to the edge is the diversity and scale of its resources and services. The infrastructure used in edge computing tends to be very effective, but the scope and purpose of edge deployment must be clearly defined. 

2. Connectivity

Edge computing overcomes typical network limitations, but even the most straightforward edge deployments require a minimum level of connectivity. It is important to design edge deployments that accommodate spotty or erratic connectivity and consider what happens at the edge when connectivity is lost. For edge computing to work well, autonomy, AI, and good failure planning after connectivity issues are essential.

3. Security

IoT devices are popular and smart, but they are notoriously insecure. It is therefore important to design edge computing deployments that will emphasize proper device management. For example, security in computing and storage resources, policy-based configuration enforcement, and factors such as software updates and patching.  

IoT services from large cloud providers include secure communication. However, this does not automatically include edge computing. Therefore, it is still necessary to use edge computing implementation. 

4. Data Lifecycle

A problem that always arises with data overload is that there is a lot of data that is not needed. An example is monitoring devices used in the medical world. The data that is important to store is only the data of patients who have problems. While the data of the patients who are classified as healthy actually does not need to be stored.

Most of the data in real-time analytics is short-term data that will not be stored in the long run. Every business must decide which data to keep and which data to discard after the analysis. Stored data must be protected in accordance with business policies and regulations. 

Network monitoring and data analysis cannot be separated from businesses, especially those whose operations rely heavily on the internet. Netmonk is here as a provider of network monitoring applications, web/API, and servers in one application. With its product, Netmonk Prime, it will be easier to understand and make decisions based on the data collected. 

Why should you choose Netmonk? Because this service is supported with Indonesian as the main language, making it more accessible than others. The service provides solutions for corporate networks, including custom requests that suit the company’s needs. The service fee is also affordable. Test it now! 

Reference:

https://www. npspemuda.co.id/edge-computing-sebuah-transformasi-teknologi-dan-akses-data/