When Facebook announced that it was changing its name to Meta, that quickly raised the profile of the metaverse from an emerging, but relatively fringe technology to the mainstream. Yes, there are established applications and a degree of public understanding through experience with consumer augmented or virtual reality, but a full-blown metaverse is still a vision.
Expanding the Metaverse
Realizing the vision of the Metaverse takes two crucial steps; one is raising awareness of the application and benefits of the metaverse; the other is having the technology infrastructure in place to ensure the optimum, reliable operation of those applications.
Take a simple museum visitor using an AR or VR headset to view a special exhibit as an example. Even at a basic level, this is likely to be a data-intensive application. For the experience to be successful, the visitor must be able to view images clearly, the system must respond immediately in real-time to any gestures or actions — and the application must be completely reliable.
If the application is controlled from a central database remote to the museum, there are potential problems. Latency, for example, can create slow response times and delays that lead to a poor experience for the visitor. Poor reliability or availability can deter visitors, while high bandwidth costs of transferring data can impact museum budgets.
That’s one simple example, but scale that up as demand for metaverse applications increases, and the problems could act as a major barrier to adoption.
Contribution of Edge Computing
However, edge computing, one of the key enabling technologies, is in a phase of rapid growth, increasing its availability for metaverse applications. According to a research study by The Insight Partners – ‘
Overcoming Latency Issues
Edge computing is a form of decentralized computing as explained in
Edge computing’s low latency is essential to improve the user experience and support customer satisfaction by enabling metaverse applications to run smoothly at extremely high speeds. Low latency also improves the reliability and robustness of the metaverse application, by reducing the risk of connection loss, delays, lags, and buffering, which is critical for real-time applications in the metaverse.
Reducing Bandwidth Requirements
Deploying edge computing can also overcome bandwidth challenges. Because networks have limited bandwidth, there is a finite limit to the amount of data — or the number of devices — that can communicate data across the network. Increasing bandwidth is one solution, but that may incur costs that outweigh any potential benefits, particularly when metaverse applications generate huge volumes of data.
Data processing and storing application data at the edge reduces data transmission requirements. In many applications, only data on the final results need to be transmitted to a central database, reducing traffic on the network and freeing up bandwidth for more critical tasks.
Storing and processing data at the edge has another important benefit. The data collected can provide valuable insights into user experience and operational efficiency. That can make it easier to identify local trends or issues when a number of metaverse applications are deployed across different regions.
Beyond The Metaverse
While edge computing offers important benefits for the evolution of the metaverse, it has other important applications in sectors such as gaming, security, industrial control, or the development of self-driving cars or drones too.
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