Reducing latency is a top priority for organizations.
High latency disrupts the user experience and weakens security – which is why more organizations are turning to cutting-edge technology like 5G and edge computing to achieve ultra-low latency.
In this post, we explore the future trends of latency and how businesses are working to reduce it.
What Is Latency?
Latency is the delay or time it takes for a data packet to travel from one point to another on a network. It’s essentially the gap between sending a request and receiving a response.
This delay can be influenced by several factors, including:
The lower the latency, the faster the communication, which is essential for applications that require real-time or near-instantaneous responses – think video conferencing, online gaming, financial transactions, or autonomous vehicle operations.
High latency significantly impacts user experience as well as the effectiveness of security measures.
When systems lag during critical processes, like authentication or transaction verification, organizations create vulnerabilities that attackers can exploit.
By prioritizing low latency, you boost performance, protect assets, and maintain customer trust.
Here are the downsides of having high latency:
Here are the industries that are most affected by latency:
Many industries depend on responsive, data-intensive services, which makes reducing latency and enhancing privacy a key concern.
Here’s how the latest trends in network architecture and cybersecurity are driving these changes:
Cyber threats today can come from anywhere in the network. This makes the zero trust model, which constantly verifies every user and device at each access point, a cornerstone of network security.
By pairing zero trust with distributed network architectures, organizations process data locally—closer to its origin. This helps them to lower network congestion and deliver fast, responsive services essential for privacy-sensitive, real-time applications in fields like finance, healthcare, and IoT.
Zero trust ensures secure data flow without sacrificing speed or accessibility. Distributed architectures enhance this approach by decentralizing data processing and minimizing delays caused by routing through central servers.
Benefits of Zero Trust:
Artificial intelligence (AI) and machine learning allow organizations to instantly and automatically analyze network traffic to identify unusual or suspicious behavior. Threat detection response reduces network congestion and ensures the ultra-low latency that’s critical for smooth operations.
By constantly monitoring traffic patterns and flagging anomalies, these technologies keep organizations prepared for incidents, especially in high-stakes industries like:
This approach also fosters trust with users who expect seamless access to services.
Benefits of Real-Time Threat Detection:
The rollout of 5G enables organizations to meet the ultra-low latency demands of real-time applications.
These networks deliver faster data transfer speeds and support more devices simultaneously. Looking ahead, technologies like 6G promise to further optimize latency and security.
However, 5G also presents challenges, such as the need for:
Yet, despite these obstacles, 5G significantly enhances network performance and security, enabling low-latency connectivity.
Benefits of 5G:
Edge computing is essential for applications that require instant data processing and ultra-low latency.
By handling data at or near its source instead of sending it to centralized servers, edge computing dramatically reduces latency. Edge computing also alleviates network congestion by minimizing the amount of data traveling across the network.
This localized processing not only boosts speed but also enhances security, as sensitive information can be analyzed directly on the device or within the local network, reducing the risk of exposure to potential threats.
Benefits of Edge Computing:
AI is transforming cybersecurity by enabling automated, real-time threat detection and adaptive responses that ensure ultra-low latency for critical applications. It processes data faster than traditional methods, and can adapt to new threats, providing strong protection while minimizing latency.
AI systems can quickly identify unusual network activity, allowing security teams to respond to potential breaches immediately. This approach not only enhances network security but also ensures real-time applications run smoothly, reducing network congestion.
Benefits of AI-Powered Cybersecurity:
Staying protected against evolving threats requires next-level security. With Check Point’s SASE, you can easily deploy, manage, and scale a high-performance, secure network that’s built for ultra-low latency and optimized for real-time applications.
Check Point’s SASE solution provides fast, secure access to both cloud and on-prem environments, backed by zero trust principles, advanced threat prevention, and AI-powered security. Book a free demo today to find out more.