Kernel Optimization: Maximizing V2Ray Throughput and Concurrency

Introduction: The V2Ray Core’s Limit

We have established that V2Ray is a powerful application, but its performance is fundamentally constrained by the host operating system, Linux. A default Linux installation is configured for safety and general-purpose computing, not for serving thousands of concurrent, long-lived network connections at high speeds. When V2Ray is deployed on default settings, it quickly runs into bottlenecks that manifest as connection failures, intermittent timeouts, and sudden service crashes under heavy load.

Kernel Optimization (Performance Tuning) is the mandatory process of adjusting low-level Linux kernel parameters—specifically using the sysctl utility—to re-engineer the networking stack. This ensures V2Ray has the resources (memory, file handlers) and the aggressiveness (buffer sizes, timeout controls) required to operate as a high-throughput, professional-grade network node. This deep-level tuning is the final step in unlocking V2Ray’s full performance potential.

Section 1: Eliminating the Concurrency Bottleneck: File Descriptors

The most common cause of V2Ray crashes under load is reaching the File Descriptor (FD) limit.

1. The File Descriptor Problem

In Linux, every resource is treated as a file, and every active network connection (or socket) uses one File Descriptor. When a client connects to V2Ray, it consumes one FD. Internal V2Ray operations (logs, routing tables, configuration files) also consume FDs. The default system limit is often a restrictive number, such as 1024 or 4096.

• Failure Mode: If V2Ray is running a large number of concurrent connections and reaches this limit, any new incoming connection is instantly and silently rejected, leading to widespread user connection failures that are difficult to trace. This can be visualized as a full parking lot denying entry.

2. The Solution: Raising System and User Limits

We must raise the limit at two levels to eliminate this bottleneck: system-wide (for the entire OS) and user-specific (for the user running the V2Ray service).

• System-wide Limit (fs.file-max): This defines the maximum number of files the entire OS can open. We raise this significantly.# Setting the system-wide limit to 655350 sysctl -w fs.file-max=655350
• User-specific Limit (ulimit): This limits the FDs a single user process (the V2Ray application) can open. This is configured in /etc/security/limits.conf and requires a server reboot to take full effect.# Add these lines to limits.conf to set the soft and hard limit for the 'root' user (or 'v2ray' user) * soft nofile 655350 * hard nofile 655350 This ensures that the V2Ray core has sufficient capacity to handle hundreds of thousands of concurrent connections without resource exhaustion.

Section 2: Optimizing TCP Buffer Sizes for Throughput

The kernel manages how much data V2Ray can hold in memory while waiting to send or receive packets. These are the network buffers. Default buffer sizes are often too small for high-speed, high-latency cross-continental links, leading to underutilization of the available bandwidth.

1. Increasing Read/Write Memory

By increasing the maximum buffer size, we allow V2Ray’s transports (VLESS/wSS) to push more data into the network pipe before waiting for acknowledgments, which is crucial for filling the “pipe” over long distances (high latency). This contrasts with standard buffers which are prone to buffer bloat.

• net.core.rmem_max (Receive Memory Max): The largest size of the receive buffer.
• net.core.wmem_max (Write Memory Max): The largest size of the send buffer.

Recommended High-Performance Settings (16 MB):

# Set max buffer size to 16 MB (16,777,216 bytes)
sysctl -w net.core.rmem_max = 16777216 
sysctl -w net.core.wmem_max = 16777216

2. Backlog and Connection Acceptance

We also increase the limits on how many connection requests the system can queue while V2Ray is busy.

• net.core.somaxconn: The maximum number of waiting TCP connections that can be in the “listen” queue. Increasing this prevents connection failures during sudden, large spikes in client traffic.sysctl -w net.core.somaxconn = 65535

Section 3: Fine-Tuning State Management and Timers

The way the kernel handles connection closure and waiting states can significantly impact performance, especially in environments where connections are frequently opened and closed (like general web browsing).

1. Reusing TIME-WAIT Sockets

When a TCP connection closes, the port enters a TIME-WAIT state to ensure all lingering packets have been processed. This state can last up to 120 seconds, during which the port cannot be immediately reused. For a high-concurrency proxy, this rapidly exhausts the available port space, leading to failures.

• net.ipv4.tcp_tw_reuse: This crucial parameter allows the system to reuse ports in the TIME-WAIT state for new connections if the new connection is determined to be safe. This significantly enhances port availability and concurrency.# Allow TIME-WAIT sockets to be reused for new connections sysctl -w net.ipv4.tcp_tw_reuse = 1

2. Reducing Connection Timeout

We can shorten the duration of certain waiting states to free up resources faster.

• net.ipv4.tcp_fin_timeout: Reduces the time a connection spends in the FIN-WAIT-2 state after closing from the default 60 seconds to a more efficient 30 seconds.# Reduce the time a connection waits to fully close sysctl -w net.ipv4.tcp_fin_timeout = 30

Section 4: Making Changes Permanent and BBR Integration

All changes made via the sysctl -w command are temporary and will be lost upon reboot. They must be saved persistently.

1. Persistent Configuration (/etc/sysctl.conf)

To make all kernel changes permanent, you must write the parameters into the /etc/sysctl.conf file.

Consolidated Configuration Block:

# --- /etc/sysctl.conf ---

# 1. File Descriptor Limit
fs.file-max = 655350

# 2. General Network Optimization
net.core.netdev_max_backlog = 250000 
net.core.somaxconn = 65535

# 3. Buffer Sizing (16 MB)
net.core.rmem_max = 16777216 
net.core.wmem_max = 16777216

# 4. State Management (Reuse TIME-WAIT sockets)
net.ipv4.tcp_tw_reuse = 1 
net.ipv4.tcp_fin_timeout = 30 

# 5. Congestion Control (BBR - Mandatory for high-speed TCP)
net.core.default_qdisc = fq 
net.ipv4.tcp_congestion_control = bbr

2. BBR Congestion Control (Article 32)

The last two lines above are essential and integrate the kernel tuning with the congestion control strategy (Article 32). Enabling BBR (Bottleneck Bandwidth and Round-trip propagation time) ensures that the newly enlarged buffers and connection limits are used intelligently, prioritizing high bandwidth and low latency over the legacy, loss-based CUBIC algorithm. BBR is the final piece of the optimization puzzle.

Conclusion: The Final Performance Frontier

Kernel Optimization is the crucial final step in maximizing the potential of a V2Ray server. By moving beyond the conservative default settings of the Linux kernel and implementing aggressive configurations for File Descriptors, network buffers, and connection state management, administrators transform a basic VPS into a powerful, high-concurrency network node. This systematic tuning eliminates hidden performance bottlenecks, ensuring that the stealth and efficiency gains achieved by VLESS and BBR are translated into robust, high-throughput, and resilient service delivery, even under massive load.