latencyreduction

Latency reduction refers to the set of techniques and practices aimed at decreasing the elapsed time between a user or system input and the corresponding response. It is a concern across networks, data centers, storage systems, databases, and user-facing applications. The goal is to minimize both average and tail latency to improve perceived responsiveness and real-time performance.

Common approaches include edge computing and content delivery networks to move computation and data closer to users; caching and hierarchical caching strategies to serve repeated requests faster; protocol and transport optimizations such as QUIC and HTTP/2 to reduce handshake overhead and improve multiplexing; data locality improvements and prefetching to hide latency; asynchronous and non-blocking I/O, event-driven architectures, and thread pools to avoid blocking on work; pipelining, batching, and parallel processing to amortize overhead; kernel bypass and RDMA in high-performance networks to reduce CPU processing; hardware accelerators, faster storage media, and memory hierarchy tuning to lower core latency; and data compression, deduplication, and delta encoding to reduce transport time.

Measurement and evaluation of latency reduction focus on tail latency (for example p95, p99, p999) in addition to average latency, along with throughput and resource utilization. Tools and benchmarks aim to isolate network, processing, and storage components to identify bottlenecks. Effective latency reduction often requires trade-offs between simplicity, complexity, and cost, and may impact energy use, throughput, or consistency.

See also latency optimization, performance engineering, edge computing, content delivery networks, quality of service, and tail latency.