Performance Comparison of Algorithms like Binary Exponential Backoff (BEB) and Linear Increase Linear Decrease (LILD) in IEEE 802.11 Networks

Efficient network access management is crucial in wireless communication, particularly with the widespread use of WLANs and their associated standards. The Distributed Coordination Function (DCF) commonly employs the Binary Exponential Backoff (BEB) algorithm to control contention in high-density user environments. However, BEB has notable drawbacks in scenarios with heavy traffic, including elevated collision rates and increased delays, which significantly degrade overall network performance. This paper addresses these challenges by exploring alternative backoff algorithms, with a focus on the Linear Increase Linear Decrease (LILD) algorithm. Unlike BEB, LILD adjusts the contention window (CW) linearly, which is expected to mitigate the issues associated with high traffic loads and improve network efficiency.LILD algorithm employs a linear adjustment mechanism to effectively manage collisions, making it particularly well-suited for moderate to high traffic loads. Its dynamic behavior enables it to strike a balance between maintaining high throughput and minimizing latency, thereby enhancing overall network performance under varying traffic conditions.This study introduces a novel approach, the Hybrid Adaptive Backoff Algorithm (HABA), which dynamically adapts to real-time network load variations. By leveraging feedback from the network, HABA adjusts backoff times to minimize collision rates and improve throughput. The algorithm’s performance is evaluated against existing methods to identify its relative effectiveness. Furthermore, the paper offers a comprehensive analysis of conventional and contemporary backoff strategies within the IEEE 802.11 standards, highlighting their individual strengths and assessing their influence on overall network performance.