5G communication brings substantial improvements in the quality of service provided to
various applications by achieving higher throughput and lower latency. However, interactive …

Abstract Large Language Models (LLMs), despite their recent impressive accomplishments,
are notably cost-prohibitive to deploy, particularly for applications involving long-content …

Modern web services use in-memory caching extensively to increase throughput and reduce
latency. There have been several workload analyses of production systems that have fueled …

The concept of Multi-access Edge Computing (MEC) has been recently introduced to
supplement cloud computing by deploying MEC servers to the network edge so as to reduce …

Mobile-Edge Computing (MEC) is a promising paradigm that provides storage and
computation resources at the network edge in order to support low-latency and computation …

Practical cache replacement policies attempt to emulate optimal replacement by predicting
the re-reference interval of a cache block. The commonly used LRU replacement policy …

Neural networks of ads systems usually take input from multiple resources, eg query-ad
relevance, ad features and user portraits. These inputs are encoded into one-hot or multi-hot …

Despite its success in many areas, deep learning is a poor fit for use in hardware predictors
because these models are impractically large and slow, but this paper shows how we can …

The demand for content oriented service and compute-intensive service stimulates the shift
of current cellular networks to deal with the explosive growth in mobile traffic. Information …

As a cache eviction algorithm, FIFO has a lot of attractive properties, such as simplicity,
speed, scalability, and flash-friendliness. The most prominent criticism of FIFO is its low …