Legacy load forecasting models are struggling with ever-more-common, unpredictable events; power-hungry AI offers a solution.

School of Computer Science, Rocket Force University of Engineering, Xi'an, Shaanxi, China Load imbalance is a major performance bottleneck in training mixture-of-experts (MoE) models, as unbalanced ...

How to use nats to do client side load balancing , removing load balancers and anycast. Means we only need Cloudflare for the initial page load of each page url . They are all 100% static , and served ...

Arista adds cluster load balancing to its flagship operating system and AI job management capabilities to its CloudVision network observability platform. Arista Networks has added load balancing and ...

Abstract: The rapid expansion of Internet of Things (IoT) devices in healthcare has increased data volumes, creating challenges for the efficiency and latency of real-time monitoring systems.

Abstract: Cloud computing, particularly within the Infrastructure as a Service (IaaS) model, faces significant challenges in workload distribution due to limited resource availability and virtual ...

In today’s fast-paced digital landscape, ensuring the availability and performance of applications is paramount. Modern infrastructures require robust solutions to distribute traffic efficiently and ...

ABSTRACT: Over the last decade, the rapid growth in traffic and the number of network devices has implicitly led to an increase in network energy consumption. In this context, a new paradigm has ...

In this paper, a sender-initiated protocol is applied which uses fuzzy logic control method to improve computer networks performance by balancing loads among computers. This new model devises ...