Related papers: QoS-Aware Load Balancing in the Computing Continuu…
The advent of Cloud Computing enabled the proliferation of IoT applications for smart environments. However, the distance of these resources makes them unsuitable for delay-sensitive applications. Hence, Fog Computing has emerged to provide…
As more IoT applications gradually move towards the cloud-edge collaborative mode, the containerized scheduling of workflows extends from the cloud to the edge. However, given the high delay of the communication network, loose coupling of…
The integration of the Industrial Internet of Things (IIoT) with Artificial Intelligence-Generated Content (AIGC) offers new opportunities for smart manufacturing, but it also introduces challenges related to computation-intensive tasks and…
Quantum computers face challenges due to hardware constraints, noise errors, and heterogeneity, and face fundamental design tradeoffs between key performance metrics such as \textit{quantum fidelity} and system utilization. This…
Energy consumption has become a bottleneck for future computing architectures, from wearable devices to leadership-class supercomputers. Existing energy management techniques largely target CPUs, even though GPUs now dominate power draw in…
The growing demand for real-time processing tasks is driving the need for multi-model inference pipelines on edge devices. However, cost-effectively deploying these pipelines while optimizing Quality of Service (QoS) and costs poses…
This letter indicates the critical need for prioritized multi-tenant quality-of-service (QoS) management by emerging mobile edge systems, particularly for high-throughput beyond fifth-generation networks. Existing traffic engineering tools…
Quality-of-Service prediction of web service is an integral part of services computing due to its diverse applications in the various facets of a service life cycle, such as service composition, service selection, service recommendation.…
Deep learning has made great strides lately with the availability of powerful computing machines and the advent of user-friendly programming environments. It is anticipated that the deep learning algorithms will entirely provision the…
Multi-agent LLM systems on edge devices need to hand off latent context efficiently, but the practical choices today are expensive re-prefill or full-precision KV transfer. We study QKVShare, a framework for quantized KV-cache handoff…
Autoscaling is a critical component for efficient resource utilization with satisfactory quality of service (QoS) in cloud computing. This paper investigates proactive autoscaling for widely-used scaling-per-query applications where scaling…
Private 5G networks are emerging as key enablers for smart factories, where a single device often handles multiple concurrent traffic flows with distinct Quality of Service (QoS) requirements. Existing simulation frameworks, however, lack…
Adopting serverless computing to edge networks benefits end-users from the pay-as-you-use billing model and flexible scaling of applications. This paradigm extends the boundaries of edge computing and remarkably improves the quality of…
In virtual desktop infrastructure (VDI) environments, the remote display protocol has a big responsibility to transmit video data from a data center-hosted desktop to the endpoint. The protocol must ensure a high level of client perceived…
The dramatic increase in the number of smart services and their diversity poses a significant challenge in Internet of Things (IoT) networks: heterogeneity. This causes significant quality of service (QoS) degradation in IoT networks. In…
The rapid evolution of Artificial Intelligence (AI) and Machine Learning (ML) has significantly heightened computational demands, particularly for inference-serving workloads. While traditional cloud-based deployments offer scalability,…
The rapid adoption of QUIC as a transport protocol has transformed content delivery by reducing latency, enhancing congestion control (CC), and enabling more efficient multiplexing. With the advent of 5G networks, which support ultra-low…
A distributed application executing on a Network of Workstations (NOW) needs to be resource state aware to possibly adapt itself accordingly in order to keep satisfying the desired Quality of Service (QoS) demands throughout its lifespan.…
To support the growing demand for data-intensive and low-latency IoT applications, Multi-Access Edge Computing (MEC) is emerging as an effective edge-computing approach enabling the execution of delay-sensitive processing tasks close to…
We propose a framework for resource provisioning with QoS guarantees in shared infrastructure networks. Our novel framework provides tunable probabilistic service guarantees for throughput and delay. Key to our approach is a Modified…