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Disaggregation maps parts of an AI workload to different types of GPUs, offering a path to utilize modern heterogeneous GPU clusters. However, existing solutions operate at a coarse granularity and are tightly coupled to specific model…
We present the design of a Resource-Aware Task Allocator (RATA) and an empirical analysis in handling real-time tasks for processing on Distributed Satellite Systems (DSS). We consider task processing performance across low Earth orbit…
With the rapid development of network-based services and applications, current data plane solutions of network node, which focus on packets forwarding traditionally, are not optimally addressing new requirements such as function…
Results from the research and development of a Data Intensive and Network Aware (DIANA) scheduling engine, to be used primarily for data intensive sciences such as physics analysis, are described. In Grid analyses, tasks can involve…
Data center operators are typically faced with three significant problems when running their data centers, i.e., rising electricity bills, growing carbon footprints and unexpected power outages. To mitigate these issues, running data…
Intelligent reflecting surface (IRS)-assisted mobile edge computing (MEC) systems have shown notable improvements in efficiency, such as reduced latency, higher data rates, and better energy efficiency. However, the resource competition…
Recent increase in energy prices has led researchers to find better ways for capacity provisioning in data centers to reduce energy wastage due to the variation in workload. This paper explores the opportunity for cost saving utilizing the…
Distributed dataflow systems like Apache Spark and Apache Hadoop enable data-parallel processing of large datasets on clusters. Yet, selecting appropriate computational resources for dataflow jobs -- that neither lead to bottlenecks nor to…
This study addresses the challenge of resource scheduling optimization in edge-cloud collaborative computing using deep reinforcement learning (DRL). The proposed DRL-based approach improves task processing efficiency, reduces overall…
Cloud computing, despite its advantages in scalability, may not always fully satisfy the low-latency demands of emerging latency-sensitive pervasive applications. The cloud-edge continuum addresses this by integrating the responsiveness of…
The energy consumption of data centers assumes a significant fraction of the world's overall energy consumption. Most data centers are statically provisioned, leading to a very low average utilization of servers. In this work, we survey…
Multi-access edge computing (MEC) and non-orthogonal multiple access (NOMA) have been regarded as promising technologies to improve computation capability and offloading efficiency of the mobile devices in the sixth generation (6G) mobile…
The challenge of optimal Routing and Spectrum Assignment (RSA) is significant in Elastic Optical Networks. Integrating adaptive modulation formats into the RSA problem - Routing, Modulation Level, and Spectrum Assignment - broadens…
In dynamic ride-sharing systems, intelligent repositioning of idle vehicles enables service providers to maximize vehicle utilization and minimize request rejection rates as well as customer waiting times. In current practice, this task is…
The "Disaggregated Server" concept has been proposed for datacenters where the same type server resources are aggregated in their respective pools, for example a compute pool, memory pool, network pool, and a storage pool. Each server is…
With the rapid expansion of cloud computing applications, optimizing resource allocation has become crucial for improving system performance and cost efficiency. This paper proposes an intelligent resource allocation algorithm that…
Resource provisioning plays a pivotal role in determining the right amount of infrastructure resource to run applications and target the global decarbonization goal. A significant portion of production clusters is now dedicated to…
A variety of computing platform like Field Programmable Gate Array (FPGA), Graphics Processing Unit (GPU) and multicore Central Processing Unit (CPU) in data centers are suitable for acceleration of data-intensive workloads. Especially,…
This comprehensive survey examines how Reconfigurable Intelligent Surfaces (RIS) revolutionize resource allocation in various network frameworks. It begins by establishing a theoretical foundation with an overview of RIS technologies,…
In this paper, we review the key figures of merit to assess the performance of advanced random access (RA) schemes exploiting physical layer coding, repetitions and collision resolution techniques. We then investigate RA modeling aspects…