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The pay-as-you-go model supported by existing cloud infrastructure providers is appealing to most application service providers to deliver their applications in the cloud. Within this context, elasticity of applications has become one of…
The increasing demand for diverse, mobile applications with various degrees of Quality of Service requirements meets the increasing elasticity of on-demand resource provisioning in virtualized cloud computing infrastructures. This paper…
In this paper we introduce algorithms for the construction of scale-free networks and for clustering around the nerve centers, nodes with a high connectivity in a scale-free networks. We argue that such overlay networks could support…
Machine learning is now a central part of how modern systems are built and used, powering everything from personalized recommendations to large-scale business analytics. As its role grows, organizations are facing new challenges in…
With weather becoming more extreme both in terms of longer dry periods and more severe rain events, municipal water networks are increasingly under pressure. The effects include damages to the pipes, flash floods on the streets and combined…
Cloud computing is an increasingly popular computing paradigm, now proving a necessity for utility computing services. Each provider offers a unique service portfolio with a range of resource configurations. Resource provisioning for cloud…
The delivery of key services in domains ranging from finance and manufacturing to healthcare and transportation is underpinned by a rapidly growing number of mission-critical enterprise applications. Ensuring the continuity of these complex…
The state-of-art of the technology focuses on data processing to deal with massive amount of data. Cloud computing is an emerging technology, which enables one to accomplish the aforementioned objective, leading towards improved business…
Distributed digital infrastructures for computation and analytics are now evolving towards an interconnected ecosystem allowing complex applications to be executed from IoT Edge devices to the HPC Cloud (aka the Computing Continuum, the…
As novel applications spring up in future network scenarios, the requirements on network service capabilities for differentiated services or burst services are diverse. Aiming at the research of collaborative computing and resource…
Autonomous vehicles generate large volumes of data for applications such as fleet monitoring, model retraining, and high-definition map updates. Existing studies often rely on generic traffic traces, which do not capture the characteristics…
Large-scale computing systems are increasingly using accelerators such as GPUs to enable peta- and exa-scale levels of compute to meet the needs of Machine Learning (ML) and scientific computing applications. Given the widespread and…
Adaptive workloads can change on--the--fly the configuration of their jobs, in terms of number of processes. In order to carry out these job reconfigurations, we have designed a methodology which enables a job to communicate with the…
Reliability is a fundamental challenge in operating large-scale machine learning (ML) infrastructures, particularly as the scale of ML models and training clusters continues to grow. Despite decades of research on infrastructure failures,…
As more businesses and users adopt cloud computing services, security vulnerabilities will be increasingly found and exploited. There are many technological and political challenges where investigation of potentially criminal incidents in…
Observability helps ensure the reliability and maintainability of cloud-native applications. As software architectures become increasingly distributed and subject to change, it becomes a greater challenge to diagnose system issues…
Datacenters provide cost-effective and flexible access to scalable compute and storage resources necessary for today's cloud computing needs. A typical datacenter is made up of thousands of servers connected with a large network and usually…
Upon the expansion of Cloud Computing and the positive outlook of organizations with regard to the movements towards using cloud computing and their expanding utilization of such valuable processing method, as well as the solutions provided…
Emerging artificial intelligence (AI) and machine learning (ML) workloads present new challenges of managing the collective communication used in distributed training across hundreds or even thousands of GPUs. This paper presents STrack, a…
Monitoring is an essential aspect of maintaining and developing computer systems that increases in difficulty proportional to the size of the system. The need for robust monitoring tools has become more evident with the advent of cloud…