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Inference serving for large language models (LLMs) is the key to unleashing their potential in people's daily lives. However, efficient LLM serving remains challenging today because the requests are inherently heterogeneous and…
The continuous increase in performance requirements, for both scientific computation and industry, motivates the need of a powerful computing infrastructure. The Grid appeared as a solution for inexpensive execution of heavy applications in…
Multi-access Edge Computing (MEC) is a 5G-enabling solution that aims to bring cloud-computing capabilities closer to the end-users. This paper focuses on mitigation techniques against Distributed Denial-of-Service (DDoS) attacks in the…
Existing processes and methods for incident handling are geared towards infrastructures and operational models that will be increasingly outdated by cloud computing. Research has shown that to adapt incident handling to cloud computing…
In the realm of real-world devices, centralized servers in Federated Learning (FL) present challenges including communication bottlenecks and susceptibility to a single point of failure. Additionally, contemporary devices inherently exhibit…
Distributed sensor networks such as IoT deployments generate large quantities of measurement data. Often, the analytics that runs on this data is available as a web service which can be purchased for a fee. A major concern in the analytics…
Large scale power failures induced by severe weather have become frequent and damaging in recent years, causing millions of people to be without electricity service for days. Although the power industry has been battling weather-induced…
Cellular networks are not merely data access networks to the Internet. Their distinct services and ability to form large complex compounds for roaming purposes make them an attractive research target in their own right. Their promise of…
Federated Learning (FL) enables collaborative model training across large-scale distributed service nodes while preserving data privacy, making it a cornerstone of intelligent service systems in edge-cloud environments. However, in…
We focus on data fusion, i.e., the problem of unifying conflicting data from data sources into a single representation by estimating the source accuracies. We propose SLiMFast, a framework that expresses data fusion as a statistical…
In an edge-cloud multi-tier network, datacenters provide services to mobile users, with each service having specific latency constraints and computational requirements. Deploying such a variety of services while matching their requirements…
The adoption of microservice architecture has seen a considerable upswing in recent years, mainly driven by the need to modernize legacy systems and address their limitations. Legacy systems, typically designed as monolithic applications,…
This paper describes an information system designed to support the large volume of monitoring information generated by a distributed testbed. This monitoring information is produced by several subsystems and consists of status and…
Modern climate projections often suffer from inadequate spatial and temporal resolution due to computational limitations, resulting in inaccurate representations of sub-grid processes. A promising technique to address this is the Multiscale…
Creating and maintaining the Metaverse requires enormous resources that have never been seen before, especially computing resources for intensive data processing to support the Extended Reality, enormous storage resources, and massive…
The performance and behavior of large-scale distributed applications is highly influenced by network properties such as latency, bandwidth, packet loss, and jitter. For instance, an engineer might need to answer questions such as: What is…
Automatic failure diagnosis is crucial for large microservice systems. Currently, most failure diagnosis methods rely solely on single-modal data (i.e., using either metrics, logs, or traces). In this study, we conduct an empirical study…
Large scale data management systems utilize State Machine Replication to provide fault tolerance and to enhance performance. Fault-tolerant protocols are extensively used in the distributed database infrastructure of large enterprises such…
Event-driven microservice architecture (EDMA) has emerged as a crucial architectural pattern for scalable cloud applications. In typical EDMAs, database systems are relegated to isolated storage engines for individual components, blind to…
The broad adoption of the Internet of Things during the last decade has widened the application horizons of distributed sensor networks, ranging from smart home appliances to automation, including remote sensing. Typically, these…