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A recent advance in networking is the deployment of path-aware multipath network architectures, where network endpoints are given multiple network paths to send their data on. In this work, we tackle the challenge of selecting paths for…
In the past decade, deep learning (DL) has achieved unprecedented success in numerous fields including computer vision, natural language processing, and healthcare. In particular, DL is experiencing an increasing development in applications…
Hybrid main memory systems combine both performance and capacity advantages from heterogeneous memory technologies. With larger capacities, higher associativities, and finer granularities, hybrid memory systems currently exhibit significant…
Load balancing plays a critical role in efficiently dispatching jobs in parallel-server systems such as cloud networks and data centers. A fundamental challenge in the design of load balancing algorithms is to achieve an optimal trade-off…
Infrastructure as a Service (IaaS) clouds have become the predominant underlying infrastructure for the operation of modern and smart technology. IaaS clouds have proven to be useful for multiple reasons such as reduced costs, increased…
Service Level Objectives (SLOs) aim to set threshold for service time in cloud services to ensure acceptable quality of service (QoS) and user satisfaction. Currently, many studies consider SLOs as a system resource to be allocated,…
The rise of microservice architectures has revolutionized application design, fostering adaptability and resilience. These architectures facilitate scaling and encourage collaborative efforts among specialized teams, streamlining deployment…
Recent improvements in both the performance and scalability of shared-nothing, transactional, in-memory NewSQL databases have reopened the research question of whether distributed metadata for hierarchical file systems can be managed using…
The Internet of Things paradigm connects edge devices via the Internet enabling them to be seamlessly integrated with a wide variety of applications. In recent years, the number of connected devices has grown significantly, along with the…
Service mesh is a fundamental technology for building cloud-native applications, which ensures the stable running of a large number of services by an intermediate layer that governs communication between services. However, service mesh is…
Autonomous navigation in crowded, complex urban environments requires interacting with other agents on the road. A common solution to this problem is to use a prediction model to guess the likely future actions of other agents. While this…
While advanced analysis of large dataset is in high demand, data sizes have surpassed capabilities of conventional software and hardware. Hadoop framework distributes large datasets over multiple commodity servers and performs parallel…
Remote attestation protocols are widely used to detect device configuration (e.g., software and/or data) compromise in Internet of Things (IoT) scenarios. Unfortunately, the performances of such protocols are unsatisfactory when dealing…
Leveraging the potential power of even small handheld devices able to communicate wirelessly requires dedicated support. In particular, collaborative applications need sophisticated assistance in terms of querying and exchanging different…
Anomaly detection is critical for finding suspicious behavior in innumerable systems. We need to detect anomalies in real-time, i.e. determine if an incoming entity is anomalous or not, as soon as we receive it, to minimize the effects of…
Heterogeneity has grown in popularity both at the core and server level as a way to improve both performance and energy efficiency. However, despite these benefits, scheduling applications in heterogeneous machines remains challenging.…
Proliferation of cloud computing has revolutionized hosting and delivery of Internet-based application services. However, with the constant launch of new cloud services and capabilities almost every month by both big (e.g., Amazon Web…
The deployment of ML models on edge devices is challenged by limited computational resources and energy availability. While split computing enables the decomposition of large neural networks (NNs) and allows partial computation on both edge…
Distributed Stream Processing systems are becoming an increasingly essential part of Big Data processing platforms as users grow ever more reliant on their ability to provide fast access to new results. As such, making timely decisions…
We present a new unified framework for minimizing congestion-dependent network cost in information-centric networks by jointly optimizing forwarding and caching strategies. As caching variables are integer-constrained, the resulting…