Related papers: Nahida: In-Band Distributed Tracing with eBPF
Distributed systems are hard to reason about largely because of uncertainty about what may go wrong in a particular execution, and about whether the system will mitigate those faults. Tools that perturb executions can help test whether a…
In the ever-evolving landscape of computing, the advent of edge and fog computing has revolutionized data processing by bringing it closer to end-users. While cloud computing offers numerous advantages, including mobility, flexibility and…
Data Distribution Service (DDS) is an innovative approach towards communication in ICS/IoT infrastructure and robotics. Being based on the cross-platform and cross-language API to be applicable in any computerised device, it offers the…
Microservices transform traditional monolithic applications into lightweight, loosely coupled application components and have been widely adopted in many enterprises. Cloud platform infrastructure providers enhance the resource utilization…
Deduplication has been largely employed in distributed storage systems to improve space efficiency. Traditional deduplication research ignores the design specifications of shared-nothing distributed storage systems such as no central…
A software vulnerability could be exploited without any visible symptoms. When no source code is available, although such silent program executions could cause very serious damage, the general problem of analyzing silent yet harmful…
Wireless edge networks in smart industrial environments increasingly operate using advanced sensors and autonomous machines interacting with each other and generating huge amounts of data. Those huge amounts of data are bound to make data…
Due to network operation and maintenance relying heavily on network traffic monitoring, traffic matrix analysis has been one of the most crucial issues for network management related tasks. However, it is challenging to reliably obtain the…
Coordination services are a fundamental building block of modern cloud systems, providing critical functionalities like configuration management and distributed locking. The major challenge is to achieve low latency and high throughput…
The rise of deep learning has led to various successful attempts to apply deep neural networks (DNNs) for important networking tasks such as intrusion detection. Yet, running DNNs in the network control plane, as typically done in existing…
Recently, several working implementations of in--band full--duplex wireless systems have been presented, where the same node can transmit and receive simultaneously in the same frequency band. The introduction of such a possibility at the…
We propose Zygarde -- which is an energy -- and accuracy-aware soft real-time task scheduling framework for batteryless systems that flexibly execute deep learning tasks1 that are suitable for running on microcontrollers. The sporadic…
Non-intrusive load monitoring (NILM), which usually utilizes machine learning methods and is effective in disaggregating smart meter readings from the household-level into appliance-level consumptions, can help to analyze electricity…
With the emergence of smart cities, Internet of Things (IoT) devices as well as deep learning technologies have witnessed an increasing adoption. To support the requirements of such paradigm in terms of memory and computation, joint and…
Seamless computing and service sharing in community networks have been gaining momentum due to the emerging technology of community network micro-clouds (CNMCs). However, running services in CNMCs can face enormous challenges such as the…
With the prevalence of online platforms, today, data is being generated and accessed by users at a very high rate. Besides, applications such as stock trading or high frequency trading require guaranteed low delays for performing an…
The recent proliferation of Data Grids and the increasingly common practice of using resources as distributed data stores provide a convenient environment for communities of researchers to share, replicate, and manage access to copies of…
Electrocardiogram (ECG) monitoring in Internet of Medical Things (IoMT) networks is constrained by strict data-sharing regulations and privacy concerns. Federated learning (FL) enables collaborative learning by keeping raw ECG data on…
This paper addresses the online monitoring of distributed component-based systems with multi-party interactions against user-provided properties expressed in linear-temporal logic and referring to global states. We consider intrinsically…
Failures in optical network backbone can lead to major disruption of internet data traffic. Hence, minimizing such failures is of paramount importance for the network operators. Even better, if the network failures can be predicted and…