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Systems and Communications Commons

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Full-Text Articles in Systems and Communications

Grammatical Evolution For Detecting Cyberattacks In Internet Of Things Environments, Hasanen Alyasiri, John Clark, Ali Malik, Ruairí De Fréin Jul 2021

Grammatical Evolution For Detecting Cyberattacks In Internet Of Things Environments, Hasanen Alyasiri, John Clark, Ali Malik, Ruairí De Fréin

Conference papers

The Internet of Things (IoT) is revolutionising nearly every aspect of modern life, playing an ever greater role in both industrial and domestic sectors. The increasing frequency of cyber-incidents is a consequence of the pervasiveness of IoT. Threats are becoming more sophisticated, with attackers using new attacks or modifying existing ones. Security teams must deal with a diverse and complex threat landscape that is constantly evolving. Traditional security solutions cannot protect such sys- tems adequately and so researchers have begun to use Machine Learning algorithms to discover effective defence systems. In this paper, we investigate how one approach from the …


Bayesian Adaptive Path Allocation Techniques For Intra-Datacenter Workloads, Ali Malik, Ruairí De Fréin, Chih-Heng Ke, Hasanen Alyasiri, Obinna Izima Jul 2021

Bayesian Adaptive Path Allocation Techniques For Intra-Datacenter Workloads, Ali Malik, Ruairí De Fréin, Chih-Heng Ke, Hasanen Alyasiri, Obinna Izima

Conference papers

Data center networks (DCNs) are the backbone of many cloud and Internet services. They are vulnerable to link failures, that occur on a daily basis, with a high frequency. Service disruption due to link failure may incur financial losses, compliance breaches and reputation damage. Performance metrics such as packet loss and routing flaps are negatively affected by these failure events. We propose a new Bayesian learning approach towards adaptive path allocation that aims to improve DCN performance by reducing both packet loss and routing flaps ratios. The proposed approach incorporates historical information about link failure and usage probabilities into its …


Virtual Network Function Embedding Under Nodal Outage Using Deep Q-Learning, Swarna Bindu Chetty, Hamed Ahmadi, Sachin Sharma, Avishek Nag Mar 2021

Virtual Network Function Embedding Under Nodal Outage Using Deep Q-Learning, Swarna Bindu Chetty, Hamed Ahmadi, Sachin Sharma, Avishek Nag

Articles

With the emergence of various types of applications such as delay-sensitive applications, future communication networks are expected to be increasingly complex and dynamic. Network Function Virtualization (NFV) provides the necessary support towards efficient management of such complex networks, by virtualizing network functions and placing them on shared commodity servers. However, one of the critical issues in NFV is the resource allocation for the highly complex services; moreover, this problem is classified as an NP-Hard problem. To solve this problem, our work investigates the potential of Deep Reinforcement Learning (DRL) as a swift yet accurate approach (as compared to integer linear …


A Two-Level Information Modelling Translation Methodology And Framework To Achieve Semantic Interoperability In Constrained Geoobservational Sensor Systems, Paul Stacey Jan 2021

A Two-Level Information Modelling Translation Methodology And Framework To Achieve Semantic Interoperability In Constrained Geoobservational Sensor Systems, Paul Stacey

Doctoral

As geographical observational data capture, storage and sharing technologies such as in situ remote monitoring systems and spatial data infrastructures evolve, the vision of a Digital Earth, first articulated by Al Gore in 1998 is getting ever closer. However, there are still many challenges and open research questions. For example, data quality, provenance and heterogeneity remain an issue due to the complexity of geo-spatial data and information representation.

Observational data are often inadequately semantically enriched by geo-observational information systems or spatial data infrastructures and so they often do not fully capture the true meaning of the associated datasets. Furthermore, data …


Near-Field Propagation Analysis For Vivaldi Antenna Design: Insight Into The Propagation Process For Optimizing The Directivity, Integrity Of Signal Transmission, And Efficiency, Ha Hoang, Matthias John, Patrick Mcevoy, Max Ammann Jan 2021

Near-Field Propagation Analysis For Vivaldi Antenna Design: Insight Into The Propagation Process For Optimizing The Directivity, Integrity Of Signal Transmission, And Efficiency, Ha Hoang, Matthias John, Patrick Mcevoy, Max Ammann

Articles

Refined optimization of complex curve–linear-shaped radiators, such as traveling-wave Vivaldi antennas, can be achieved by considering simulated near fields to interpret in detail the structural influences of a design. The relationships between the space and time distributions of electromagnetic (EM) energy clusters and the geometric features are revealed with appropriate use of impulse response analysis combined with the multiple signal classification (MUSIC) algorithm. This article reports a deeper approach when applied to the adjustment of the geometric features of a traveling-wave antenna based on an analysis of near-field propagation features.