All Outputs (242)

FRCA: A Novel Flexible Routing Computing Approach for Wireless Sensor Networks (2019)
Journal Article
Liu, P., Wang, X., Hawbani, A., Busaileh, O., Zhao, L., & Al-Dubai, A. (2020). FRCA: A Novel Flexible Routing Computing Approach for Wireless Sensor Networks. IEEE Transactions on Mobile Computing, 19(11), 2623-2639. https://doi.org/10.1109/tmc.2019.2928805

In wireless sensor networks, routing protocols with immutable network policies lacking the flexibility are generally incapable of maintaining desired performance due to the complicated and changeable environment situations and application requirement... Read More about FRCA: A Novel Flexible Routing Computing Approach for Wireless Sensor Networks.

Blockchain and Random Subspace Learning-Based IDS for SDN-Enabled Industrial IoT Security (2019)
Journal Article
Derhab, A., Guerroumi, M., Gumaei, A., Maglaras, L., Ferrag, M. A., Mukherjee, M., & Khan, F. A. (2019). Blockchain and Random Subspace Learning-Based IDS for SDN-Enabled Industrial IoT Security. Sensors, 19(14), Article 3119. https://doi.org/10.3390/s19143119

The industrial control systems are facing an increasing number of sophisticated cyber attacks that can have very dangerous consequences on humans and their environments. In order to deal with these issues, novel technologies and approaches should be... Read More about Blockchain and Random Subspace Learning-Based IDS for SDN-Enabled Industrial IoT Security.

Authentication Layer for IEC 61113-3 Applications (2019)
Presentation / Conference Contribution
Homay, A., Chrysoulas, C., & de Sousa, M. (2019). Authentication Layer for IEC 61113-3 Applications. . https://doi.org/10.1109/ntms.2019.8763839

Mid 2010, the Stuxnet ICS attack targeted the Siemens automation products, and after this attack the ICS security was thrust into spotlight, automation products suppliers started to re-examine their business approach to cyber security. The OPC Founda... Read More about Authentication Layer for IEC 61113-3 Applications.

Being a leader or being the leader: The evolution of institutionalised hierarchy (2019)
Presentation / Conference Contribution
Perret, C., Hart, E., & Powers, S. T. (2019, July). Being a leader or being the leader: The evolution of institutionalised hierarchy. Presented at ALIFE 2019, Newcastle upon Tyne

Human social hierarchy has the unique characteristic of existing in two forms. Firstly, as an informal hierarchy where leaders and followers are implicitly defined by their personal characteristics, and secondly, as an institutional hierarchy where l... Read More about Being a leader or being the leader: The evolution of institutionalised hierarchy.

The ARE Robot Fabricator: How to (Re)produce Robots that Can Evolve in the Real World (2019)
Presentation / Conference Contribution
Hale, M. F., Buchanan, E., Winfield, A. F., Timmis, J., Hart, E., Eiben, A. E., Angus, M., Veenstra, F., Li, W., Woolley, R., De Carlo, M., & Tyrrell, A. M. (2019, July). The ARE Robot Fabricator: How to (Re)produce Robots that Can Evolve in the Real World. Presented at Artificial Life, Newcastle, UK

The long term vision of the Autonomous Robot Evolution (ARE) project is to create an ecosystem of both virtual and physical robots with evolving brains and bodies. One of the major challenges for such a vision is the need to construct many unique ind... Read More about The ARE Robot Fabricator: How to (Re)produce Robots that Can Evolve in the Real World.

Assessing the Relative Importance of an E-learning system Usability Design Characteristics Based on Students' Preferences (2019)
Journal Article
Rutter, M. J., Smith, S., & Alshehri, A. (2019). Assessing the Relative Importance of an E-learning system Usability Design Characteristics Based on Students' Preferences. European Journal of Educational Research, 8(3), 839-855. https://doi.org/10.12973/eu-jer.8.3.839

This study considers the interaction between an e-learning system, the Blackboard system, and the students who use it in Saudi Arabia. While previous work exists, there is limited consideration of the assessment of the preferences of e-learning syste... Read More about Assessing the Relative Importance of an E-learning system Usability Design Characteristics Based on Students' Preferences.

A novel adaptive routing and switching scheme for software-defined vehicular Networks (2019)
Presentation / Conference Contribution
Zhoa, L., Zhao, W., Gong, C., Al-Dubai, A., & Min, G. (2019, May). A novel adaptive routing and switching scheme for software-defined vehicular Networks. Presented at IEEE International Conference on Communications, Shanghai, China

Software-Defined Vehicular Networks (SDVNs) technology has been attracting significant attention as it can make Vehicular Ad Hoc Network (VANET) more efficient and intelligent. SDVN provides a flexible architecture which can decouple the network mana... Read More about A novel adaptive routing and switching scheme for software-defined vehicular Networks.

A temporal-information-based adaptive routing algorithm for software defined vehicular networks (2019)
Presentation / Conference Contribution
Zhao, L., Li, Z., Li, J., Al-Dubai, A., Min, G., & Zomaya, A. Y. (2019, May). A temporal-information-based adaptive routing algorithm for software defined vehicular networks. Presented at IEEE International Conference on Communications (ICC): Ad Hoc and Sensor Networks Symposium, Shanghai, China

In Software Defined Vehicular Networks (SDVNs), most existing studies of routing consider the vehicular network as a static graph and compute the flow table based on static information. However, a static graph could only contain partial network data.... Read More about A temporal-information-based adaptive routing algorithm for software defined vehicular networks.

Comparing encodings for performance and phenotypic exploration in evolving modular robots (2019)
Presentation / Conference Contribution
Veenstra, F., Hart, E., Buchanan, E., Li, W., De Carlo, M., & Eiben, A. E. (2019, July). Comparing encodings for performance and phenotypic exploration in evolving modular robots. Presented at GECCO '19: Genetic and Evolutionary Computation Conference, Prague, Czech Republic

To investigate how encodings influence evolving the morphology and control of modular robots, we compared three encodings: a direct encoding and two generative encodings---a compositional pattern producing network (CPPN) and a Lindenmayer System (L-S... Read More about Comparing encodings for performance and phenotypic exploration in evolving modular robots.

Increasing Trust in Meta-Heuristics by Using MAP-Elites (2019)
Presentation / Conference Contribution
Urquhart, N., Guckert, M., & Powers, S. (2019, July). Increasing Trust in Meta-Heuristics by Using MAP-Elites. Presented at Genetic and Evolutionary Computation COnference, Prague, Czech Republic

Intelligent AI systems using approaches containing emergent elements often encounter acceptance problems. Results do not get sufficiently explained and the procedure itself can not be fully retraced because the flow of control is dependent on stochas... Read More about Increasing Trust in Meta-Heuristics by Using MAP-Elites.

Evolving robust policies for community energy system management (2019)
Presentation / Conference Contribution
Cardoso, R., Hart, E., & Pitt, J. (2019, July). Evolving robust policies for community energy system management. Presented at GECCO '19, Prague, Czech Republic

Community energy systems (CESs) are shared energy systems in which multiple communities generate and consume energy from renewable resources. At regular time intervals, each participating community decides whether to self-supply, store, trade, or sel... Read More about Evolving robust policies for community energy system management.

Algorithm selection using deep learning without feature extraction (2019)
Presentation / Conference Contribution
Alissa, M., Sim, K., & Hart, E. (2019). Algorithm selection using deep learning without feature extraction. In GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion (198-206). https://doi.org/10.1145/3321707.3321845

We propose a novel technique for algorithm-selection which adopts a deep-learning approach, specifically a Recurrent-Neural Network with Long-Short-Term-Memory (RNN-LSTM). In contrast to the majority of work in algorithm-selection, the approach does... Read More about Algorithm selection using deep learning without feature extraction.

An Illumination Algorithm Approach to Solving the Micro-Depot Routing Problem (2019)
Presentation / Conference Contribution
Urquhart, N., Hoehl, S., & Hart, E. (2019, July). An Illumination Algorithm Approach to Solving the Micro-Depot Routing Problem. Presented at Genetic and Evolutionary Computation Conference (GECCO '19), Prague, Czech Republic

An increasing emphasis on reducing pollution and congestion in city centres combined with an increase in online shopping is changing the ways in which logistics companies address vehicle routing problems (VRP). We introduce the {\em micro-depot}-VRP,... Read More about An Illumination Algorithm Approach to Solving the Micro-Depot Routing Problem.

Subjective Evaluation of Music Compressed with the ACER Codec Compared to AAC, MP3, and Uncompressed PCM (2019)
Journal Article
Cunningham, S., & McGregor, I. (2019). Subjective Evaluation of Music Compressed with the ACER Codec Compared to AAC, MP3, and Uncompressed PCM. International Journal of Digital Multimedia Broadcasting, 2019, 1-16. https://doi.org/10.1155/2019/8265301

Audio data compression has revolutionised the way in which the music industry and musicians sell and distribute their products. Our previous research presented a novel codec named ACER (Audio Compression Exploiting Repetition), which achieves data re... Read More about Subjective Evaluation of Music Compressed with the ACER Codec Compared to AAC, MP3, and Uncompressed PCM.

DeepCoin: A Novel Deep Learning and Blockchain-Based Energy Exchange Framework for Smart Grids (2019)
Journal Article
Ferrag, M. A., & Maglaras, L. (2020). DeepCoin: A Novel Deep Learning and Blockchain-Based Energy Exchange Framework for Smart Grids. IEEE Transactions on Engineering Management, 67(4), 1285-1297. https://doi.org/10.1109/tem.2019.2922936

In this paper, we propose a novel deep learning and blockchain-based energy framework for smart grids, entitled DeepCoin. The DeepCoin framework uses two schemes, a blockchain-based scheme and a deep learning-based scheme. The blockchain-based scheme... Read More about DeepCoin: A Novel Deep Learning and Blockchain-Based Energy Exchange Framework for Smart Grids.

Semantic Stream Management Framework for Data Consistency in Smart Spaces (2019)
Presentation / Conference Contribution
Bamgboye, O., Liu, X., & Cruickshank, P. (2019). Semantic Stream Management Framework for Data Consistency in Smart Spaces. . https://doi.org/10.1109/COMPSAC.2019.10188

Semantic technology can provide a bridge between smart applications and Internet of Things (IoT) to enable possible integration and interoperability of data produced by heterogeneous devices. In IoT, data quality plays an important role when it c... Read More about Semantic Stream Management Framework for Data Consistency in Smart Spaces.

A Load-Aware Clustering Model for Coordinated Transmission in Future Wireless Networks (2019)
Journal Article
Bassoy, S., Imran, M. A., Yang, S., & Tafazolli, R. (2019). A Load-Aware Clustering Model for Coordinated Transmission in Future Wireless Networks. IEEE Access, 7, 92693-92708. https://doi.org/10.1109/access.2019.2927093

Coordinated multi-point (CoMP) transmission is one of the key features for long term evolution advanced (LTE-A) and a promising concept for interference mitigation in 5th generation (5G) and beyond future densely deployed wireless networks. Due to th... Read More about A Load-Aware Clustering Model for Coordinated Transmission in Future Wireless Networks.

How autonomous control can improve the performance of logistics networks - a simulation experiment (2019)
Thesis
Preinl, T. How autonomous control can improve the performance of logistics networks - a simulation experiment. (Thesis). Edinburgh Napier University. http://researchrepository.napier.ac.uk/Output/2089989

In this thesis the application of autonomous control concepts to logistics networks is studied by means of a simulation model. This simulation model is based on an actual outbound bulk product supply network of a commodity company. Logistics planni... Read More about How autonomous control can improve the performance of logistics networks - a simulation experiment.

Reviving legacy enterprise systems with microservice-based architecture within cloud environments (2019)
Presentation / Conference Contribution
Habibullah, S., Liu, X., Tan, Z., Zhang, Y., & Liu, Q. (2019). Reviving legacy enterprise systems with microservice-based architecture within cloud environments. In Computer Science Conference Proceedings. https://doi.org/10.5121/csit.2019.90713

Evolution has always been a challenge for enterprise computing systems. The microservice based architecture is a new design model which is rapidly becoming one of the most effective means to re-architect legacy enterprise systems and to reengineer th... Read More about Reviving legacy enterprise systems with microservice-based architecture within cloud environments.

Embedded document security using sticky policies and identity based encryption (2019)
Thesis
Spyra, G. K. Embedded document security using sticky policies and identity based encryption. (Thesis). Edinburgh Napier University. http://researchrepository.napier.ac.uk/Output/2090564

Data sharing domains have expanded over several, both trusted and insecure environments. At the same time, the data security boundaries have shrunk from internal network perimeters down to a single identity and a piece of information. Since new EU GD... Read More about Embedded document security using sticky policies and identity based encryption.