PTAOD: A Novel Framework For Supporting Approximate Outlier Detection over Streaming Data for Edge Computing
Zhu, R., Yu, T., Tan, Z., Du, W., Zhao, L., Li, J., & Xia, X. (2019)
PTAOD: A Novel Framework For Supporting Approximate Outlier Detection over Streaming Data for Edge Computing. IEEE Access, 8, 1475-1485. https://doi.org/10.1109/ACCESS.2019.2962066
Outlier detection over sliding window is a fundamental problem in the domain of streaming data management, which has been studied over 10 years. The key of supporting outlier ...
Fuzzy-Based Distributed Protocol for Vehicle-to-Vehicle Communication
Hawbani, A., Torbosh, E., Wang, X., Sincak, P., Zhao, L., & Al-Dubai, A. (2021)
Fuzzy-Based Distributed Protocol for Vehicle-to-Vehicle Communication. IEEE Transactions on Fuzzy Systems, 29(3), 612-626. https://doi.org/10.1109/tfuzz.2019.2957254
This paper modeled the multihop data-routing in Vehicular Ad-hoc Networks(VANET) as Multiple Criteria Decision Making (MCDM) in four steps. First, the criteria which have an i...
Novel Fuzzy and Game Theory Based Clustering and Decision Making for VANETs
Alsarhan, A., Kilani, Y., Al-Dubai, A., Zomaya, A. Y., & Hussain, A. (2020)
Novel Fuzzy and Game Theory Based Clustering and Decision Making for VANETs. IEEE Transactions on Vehicular Technology, 69(2), 1568-1581. https://doi.org/10.1109/TVT.2019.2956228
Different studies have recently emphasized the importance of deploying clustering schemes in Vehicular ad hoc Network (VANET) to overcome challenging problems related to scala...
Reliable and energy efficient mechanisms for wireless sensor networks
Ali, A. O. E. S. Reliable and energy efficient mechanisms for wireless sensor networks. (Thesis)
Edinburgh Napier University. Retrieved from http://researchrepository.napier.ac.uk/Output/2404287
Sensor nodes and their underlying communication technologies are characterised by restricted power resources, restricted processing, limited storage capacities, low data rates...
PFARS: Enhancing Throughput and Lifetime of Heterogeneous WSNs through Power-aware Fusion, Aggregation and Routing Scheme
Khan, R., Zakarya, M., Tan, Z., Usman, M., Jan, M. A., & Khan, M. (2019)
PFARS: Enhancing Throughput and Lifetime of Heterogeneous WSNs through Power-aware Fusion, Aggregation and Routing Scheme. International Journal of Communication Systems, 32(18), https://doi.org/10.1002/dac.4144
Heterogeneous wireless sensor networks (WSNs) consist of resource-starving nodes that face a challenging task of handling various issues such as data redundancy, data fusion, ...
A Lightweight and Efficient Digital Image Encryption Using Hybrid Chaotic Systems for Wireless Network Applications
Almalkawi, I. T., Halloush, . R., Alsarhan, A., Al-Dubai, A., & Al-karaki, J. N. (2019)
A Lightweight and Efficient Digital Image Encryption Using Hybrid Chaotic Systems for Wireless Network Applications. Journal of Information Security and Applications, 49, https://doi.org/10.1016/j.jisa.2019.102384
Due to limited processing capabilities and other constraints of most wireless networks, many existing security algorithms do not consider the network efficiency. This is becau...
An AI approach to Collecting and Analyzing Human Interactions with Urban Environments
Ferrara, E., Fragale, L., Fortino, G., Song, W., Perra, C., di Mauro, M., & Liotta, A. (2019)
An AI approach to Collecting and Analyzing Human Interactions with Urban Environments. IEEE Access, 7, 141476-141486. https://doi.org/10.1109/access.2019.2943845
Thanks to advances in Internet of Things and crowd-sensing, it is possible to collect vast amounts of urban data, to better understand how citizens interact with cities and, i...
Lightweight Reinforcement Learning for Energy Efficient Communications in Wireless Sensor Networks
Savaglio, C., Pace, P., Aloi, G., Liotta, A., & Fortino, G. (2019)
Lightweight Reinforcement Learning for Energy Efficient Communications in Wireless Sensor Networks. IEEE Access, 7, 29355-29364. https://doi.org/10.1109/access.2019.2902371
High-density communications in wireless sensor networks (WSNs) demand for new approaches to meet stringent energy and spectrum requirements. We turn to reinforcement learning,...
Analyzing Objective and Subjective Data in Social Sciences: Implications for Smart Cities
Erhan, L., Ndubuaku, M., Ferrara, E., Richardson, M., Sheffield, D., Ferguson, F. J., …Liotta, A. (2019)
Analyzing Objective and Subjective Data in Social Sciences: Implications for Smart Cities. IEEE Access, 7, 19890-19906. https://doi.org/10.1109/access.2019.2897217
The ease of deployment of digital technologies and the Internet of Things gives us the opportunity to carry out large-scale social studies and to collect vast amounts of data ...
A supervised energy monitoring-based machine learning approach for anomaly detection in a clean water supply system
Robles-Durazno, A., Moradpoor, N., McWhinnie, J., & Russell, G. (2018)
A supervised energy monitoring-based machine learning approach for anomaly detection in a clean water supply system. In Proceedings of the IEEE International Conference on Cyber Security and Protection of Digital Services (Cyber Security 2018)https://doi.org/10.1109/CyberSecPODS.2018.8560683
Industrial Control Systems are part of our daily life in industries such as transportation, water, gas, oil, smart cities, and telecommunications. Technological development ov...