A5018791184- Opportunistic and Delay-Tolerant Networks
- Mobile Ad Hoc Networks
- Caching and Content Delivery
- Peer-to-Peer Network Technologies
- Distributed and Parallel Computing Systems
- Oceanographic and Atmospheric Processes
- Energy Efficient Wireless Sensor Networks
- IoT and Edge/Fog Computing
- Multimedia Communication and Technology
- Network Traffic and Congestion Control
- Vehicular Ad Hoc Networks (VANETs)
- Energy Harvesting in Wireless Networks
- Scientific Computing and Data Management
- Smart Grid Security and Resilience
- Underwater Acoustics Research
- Smart Grid Energy Management
- Wireless Networks and Protocols
- Meteorological Phenomena and Simulations
- Information and Cyber Security
- Human Mobility and Location-Based Analysis
- Privacy, Security, and Data Protection
- Cooperative Communication and Network Coding
- Marine and coastal ecosystems
- Technology Adoption and User Behaviour
- Privacy-Preserving Technologies in Data
University of Nottingham
2015-2024
South African National Biodiversity Institute
2021
University of Derby
2021
Graz University of Technology
2021
Dublin City University
2021
Juraj Dobrila University of Pula
2021
University of Washington
2021
Cardiff University
2021
Edge Technologies (United States)
2021
University of Bari Aldo Moro
2021
Rising energy costs, losses in the present-day electricity grid, risks from nuclear power generation, and global environmental changes are motivating a transformation of conventional ways generating electricity. Globally, there is desire to rely more on renewable resources (RERs) for generation. RERs reduce greenhouse gas emissions may have economic benefits, e.g., through applying demand side management with dynamic pricing so as shift loads fossil fuel-based generators RERs. The grid...
The smart grid is an important hub of interdisciplinary research where researchers from different areas science and technology combine their efforts to enhance the traditional electrical power grid. Due these efforts, now evolving. envisioned will bring social, environmental, ethical, legal economic benefits. Smart systems increasingly involve machine-to-machine communication as well human-to-human, or simple information retrieval. Thus, dimensionality system massive. combination...
Oceanic eddy is the ubiquitous ocean flow phenomenon, which has been key factor in transportation of energy and materials. Consequently, oceanographic understanding can be enhanced by intelligent identification eddy. State-of-the-art deep learning technologies are gradually improving methods. This letter proposes pyramid split attention (PSA) detection U-Net architecture (PSA-EDUNet) that targets oceanic from remote sensing imagery. As for PSA-EDUNet, its inspiration comes U-Net, contains...
Drawing on the experiences of a novel collaborative project between sociologists and computer scientists, this paper identifies set challenges for fieldwork that are generated by wild interdisciplinarity. Public Access Wi-Fi Service was funded an 'in-the-wild' research programme, involving study digital technologies within marginalised community, with goal addressing exclusion. We argue similar forms research, in which social scientists involved deployment experimental real world settings,...
Detecting and dealing with congestion in delay-tolerant networks (DTNs) is an important challenging problem. Current DTN forwarding algorithms typically direct traffic towards more central nodes order to maximise delivery ratios minimise delays, but as demands increase these may become saturated unusable. We propose CafRep, adaptive aware protocol that detects reacts congested parts of the network by using implicit hybrid contact resources heuristics. CafRep exploits localised relative...
Efficient eddy trajectory prediction driven by multi-information fusion can facilitate the scientific research of oceanography, while complicated dynamics mechanism makes this issue challenging. Benefiting from ocean observing technology, dataset be qualified for data-intensive paradigms. In paper, is used to inspire design idea neural network (termed EddyTPNet) and also transformed into prior knowledge guide learning process. This study among first implement with physics informed network....
Pervasive gaming is a new form of multimedia entertainment that extends the traditional computer experience out into real world. Through combination personal devices, positioning systems and other sensors, combined with wireless networking, pervasive game can respond to player's movements context enable them communicate server players. We review recent examples games in order explain their distinctive characteristics as applications. then consider challenge scaling include potentially very...
This paper is concerned with fully distributed reputation-based mechanisms that improve security in MANETS. We introduce a number of optimisations to the current reputation schemes used MANETs such as selective deviation tests and adaptive expiration timer aim deal congestion quick convergence. propose use two different centrality measures for evaluation individual trust claims resolving aggregated ones. design build our prototype over AODV test it NS-2 presence variable active blackhole...
We propose an approach for opportunistic forwarding that supports optimization of multipoint high volume data flow transfer while maintaining buffer availability and low delays. This paper explores a number social, delay heuristics to offload the traffic from congested parts network spread it over less in order keep delays, success ratios nodes. conduct extensive set experiments assessing performance four newly proposed compare them with Epidemic, Prophet, Spay Wait Focus protocols real...
This paper is concerned with congestion aware forwarding algorithms within opportunistic networks. We remove the reoccurring assumption of unlimited storage, and make it evident that a prominent problem needs to be addressed. propose distributed control algorithm adaptively chooses next hop based on contact history statistics, as well storage statistics. aim distribute load away from hotspots in order spread traffic around. perform an extensive set trace driven simulations for...
This paper proposes a novel fully distributed and collaborative k-anonymity protocol (LPAF) to protect users' location information ensure better privacy while forwarding queries/replies to/from untrusted location-based service (LBS) over opportunistic mobile networks (OppMNets). We utilize lightweight multihop Markov-based stochastic model for prediction guide queries toward the LBS's reduce required resources in terms of retransmission overheads. develop formal analytical present...
Efficient classification for hyperspectral image (HSI), which assigns each pixel of the into a specific category, has been critical research topic in HSI analysis area. Under supervised settings, deep learning approaches are very useful label prediction. However, most modeling methods cannot get utmost out spectral information, is critically important object interpretation. Consequently, sequence-based nonlocal long short-term memory (LSTM) network proposed this article. To boost dominant...
My Grid is an e-Science project that aims to help biologists and bioinformaticians perform workflow-based in silico experiments, them automate the management of such workflows through personalisation, notification change publication experiments. In this paper, we describe architecture my how it will be used by scientist. We then show can benefit from agents technologies. have identified three key uses agent technologies Grid: user agents, able customize personalise data, communication...
Purpose This paper presents an initial development of a personal data attitude (PDA) measurement instrument based on established psychometric principles. The aim the research was to develop reliable scale for quantifying and comparing attitudes towards that can be incorporated into cybersecurity behavioural models. Such has become necessary understanding individuals’ specific sets data, as more technologies are being designed harvest, collate, share analyse data. Design/methodology/approach...
Oceans at a depth ranging from ~100 to ~1000-m (defined as the intermediate water here), though poorly understood compared sea surface, is critical layer of Earth system where many important oceanographic processes take place. Advances in ocean observation and computer technology have allowed science enter era big data (to be precise, for surface layer, small bottom sits between) greatly promoted our understanding near-surface phenomena. During past few decades, however, also undergoing...
Wild fish recognition is a fundamental problem of ocean ecology research and contributes to the understanding biodiversity. Given huge number wild species unrecognized category, essence open set fine-grained recognition. Moreover, unrestricted marine environment makes even more challenging. Deep learning has been demonstrated as powerful paradigm in image classification tasks. In this paper, deep neural network (termed WildFishNet) proposed. Specifically, an with fused activation pattern...
Detecting and dealing with congestion in delay tolerant opportunistic networks is an important challenging problem. In this paper we describe CAFREP, a unified control framework for routing such that adapts both data sending rates forwarding policies through novel reactive fully distributed approach. CAFREP enables by detecting reacting to congested nodes parts of the network using implicit hybrid contact resources heuristic. exploits localized relative utility based approach offload traffic...