A5022702504- Opportunistic and Delay-Tolerant Networks
- Context-Aware Activity Recognition Systems
- IoT and Edge/Fog Computing
- Caching and Content Delivery
- Energy Efficient Wireless Sensor Networks
- Mobile Crowdsensing and Crowdsourcing
- Human Mobility and Location-Based Analysis
- Advanced Wireless Communication Technologies
- Data Management and Algorithms
- IoT Networks and Protocols
- Software-Defined Networks and 5G
- Age of Information Optimization
- Video Surveillance and Tracking Methods
- Mobile Ad Hoc Networks
- Innovative Human-Technology Interaction
University of Surrey
2012-2023
Neighbor discovery was initially conceived as a means to deal with energy issues at deployment, where the main objective acquire information about network topology for subsequent communication. Nevertheless, over recent years, it has been facing new challenges due introduction of mobility nodes static networks mainly caused by opportunistic presence in such scenario. The focus has, therefore, shifted toward more challenging environments, connectivity opportunities need be exploited achieving...
The evolution of network technologies has witnessed a paradigm shift toward open and intelligent networks, with the Open Radio Access Network (O-RAN) architecture emerging as promising solution. O-RAN introduces disaggregation virtualization, enabling operators to deploy multi-vendor interoperable solutions. However, managing automating complex ecosystem presents numerous challenges. To address this, machine learning (ML) techniques have gained considerable attention in recent years,...
Understanding home activities is important in social research to study aspects of life, e.g., energy-related practices and assisted living arrangements. Common approaches identifying which are being carried out the rely on self-reporting, either retrospectively (e.g., interviews, questionnaires, surveys) or at time activity use diaries). The digital sensors may provide an alternative means observing home. For example, temperature, humidity light can report physical environment where occur,...
The occurrence of short but recurrent opportunistic contacts between static infrastructure and mobile devices largely characterizes recent Internet Things (IoT) applications for Smart Cities Buildings scenarios. In order to efficiently exploit such existing communication opportunities access services, share collect data, IoT cannot rely on standard discovery mechanisms that periodically probe the environment discover resources. Discovery protocols resilient different contact able optimize...
The recently growing need to experiment with Internet of Things (IoT) technologies in more realistic environments requires the experimenter have remote and precise observation heterogeneous IoT devices under test. This paper introduces SmartEye, an energy efficient observer platform for testbeds. SmartEye embeds many features that are currently available on different systems into a common platform, while placing efficiency autonomous operation at core its design. It will provide foundation...
What activities take place at home? When do they occur, for how long last and who is involved? Asking such questions important in social research on households, e.g., to study energy-related practices, assisted living arrangements various aspects of family home life. Common ways seeking the answers rest self-reporting which provoked by researchers (interviews, questionnaires, surveys) or non-provoked (time use diaries). Longitudinal observations are also common, but all these methods...
There has been increasing interest in deploying Internet of Things (IoT) devices to study human behavior locations such as homes and offices. Such can be deployed a laboratory or “in the wild” natural environments. The latter allows one collect behavioral data that is not contaminated by artificiality experiment. Using IoT ordinary environments also brings benefits reduced cost, compared with lab experiments, less disturbance participants’ daily routines, which turn helps recruiting them...
There has been increasing interest in deploying IoT devices to study human behaviour locations such as homes and offices. Such can be deployed a laboratory or `in the wild' natural environments. The latter allows one collect behavioural data that is not contaminated by artificiality of experiment. Using ordinary environments also brings benefits reduced cost, compared with lab experiments, less disturbance participants' daily routines which turn helps recruiting them into research. However,...
In this article, an Arrival and Departure Time Predictor (ADTP) for scheduling communication in opportunistic Internet of Things (IoT) is presented. The proposed algorithm learns about temporal patterns encounters between IoT devices predicts future arrival departure times, therefore contact durations. By relying on such predictions, a neighbour discovery scheduler proposed, capable jointly optimizing latency power consumption order to maximize time when contacts are expected with high...