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Internet of Things Driven Data Analytics (IoT-DA) has the potential to excel data-driven operationalisation of smart environments. However, limited research exists on how IoT-DA applications are designed, implemented, operationalised, and…
This paper presents a methodology for simulating the Internet of Things (IoT) using multi-level simulation models. With respect to conventional simulators, this approach allows us to tune the level of detail of different parts of the model…
The complexity of IoT, owing to the inherent distributed and dynamic nature of such systems, brings more challenges to the software development process. A vast number of devices with different communication protocols and data formats is…
As IoT systems are given more responsibility and autonomy, they offer greater benefits, but also carry greater risks. We believe this trend invigorates an old challenge of software engineering: how to develop high-risk software-intensive…
The goal of this dissertation is to design efficient data aggregation frameworks for massive IoT networks in different scenarios to support the proper functioning of IoT analytics layer. This dissertation includes modern algorithmic…
Internet of things (IoT) is the epitome of sustainable development. It has facilitated the development of smart systems, industrialization, and the state-of-the-art quality of life. IoT architecture is one of the essential baselines of…
The design space exploration of scaled-out manycores for communication-intensive applications (e.g., graph analytics and sparse linear algebra) is hampered due to either lack of scalability or accuracy of existing frameworks at simulating…
Developing Internet of Things (IoT) systems has to cope with several challenges mainly because of the heterogeneity of the involved sub-systems and components. With the aim of conceiving languages and tools supporting the development of IoT…
Fog computing is an emerging computing paradigm which is mainly suitable for time-sensitive and real-time Internet of Things (IoT) applications. Academia and industries are focusing on the exploration of various aspects of Fog computing for…
As the ratification of 5G New Radio technology is being completed, enabling network architectures are expected to undertake a matching effort. Conventional cloud and edge computing paradigms may thus become insufficient in supporting the…
Making cities smarter help improve city services and increase citizens' quality of life. Information and communication technologies (ICT) are fundamental for progressing towards smarter city environments. Smart City software platforms…
Driven by the visions of Internet of Things and 5G communications, the edge computing systems integrate computing, storage and network resources at the edge of the network to provide computing infrastructure, enabling developers to quickly…
Fog/Edge computing model allows harnessing of resources in the proximity of the Internet of Things (IoT) devices to support various types of real-time IoT applications. However, due to the mobility of users and a wide range of IoT…
The Internet of Things (IoT) is becoming an integral part of our modern lives as we converge towards a world surrounded by ubiquitous connectivity. The inherent complexity presented by the vast IoT ecosystem ends up in an insufficient…
Owing to the large volume of sensed data from the enormous number of IoT devices in operation today, centralized machine learning algorithms operating on such data incur an unbearable training time, and thus cannot satisfy the requirements…
The proliferation of the Internet of Things (IoT) has since seen a growing interest in architectural design and adaptive frameworks to promote the connection between heterogeneous IoT devices and IoT systems. The most widely favoured…
This paper proposes V2Sim, an open source Pythonbased simulation platform designed for advanced vehicle-to-grid (V2G) analysis in coupled urban power and transportation networks. By integrating a microscopic urban transportation network…
Internet of Things and cloud computing are two technological paradigms that reached widespread adoption in recent years. These paradigms are complementary: IoT applications often rely on the computational resources of the cloud to process…
The Internet of Everything (IoE) solutions gradually bring every object online, and processing data in centralized cloud does not scale to requirements of such environment. This is because, there are applications such as health monitoring…
GPU-accelerated Self-Organizing Map (SOM) implementations are among the most competitive options for large-scale SOM analysis, but growing dataset sizes increasingly challenge their practical use because workloads no longer fit cleanly…