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Provides an abstract of the keynote presentation and a brief professional biography of the presenter. The complete presentation was not made available for publication as part of the conference proceedings.
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Sensitive personal user-data collected by Internet-of-Things (IoT) devices is vulnerable to information leaks when uploaded to third-party cloud computing infrastructures. Even though data is encrypted before being sent, to perform analyses on the received data, the computing infrastructure typically decrypts the data, and then performs computation. Therefore, during computation, data can be leaked...
Efficient and secure device to device communication is a necessary enabler for realization of fog and edge computing models. With an ever-increasing number, diversity, and geographical distribution of heterogeneous devices, ranging from pervasive sensor networks to edge cloudlets, the interconnection and network management of these devices emerges as a major challenge. Peer-to-peer (P2P) network overlays...
Nowadays, data analytics is utilized on edge based systems to perform near real-time decisions in proximity of the user. When performing near real-time decisions on the Edge, we need historical data to perform accurate data analytics. Since storage capacities on the Edge are limited, we are faced with a challenge to balance the quantity of data stored with the quality of near real-time decisions....
The popularity and proliferation of the Internet of Things (IoT) paradigm is resulting in a growing number of devices connected to the Internet. These devices are generating and consuming unprecedented amounts of data at the edges of the infrastructure, and are enabling new classes of data-drivenapplications, however, current approaches typically rely on cloud platforms located at the core of the...
Fog and Edge Computing infrastructures have been proposed to address the latency issue of the current Cloud Computing platforms. While a couple of works illustrated the advantages of these infrastructures in particular for the Internet of Things (IoT) applications, elementary Cloud services that can take advantage of the geo-distribution of resources have not been proposed yet. In this paper, we propose...
The Mobile Cloud Network is an emerging cost and capacity heterogeneous distributed cloud topological paradigm that aims to remedy the application performance constraints imposed by centralised cloud infrastructures. A centralised cloud infrastructure and the adjoining Telecom network will struggle to accommodate the exploding amount of traffic generated by forthcoming highly interactive applications...
Crowd-sourcing the resources of mobile devices is a hot topic of research given the game-changing applications it may enable. In this paper we study the feasibility of using edge-clouds of mobile devices to reduce the load in traditional WiFi infrastructures for video dissemination applications. For this purpose, we designed and implemented a mobile application for video dissemination in sport venues...
With advances in the information and communication technology (ICT), connected vehicles are one of the key enablers to unleash intelligent transportation systems (ITS). On the other hand, the envisioned massive number of connected vehicles raises the need for powerful communication and computation capabilities. As an emerging technique, fog computing is expected to be integrated with existing communication...
Despite the known benefits of hosting cloud-based services, the longer and often unpredictable end-to-end network latencies between the end user and the cloud can be detrimental to the response time requirements of the interactive cloud-hosted applications. Existing efforts that exploit edge/fog technology to migrate services closer to clients in order to improve response times do not fully resolve...
With the widespread availability of connected smart devices, Internet of Things (IoT) is becoming the world's largest computing platform. These large-scale, heterogeneous and resource-constrained devices bring many significant new challenges to the design of efficient and reliable IoT systems. Security is one of the most crucial ones that need to be effectively addressed for the wide adoption of IoT...
Fog computing provides a decentralized approach to data processing and resource provisioning in the Internet of Things (IoT). Particular challenges of adopting fog-based computational resources are the adherence to geographical distribution of IoT data sources, the delay sensitivity of IoT services, and the potentially very large amounts of data emitted and consumed by IoT devices. Despite existing...
Internet of Things (IoT) will be one of the driving application for digital data generation in the next years as more than 50 billions of objects will be connected by 2020. IoT data can be processed and used by different devices spread all over the network. The traditional way of centralizing data processing in the Cloud can hardly scale because it cannot satisfy many of the latency critical IoT applications...
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