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Ivan Farris

Researcher at Aalto University

Publications -  28
Citations -  1138

Ivan Farris is an academic researcher from Aalto University. The author has contributed to research in topics: Cloud computing & Edge device. The author has an hindex of 15, co-authored 28 publications receiving 906 citations.

Papers
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Journal ArticleDOI

A Survey on Emerging SDN and NFV Security Mechanisms for IoT Systems

TL;DR: A comprehensive analysis of security features introduced by NFV and SDN, describing the manifold strategies able to monitor, protect, and react to IoT security threats and the open challenges related to emerging SDN- and NFV-based security mechanisms.
Proceedings Article

Device-to-Device Communications for 5G Internet of Things

TL;DR: The added-value features introduced by cellular/noncellular D2D communications and its potential in efficiently fulfilling IoT requirements in 5G networks are discussed.
Journal ArticleDOI

Evaluating Performance of Containerized IoT Services for Clustered Devices at the Network Edge

TL;DR: This paper focuses on lightweight virtualization technologies for IoT devices, suitably thought to effectively deploy new integrated applications and to create a novel distributed and virtualized ecosystem.
Journal ArticleDOI

Providing ultra‐short latency to user‐centric 5G applications at the mobile network edge

TL;DR: This paper investigates a novel approach to support service provisioning in dynamic MEC environments by leveraging the potential of lightweight container‐based virtualization techniques and presents a framework where proactive service replication for stateless applications is exploited to drastically reduce the time of service migration between different cloudlets and to meet the latency requirements.
Proceedings ArticleDOI

Optimizing service replication for mobile delay-sensitive applications in 5G edge network

TL;DR: Different optimization models for proactive service migration at the Network Edge are investigated, which can exploit prediction of user mobility patterns and aim at respectively minimizing the QoE degradation due to service migration, and the cost of replicas' deployment.