Equalizing service probability in UAV-assisted wireless powered mmWave networks for post-disaster rescue
Unmanned aerial vehicles (UAVs) are widely used in the areas where ground network infrastructure is inadequate (or crippled by accidents and disasters) to provide services for ground user equipments (UEs). However, the existing related ...
BMS: Bandwidth-aware Multi-interface Scheduling for energy-efficient and delay-constrained gateway-to-device communications in IoT
With the rapid growth of Internet of Things (IoT), gateways are being widely deployed and constantly deliver data traffic to their surrounding IoT devices, referred to as gateway-to-device or G2D communications. As the most commonly-...
Use of QUIC for AMQP in IoT networks
The use of IoT devices is expanding every day in today’s environment. An interoperable protocol like AMQP is essential for supporting multiple IoT use cases and interconnecting IoT devices from different vendors. Many IoT applications ...
Joint load-balancing and power control strategy to maximize the data extraction rate of LoRaWAN networks
LPWAN enabled networks have a dizzying growth and continue to meet an essential need in the Internet of Things market due to their ability to provide low-cost wireless access to geographically spread-out devices. Consequently, an ...
Collaborative prediction and detection of DDoS attacks in edge computing: A deep learning-based approach with distributed SDN
Edge computing (EC) has greatly facilitated the deployment of networked services with fast responses and low bandwidth, by deploying computing and storage at the network edge which is closer to the data sources. However, it is ...
Intelligent time-series forecasting framework for non-linear dynamic workload and resource prediction in cloud
The industrial revolution 4.0 (I4.0), internet of things developments, and the expansion of online web services have caused exponential growth and deployment in the number of cloud data centers(CDC). Cloud computing is a paradigm that ...
Highlights
- Proposed multivariate-time-series-based intelligent forecasting framework for cloud resources provisioning and utilization.
Intrusion detection game for ubiquitous security in vehicular networks: A signaling game based approach
Wireless communications between smart vehicles can make travel quicker and more secure in vehicular networks. However, hackers can perform malicious activities against the communication system, which may cause accidents. To overcome ...
Packet rank-aware active queue management for programmable flow scheduling
Flow scheduling is crucial in improving network Quality of Service (QoS). According to different optimization goals, many scheduling algorithms (e.g., STFQ, pFabric, SRPT, WFQ) have emerged in network. However, these scheduling ...
Fog-cloud based intrusion detection system using Recurrent Neural Networks and feature selection for IoT networks
Deep learning (DL) techniques are being widely researched for their effectiveness in detecting cyber intrusions against the Internet of Things (IoT). Time sensitive Critical Infrastructures (CIs) that rely on IoT require rapid ...
NORD: NOde Ranking-based efficient virtual network embedding over single Domain substrate networks
Network virtualization (NV) allows the service providers (SPs) to partition the substrate resources in the form of isolated virtual networks (VNs) comprising multiple correlated virtual machines (VMs) and virtual links (VLs), capturing ...
Demand Island Routing for LEO satellite constellations
Low Earth Orbit (LEO) constellations create a network that includes the satellites (as routing nodes) connected by Inter-Satellite Links (ISLs) and the terminals dynamically connected to one or more satellites. The combination of ...
Intelligent drone-assisted robust lightweight multi-factor authentication for military zone surveillance in the 6G era
In the diverse range of surveillance applications, large-scale deployment of next-generation communication technologies and the fast-growing development of unmanned aerial vehicles (UAVs) are envisioned as key innovations in the ...
Traffic-aware service relocation in software-defined and intent-based elastic optical networks
The paper focuses on the efficient dynamic routing of unicast and data center (dc)-related requests in elastic optical networks (eons) implementing software-defined networking (sdn) and intend-based networking (ibn) paradigms. To ...
Virtualization Technology Blending for resource-efficient edge clouds
Edge computing brings virtualized services closer to users to improve their operation (e.g., in terms of communication latency, reliability, or data privacy) and is considered as a main technological enabler for 5G and beyond ...
Auto-tune: An efficient autonomous multi-path payment routing algorithm for Payment Channel Networks
Payment Channel Network (PCN) is a scaling solution for Cryptocurrency networks. We advance the PCN multi-path routing by better modeling the system and incorporating the cost of routing fee and the privacy requirement of the channel ...
Highlights
- Auto-Tune optimizes multi-path payment routing using limited capacity information.
A joint strategy for service deployment and task offloading in satellite–terrestrial IoT
In recent years, low earth orbit satellite constellations, which are an important component of 6G, have been considered as a potential solution to achieve seamless network services for remote areas. Service deployment based on network ...
Experimental analysis of RSSI-based localization algorithms with NLOS pre-mitigation for IoT applications
In this paper, we propose an effective target localization strategy for Internet of Things (IoT) scenarios, where positioning is performed by resource-constrained devices. Target-anchor links may be impaired by Non-Line-Of-Sight (NLOS) ...
IRIS: A low duty cycle cross-layer protocol for long-range wireless sensor networks with low power budget
This paper presents a lightweight cross-layer protocol relIable Routing with coordInated medium acceSs control (IRIS) which is designed for long-range pipeline Wireless Sensor Networks (WSNs) with extremely low power budget, typically ...
From centralized to Federated Learning: Exploring performance and end-to-end resource consumption
- Georgios Drainakis,
- Panagiotis Pantazopoulos,
- Konstantinos V. Katsaros,
- Vasilis Sourlas,
- Angelos Amditis,
- Dimitra I. Kaklamani
Machine Learning (ML) is increasingly implemented in a distributed fashion to harness the data abundance generated in the mobile client devices. Contrary to cloud-based centralized learning (CL), distributed schemes like Federated ...
Highlights
- Federated Learning without tuning can lead to divergence if clients hold insufficient data.
A general QoE assessment framework for applications and services
- Hua Wang,
- Adrián Pérez Aguilar,
- Almudena Díaz Zayas,
- Germán Corrales Madueño,
- Changming Zhang,
- Nan Hao,
- Xianbin Yu
In this paper, we have designed a testbed to evaluate end-to-end Quality of Experience (QoE) performance for mobile applications and devices in a controllable and repeatable manner. Various network scenarios have been defined which ...
A user subscription model in mobile radio access networks with network slicing
Network slicing is an architectural enabling technology that logically decouples the current cellular networks into infrastructure providers (InPs) and Network Slice Tenants (NSTs). The network resources (e.g., radio access resources ...
A lightweight D2D authentication protocol for relay coverage scenario in 5G mobile network
5G cellular network is becoming a preferred communication network for deployment of the Internet of Things (IoT), due to its high speed, better connectivity, increased bandwidth, lower latency and flexibility. As a result, the traffic ...
A survey on opportunistic routing protocols in the Internet of Underwater Things
Compared with traditional ocean monitoring technologies, such as cable seabed observation networks, the Internet of Underwater Things (IoUT) can provide real-time underwater environment monitoring and improve efficiency of data ...
Self-adaptive end-to-end resource management for real-time monitoring in cyber–physical systems
This paper proposes a novel self-adaptive resource management framework that preserves a low end-to-end monitoring delay in large-scale cyber–physical systems (CPS) while providing high monitoring resolution. According to the tradeoff ...
Deep learning for encrypted traffic classification in the face of data drift: An empirical study
- Navid Malekghaini,
- Elham Akbari,
- Mohammad A. Salahuddin,
- Noura Limam,
- Raouf Boutaba,
- Bertrand Mathieu,
- Stephanie Moteau,
- Stephane Tuffin
Deep learning models have shown to achieve high performance in encrypted traffic classification. However, when it comes to production use, multiple factors challenge the performance of these models. The emergence of new protocols, ...
Truthful and performance-optimal computation outsourcing for aerial surveillance platforms via learning-based auction
This paper proposes a novel truthful computing algorithm for learning task outsourcing decision-making strategies in edge-enabled unmanned aerial vehicle (UAV) networks. In our considered scenario, a single UAV performs face ...
GLADS: A global-local attention data selection model for multimodal multitask encrypted traffic classification of IoT
With the rapid development of the Internet of Things (IoT), numerous of IoT devices and different characteristics in IoT traffic patterns need traffic classification to enable many important applications. Deep-learning-based (DL-based) ...
Federated learning using game strategies: State-of-the-art and future trends
Federated learning (FL) is a new and promising paradigm that allows devices to learn without sharing data with the centralized server. It is often built on decentralized data where edge nodes use the internet of everything to mitigate ...