IET Networks

Abstract A peer‐to‐peer (P2P) network is defined as a distributed network in which nodes with similar characteristics exchange data with others. Efficient data sharing in P2P systems is essentially faced with challenges due to uncertainties of erratic node failures and unreliable network connectivity. Data replication on multiple nodes can improve availability and alleviate latency. However, the number of created replicas and the corresponding location of these replicas need to be determined optimally. In this paper, a novel framework for data replication is proposed in P2P networks, in which optimal allocations are achieved based on the two objectives including the minimisation of delay and maximisation of hit rate of queries. The proposed model finds allocations that specify the number and location of each replica of existing files in the network based on two considered objectives. A multi‐objective technique based on the Non‐Dominated Sorting Genetic Algorithm II (NSGA‐II) algorithm is utilised to solve the proposed model and to extract non‐dominated Pareto‐optimal solutions of the allocations. Finally, one of the allocations of the obtained Pareto optimal set is applied to the network and the delay and hit rate of queries pertaining to this situation is compared with two models: i) initial model of the network, that is, the state where there is no replica of the files except the original version of the file, and ii) the random replication model to verify the efficiency of the presented method. All simulations in this paper have been done using C++ programming language.

Abouzar Samimi

Maryam Goudarzi

A novel strategy for optimal data replication in peer‐to‐peer networks based on a multi‐objective optimisation – NSGA‐II algorithm

基于多目标优化NSGA‐II算法的新型对等网络最优数据复制策略

Abstract A decode and forward relay assisted device‐to‐device (D2D) communications over a novel multicluster two‐wave (MTW) fading is analysed with Terahertz (THz) channel conditions. Co‐channel interference (CCI) over a recently proposed multi‐cluster fluctuating two‐ray (MFTR) fading is also present at relay and receiver. Maximal ratio combining (MRC) and power harvesting based on power splitting are present at relay and receiver. A characteristic function based approach is used here to derive success probability, outage probability and capacity with outage expressions. The expressions depend on THz channel parameters, distances between various nodes in D2D system, power harvesting parameter and fading channel conditions. The system is numerically analysed under various D2D network conditions.

Haider Mehdi

Zakir Hussain

Muhammad Junaid Rabbani

Syed Muhammad Atif Saleem

Syed Areeb Ahmed

Relay‐assisted D2D communication over novel multicluster two‐wave and multi‐cluster fluctuating two‐ray channels

中继辅助的D2D通信在新型的多簇双波和多簇波动双射线信道上的研究

Network traffic classification has many applications including network management and security monitoring. Deep-packet-inspection is a commonly used method for identifying applications. However, the methods found in the literature only use these keywords or bytes in payload disregarding their position. The authors propose RDClass a content-based traffic classifier for accurately classifying network flows. RDClass uses a set of keywords extracted from the payload and the relative distance between keywords to identify applications. The idea of using the relative distance between keywords is motivated by the fact that for many applications the set of keywords appear within specific portions of payload. These sets of keywords and their relative distances are encoded in the form of a state transition machine. The authors design a new state transition machine called relative distance constrained counting automata (RDCCA) which can check both ordering of keywords and their relative distance within the payload to classify flows. RDClass can automatically generate a set of keywords and find their relative ordering to generate RDCCA when presented with unknown application payloads. The authors experiment with a range of applications and show that RDClass has better classification performance than previous methods which use only ordering of keywords.

Mayank Swarnkar

Neminath Hubballi

<i>RDClass</i> : on using relative distance of keywords for accurate network traffic classification

《RDClass》：利用关键词相对距离实现精确网络流量分类

Abstract Over the past two decades, the cloud computing paradigm has gradually attracted more popularity due to its efficient resource usage and simple service access model. Virtualisation technology is the fundamental element of cloud computing that brings several benefits to cloud users and providers, such as workload isolation, energy efficiency, server consolidation, and cost reduction. This paper examines the combination of operating system‐level virtualisation (containers) and hardware‐level virtualisation (virtual machines). To this end, the performance of containers running on top of virtual machines is experimentally compared with standalone virtual machines and containers based on different hardware resources, including the processor, main memory, disk, and network in a real testbed by running the most commonly used benchmarks. Paravirtualisation and full virtualisation as well as type 1 and type 2 hypervisors are covered in this study. In addition, three prevalent containerisation platforms are examined.

Hossein Aqasizade

Ehsan Ataie

Mostafa Bastam

Experimental assessment of containers running on top of virtual machines

虚拟机上运行的容器的实验评估

Abstract The Industrial Internet of Things (IIoT) has transformed industrial operations with real‐time monitoring and control, enhancing efficiency and productivity. However, this connectivity brings significant security challenges. This study addresses these challenges by identifying abnormal sensor data patterns using machine learning‐based anomaly detection models. The proposed framework employs advanced algorithms to strengthen industrial defences against cyber threats and disruptions. Focusing on temperature anomalies, a critical yet often overlooked aspect of industrial security, this research fills a gap in the literature by evaluating machine learning models for this purpose. A novel variance‐based model for temperature anomaly detection is introduced, demonstrating high efficacy with accuracy scores of 0.92 and 0.82 on the NAB and AnoML‐IOT datasets, respectively. Additionally, the model achieved F1 scores of 0.96 and 0.89 on these datasets, underscoring its effectiveness in enhancing IIoT security and optimising cybersecurity for industrial processes. This research not only identifies security vulnerabilities but also presents concrete solutions to improve the security posture of IIoT systems.

Hardik Gupta

Sunil K. Singh

Sudhakar Kumar

Karan Sharma

Hardeep Saini

Brij B. Gupta

Varsha Arya

Kwok Tai Chui

Variance‐driven security optimisation in industrial IoT sensors

工业物联网传感器中的方差驱动安全优化

Abstract Forests play a pivotal role in protecting the environment, preserving vital natural resources, and ultimately sustaining human life. However, the escalating occurrences of forest fires, whether of human origin or due to climate change, poses a significant threat to this ecosystem. In recent decades, the emergence of the IoT has been characterised by the utilisation of smart sensors for real‐time data collection. IoT facilitates proactive decision‐making for forest monitoring, control, and protection through advanced data analysis techniques, including AI algorithms. This research study presents a comprehensive approach to deploying a dynamic and adaptable network topology in forest environments, aimed at optimising data transmission and enhancing system reliability. Three distinct topologies are proposed in this research study: direct transmission from nodes to gateways, cluster formation with multi‐step data transmission, and clustering with data relayed by cluster heads. A key innovation is the use of high‐powered telecommunication modules in cluster heads, enabling long‐range data transmission while considering energy efficiency through solar power. To enhance system reliability, this study incorporates a reserve routing mechanism to mitigate the impact of node or cluster head failures. Additionally, the placement of gateway nodes is optimised using meta‐heuristic algorithms, including particle swarm optimisation (PSO), harmony search algorithm (HSA), and ant colony optimisation for continuous domains (ACOR), with ACOR emerging as the most effective. The primary objective of this article is to reduce power consumption, alleviate network traffic, and decrease nodes' interdependence, while also considering reliability coefficients and error tolerance as additional considerations. As shown in the results, the proposed methods effectively reduce network traffic, optimise routing, and ensure robust performance across various environmental conditions, highlighting the importance of these tailored topologies in enhancing energy efficiency, data accuracy, and network reliability in forest monitoring applications.

Alireza Etaati

Smart forest monitoring: A novel Internet of Things framework with shortest path routing for sustainable environmental management

智能森林监测：一种具有最短路径路由的物联网框架，用于可持续环境管理

Abbreviation	IET Netw.
Journal Impact	1.15
Quartiles(Global)	COMPUTER SCIENCE, INFORMATION SYSTEMS(Q3)

ISSN	2047-4954, 2047-4962
h-index	31

Publication Information	Publisher: John Wiley & Sons Inc.，Publishing cycle: ，Journal Type: journal，Open Access Journals: Yes
Basic data	Year of publication: 2014，Proportion of original research papers: 97.62%，Self Citation Rate:7.70%， Gold OA Rate: 76.60%
Journal Fees	$2340Details
Average review cycle	网友分享经验：33 Weeks

IET Networks

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A novel strategy for optimal data replication in peer‐to‐peer networks based on a multi‐objective optimisation – NSGA‐II algorithm

Relay‐assisted D2D communication over novel multicluster two‐wave and multi‐cluster fluctuating two‐ray channels

RDClass : on using relative distance of keywords for accurate network traffic classification

Experimental assessment of containers running on top of virtual machines

Variance‐driven security optimisation in industrial IoT sensors

Relay‐assisted D2D communication over novel multicluster two‐wave and multi‐cluster fluctuating two‐ray channels

A novel strategy for optimal data replication in peer‐to‐peer networks based on a multi‐objective optimisation – NSGA‐II algorithm

Variance‐driven security optimisation in industrial IoT sensors

Experimental assessment of containers running on top of virtual machines

Smart forest monitoring: A novel Internet of Things framework with shortest path routing for sustainable environmental management