Deployment Strategy for Multiple Controllers Based on the Aviation On-Board Software-Defined Data Link Network

In light of the escalating demand and intricacy of services in contemporary terrestrial,maritime,and aerial combat operations,there is a compelling need for enhanced service quality and efficiency in airborne cluster communication networks.Software-Defined Networking(SDN)proffers a viable solution for the multifaceted task of cooperative communication transmission and management across different operational domains within complex combat contexts,due to its intrinsic ability to flexibly allocate and centrally administer network resources.This study pivots around the optimization of SDN controller deployment within airborne data link clusters.A collaborative multi-controller architecture predicated on airborne data link clusters is thus proposed.Within this architectural framework,the controller deployment issue is reframed as a two-fold problem:subdomain partition-ing and central interaction node selection.We advocate a subdomain segmentation approach grounded in node value ranking(NDVR)and a central interaction node selection methodology predicated on an enhanced Artificial Fish Swarm Algorithm(AFSA).The advanced NDVR-AFSA(Node value ranking-Improved artificial fish swarm algorithm)algorithm makes use of a chaos algorithm for population initialization,boosting population diversity and circumventing premature algorithm convergence.By the integration of adaptive strategies and incorporation of the genetic algorithm’s crossover and mutation operations,the algorithm’s search range adaptability is enhanced,thereby increasing the possibility of obtaining globally optimal solutions,while concurrently augmenting cluster reliability.The simulation results verify the advantages of the NDVR-IAFSA algorithm,achieve a better load balancing effect,improve the reliability of aviation data link cluster,and significantly reduce the average propagation delay and disconnection rate,respectively,by 12.8%and 11.7%.This shows that the optimization scheme has important significance in practical application,and can meet the high requirements of modern sea,land,and air operations to aviation airborne communication networks.

Studies on Novel Anti-jamming Technique of Unmanned Aerial Vehicle Data Link

Based on the M-ary spread spectrum （M-ary-SS）, direct sequence spread spectrum （DS-SS）, and orthogonal frequency division multiplex （OFDM）, a novel anti-jamming scheme, named orthogonal code time division multi-subchannels spread spectrum modulation （OC-TDMSCSSM）, is proposed to enhance the anti-jamming ability of the unmanned aerial vehicle （UAV） data link. The anti-jamming system with its mathematical model is presented first, and then the signal formats of transmitter and receiver are derived. The receiver＇s bit error rate （BER） is demonstrated and anti-jamming performance analysis is carded out in an additive white Ganssian noise （AWGN） channel. Theoretical research and simulation results show the anti-jamming performance of the proposed scheme better than that of the hybrid direct sequence frequency hopping spread spectrum （DS/FH SS） system. The jamming margin of the OC-TDMSCSSM system is 5 dB higher than that of DS/FH SS system under the condition of Rician channel and full-band jamming, and 6 dB higher under the condition of Rician channel environment and partial-band jamming.

Enhanced DDoS Detection Using Advanced Machine Learning and Ensemble Techniques in Software Defined Networking

Detecting sophisticated cyberattacks,mainly Distributed Denial of Service(DDoS)attacks,with unexpected patterns remains challenging in modern networks.Traditional detection systems often struggle to mitigate such attacks in conventional and software-defined networking(SDN)environments.While Machine Learning(ML)models can distinguish between benign and malicious traffic,their limited feature scope hinders the detection of new zero-day or low-rate DDoS attacks requiring frequent retraining.In this paper,we propose a novel DDoS detection framework that combines Machine Learning(ML)and Ensemble Learning(EL)techniques to improve DDoS attack detection and mitigation in SDN environments.Our model leverages the“DDoS SDN”dataset for training and evaluation and employs a dynamic feature selection mechanism that enhances detection accuracy by focusing on the most relevant features.This adaptive approach addresses the limitations of conventional ML models and provides more accurate detection of various DDoS attack scenarios.Our proposed ensemble model introduces an additional layer of detection,increasing reliability through the innovative application of ensemble techniques.The proposed solution significantly enhances the model’s ability to identify and respond to dynamic threats in SDNs.It provides a strong foundation for proactive DDoS detection and mitigation,enhancing network defenses against evolving threats.Our comprehensive runtime analysis of Simultaneous Multi-Threading(SMT)on identical configurations shows superior accuracy and efficiency,with significantly reduced computational time,making it ideal for real-time DDoS detection in dynamic,rapidly changing SDNs.Experimental results demonstrate that our model achieves outstanding performance,outperforming traditional algorithms with 99%accuracy using Random Forest(RF)and K-Nearest Neighbors(KNN)and 98%accuracy using XGBoost.

Simulation of Dynamic Electromagnetic Interference Environment for Unmanned Aerial Vehicle Data Link

In order to test the anti-interference ability of an Unmanned Aerial Vehicle(UAV) data link in a complex electromagnetic environment,a method for simulating the dynamic electromagnetic interference of an indoor wireless environment is proposed.This method can estimate the relational degree between the actual face of an UAV data link in an interface environment and the simulation scenarios in an anechoic chamber by using the Grey Relational Analysis(GRA) theory.The dynamic drive of the microwave instrument produces a real-time corresponding interference signal and realises scene mapping.The experimental results show that the maximal correlation between the interference signal in the real scene and the angular domain of the radiation antenna in the anechoic chamber is 0.959 3.Further,the relational degree of the Signal-toInterference Ratio(SIR) of the UAV at its reception terminal indoors and in the anechoic chamber is 0.996 8,and the time of instrument drive is only approximately 10 μs.All of the above illustrates that this method can achieve a simulation close to a real field dynamic electromagnetic interference signal of an indoor UAV data link.

Blockchain-based data transmission control for Tactical Data Link

Tactical Data Link(TDL)is a communication system that utilizes a particular message format and a protocol to transmit data via wireless channels in an instant,automatic,and secure way.So far,TDL has shown its excellence in military applications.Current TDL adopts a distributed architecture to enhance anti-destruction capacity.However,It still faces a problem of data inconsistency and thus cannot well support cooperation across multiple militarily domains.To tackle this problem,we propose to leverage blockchain to build an automatic and adaptive data transmission control scheme for TDL.It achieves automatic data transmission and realizes information consistency among different TDL entities.Besides,applying smart contracts based on blockchain further enables adjusting data transmission policies automatically.Security analysis and experimental results based on simulations illustrate the effectiveness and efficiency of our proposed scheme.

RDFAdaptor:Efficient ETL Plugins for RDF Data Process

Purpose:The interdisciplinary nature and rapid development of the Semantic Web led to the mass publication of RDF data in a large number of widely accepted serialization formats,thus developing out the necessity for RDF data processing with specific purposes.The paper reports on an assessment of chief RDF data endpoint challenges and introduces the RDF Adaptor,a set of plugins for RDF data processing which covers the whole life-cycle with high efficiency.Design/methodology/approach:The RDFAdaptor is designed based on the prominent ETL tool—Pentaho Data Integration—which provides a user-friendly and intuitive interface and allows connect to various data sources and formats,and reuses the Java framework RDF4J as middleware that realizes access to data repositories,SPARQL endpoints and all leading RDF database solutions with SPARQL 1.1 support.It can support effortless services with various configuration templates in multi-scenario applications,and help extend data process tasks in other services or tools to complement missing functions.Findings:The proposed comprehensive RDF ETL solution—RDFAdaptor—provides an easy-to-use and intuitive interface,supports data integration and federation over multi-source heterogeneous repositories or endpoints,as well as manage linked data in hybrid storage mode.Research limitations:The plugin set can support several application scenarios of RDF data process,but error detection/check and interaction with other graph repositories remain to be improved.Practical implications:The plugin set can provide user interface and configuration templates which enable its usability in various applications of RDF data generation,multi-format data conversion,remote RDF data migration,and RDF graph update in semantic query process.Originality/value:This is the first attempt to develop components instead of systems that can include extract,consolidate,and store RDF data on the basis of an ecologically mature data warehousing environment.

A Mathematical Solution to String Matching for Big Data Linking

This paper describes how data records can be matched across large datasets using a technique called the Identity Correlation Approach （ICA）. The ICA technique is then compared with a string matching exercise. Both the string matching exercise and the ICA technique were employed for a big data project carried out by the CSO. The project was called the SESADP （Structure of Earnings Survey Administrative Data Project） and involved linking the Irish Census dataset 2011 to a large Public Sector Dataset. The ICA technique provides a mathematical tool to link the datasets and the matching rate for an exact match can be calculated before the matching process begins. Based on the number of variables and the size of the population, the matching rate is calculated in the ICA approach from the MRUI （Matching Rate for Unique Identifier） formula, and false positives are eliminated. No string matching is used in the ICA, therefore names are not required on the dataset, making the data more secure ＆ ensuring confidentiality. The SESADP Project was highly successful using the ICA technique. A comparison of the results using a string matching exercise for the SESADP and the ICA are discussed here.

Privacy Protection for Big Data Linking using the Identity Correlation Approach

Privacy protection for big data linking is discussed here in relation to the Central Statistics Office （CSO）, Ireland＇s, big data linking project titled the ＇Structure of Earnings Survey - Administrative Data Project＇ （SESADP）. The result of the project was the creation of datasets and statistical outputs for the years 2011 to 2014 to meet Eurostat＇s annual earnings statistics requirements and the Structure of Earnings Survey （SES） Regulation. Record linking across the Census and various public sector datasets enabled the necessary information to be acquired to meet the Eurostat earnings requirements. However, the risk of statistical disclosure （i.e. identifying an individual on the dataset） is high unless privacy and confidentiality safe-guards are built into the data matching process. This paper looks at the three methods of linking records on big datasets employed on the SESADP, and how to anonymise the data to protect the identity of the individuals, where potentially disclosive variables exist.

FAIR + FIT: Guiding Principles and Functional Metrics for Linked Open Data(LOD) KOS Products

Purpose:To develop a set of metrics and identify criteria for assessing the functionality of LOD KOS products while providing common guiding principles that can be used by LOD KOS producers and users to maximize the functions and usages of LOD KOS products.Design/methodology/approach:Data collection and analysis were conducted at three time periods in 2015–16,2017 and 2019.The sample data used in the comprehensive data analysis comprises all datasets tagged as types of KOS in the Datahub and extracted through their respective SPARQL endpoints.A comparative study of the LOD KOS collected from terminology services Linked Open Vocabularies(LOV)and BioPortal was also performed.Findings:The study proposes a set of Functional,Impactful and Transformable(FIT)metrics for LOD KOS as value vocabularies.The FAIR principles,with additional recommendations,are presented for LOD KOS as open data.Research limitations:The metrics need to be further tested and aligned with the best practices and international standards of both open data and various types of KOS.Practical implications:Assessment performed with FAIR and FIT metrics support the creation and delivery of user-friendly,discoverable and interoperable LOD KOS datasets which can be used for innovative applications,act as a knowledge base,become a foundation of semantic analysis and entity extractions and enhance research in science and the humanities.Originality/value:Our research provides best practice guidelines for LOD KOS as value vocabularies.

NEW DYNAMIC SLOT ASSIGNMENT SCHEME OF SELF-ORGANIZED TDMA VHF DATA LINK

According to the analysis of the very high frequency (VHF) self organized time division multiple access (S TDMA) aviation data link, a new dynamic slot assignment scheme is proposed in this paper, which adopts variable data frame structure and can eliminate the effect of the idle slot on message delay. By using queue theory, the analysis models of the new scheme and previous scheme are presented, and the performance of message delay and that of system throughput are analyzed under two schemes. The simulation results show that the new scheme has a better performance than the previous one in the message delay and system throughput.

System Design Of Security Evaluation For Data Link Communications

Data link communication requires data communication process must have reliability, availability, confidentiality, availability, integrity, non-repudiation, controllability.This has a great effect to ensure the normal communication functions.In this paper the author on the basis of many years of work experience, first discussed the establishment of a risk assessment system data link,then focused on the problem of index weight assessment.To data communication security, this research article will provide some references.

Linked Data-based Slide Repository： The Episodic Slide Retrieval Using the Episodic Keyword Networks

This paper focuses on developing a system that allows presentation authors to effectively retrieve presentation slides for reuse from a large volume of existing presentation materials. We assume episodic memories of the authors can be used as contextual keywords in query expressions to efficiently dig out the expected slides for reuse rather than using only the part-of-slide-descriptions-based keyword queries. As a system, a new slide repository is proposed, composed of slide material collections, slide content data and pieces of information from authors＇ episodic memories related to each slide and presentation together with a slide retrieval application enabling authors to use the episodic memories as part of queries. The result of our experiment shows that the episodic memory-used queries can give more discoverability than the keyword-based queries. Additionally, an improvement model is discussed on the slide retrieval for further slide-finding efficiency by expanding the episodic memories model in the repository taking in the links with the author-and-slide-related data and events having been post on the private and social media sites.

Optimization of RDF link traversal based query execution

Aiming at the problem that only some types of SPARQL （ simple protocal and resource description framework query language） queries can be answered by using the current resource description framework link traversal based query execution （RDF-LTE） approach, this paper discusses how the execution order of the triple pattern affects the query results and cost based on concrete SPARQL queries, and analyzes two properties of the web of linked data, missing backward links and missing contingency solution. Then three heuristic principles for logic query plan optimization, namely, the filtered basic graph pattern （FBGP） principle, the triple pattern chain principle and the seed URIs principle, are proposed. The three principles contribute to decrease the intermediate solutions and increase the types of queries that can be answered. The effectiveness and feasibility of the proposed approach is evaluated. The experimental results show that more query results can be returned with less cost, thus enabling users to develop the full potential of the web of linked data.

Improving Archival Records and Service of Traditional Korean Performing Arts in a Semantic Web Environment

Purpose:This research project aims to organize the archival information of traditional Korean performing arts in a semantic web environment.Key requirements,which the archival records manager should consider for publishing and distribution of gugak performing archival information in a semantic web environment,are presented in the perspective of linked data.Design/methodology/approach:This study analyzes the metadata provided by the National Gugak Center’s Gugak Archive,the search and browse menus of Gugak Archive’s website and K-PAAN,the performing arts portal site.Findings:The importance of consistency,continuity,and systematicity—crucial qualities in traditional record management practices—is undiminished in a semantic web environment.However,a semantic web environment also requires new tools such as web identifiers(URIs),data models(RDF),and link information(interlinking).Research limitations:The scope of this study does not include practical implementation strategies for the archival records management system and website services.The suggestions also do not discuss issues related to copyright or policy coordination between related organizations.Practical implications:The findings of this study can assist records managers in converting a traditional performing arts information archive into a semantic web environment-based online archival service and system.This can also be useful for collaboration with record managers who are unfamiliar with relational or triple database system.Originality/value:This study analyzed the metadata of the Gugak Archive and its online services to present practical requirements for managing and disseminating gugak performing arts information in a semantic web environment.In the application of the semantic web services’principles and methods to an Gugak Archive,this study can contribute to the improvement of information organization and services in the field of Korean traditional music.

World-Wide Semantic Web of Agriculture Knowledge

The rapid increase in the publication of knowledge bases as linked open data （LOD） warrants serious consideration from all concerned, as this phenomenon will potentially scale exponentially. This paper will briefly describe the evolution of the LOD, the emerging world-wide semantic web （WWSW）, and explore the scalability and performance features Of the service oriented architecture that forms the foundation of the semantic technology platform developed at MIMOS Bhd., for addressing the challenges posed by the intelligent future internet. This paper＂ concludes with a review of the current status of the agriculture linked open data.

A Secure DHCP Protocol to Mitigate LAN Attacks

Network security has become more of a concern with the rapid growth and expansion of the Internet. While there are several ways to provide security in the application, transport, or network layers of a network, the data link layer (Layer 2) security has not yet been adequately addressed. Data link layer protocols used in local area networks (LANs) are not designed with security features. Dynamic host configuration protocol (DHCP) is one of the most used network protocols for host configuration that works in data link layer. DHCP is vulnerable to a number of attacks, such as the DHCP rouge server attack, DHCP starvation attack, and malicious DHCP client attack. This work introduces a new scheme called Secure DHCP (S-DHCP) to secure DHCP protocol. The proposed solution consists of two techniques. The first is the authentication and key management technique that is used for entities authentication and management of security key. It is based on using Diffie-Hellman key exchange algorithm supported by the difficulty of Elliptic Curve Discrete Logarithm Problem (ECDLP) and a strong cryptographic one-way hash function. The second technique is the message authentication technique, which uses the digital signature to authenticate the DHCP messages exchanged between the clients and server.

FAIR Data Point:A FAIR-Oriented Approach for Metadata Publication

Metadata,data about other digital objects,play an important role in FAIR with a direct relation to all FAIR principles.In this paper we present and discuss the FAIR Data Point(FDP),a software architecture aiming to define a common approach to publish semantically-rich and machine-actionable metadata according to the FAIR principles.We present the core components and features of the FDP,its approach to metadata provision,the criteria to evaluate whether an application adheres to the FDP specifications and the service to register,index and allow users to search for metadata content of available FDPs.

Design of Multichannel Adaptive Filter by Constructing Multidimensional Wiener-Hopf Equation

In the satellite-to-ground high-speed data transmission link,there are signal self-interference problems of symbols in the co-channel,as well as between orthogonal and polarized channels.A multichannel adaptive filter is designed by constructing a multichannel Wiener-Hopf equation,and the influence of five channel nonideal factors is suppressed to improve the BER performance.Experiments show that this method is effective to suppress the signal selfinterference,and the BER floor is optimized from 1E3 to 1E-7.

Dictionary,Thesaurus or Ontology? Disentangling Our Choices in the Semantic Web Jungle

The Semantic Web seems finally close to maintaining its promise about a real world-wide graph of interconnected resources. The SPARQL query language and protocols and the Linked Open Data initiative have laid the way for endless data endpoints sparse around the globe. However, for the Semantic Web to really happen, it does not suffice to get billions of triples out there： these must be shareable, interlinked and conform to widely accepted vocabularies. While more and more data are converted from already available large knowledge repositories of companies and organizations, the question whether these should be carefully converted to semantically consistent ontology vocabularies or find other shallow representations for their content naturally arises. The danger is to come up with massive amounts of useless data, a boomerang which could result to be contradictory for the success of the web of data. In this paper, I provide some insights on common problems which may arise when porting huge amount of existing data or conceptual schemes （very common in the agriculture domain） to resource description framwork （RDF）, and will address different modeling choices, by discussing in particular the relationship between the two main modeling vocabularies offered by W3C： OWL and SKOS.

Using Semantic Web Technologies to Improve the Extract Transform Load Model

Semantic Web(SW)provides new opportunities for the study and application of big data,massive ranges of data sets in varied formats from multiple sources.Related studies focus on potential SW technologies for resolving big data problems,such as structurally and semantically heterogeneous data that result from the variety of data formats(structured,semi-structured,numeric,unstructured text data,email,video,audio,stock ticker).SW offers information semantically both for people and machines to retain the vast volume of data and provide a meaningful output of unstructured data.In the current research,we implement a new semantic Extract Transform Load(ETL)model that uses SW technologies for aggregating,integrating,and representing data as linked data.First,geospatial data resources are aggregated from the internet,and then a semantic ETL model is used to store the aggregated data in a semantic model after converting it to Resource Description Framework(RDF)format for successful integration and representation.The principal contribution of this research is the synthesis,aggregation,and semantic representation of geospatial data to solve problems.A case study of city data is used to illustrate the semantic ETL model’s functionalities.The results show that the proposed model solves the structural and semantic heterogeneity problems in diverse data sources for successful data aggregation,integration,and representation.