Sea Turtle Foraging Optimization-Based Controller Placement with Blockchain-Assisted Intrusion Detection in Software-Defined Networks

Software-defined networking(SDN)algorithms are gaining increas-ing interest and are making networks flexible and agile.The basic idea of SDN is to move the control planes to more than one server’s named controllers and limit the data planes to numerous sending network components,enabling flexible and dynamic network management.A distinctive characteristic of SDN is that it can logically centralize the control plane by utilizing many physical controllers.The deployment of the controller—that is,the controller placement problem(CPP)—becomes a vital model challenge.Through the advancements of blockchain technology,data integrity between nodes can be enhanced with no requirement for a trusted third party.Using the lat-est developments in blockchain technology,this article designs a novel sea turtle foraging optimization algorithm for the controller placement problem(STFOA-CPP)with blockchain-based intrusion detection in an SDN environ-ment.The major intention of the STFOA-CPP technique is the maximization of lifetime,network connectivity,and load balancing with the minimization of latency.In addition,the STFOA-CPP technique is based on the sea turtles’food-searching characteristics of tracking the odour path of dimethyl sulphide(DMS)released from food sources.Moreover,the presented STFOA-CPP technique can adapt with the controller’s count mandated and the shift to controller mapping to variable network traffic.Finally,the blockchain can inspect the data integrity,determine significantly malicious input,and improve the robust nature of developing a trust relationship between sev-eral nodes in the SDN.To demonstrate the improved performance of the STFOA-CPP algorithm,a wide-ranging experimental analysis was carried out.The extensive comparison study highlighted the improved outcomes of the STFOA-CPP technique over other recent approaches.

Performance Evaluation of Topologies for Multi-Domain Software-Defined Networking

Software-defined networking(SDN)is widely used in multiple types of data center networks,and these distributed data center networks can be integrated into a multi-domain SDN by utilizing multiple controllers.However,the network topology of each control domain of SDN will affect the performance of the multidomain network,so performance evaluation is required before the deployment of the multi-domain SDN.Besides,there is a high cost to build real multi-domain SDN networks with different topologies,so it is necessary to use simulation testing methods to evaluate the topological performance of the multi-domain SDN network.As there is a lack of existing methods to construct a multi-domain SDN simulation network for the tool to evaluate the topological performance automatically,this paper proposes an automated multi-domain SDN topology performance evaluation framework,which supports multiple types of SDN network topologies in cooperating to construct a multi-domain SDN network.The framework integrates existing single-domain SDN simulation tools with network performance testing tools to realize automated performance evaluation of multidomain SDN network topologies.We designed and implemented a Mininet-based simulation tool that can connect multiple controllers and run user-specified topologies in multiple SDN control domains to build and test multi-domain SDN networks faster.Then,we used the tool to perform performance tests on various data center network topologies in single-domain and multi-domain SDN simulation environments.Test results show that Space Shuffle has the most stable performance in a single-domain environment,and Fat-tree has the best performance in a multi-domain environment.Also,this tool has the characteristics of simplicity and stability,which can meet the needs of multi-domain SDN topology performance evaluation.

Multi-Attack Intrusion Detection System for Software-Defined Internet of Things Network

Currently,the Internet of Things(IoT)is revolutionizing communi-cation technology by facilitating the sharing of information between different physical devices connected to a network.To improve control,customization,flexibility,and reduce network maintenance costs,a new Software-Defined Network(SDN)technology must be used in this infrastructure.Despite the various advantages of combining SDN and IoT,this environment is more vulnerable to various attacks due to the centralization of control.Most methods to ensure IoT security are designed to detect Distributed Denial-of-Service(DDoS)attacks,but they often lack mechanisms to mitigate their severity.This paper proposes a Multi-Attack Intrusion Detection System(MAIDS)for Software-Defined IoT Networks(SDN-IoT).The proposed scheme uses two machine-learning algorithms to improve detection efficiency and provide a mechanism to prevent false alarms.First,a comparative analysis of the most commonly used machine-learning algorithms to secure the SDN was performed on two datasets:the Network Security Laboratory Knowledge Discovery in Databases(NSL-KDD)and the Canadian Institute for Cyberse-curity Intrusion Detection Systems(CICIDS2017),to select the most suitable algorithms for the proposed scheme and for securing SDN-IoT systems.The algorithms evaluated include Extreme Gradient Boosting(XGBoost),K-Nearest Neighbor(KNN),Random Forest(RF),Support Vector Machine(SVM),and Logistic Regression(LR).Second,an algorithm for selecting the best dataset for machine learning in Intrusion Detection Systems(IDS)was developed to enable effective comparison between the datasets used in the development of the security scheme.The results showed that XGBoost and RF are the best algorithms to ensure the security of SDN-IoT and to be applied in the proposed security system,with average accuracies of 99.88%and 99.89%,respectively.Furthermore,the proposed security scheme reduced the false alarm rate by 33.23%,which is a significant improvement over prevalent schemes.Finally,tests of the algorithm for dataset selection showed that the rates of false positives and false negatives were reduced when the XGBoost and RF algorithms were trained on the CICIDS2017 dataset,making it the best for IDS compared to the NSL-KDD dataset.

Toward Secure Software-Defined Networks Using Machine Learning: A Review, Research Challenges, and Future Directions

Over the past few years,rapid advancements in the internet and communication technologies have led to increasingly intricate and diverse networking systems.As a result,greater intelligence is necessary to effectively manage,optimize,and maintain these systems.Due to their distributed nature,machine learning models are challenging to deploy in traditional networks.However,Software-Defined Networking(SDN)presents an opportunity to integrate intelligence into networks by offering a programmable architecture that separates data and control planes.SDN provides a centralized network view and allows for dynamic updates of flow rules and softwarebased traffic analysis.While the programmable nature of SDN makes it easier to deploy machine learning techniques,the centralized control logic also makes it vulnerable to cyberattacks.To address these issues,recent research has focused on developing powerful machine-learning methods for detecting and mitigating attacks in SDN environments.This paper highlighted the countermeasures for cyberattacks on SDN and how current machine learningbased solutions can overcome these emerging issues.We also discuss the pros and cons of using machine learning algorithms for detecting and mitigating these attacks.Finally,we highlighted research issues,gaps,and challenges in developing machine learning-based solutions to secure the SDN controller,to help the research and network community to develop more robust and reliable solutions.

Relationship between the rs2241766 ADIPOQ Polymorphism in a Black African Population and the Occurrence of Type 2 Diabetes

Background: Type 2 diabetes mellitus (T2DM) is a metabolic disease, characterized by chronic hyperglycemia. This pathology is linked to various genes whose interaction with the environment promotes its development. The aim of this work was to determine the relationship between the rs2241766 (T/G) polymorphism of the ADIPOQ gene with type 2 diabetes in the black population. Material and Methods: This work was a case-control study, involving type 2 diabetics subjects (n = 94) and controls (n = 82). The study took place from September 2022 to September 2023. Patients were recruited in the Endocrinology Department of the Libreville University Hospital Center. Analysis was performed in the Biochemistry laboratory of the University of Health Sciences in Libreville and at the Research Institute of Health Sciences of Bobodioulasso. Genomic DNA was extracted using the protocol Qiagen kit and the PCR-RFLP method was used to determine the rs2241766 (T/G) polymorphism of the ADIPOQ gene. Results: Only 2 genotypes were found in this population, the TT genotype and the GT genotype. The proportions were not different between the two groups (p = 0.1095) neither the distribution of G and T alleles (p = 0.1095). On the other hand, the HDL hypocholesterolemia was frequent in subjects with the GT genotype compared to TT heterozygous (51.1% vs 48.9%, p = 0.0280;OR = 0.55 [0.30 - 1.01]). Conclusion: There was no association between the rs2241766 (T/G) variant of the ADIPOQ gene and the occurrence of type 2 diabetes in this population. On the other hand, a relationship between HDL hypocholesterolemia and the GT genotype has been established.

Single nucleotide polymorphism within chromosome 8q24 is associated with prostate cancer development in Saudi Arabia

Objective: Genome-wide association studies have demonstrated that single nucleotide polymorphisms (SNPs) are important risk factors for the development of prostate cancer (PCa). Preliminary studies have suggested that the incidence of PCa in Saudi males is low but is probably familial or genetically related.Methods: To identify any possible association of SNP with PCa development in Saudi patients, we investigated a group of SNPs in Saudi PCa patients (n=85) and compared the outcomes to healthy normal controls (n=115) and nodular hyperplasia patients (n=120). DNA was extracted from paraffin-embedded formalin fixed tissue or whole blood from both patients’ groups and healthy control group. A total of thirteen SNPs were genotyped using TaqMan® minor groove binder polymerase chain reaction assay.Results: The rs16901979A, s629242T and rs1447295A alleles were found at significantly higher frequency in PCa patients than controls (p< 0.05). The rs16901979 CA genotype was found at significantly greater frequency in PCa patients than in healthy controls (43% vs. 14%, odds ratio=4.6, p=0.0001) and benign hyperplasia group (43% vs. 25%, odds ratio=2.2, p=0.009).Conclusion: Our study has highlighted the association of rs16901979 SNP with PCa in Saudi males. Such findings have important implications in the PCa diagnosis and in screening unaffected family members of Saudi patients.

Nucleotide excision repair gene polymorphisms and hepatoblastoma susceptibility in Eastern Chinese children:A five-center case-control study

Objective:Nucleotide excision repair(NER)plays a vital role in maintaining genome stability,and the effect of NER gene polymorphisms on hepatoblastoma susceptibility is still under investigation.This study aimed to evaluate the relationship between NER gene polymorphisms and the risk of hepatoblastoma in Eastern Chinese Han children.Methods:In this five-center case-control study,we enrolled 966 subjects from East China(193 hepatoblastoma patients and 773 healthy controls).The TaqMan method was used to genotype 19 single nucleotide polymorphisms(SNPs)in NER pathway genes,including ERCC1,XPA,XPC,XPD,XPF,and XPG.Then,multivariate logistic regression analysis was performed,and odds ratios(ORs)and 95%confidence intervals(95%CIs)were utilized to assess the strength of associations.Results:Three SNPs were related to hepatoblastoma risk.XPC rs2229090 and XPD rs3810366 significantly contributed to hepatoblastoma risk according to the dominant model(adjusted OR=1.49,95%CI=1.07−2.08,P=0.019;adjusted OR=1.66,95%CI=1.12−2.45,P=0.012,respectively).However,XPD rs238406 conferred a significantly decreased risk of hepatoblastoma under the dominant model(adjusted OR=0.68,95%CI=0.49−0.95;P=0.024).Stratified analysis demonstrated that these significant associations were more prominent in certain subgroups.Moreover,there was evidence of functional implications of these significant SNPs suggested by online expression quantitative trait loci(eQTLs)and splicing quantitative trait loci(sQTLs)analysis.Conclusions:In summary,NER pathway gene polymorphisms(XPC rs2229090,XPD rs3810366,and XPD rs238406)are significantly associated with hepatoblastoma risk,and further research is required to verify these findings.

Distribution of gene polymorphisms associated with aspirin antiplatelet in the Han NSTEMI population

Objective:To analyze the genotype and allele distribution characteristics of GPⅢa PLA2(rs5918),PEAR1(rs12041331),and PTGS1(rs10306114)genes related to the antiplatelet pharmacological effects of aspirin,providing reference for individualized treatment of Chinese Han NSTEMI patients.Methods:A total of 107 Han patients with NSTEMI in Beijing Luhe Hospital affiliated to Capital Medical University from January 2016 to December 2022 were selected as the research subjects.The genotypes of GPⅢa PLA2(rs5918),PEAR1(rs12041331)and PTGS1(rs10306114)were detected by fluorescence staining in situ hybridization.The frequency distribution and allele distribution of genotype were analyzed.The results were analyzed whether there were statistical differences in the distribution of related alleles between the Han NSTEMI population and some populations in the 1000 Genomes database.Results:In the Han NSTEMI population,the genotype frequencies of GPⅢa PLA2(rs5918)locus were TT 97.20%,TC 2.80%and CC 0%,the allele frequencies were T 98.60%and C 1.40%.The genotype frequencies of PEAR1(rs12041331)locus were GG 42.06%,GA 44.86%and AA 13.08%,the allele frequencies were G 64.49%and A 35.51%.The genotypes at the PTGS1(rs10306114)locus were all AA(100%),no AG or GG genotype was found.Conclusion:In the NSTEMI population of Han nationality,the mutation at GPⅢa PLA2(rs5918)site related to aspirin antiplatelet pharmacology is rare,and there is no mutation at PTGS1(rs10306114)site.Wild homozygotes are dominant in these two gene loci,while mutations in PEAR1(rs12041331)are more common.Some of the findings in this study are similar to those in previous reports or other populations included in the relevant database;however,some results differ from previous reports or other populations。

KCNQ1 rs2237895 gene polymorphism increases susceptibility to type 2 diabetes mellitus in Asian populations

BACKGROUND The association of single nucleotide polymorphism of KCNQ1 gene rs2237895 with type 2 diabetes mellitus(T2DM)is currently controversial.It is unknown whether this association can be gene realized across different populations.AIM To determine the association of KCNQ1 rs2237895 with T2DM and provide reliable evidence for genetic susceptibility to T2DM.METHODS We searched PubMed,Embase,Web of Science,Cochrane Library,Medline,Baidu Academic,China National Knowledge Infrastructure,China Biomedical Literature Database,and Wanfang to investigate the association between KCNQ1 gene rs2237895 and the risk of T2DM up to January 12,2022.Review Manager 5.4 was used to analyze the association of the KCNQ1 gene rs2237895 polymorphism with T2DM and to evaluate the publication bias of the selected literature.RESULTS Twelve case–control studies(including 11273 cases and 11654 controls)met our inclusion criteria.In the full population,allelic model[odds ratio(OR):1.19;95%confidence interval(95%CI):1.09–1.29;P<0.0001],recessive model(OR:1.20;95%CI:1.11–1.29;P<0.0001),dominant model(OR:1.27.95%CI:1.14–1.42;P<0.0001),and codominant model(OR:1.36;95%CI:1.15–1.60;P=0.0003)(OR:1.22;95%CI:1.10–1.36;P=0.0002)indicated that the KCNQ1 gene rs2237895 polymorphism was significantly correlated with susceptibility to T2DM.In stratified analysis,this association was confirmed in Asian populations:allelic model(OR:1.25;95%CI:1.13–1.37;P<0.0001),recessive model(OR:1.29;95%CI:1.11–1.49;P=0.0007),dominant model(OR:1.35;95%CI:1.20–1.52;P<0.0001),codominant model(OR:1.49;95%CI:1.22–1.81;P<0.0001)(OR:1.26;95%CI:1.16–1.36;P<0.0001).In non-Asian populations,this association was not significant:Allelic model(OR:1.06,95%CI:0.98–1.14;P=0.12),recessive model(OR:1.04;95%CI:0.75–1.42;P=0.83),dominant model(OR:1.06;95%CI:0.98–1.15;P=0.15),codominant model(OR:1.08;95%CI:0.82–1.42;P=0.60.OR:1.15;95%CI:0.95–1.39;P=0.14).CONCLUSION KCNQ1 gene rs2237895 was significantly associated with susceptibility to T2DM in an Asian population.Carriers of the C allele had a higher risk of T2DM.This association was not significant in non-Asian populations.

Interaction between catechol-O-methyltransferase Val/Met polymorphism and cognitive reserve for negative symptoms in schizophrenia

BACKGROUND Cognitive reserve(CR)and the catechol-O-methyltransferase(COMT)Val/Met polymorphism are reportedly linked to negative symptoms in schizophrenia.However,the regulatory effect of the COMT genotype on the relationship between CR and negative symptoms is still unexamined.AIM To investigate whether the relationship between CR and negative symptoms could be regulated by the COMT Val/Met polymorphism.METHODS In a cross-sectional study,54 clinically stable patients with schizophrenia underwent assessments for the COMT genotype,CR,and negative symptoms.CR was estimated using scores in the information and similarities subtests of a short form of the Chinese version of the Wechsler Adult Intelligence Scale.RESULTS COMT Met-carriers exhibited fewer negative symptoms than Val homozygotes.In the total sample,significant negative correlations were found between negative symptoms and information,similarities.Associations between information,similarities and negative symptoms were observed in Val homozygotes only,with information and similarities showing interaction effects with the COMT genotype in relation to negative symptoms(information,β=-0.282,95%CI:-0.552 to-0.011,P=0.042;similarities,β=-0.250,95%CI:-0.495 to-0.004,P=0.046).CONCLUSION This study provides initial evidence that the association between negative symptoms and CR is under the regulation of the COMT genotype in schizophrenia.

Research on the Correlation Between rs2110385 Polymorphisms of the Visfatin Gene and Nonproliferative Diabetic Retinopathy

Objective:To investigate the association between rs2110385 polymorphisms of the visfatin gene and the risk of type 2 diabetic retinopathy(DR).Methods:172 Han subjects were selected from Xi’an Shaanxi Province;140 patients with type 2 diabetes mellitus(T2DM)and 32 normal controls(NC)were selected from our hospital.Patients with diabetes were divided into a non-DR group(T2DM)(n=69)and a nonproliferative diabetic retinopathy Group(DR)(n=71)after dilated fundus photography and fundus fluorescein angiography.rs2110385/AluⅠgenotypes were detected by standardized polymerase chain reaction-restriction fragment length polymorphism(PCR-RFLP),and the differences in the detection rates of different genotypes in the above populations were compared.Results:1)The visfatin level in the DR Group was significantly higher than that in the NC and T2DM groups(P<0.05).2)The frequency of GG genotype and G allele of rs2110385 in the DR Group were higher than those in the T2DM and NC groups(80.3,69.6,50.0,86.6,79,65.6,P<0.05).3)There were significant differences in allele frequency and genotype frequency distribution of rs2110385 between the DR Group and the NC group(P<0.01).Conclusion:Visfatin increased in the nonproliferative diabetic retinopathy group and could be a potential indicator for the clinical prediction of DR.The G allele of the rs2110385 polymorphic site may be related to the risk of DR.

Association between Gene Polymorphisms and SNP-SNP Interactions of the Matrix Metalloproteinase 2 Signaling Pathway and the Risk of Vascular Senescence

Objective This study aimed to explore the association of single nucleotide polymorphisms(SNP)in the matrix metalloproteinase 2(MMP-2)signaling pathway and the risk of vascular senescence(VS).Methods In this cross-sectional study,between May and November 2022,peripheral venous blood of151 VS patients(case group)and 233 volunteers(control group)were collected.Fourteen SNPs were identified in five genes encoding the components of the MMP-2 signaling pathway,assessed through carotid-femoral pulse wave velocity(cf PWV),and analyzed using multivariate logistic regression.The multigene influence on the risk of VS was assessed using multifactor dimensionality reduction(MDR)and generalized multifactor dimensionality regression(GMDR)modeling.Results Within the multivariate logistic regression models,four SNPs were screened to have significant associations with VS:chemokine(C-C motif)ligand 2(CCL2)rs4586,MMP2 rs14070,MMP2rs7201,and MMP2 rs1053605.Carriers of the T/C genotype of MMP2 rs14070 had a 2.17-fold increased risk of developing VS compared with those of the C/C genotype,and those of the T/T genotype had a19.375-fold increased risk.CCL2 rs4586 and MMP-2 rs14070 exhibited the most significant interactions.Conclusion CCL2 rs4586,MMP-2 rs14070,MMP-2 rs7201,and MMP-2 rs1053605 polymorphisms were significantly associated with the risk of VS.

Heavy metal induced DNA changes in aquatic macrophytes: Random amplified polymorphic DNA analysis and identification of sequence characterized amplified region marker

Plants have been used as good bio-indicators and genetic toxicity of environmental pollution in recent years. In this study, aquatic plants Hydrilla verticillata and Ceratophyllum demersum treated with 10umol/L Cd, 5 umol/L Hg, and 20 umol/L Cu for 96 h, showed changes in chlorophyll, protein content, and in DNA profiles. The changes in DNA profiles included variation in band intensity, presence or absence of certain bands and even appearance of new bands. Genomic template stability test performed for the qualitative measurement of changes in randomly amplified polymorphic DNA （RAPD） profiles, showed significant effect at the given concentration of metals. Cloning and sequencing of bands suggested that these markers although may not be homologous to any known gene but its conversion as a sequence characterized amplified region （SCAR） marker is useful in detecting the effects of genotoxin agents.

A Survey: Typical Security Issues of Software-Defined Networking

Software-Defined Networking (SDN) has been a hot topic for future network development, which implements the different layers of control plane and data plane respectively. Despite providing high openness and programmability, the “three-layer two-interface” architecture of SDN changes the traditional network and increases the network attack nodes, which results in new security issues. In this paper, we firstly introduced the background, architecture and working process of SDN. Secondly, we summarized and analyzed the typical security issues from north to south: application layer, northbound interface, control layer, southbound interface and data layer. Another contribution is to review and analyze the existing solutions and latest research progress of each layer, mainly including: authorized authentication module, application isolation, DoS/DDoS defense, multi-controller deployment and flow rule consistency detection. Finally, a conclusion about the future works of SDN security and an idealized global security architecture is proposed.

Meiotic abnormalities in metaphase I human spermatocytes from infertile males： frequencies, chromosomes involved, and relationship with polymorphic karyotype and seminal parameters

The aim of this study was to look in depth at the relationship between meiotic anomalies and male infertility, such as the determination of the chromosomes involved or the correlation with patient features. For this purpose, a total of 31 testicular tissue samples from individuals consulting for fertility problems were analyzed. Metaphase I cells were evaluated using a sequential methodology combining Leishman stained procedures and multiplex fluorescence in situ hybridization protocols. The number of chromosomal units and chiasmata count per bivalent were established and a hierarchical cluster analysis of the individuals was performed. The relationship of the seminogram and the karyotype over recombination were evaluated using Poisson regression models. Results obtained in this study show a significant percentage of infertile individuals with altered meiotic behavior, mostly specified as a reduction in chiasmata count in medium and large chromosomes, the presence of univalents, and the observation of tetraploid metaphases. Moreover, the number and the type of anomalies were found to be different between cells of the same individual, suggesting the coexistence of cell lines with normal meiotic behavior and cell lines with abnormalities. In addition, chromosomal abnormalities in metaphase I are significantly associated with oligozoospermia and/or polymorphic karyotype variants.

A Cleaved Amplified Polymorphic Sequence Marker to Detect Variation in Wx Locus Conditioning Translucent Endosperm in Rice

The translucent endosperm trait in a japonica rice variety ＇Kantou 194＇ is controlled by a Wx-mq gene which is allelic to Wx locus by genetic analysis and allelic test. The amylose content analysis showed that an intermediate amylose content between those of glutinous and non-glutinous rice existed in endosperm of homozygous Wx-mq genotype. The slight changes of amylose content in different varieties and F1 grains with an identical Wx-mq genotype might be influenced by dissimilar genetic background. To identify the Wx-mq genotype simply and rapidly, a cleaved amplified polymorphic sequence （CAPS） marker was designed. The result from the molecular detection indicated that it could be used for marker-assisted selection for low amylose content varieties in rice breeding.

Quality of Service Improvement with Optimal Software-Defined Networking Controller and Control Plane Clustering

The controller is indispensable in software-defined networking(SDN).With several features,controllers monitor the network and respond promptly to dynamic changes.Their performance affects the quality-of-service(QoS)in SDN.Every controller supports a set of features.However,the support of the features may be more prominent in one controller.Moreover,a single controller leads to performance,single-point-of-failure(SPOF),and scalability problems.To overcome this,a controller with an optimum feature set must be available for SDN.Furthermore,a cluster of optimum feature set controllers will overcome an SPOF and improve the QoS in SDN.Herein,leveraging an analytical network process(ANP),we rank SDN controllers regarding their supporting features and create a hierarchical control plane based cluster(HCPC)of the highly ranked controller computed using the ANP,evaluating their performance for the OS3E topology.The results demonstrated in Mininet reveal that a HCPC environment with an optimum controller achieves an improved QoS.Moreover,the experimental results validated in Mininet show that our proposed approach surpasses the existing distributed controller clustering(DCC)schemes in terms of several performance metrics i.e.,delay,jitter,throughput,load balancing,scalability and CPU(central processing unit)utilization.

Retrieval of leaf biochemical properties by inversed PROSPECT model and hyperspectral indices:an application to Populus euphratica polymorphic leaves

Leaf biochemical properties have been widely assessed using hyperspectral reflectance information by inversion of PROSPECT model or by using hyperspectral indices, but few studies have focused on arid ecosystems. As a dominant species of riparian ecosystems in arid lands, Populus euphratica Oliv. is an unusual tree species with polymorphic leaves along the vertical profile of canopy corresponding to different growth stages. In this study, we evaluated both the inversed PROSPECT model and hyperspectral indices for estimating biochemical properties of P. euphratica leaves. Both the shapes and biochemical properties of P. euphratica leaves were found to change with the heights from ground surface. The results indicated that the model inversion calibrated for each leaf shape performed much better than the model calibrated for all leaf shapes, and also better than hyperspectral indices. Similar results were obtained for estimations of equivalent water thickness （EWT） and leaf mass per area （LMA）. Hyperspectral indices identified in this study for estimating these leaf properties had root mean square error （RMSE） and R2 values between those obtained with the two calibration strategies using the inversed PROSPECT model. Hence, the inversed PROSPECT model can be applied to estimate leaf biochemical properties in arid ecosystems, but the calibration to the model requires special attention.

On the use of the genetic programming for balanced load distribution in software-defined networks

As a new networking paradigm,Software-Defined Networking(SDN)enables us to cope with the limitations of traditional networks.SDN uses a controller that has a global view of the network and switch devices which act as packet forwarding hardware,known as“OpenFlow switches”.Since load balancing service is essential to distribute workload across servers in data centers,we propose an effective load balancing scheme in SDN,using a genetic programming approach,called Genetic Programming based Load Balancing(GPLB).We formulate the problem to find a path:1)with the best bottleneck switch which has the lowest capacity within bottleneck switches of each path,2)with the shortest path,and 3)requiring the less possible operations.For the purpose of choosing the real-time least loaded path,GPLB immediately calculates the integrated load of paths based on the information that receives from the SDN controller.Hence,in this design,the controller sends the load information of each path to the load balancing algorithm periodically and then the load balancing algorithm returns a least loaded path to the controller.In this paper,we use the Mininet emulator and the OpenDaylight controller to evaluate the effectiveness of the GPLB.The simulative study of the GPLB shows that there is a big improvement in performance metrics and the latency and the jitter are minimized.The GPLB also has the maximum throughput in comparison with related works and has performed better in the heavy traffic situation.The results show that our model stands smartly while not increasing further overhead.

Challenge-based collaborative intrusion detection in software-defined networking: An evaluation

Software-Defined Networking(SDN)is an emerging architecture that enables a computer network to be intelligently and centrally controlled via software applications.It can help manage the whole network environment in a consistent and holistic way,without the need of understanding the underlying network structure.At present,SDN may face many challenges like insider attacks,i.e.,the centralized control plane would be attacked by malicious underlying devices and switches.To protect the security of SDN,effective detection approaches are indispensable.In the literature,challenge-based collaborative intrusion detection networks(CIDNs)are an effective detection framework in identifying malicious nodes.It calculates the nodes'reputation and detects a malicious node by sending out a special message called a challenge.In this work,we devise a challenge-based CIDN in SDN and measure its performance against malicious internal nodes.Our results demonstrate that such a mechanism can be effective in SDN environments.