Journal of Intelligent & Fuzzy Systems - Volume 41, issue 1

Authors: Selvakumar, K. | SaiRamesh, L. | Ayyasamy, A. | Archana, M.

Article Type: Research Article

Abstract: This research work confronts a sender-based responsive and novel protocol named “Intelligent Energy-Aware Multiple restraints Secured Optimal Routing (IEAMSOR)” protocol for WSNs. In order to deal with the various emerges like packet routing, node mobility, and energy optimization as well as energy balancing in WSNs. The proposed protocol accounts for the basic QoS restraints such as Delay, HopCount and Energy Level for each link of ‘n’ number of routes and predicts the best optimal path among these in-between sender and receiver nodes throughout the route discovery process. It also assures the energy level of each node existing on the route …during the route reply process. It incorporates the modified mobility prediction approach in order to estimate the stableness of link failure time for every link of each path during the route reply process. The main objective of this work to achieve the energy balancing among the nodes is achieved through fuzzy rules based node’s trust classification is introduced and based on this energy weight of each node is adjusted according to their trustworthiness. It accomplishes the path sustainment process when the link among the two nodes goes down. Moreover, the proposed model has been given careful attention for selecting additional substitute routes throughout link failure. The experimental results have seemed that the IEAMSOR protocol performs better than the existing traditional protocols. Show more

Keywords: QoS, energy level, fuzzy rules, mobility prediction, optimal path, trustworthiness

DOI: 10.3233/JIFS-190050

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1-17, 2021

Authors: Aziz, Ahmed | Singh, Karan | Osamy, Walid | Khder, Ahmed M. | Tuan, Le Minh | Son, Le Hoang | Long, Hoang Viet | Rakhmonov, Dilshodjon

Article Type: Research Article

Abstract: Data acquisition problem on large distributed wireless sensor networks (WSNs) is considered as a challenge in the growth of Internet of Things (IoT). Recently, the combination of compressive sensing (CS) and routing techniques has attracted much attention of researchers. An open question of this combination is how to integrate these techniques effectively for specific tasks. On the other hand, CS data reconstruction process is considered as one of the CS challenges because it requires to recover N data from only M measurement where M < <N. Through this paper, we propose a new scheme for data gathering in IoT based …heterogeneous WSN that includes a new effective Deterministic Clustering using CS technique (DCCS) to handle the data acquisition problem. DCCS reduces the total overhead computational cost needed to self-organize WSN using a simple approach and then uses CS at each sensor node to decrease the overall energy consumption and increase the network lifetime. The proposed scheme includes also an effective CS reconstruction algorithm called Random Selection Matching Pursuit (RSMP) to improve the recovery process at the base station (BS). RSMP adds a random selection process during the forward step to give the opportunity for more columns to be selected as an estimated solution in each iteration. The simulation results show that the proposed scheme succeeds to minimize the overall network power consumption and prolong the network lifetime beside provide better performance in CS data reconstruction. Show more

Keywords: Internet of things, clustering based wireless sensor networks, compressive sensing, routing techniques, data reconstruction, network lifetime

DOI: 10.3233/JIFS-190862

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 19-35, 2021

Authors: Iqbal, Jawaid | Umar, Arif Iqbal | Ul Amin, Noor | Waheed, Abdul | Abdullah, Saleem | Zareei, Mahdi | Khattak, Muazzam Ali Khan

Article Type: Research Article

Abstract: In the last decade, due to wireless technology’s enhancement, the people’s interest is highly increased in Wireless Body Sensor Networks (WBSNs). WBSNs consist of many tiny biosensor nodes that are continuously monitoring diverse physiological signals such as BP (systolic and diastolic), ECG, EMG, SpO2, and activity recognition and transmit these sensed patients’ sensitive information to the central node, which is straight communicate with the controller. To disseminate this sensitive patient information from the controller to remote Medical Server (MS) needs to be prolonged high-speed wireless technology, i.e., LTE, UMTS, WiMAX, WiFi, and satellite communication. It is a challenging task for …the controller to choose the optimal network to disseminate various patient vital signs, i.e., emergency data, normal data, and delay-sensitive data. According to the nature of various biosensor nodes in WBSNs, monitor patient vital signs and provide complete intelligent treatment when any abnormality occurs in the human body, i.e., accurate insulin injection when patient sugar level increased. In this paper, first, we select the optimal network from accessible networks using four different fuzzy attribute-based decision-making techniques (Triangular Cubic Hesistent Fuzzy Weighted Averaging Operator, Neutrosophic Linguistic TOPSIS method, Trangualar Cubic Hesistent Fuzzy Hamacher Weighted Averaging Operator and Cubic Grey Relational Analysis) depending upon the quality of service requirement for various application of WBSNs to prolong the human life, enhanced the society’s medical treatment and indorse living qualities of people. Similarly, leakage and misuse of patient data can be a security threat to human life. Thus, confidential data transmission is of great importance. For this purpose, in our proposed scheme, we used HECC for secure key exchange and an AES algorithm to secure patient vital signs to protect patient information from illegal usage. Furthermore, MAC protocol is used for mutual authentication among sensor nodes and Base Stations (BS). Mathematical results show that our scheme is efficient for optimal network selection in such circumstances where conflict arises among diverse QoS requirements for different applications of WBSNs. Show more

Keywords: Wireless body sensor network, quality of service, security, fuzzy logic, decision making

DOI: 10.3233/JIFS-191104

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 37-55, 2021

Authors: Ji, Junqing | Kong, Xiaojia | Zhang, Yajing | Xu, Tongle | Zhang, Jing

Article Type: Research Article

Abstract: The traditional blind source separation (BSS) algorithm is mainly used to deal with signal separation under the noiseless model, but it does not apply to data with the low signal to noise ratio (SNR). To solve the problem, an adaptive variable step size natural gradient BSS algorithm based on an improved wavelet threshold is proposed in this paper. Firstly, an improved wavelet threshold method is used to reduce the noise of the signal. Secondly, the wavelet coefficient layer with obvious periodicity is denoised using a morphological component analysis (MCA) algorithm, and the processed wavelet coefficients are recombined to obtain the …ideal model. Thirdly, the recombined signal is pre-whitened, and a new separation matrix update formula of natural gradient algorithm is constructed by defining a new separation degree estimation function. Finally, the adaptive variable step size natural gradient blind source algorithm is used to separate the noise reduction signal. The results show that the algorithm can not only adaptively adjust the step size according to different signals, but also improve the convergence speed, stability and separation accuracy. Show more

Keywords: Improved wavelet threshold function, noise reduction, blind source separation, natural gradient, adaptive variable step size

DOI: 10.3233/JIFS-200111

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 57-68, 2021

Authors: Zhang, Yikai | Peng, Yong | Bian, Hongyu | Ge, Yuan | Qin, Feiwei | Kong, Wanzeng

Article Type: Research Article

Abstract: Concept factorization (CF) is an effective matrix factorization model which has been widely used in many applications. In CF, the linear combination of data points serves as the dictionary based on which CF can be performed in both the original feature space as well as the reproducible kernel Hilbert space (RKHS). The conventional CF treats each dimension of the feature vector equally during the data reconstruction process, which might violate the common sense that different features have different discriminative abilities and therefore contribute differently in pattern recognition. In this paper, we introduce an auto-weighting variable into the conventional CF objective …function to adaptively learn the corresponding contributions of different features and propose a new model termed Auto-Weighted Concept Factorization (AWCF). In AWCF, on one hand, the feature importance can be quantitatively measured by the auto-weighting variable in which the features with better discriminative abilities are assigned larger weights; on the other hand, we can obtain more efficient data representation to depict its semantic information. The detailed optimization procedure to AWCF objective function is derived whose complexity and convergence are also analyzed. Experiments are conducted on both synthetic and representative benchmark data sets and the clustering results demonstrate the effectiveness of AWCF in comparison with some related models. Show more

Keywords: Concept factorization, auto-weighting, feature map, data representation, clustering

DOI: 10.3233/JIFS-200298

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 69-81, 2021

Authors: Hussain, Abid | Munawar, Saima | Naveed, Nasir

Article Type: Research Article

Abstract: Wireless Sensor Networks (WSNs) consist of various low-cost devices with limited battery power for surveillance of certain vicinity. The main concern was to prolong the network lifetime to save energy. The heterogeneous nodes are deployed in the given setting divided into two INSTANT-OFF and NEVER-OFF states. Then each one is further subdivided by a Fuzzy Inference System (FIS). The INSTANT-OFF (Good, Better, and Best) has three states active, idle, sleep, and always worked as Cluster Members (CMs) to sense the physical environment. The NEVER-OFF (Good, Better, and Best) has active and idle states. The first two most optimum NEVER-OFF selected …as Cluster Head (CH) and Data Collector (DC), and the remaining belonged to CMs. The cluster boundary was defined by parameter Distance from Base Station (DisBS) to meet the unequal clustering approach. The energy consumes during sensing, processing, and transmission phases by its appropriate nodes. The CMs worked reactively and saved energy by idle and sleep states, while the CH and DC worked in a proactive mode and saved energy in an idle state. The sensing job was done by CMs that consumed a minor amount of energy and transmitted packets of 200 bits length to DC. The DC received packets of 200 bits length from CMs and aggregated them into 6400 bits length packets, then delivered them to CH. The reactive and proactive mechanisms saved the energy as 85.1033% in 2000 rounds; increased lifetime up to 774 rounds, re-clustering setup took place after 1912 rounds, and enhanced the throughput as 100% and latency time 0.001123 by experiment evaluation. The result shows that most energy consumption job were communicated with BS performed by CH hop by hop through other CH. The unequal clustering approach maintained the consumption of energy levels throughout WSNs processing. Show more

Keywords: Wireless Sensor Networks, Fuzzy Inference System, Residual Energy, Sensor Node, energy constraint, clustering

DOI: 10.3233/JIFS-200382

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 83-98, 2021

Authors: Cao, Lianglin | Ben, Kerong | Peng, Hu

Article Type: Research Article

Abstract: Firefly algorithm (FA) is one of most important nature-inspired algorithm based on swarm intelligence. Meanwhile, FA uses the full attraction model, which results too many unnecessary movements and reduces the efficiency of searching the optimal solution. To overcome these problems, this paper presents a new job, how the better fireflies move, which is always ignored. The novel algorithm is called multiple swarm strategy firefly algorithm (MSFFA), in which multiple swarm attraction model and status adaptively switch approach are proposed. It is characterized by employing the multiple swarm attraction model, which not only improves the efficiency of searching the optimal solution, …but also quickly finds the better fireflies that move in free status. In addition, the novel approach defines that the fireflies followed different rules in different status, and can adaptively switch the status of fireflies between the original status and the free status to balance the exploration and the exploitation. To verify the robustness of MSFFA, it is compared with other improved FA variants on CEC2013. In one case of 30 dimension on 28 test functions, the proposed algorithm is significantly better than FA, DFA, PaFA, MFA, NaFA,and NSRaFA on 24, 23, 23, 17, 15, and 24 functions, respectively. The experimental results prove that MSFFA has obvious advantages over other FA variants. Show more

Keywords: Fiefly algorithm, multiple swarm strategy, adaptively switch, global optimization

DOI: 10.3233/JIFS-200619

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 99-112, 2021

Authors: Wang, Yan | Wang, Jianchun | Li, Yanju | Yu, Ming | Zhou, Yancong | Zhang, Bo

Article Type: Research Article

Abstract: Facial expression recognition (FER) has been an active research area in recent years, which plays a vital role in national security and human-computer interaction. Due to the lacking of sufficient expression features and facial images, it is challenging to automatically recognize facial expression with high accuracy. In this paper, we propose a fusion handcraft feature method to improve FER from images. Firstly, a new texture feature extraction method PD-LDN (Pixel Difference Local Directional Number pattern) is proposed, which can extract more local information, reduce noise disturbance and feature dimension. Secondly, the handcrafted features including PD-LDN texture features, geometric features, and …BOVW (Bag of Visual Words) semantic features are connected in parallel to an improved autoencoder network for fusion. Finally, the fused features are input into the softmax classifier for recognizing facial expression. We conduct extensive experiments on JAFFE and CK+datasets. Our proposed method shows superior performance than the state-of-the-art approaches on recognizing facial expressions. Show more

Keywords: Facial expression recognition, LDN, feature fusion, softmax

DOI: 10.3233/JIFS-200713

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 113-123, 2021

Authors: Hussain, Muhammad Iftikhar | He, Jingsha | Zhu, Nafei | Ali Zardari, Zulfiqar | Razque, Fahad | Hussain, Saqib | Pathan, Muhammad Salman

Article Type: Research Article

Abstract: Cloud computing on-demand dynamicity in nature of end-user that leads towards a hybrid cloud model deployment is called a multi-cloud. Multi-cloud is a multi-tenant and multi-vendor heterogeneous cloud platform in terms of services and security under a defined SLA (service level agreement). The diverse deployment of the multi-cloud model leads to rise in security risks. In this paper, we define a multi-cloud model with hybridization of vendor and security to increase the end-user experience. The proposed model has a heterogeneous cloud paradigm with a combination of firewall tracts to overcome rising security issues. The proposed work consists of three steps, …firstly, all incoming traffic from the consumer end into five major groups called ambient. Secondly, design a next-generation firewall (NGFW) topology with a mixture of tree-based and demilitarized zone (DMZ) implications. Test implementation of designed topology performed by using a simple DMZ technique in case of vendor-specific model and NGFW on hybrid vendor based multi-cloud model. Furthermore, it also defines some advantages of NGFW to overcome these concerns. The proposed work is helpful for the new consumer to define their dynamic secure cloud services under a single SLA before adopting a multi-cloud platform. Finally, results are compared in terms of throughput and CPU utilization in both cases. Show more

Keywords: Multi-cloud, next-generation firewall (NGFW), firewall security, cloud computing, single SLA

DOI: 10.3233/JIFS-200835

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 125-136, 2021

Authors: Zhang, Tao | Li, Shizheng | Wang, Jin

Article Type: Research Article

Abstract: China has proposed medical couplet body to alleviate residents’ difficulties in seeking medical treatment, and the future development ability of medical couplet body has gradually become a research interest. On the basis of prospect theory, this study constructs a comprehensive evaluation index system with qualitative and quantitative indexes, clear hierarchy, and diverse attribute characteristics. The development ability of medical couplet body is also comprehensively and systematically evaluated. In addition, the evidential reasoning method is proposed on the basis of the equivalent transformation of prospect value. Furthermore, the validity and feasibility of the model are proven through experiments, and the influence …of decision makers’ risk attitude on the evaluation results is discussed. Show more

Keywords: Medical couplet body, prospect theory, evidence reasoning

DOI: 10.3233/JIFS-200883

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 137-154, 2021