International Journal of Communication Networks and Distributed Systems (23 papers in press)

Regular Issues

• Deep Learning based on Multimedia Encoding to Enhance of Video Quality  
  by Nagendra Panini Challa, Shanmuganathan C, Shobana M, Ch.Venkata Sasi Deepthi, Bharathiraja N 
  Abstract: Over the years, video compression has become a key method of sharing information and communicating in the world of media. The future image quality of the ISO standards groups will expect high quality images. Also, visual video codecs (VVC) have optimised encoding decisions that use the same average square error, or total square difference, for decades. At the same time, the sudden increase in deep learning (DL) methods raises the issue of whether DL could actually profoundly change the way the clip was programmed. We developed a new visual quality measurement (VQM) to find ways to make it better. The proposed approach could significantly reduce the encoding compute load while maintaining almost the same enhanced rate distortion optimisation (ERDO) efficiency as the previous encoder, based on experimental measurements. To further improve efficiency, the proposed methodology could be combined with fast motion search algorithms and filtration methods.
  Keywords: multimedia; deep learning; visual quality measurement; VQM; quality; encoding optimiser; visual video codecs; VVC; enhanced rate distortion optimisation; ERDO.
  DOI: 10.1504/IJCNDS.2023.10049772
   
  
• Effect of Different Attack Strategies on Controllability Robustness of Directed Complex Networks  
  by Peng Geng, Annan Yang, Lai Wei, Rui Chen, Ziyu Pan 
  Abstract: This article summarises the controllability robustness of various directed complex networks under different attack strategies. Based on the theory of node-degree, edge-degree, node-betweenness and edge-betweenness, the controllability robustness evaluation criterion for complex networks is proposed. Considering directed complex networks, we describe the construction of seven network models (RGN, SFN, OLN, MCN, QSN, RTN and RRN). Based on six attack strategies (NABR, NABB, NABD, EABR, EABB and EABD), we conduct simulated attacks on the above seven network models and analyse the results. All the attacks are classified into node-based and edge-based. Through simulation experiments, we can see that under the same network environment, the damage caused by the betweenness-based attack to the network is greater than that of the degree-based attack. The controllability robustness of scale-free network and onion-like network is almost the same regardless of the attack. Compared with other networks, random rectangle network has the best controllability robustness. Therefore, the simulation results can also draw the conclusion that the multi-ring structure is helpful to improve the controllability robustness.
  Keywords: directed complex networks; controllability robustness; attack strategy.
  DOI: 10.1504/IJCNDS.2023.10049880
   
  
• Internet of Things Producer Mobility Management in Named Data Networks: A Survey, Outlook, and Open Issues  
  by Ahmad Abrar, Ahmad Suki Che Mohamed Arif, Khuzairi Mohd Zaini 
  Abstract: The sustainability of the current internet architecture is a challenging task under consideration of tremendous and dramatic growth of smart mobile devices and content demands. The mobility support plays an essential role in growing trend of smart mobile devices, making mobility more intriguing and widely discussed domain. Therefore, this study provides broad discussion on mobility support. Also, describes consumer and producer mobility in internet of things-based wireless body area networks (IoT-WBANs) using named data networks (NDN). NDN is a significant paradigm for data distribution in IoT networks, but it confronts considerable challenges in terms of producer mobility. We discuss producer mobility extensively and categories into different approaches based on their characteristics and functionalities. Moreover, we constructed a clear research roadmap regarding IoT in NDN and critically reviewed each approach to identify the various research concerns and long-standing challenges. Furthermore, we investigated various challenges in IoT-WBANs caused by producer mobility and suggested intuitive solutions.
  Keywords: named data networking; internet of things; IoT; wireless body area networks; WBANs; information centric networks; consumer mobility; producer mobility.
  DOI: 10.1504/IJCNDS.2023.10050099
   
  
• Leveraging capsule network to learn content text for collaborative filtering  
  by Ji Li, Suhua Wang 
  Abstract: At present, most of the building components, technologies and frameworks of deep learning are based on convolutional networks. However, some deep learning studies on image processing have shown that the capsule network can be more representational because it can capture various posture changes, including translation, rotation and scaling, and can remember the position relationship between parts. Despite the intriguing nature of capsule network and their potential to open up entirely new natural language processing architectures, little work has been done in this area. In this work, we use the capsule network to learn the content text of the item (such as the plot text of the movie or the description document of the product), so as to obtain a better representation of the item and help achieve a more accurate recommendation. We proposed leveraging capsule network to learn content text for collaborative filtering (CCCF). This model combines capsule network and neural matrix factorisation to effectively model text data and user-item ratings. Experiments conducted from different perspectives on two popular datasets show that CCCF achieves good performance in common recommendation tasks, which proves the effectiveness of capsule network in recommendation.
  Keywords: capsule network; content text; generalised matrix factorisation; collaborative filtering.
  DOI: 10.1504/IJCNDS.2023.10050805
   
  
• Cluster-Based Combined Hybrid Relay Vehicle Selection Approach for Improving Performance and Reliability in Vehicular Ad-hoc Network  
  by Puja Padiya, Amarsinh V. Vidhate, Ramesh Vasappanavara 
  Abstract: One of the main objectives of smart transport systems is to improve road safety. Ad hoc vehicle network uses vehicle accident alert systems that broadcast crashes to vehicles. Reliable and timely receipts of messages are two of the main intents for the creation of VANET security alert protocols. Existing techniques are hard to meet both objectives at the same time. With proposed suggestion, the vehicle transmits by employing the combined cluster and broadcast technique all the accident warning messages. The multi-hop message dissemination in VANET involving the selection process of relay vehicles in our proposed combined approach helps to improve performance in terms of reduced collision and reliability in terms of improved reachability and thus helps faster dissemination of emergency messages which in turn reduces the further impact of emergency situations.
  Keywords: vehicular communications; reliability; relay vehicle; emergency messages; ad hoc networks; safety; broadcast; cluster; message dissemination; vehicular ad hoc network.
  DOI: 10.1504/IJCNDS.2023.10051054
   
  
• Software-defined network planes - a survey on attacks and countermeasure  
  by Sendil Vadivu D, Narendran Rajagopalan 
  Abstract: A smartly managed framework that enables the network to be configured via software application is termed software-defined networks (SDN). SDN gracefully abstracts the network management regardless of the underlying technology. The fundamental drive of SDN is to move from distributed control architecture to centralised control architecture. Though SDN provides complex security policies that can be easily customised to safeguard the network, it suffers from a single point of failure and opens to many security challenges. In order to withstand this centralised architecture, it is crucial to study the security aspects of the SDN. This paper surveys the various security techniques of the SDN stack from the perspective of individual layers.
  Keywords: software-defined network; SDN; SDN planes; security; flow table; OpenFlow; attacks; countermeasure.
  DOI: 10.1504/IJCNDS.2023.10051589
   
  
• A LEARNING-BASED APPROACH TO IMPROVING MULTICAST NETWORK PERFORMANCE  
  by Hazem A. Abdulmajeed, Hesham A. Hefny, Assem Alsawy 
  Abstract: A neural network approach is recommended by us in this research paper, to solve the problem of multicast routing subject to some quality of service (QoS) restrictions in communications and internet of things (IoT) networks, which is considered a complete nondeterministic polynomial (NP) problem. This approach was taken to identify a multicast tree that satisfies those restrictions, in particular cost, delay, and data loss rate. The exemplary (shortest) path is identified by the recommended routing algorithm considering the traffic conditions (the incoming traffic flow, routers occupancy, and link capacities). The experimental results showed a significant difference in obtaining the exemplary path that was executed by the recommended method using the Hopfield neural network (HNN) approach, besides the number of iterations. Furthermore, the execution time is less compared with the recommendations of heuristic algorithms, such as the ant colony optimisation algorithm (ACO) and genetic algorithms (GAs).
  Keywords: multicast routing; internet of things; IoT; neural network; quality of services; QoS; heuristic algorithms.
  DOI: 10.1504/IJCNDS.2023.10051590
   
  
• Fuzzy Logic-Based Delay Efficient Data Collection Technique for IoT Environment  
  by Deepa Rani, Tanuj Wala, Rajeev Kumar, Naveen Chauhan 
  Abstract: The sensor nodes in WSNs are resource constraints and data collection is draining the sensor node’s energy. Therefore, collecting data in a single hop by the mobile device helps in preserving the sensor node energy. This paper is introducing a fuzzy logic-based one hop data collection path (FLO-DCP) algorithm to find stop points from the set of intersecting points of the overlapped clusters and to reduce the data collection time by shorting the path length of the mobile device and increasing the lifetime of the network by preserving the sensor node’s energy. The proposed method consists of three phases. First, fuzzy logic-based overlapped clusters are formed, thereafter the stop points and trajectory path for the mobile device is being computed, and last, the data collection process is done. Also, in comparison with NDCMC, CB, and ORLP-RP algorithms, simulation results show that the proposed algorithm has better performance.
  Keywords: internet of things; data collection; fuzzy C-mean; FCM; clustering; trajectory; one-hop transmission; mobile device.
  DOI: 10.1504/IJCNDS.2023.10051768
   
  
• Atrial fibrillation medical image encryption algorithm based on deep learning and adaptive block  
  by Jiangjiang Li, Lijuan Feng, Xibin Guo 
  Abstract: In this paper, a deep learning and adaptive block-based chaotic encryption algorithm for atrial fibrillation medical image is proposed. Firstly, we use 2D Sine Logistic chaos system to generate two security sequences with good chaotic characteristics. Then the image is divided into fixed size image blocks, and the maximum pixel difference and variance of the image blocks are calculated. Finally, chaotic sequence 1 is used for ciphertext feedback encryption of smooth blocks, and chaotic sequence 2 is used for plaintext feedback encryption of complex blocks. So the encrypted image is obtained. The RBF network is used to predict the chaotic sequence, and the predictive key stream is obtained. Experiment results show that the proposed algorithm has high encryption efficiency, and the encryption speed is about 1 times higher than that of the existing methods. The new algorithm is suitable for real-time encryption of medical images with large amount of data.
  Keywords: atrial fibrillation medical image encryption; 2D sine logistic chaos system; deep learning; adaptive block; RBF neural network.
  DOI: 10.1504/IJCNDS.2023.10052828
   
  
• Research on the optimization of whitelisting technology for network firewall in industrial control system using genetic algorithm
  by Xiuhong Zhou, Wenbing Shi 
  Abstract: Industrial control systems improve the efficiency of industrial production management but also bring network risks. This paper briefly introduced the industrial control system and the industrial firewall adopting whitelist policy and proposed to optimise the whitelist of industrial firewall with the genetic algorithm-support vector machine (GA-SVM) algorithm to make it learn the rules independently. Finally, simulation experiments were performed using industrial control data collected from light-emitting diode (LED) lamp production enterprises to compare the GA-SVM algorithm with K-means and traditional SVM algorithms. The results demonstrated that the GA-SVM algorithm had better detection accuracy and shorter detection time for abnormal industrial control data; the industrial firewall adopting the GA-SVM-optimised whitelist had lower false blocking rate.
  Keywords: industrial firewall; industrial control system; whitelist; genetic algorithm.
  
  
• Cluster-based multiple malicious node detection using honeypot AODV (H-AODV) in MANETs
  by Sampada H. K. Kubsad, Shobha K. R 
  Abstract: Security and scalability are two major research areas in the field of mobile ad-hoc networks (MANETs). The existing solutions for security and scalability are majorly used for static networks e.g., sensor networks. The focus of the present work is to detect and remove the multiple malicious black holes (MBH) and multiple malicious grey hole (MGH) nodes from the dynamic networks e.g., MANETs. The proposed solution increases network security. An efficient weight-based clustering technique is used to enhance the stability and load balancing of the network. Cluster head (CH) is selected based on the maximum weight factor. The weight of the node is based on three factors constancy factor (Cx) trust value (Ty) and link factor (Lz). Weightage values for the parameters can be prioritised and tested for consistency using analytic hierarchy process (AHP) algorithm. Each CH executes honey pot-AODV (H-AODV) to find the MBH and MGH nodes in its network.
  Keywords: mobile ad hoc networks; MANETs; honeypot-AODV; H-AODV; modified-AODV; M-AODV; clustering; malicious blackhole/grayhole attack; MBH/MGH.
  DOI: 10.1504/IJCNDS.2024.10053453
   
  
• Effect of User Mobility under Rician Fading on Power Allocation for Non-Orthogonal Multiple Access (PA-NOMA) Strategy  
  by Sandeep Singh Rana, Gaurav Verma, O.P. Sahu 
  Abstract: Non-orthogonal multiple access (NOMA) has been envisaged as a promising technique to meet the demand for massive machine-type communication (mMTC) devices. However, designing a NOMA system required a proper comprehensive study of user mobility, user switching, and imperfect successive interference cancellation (Im-SIC). In this paper, the effect of user mobility and Rician fading channel on power allocation for non-orthogonal multiple access (PA-NOMA) strategy is thoroughly investigated. This paper also discusses the challenges faced during the power allocation to multiple NOMA users. Mobility of the users violates the basic channel gain conditions of the NOMA users, therefore, to maintain the fairness index of the individual cell edge users dynamic power allocation strategy is adopted. Simulation results show that user mobility and Im-SIC have a significant effect on the PA-NOMA strategy for multiple users in terms of sum-rate capacity, average bit error rate, and fairness index.
  Keywords: fairness index; PA-NOMA; imperfect SIC; Rician fading; user mobility; user switching.
  DOI: 10.1504/IJCNDS.2024.10053703
   
  
• Metaheuristic Enabled Hot Event Detection and Product Recommendation in Social Media Data Streams  
  by MANU G. THOMAS, SENTHIL S 
  Abstract: In this study, a unique system that recognizes hot events and reliably integrates them with product recommendation systems is modelled. The correlation between the detected hot event and the user interestingness identifies the respective product that influenced the discussion. This results in the hottest action recognition being carried out through pre-processing, extraction of features and weight, text data modeling, and cluster dependent topic identification. The keywords are initially extracted from each tweet. The evaluation of the different feature space is then completed and submitted to determine the design of the text model. Finally, clustering dependent hot topic identification takes place, where the optimization logic plays its major role. Two different clustering processes take place: micro and macro based clustering, where the selection of optimal centroid is made by a new Enhanced Monarch Butterfly Optimization with 3-level Butterfly Adjusting Operator (EMBO-3BAR).
  Keywords: Hot Topic Detection; Pre-Processing: Feature selection; User Interestingness; Optimization; Product Recommendation.
  DOI: 10.1504/IJCNDS.2023.10054096
   
  
• Developing Policy Hierarchies for an Effective Distributed Systems and Network Management. Case Study in a Videoconference Service.  
  by Sarandis Mitropoulos 
  Abstract: Large-scale distributed systems and network management depends on complex relationships which are strongly related to the manager roles which are depended by a set of management policies. Management policies express peer-to-peer or hierarchical management relationships which constitute the policy hierarchies. Policy hierarchies must satisfy at the highest management level, the business goals, while the complex relationships between policies must be analysed for avoiding conflicts, developing in parallel synergy, strategic convergence, and optimisation of policy usage. This paper proposes an integrated approach for constructing policy hierarchies. A generic policy refinement framework is presented as a crucial factor for a succeeded policy hierarchy construction. The policy hierarchy analysis functionality is defined, providing a respective software tool in Prolog. The high applicability of the proposed approach is depicted in a case study concerning the management of a videoconference service.
  Keywords: integrated distributed system and network management; management policy hierarchies; policy refinement and analysis; videoconference service provision.
  DOI: 10.1504/IJCNDS.2024.10054947
   
  
• Detection and Mitigation of a Link Flooding based DDoS attacks on a Software Defined Network using Network Function Virtualization  
  by Shariq Murtuza, Krishna Asawa 
  Abstract: Software Defined Networks (SDN) are emerging as the first choice for network administrators due to their agility, modularity and dynamism. Network operators can change the network topology, routes and other parameters as per their current requirement. Like the traditional computer networks SDNs are also prone to various Denial of Service attacks(DDoS). Link flooding attacks are a class of DDoS attack that aims to choke crucial network connections and can fully detach the victim from the network. In this paper we have discussed two Link Flooding based Denial of Service attacks, namely Coremelt and Crossfire, in the context of SDN along with the possible mitigation. These attacks are aimed at disconnecting services from the network. We demonstrate the usage of Network Function Virtualization along with SDN features to mitigate these attacks by recreating replicas of the services under attack and connecting them to the network.
  Keywords: Software Defined Networks; Network Function Virtualization; Denial of Service Attacks; Virtual Network Functions.
  DOI: 10.1504/IJCNDS.2024.10055095
   
  
• An Enhanced Priority based Multi-hop Clustering Algorithm for Vehicular Adhoc Networks  
  by RAKHI S, Shobha K. R 
  Abstract: The importance of intelligence transportation system is increasing as it improves road safety and efficacy by means of vehicular ad hoc networks (VANET). The nodes in VANET are intelligent machines that can communicate with each other. Due to high mobility and frequent network fragmentation, stability is always a challenge in VANET. Even though traditional clustering methods address this issue, they exhibit less stability in highly dynamic scenarios. To improve the stability of the clusters, a new multi-hop clustering method named enhanced priority-based multi-hop clustering algorithm (EPMCA) is proposed. The best neighbours are chosen using neighbour following method. Then, stable clusters are established based on the average velocity of the cluster and association lifetime between the nodes by the cluster head. The proposed algorithm shows significant improvement in average cluster head and cluster member duration, average cluster head changes and number of clusters for varying communication ranges compared to existing techniques.
  Keywords: vehicles; stability; cluster; priority; multi-hop; vehicular ad hoc networks; VANET; enhanced priority-based multi-hop clustering algorithm; EPMCA.
  DOI: 10.1504/IJCNDS.2024.10055893
   
  
• Asymmetric Multi-period Deep Residual Network Face Age Estimation  
  by Yilihamu Yaermaimaiti, Yan Tian Xing, Tusongjiang Kari 
  Abstract: Aiming at the problem that it is difficult for face age estimation to find features that accurately characterise face age changes, this paper proposes an asymmetric multi-period deep residual network face age estimation model. First, use an asymmetric residual block to improve the feature extraction ability of the network model; secondly, build a multi-period residual structure to solve the optimisation problem caused by network deepening; then, use a shortcut connection that combines pooling and convolution to reduce The information loss of the shortcut layer; finally, the age estimation method combining multi-classification and sequential regression is used to reduce the prediction error. Experimental results on three public datasets showed that the error (MAE/RMSE) of this model is reduced to 2.42/3.44, 3.38/4.69 and 5.17/7.34, respectively, which proved the effectiveness of the proposed algorithm.
  Keywords: feature extraction; asymmetric convolution; shortcut connection; information loss; error.
  DOI: 10.1504/IJCNDS.2024.10056335
   
  
• Applications of Bluetooth and Wifi-Direct for Local Communication and their Performance Evaluation  
  by YUGBHANU RAJWADE, Divi Arpit, K. Jairam Naik 
  Abstract: Wireless connectivity may not be available in congested locations (such as concerts or conference-halls) or may be interrupted by infrastructure outages caused by earthquakes and tsunamis. They are the great boon when it comes to device-to-device communication based on technologies like Wifi-Direct and Bluetooth. However, no existing research builds a fully functional communication system which is local in nature, nor does it consider how the user mobility can be supported. A fuzzy logic-based normalised quantitative decision (FNQD) approach was proposed by the recent researchers, but it is suffering with the distance coverage among the communicating devices. We put forward an intragroup communication solution for local setup without the interference of any external network support. We propose a Bluetooth and Wifi-Direct (Wifi_BL) system that improves the distance coverage obtained from the existing fuzzy logic-based normalised quantitative decisions. The proposed Wifi_BL system attains better distance coverage over the existing FNQD.
  Keywords: local communication; Bluetooth; Wifi-direct; distance coverage; fuzzy logic.
  DOI: 10.1504/IJCNDS.2024.10056567
   
  
• Performance analysis of the hard-decision cooperative multi-stage spectrum sensing for cognitive radio  
  by Mohammad Hallaq, Wissam Altabban, Omran Abbas 
  Abstract: The number of applications that depend on wireless communications is increasing consistently. Therefore, the spectrum, which is a scarce resource, is becoming more crowded. Recently, cognitive radio (CR) technology has stood out to be a solution for this issue. However, this technology still faces problems that drag its performance such as the hidden terminal problem which occurs while CR is performing the spectrum sensing process. This problem can be solved by using cooperative sensing, where we rely on multiple cognitive radios rather than using a single one. In this paper, the authors propose a novel cooperative spectrum sensing model with multi-stage local sensing. First, each CR applies two-stage local sensing, the first stage is energy detection, and the second is maximum-minimum eigenvalues detection. Afterwards, each CR sends its detection result to a fusion centre to make the final decision. The approach is analysed in light of different rules and parameters under IEEE 802.22 standard. Finally, the results demonstrate that the best fusion rule for this system is the majority rule.
  Keywords: cognitive radio; multi-stage sensing; cooperative spectrum sensing; CSS; hard decision rules; hidden terminal problem; fusion centre; energy detection; maximum-minimum eigenvalues; MME.
  DOI: 10.1504/IJCNDS.2023.10047753
   
  
• Privacy and security improvement in UAV network using blockchain  
  by Hardik Sachdeva, Shivam Gupta, Anushka Misra, Khushbu Chauhan, Mayank Dave 
  Abstract: Unmanned aerial vehicles (UAVs), also known as drones, have exploded in every segment present in today's business industry. They have scope in reinventing old businesses, and they are even developing new opportunities for various brands and franchisors. UAVs are used in the supply chain, maintaining surveillance and serving as mobile hotspots. Although UAVs have potential applications, they bring several societal concerns and challenges that need addressing in public safety, privacy, and cyber security. UAVs are prone to various cyber-attacks and vulnerabilities; they can also be hacked and misused by malicious entities resulting in cyber-crime. The adversaries can exploit these vulnerabilities, leading to data loss, property, and destruction of life. One can partially detect the attacks like false information dissemination, jamming, grey hole, blackhole, and GPS spoofing by monitoring the UAV behaviour, but it may not resolve privacy issues. This paper presents secure communication between UAVs using blockchain technology. Our approach involves building smart contracts and making a secure and reliable UAV ad hoc network. This network will be resilient to various network attacks and is secure against malicious intrusions.
  Keywords: unmanned aerial vehicles; UAVs; blockchain; data privacy; network security; smart contract; Ethereum.
  DOI: 10.1504/IJCNDS.2023.10048925
   
  
• An ECC-based enhanced and secured authentication protocol for IoT and cloud server  
  by Bhanu Chander, Kumaravelan Gopalakrishnan 
  Abstract: Due to the tremendous development in various domains, both internet of things (IoTs) and cloud-based computing are recognised as emerged technologies of the 20th century. IoT collection of heterogeneous interconnected embedded devices, then cloud computing provides the possible infrastructure which could be used at any time and from anywhere. In recent times, due to the advancements in IoT and cloud computing-based devices, mainly their ability to provide remote services, they have been employed in various real-life domains. The integration of IoT with the cloud infrastructure may lead to security issues. Moreover, these IoT-based devices act as a prerequisite for linking through high-resource hubs such as cloud server (CS) for communication and resource sharing. Such a combination comprises security hazards and introduces dishonest data, the principal factors in a system fiasco. In addition, IoT policies are accommodated on public web links, which perturb the secrecy of trustworthy operators. Hence, this article planned an authentication idea on ECC for IoT-based embedded devices with CS. We discover the fuzzy structure facility for channel non-reciprocal, then ECC with one-way hash functions for secure validation. In conclusion, we scrutinise the planned procedure through the AVISPA and related the resource constraints costs with existing authentication procedures.
  Keywords: internet of things; IoTs; cloud server; one-way hash function; embedded device; fuzzy logic; ECC; security and privacy.
  DOI: 10.1504/IJCNDS.2023.10049289
   
  
• A random forest algorithm under the ensemble approach for feature selection and classification  
  by Ankit Kharwar, Devendra Thakor 
  Abstract: Over the years, research analysts have proposed diverse intrusion detection systems' (IDS) tactics to manage the increasing number and complexity of computer threats. IDS takes all the data over the network and analyses the data using machine learning for finding the attacks. It is tough to find attacks on the network because it contains fewer records than standard data. It is significantly challenging to design an IDS for high accuracy. It also foregrounds different feature selection methods to select the best feature subset. We use the random forest feature importance for finding the best features. Single classifiers can mislead the find result, so we use random forest as classification with the help of best features. The proposed model is assessed on standard datasets like KDD'99, NSL-KDD, and UNSW-NB15. The experimental result shows that the proposed model outperforms the existing methods in terms of accuracy, detection rate, and false alarm rate.
  Keywords: intrusion detection; anomaly detection; machine learning; ensemble methods; random forest; feature selection; feature importance; classification; cybersecurity; network security.
  DOI: 10.1504/IJCNDS.2023.10049123
   
  
• Energy efficient congestion control in wireless sensor networks using meta-heuristic algorithms  
  by Abdul Ali, M. Vadivel 
  Abstract: A wireless sensor network (WSN) is an infrastructure-less wireless network that is used to monitor the physical or environmental conditions. In WSN, energy is the main constraint in congestion control that decreases the network's lifetime. This paper's main goal is to propose a novel clustering-based routing protocol to mitigate the congestion issue in the network and to maximise the lifespan of WSN. To control the congestion problem in WSN, an energy-efficient ultra scalable ensemble clustering is introduced in this paper. In addition, the flamingo search algorithm-based fuzzy inference system is applied for cluster head (CH) selection. Rat swarm optimisation is used to select the route between CH and BS. The experimental results demonstrated that the proposed methodology gives better results than the existing techniques and it enhances the energy efficiency of WSN. The residual energy of the proposed approach (5 J at 2,000 rounds) is greater than the existing methods.
  Keywords: wireless sensor network; WSN; ultra-scalable ensemble clustering; flamingo search algorithm; FSA; rat swarm optimisation; RSO; cluster head selection.
  DOI: 10.1504/IJCNDS.2023.10050125