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International Journal of Communication Networks and Distributed Systems

International Journal of Communication Networks and Distributed Systems (IJCNDS)

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International Journal of Communication Networks and Distributed Systems (25 papers in press)

Regular Issues

  • A Hybrid of Encryption and Error Correction Method for Multiple-Input Multiple-Output Wireless Communication Systems   Order a copy of this article
    by Van Linh Dinh, Thi Phuong Thao Hoang, Van Yem Vu 
    Abstract: In this paper, we propose a security approach in the physical layer based on Turbo code and the changeable secret key to enhance the reliability and security of the multiple-input multiple-output (MIMO) wireless communication systems. The secret key created from complex impulse response (CIR) between authorised users is simultaneously used to manage the Turbo code’s interleaving and puncturing blocks. The proposed scheme is implemented in the MIMO systems via Rayleigh fading. The results from system simulations and security evaluations demonstrate that the proposed scheme provides greater efficiency for MIMO systems compared to that of the standard Turbo code. Moreover, it successfully provides good concealment and prevents attacks on digitally encrypted images. Therefore, this proposed method is ideal for use in actual MIMO systems. By using the proposed method, the system can jointly perform data security and error correction functions without altering the transceiver’s physical design.
    Keywords: session key; turbo code; interleaving block; puncturing block; image encryption; MIMO.
    DOI: 10.1504/IJCNDS.2024.10061300
  • A hybrid zone based routing protocol based on ZRP and DSR for emergency application   Order a copy of this article
    by SANJOY DEBNATH, Wasim Arif 
    Abstract: Mobile Ad hoc Networks (MANET) can be rethought for use in disaster relief operations due to their attractive features such as no-infrastructure, fast-deployment, and self-organizability. It has also been observed that improving scalability, mobility, bandwidth, and energy efficiency has always been a challenging aspect in Ad-hoc routing protocols like MANET. In this paper, we present a comprehensive survey of all the promising routing protocols in MANET, considering the key constraints such as energy-efficiency and throughput delivery in disaster relief operations. We propose HZDL: a hybrid routing protocol based mainly on ZRP and DSR with cluster hierarchy features from the LEACH-algorithm. The key controlling parameters include mobile node processing speed, background running applications, data storage capacity, and residual battery power. The results of a comprehensive simulation encompassing several performance measurement matrices reveal that the proposed algorithm provides significantly improved results toward the betterment of the node’s lifetime and achievable throughput.
    Keywords: MANET; Hybrid Routing protocol; Energy efficiency; Disaster management.
    DOI: 10.1504/IJCNDS.2025.10061546
  • Multimodal Sentiment Analysis Based on Improved Correlation Representation Network   Order a copy of this article
    by Yilihamu Yaermaimaiti, Tianxing Yan, Guohang ZHUANG, Tusongjiang Kari 
    Abstract: Multimodal sentiment analysis (MSA) refers to extracting emotional information from language, acoustic, and visual sequences. Due to the gap between multimodal features, previous work did not take full advantage of multimodal correlations, resulting in limited improvement in fusion strategies. To this end, we propose a multimodal correlation representation network (MCRN) to extract multimodal features by a dual output Transformer. The first output of the Transformer is used by depth canonical correlation analysis (DCCA) to model the correlation between multimodal data. Then the secondary output of the Transformer uses the attention mechanism to fuse multi-modality, and the final output of the model is emotional intensity. In addition, in the second output stage, we designed a single-mode output loss to balance the differences between subtasks. Extensive experiments suggest that our model reaches state-of-the-start performance in most the of existing methods on multimodal opinion-level sentiment intensity (MOSI) dataset and multimodal opinion sentiment and emotion intensity (MOSEI) dataset.
    Keywords: emotion recognition; multimodal learning; multimodal representations; attention fusion.
    DOI: 10.1504/IJCNDS.2024.10061627
  • Clustering Based RSSI and AOA combination for Localization in Wireless Sensor Networks   Order a copy of this article
    by Dipak Wajgi 
    Abstract: In this paper, we propose the clustering based localisation algorithm which is energy efficient and has less computational complexity. The sensor nodes are grouped in a cluster which is based on the received signal strength at the respective anchor nodes which are acting as cluster heads. The distance of the sensor node from their cluster head is calculated. The distance information along with the angle of arrival (AoA) information is combined to estimate the location of the cluster members creating the local map. This combination of RSSI and AoA makes the clustering algorithm more efficient to achieve better accuracy in location estimation with less computational complexity. The distance information is used to calculate the energy dissipation of the sensor nodes. The energy dissipation is reduced by adopting the density control strategy during cluster formation and reducing the communication among the sensor and hence increasing the lifetime of the network. The proposed algorithm performs well as compared to the adaptive clustering and improved K-means algorithm on parameters like average energy consumption and network lifetime.
    Keywords: energy efficiency; localisation; clustering; received signal strength indicator; RSSI; angle of arrival; AoA; wireless sensor network.
    DOI: 10.1504/IJCNDS.2024.10061884
  • Attractiveness of firms with chatbot as job interviewers. Does the interviewer-type matter to be the first contact with candidates?   Order a copy of this article
    by Helena Repova, Jan Zouhar, Pavel Kral 
    Abstract: Chatbot-mediated job interviews, raise questions about applicant perception of justice, which in turn affects organisational attractiveness. This study uses experimental data to assess applicants’ perceptions of procedural, interactional, and interpersonal justice, and their relationship to organisational attractiveness in three scenarios: chatbot, human and unspecified interviewer. The research aims to differentiate the fairness perception effect between robots and human interviewers using an identical written job interview preselection procedure. The results show that the perception of justice significantly impacts organisational attractiveness. Organisations that comply with rules of procedural and interactional justice can implement chatbots without compromising organisational attractiveness. Although the results are mixed, we do not find evidence to suggest that revealing information about chatbots endangers the organisation’s attractiveness relative to that of the human recruiter. Younger candidates with previous experience in chatbot interviews even preferred a chatbot to a human recruiter.
    Keywords: chatbot; recruitment; organisational attractiveness; perception of fairness; age; chatbot experience; the nature of chatbot.
    DOI: 10.1504/IJCNDS.2024.10061922
  • An Efficient Attack Detection Approach for Software Defined Internet of Things using Jaya Optimization based Feature Selection Technique   Order a copy of this article
    by Pinkey Chauhan, Mithilesh Atulkar 
    Abstract: The Internet of Things and Software Defined Networks are two recent subjects that are being studied in both academia and the IT sector. In the SD-IoT , they have drawn several attacks as a result of their novelty. To counter such attacks, this paper presents a study on feature selection using Jaya Optimization for making lightweight IDS for the data plane of SD-IoT. Using Jaya algorithm, a set of 6 features is selected from the SD-IoT dataset which when used with LGBM gave the better performance than when LGBM is trained with all the features. For performance evaluation, some well-known metrics have been used which deal with binary as well multi-class classification, namely recall, accuracy, FAR, F1, precision, CKC, and prediction time. This trained model is deployed for attack detection in the OpenFlow enabled devices of data plane of SD-IoT where it can detect the attacks in a distributed manner.
    Keywords: OpenFlow; Ryu Controller; Software Defined Internet of Things; Jaya Optimization; Machine Learning; Distributed Denial of Service Attack.
    DOI: 10.1504/IJCNDS.2025.10062282
  • Network-aware cache provisioning and request routing in Heterogeneous Cellular Networks   Order a copy of this article
    by Marisangila Alves, Guilherme Piêgas Koslovski 
    Abstract: In past years there has been an increase in the number of mobile devices and data traffic triggered by the popularisation of multimedia applications. In parallel, new applications and services with restricted requirements of delay and throughput have been developed. The 5G architecture is an enabler for such evolution, however, some fundamental management tasks deserve deep research, specially the cache placement. There are still challenges concerning the design of caching policies, such as limited storage space, content popularity, user requirements, and network congestion. In this context, we propose, implement, and evaluate a model of network-aware cooperative cache policy to decrease the latency experienced by heterogeneous cellular network (HCN) end-users. The model was formulated through integer linear programming (ILP) and performs both cache placement and request routing tasks. To composing a baseline for comparisons, we improved state-of-the-art policies by adding network-based attributes. Later, numerical simulations showed that the policy successfully chose paths decreasing the network latency and overcoming the counterparts.
    Keywords: caching; heterogeneous cellular networks; placement; routing. .
    DOI: 10.1504/IJCNDS.2025.10062283
  • Relatively Strong Barrier Coverage for β-Breadth Intruder in Hybrid Visual IoT   Order a copy of this article
    by Gong Chen, Yonghua Xiong, Jinhua She, Anjun Yu 
    Abstract: In the pursuit of reducing the costs associated with barrier coverage construction while maintaining surveillance quality, we propose a robust barrier coverage strategy for visual applications within the Internet of Things (IoT), considering the varying breadth of intruder paths. When coverage gaps arise or mission requirements evolve, it becomes imperative to reconfigure the network topology to sustain coverage through the rescheduling of sensor nodes. To minimize the rescheduling costs in hybrid networks, we develop a two-phase hybrid node rescheduling algorithm to achieve strong barrier coverage. The initial phase of our algorithm enables the static sensor nodes to optimize their operational directions, effectively reducing barrier gaps. In the second phase, we strategically reposition mobile sensor nodes to achieve a relatively strong barrier with the least number of nodes and the shortest total movement distance. Simulation results demonstrate that our algorithm outperforms existing methods in terms of efficiency and effectiveness.
    Keywords: IoT; Hybrid Network; Coverage Holes; Nodes Rescheduling.
    DOI: 10.1504/IJCNDS.2025.10062558
  • The intelligent object detection framework for detecting fish from underwater images   Order a copy of this article
    by Kalyani Peddina, Ajay Kumar Mandava 
    Abstract: Marine applications heavily rely on underwater object detection, yet challenges like complex backgrounds and image quality issues impede deep learning-based detectors. Monitoring feed pellet utilisation in aquaculture is vital for efficient resource management. This study introduces a novel framework, DYNFS, merging underwater object detection and image reconstruction using YOLO-V5. Initially, we curate an underwater image dataset, refining it to remove noise, then employ DYNFS for classification. Our approach achieves a 98.93% accuracy rate in identifying submerged feed pellets, crucial for aquaculture efficiency. However, locating pellets remains challenging due to poor image quality and small object sizes. The enhanced YOLO-V5 networks show promise in real-world aquaculture scenarios. This framework enhances underwater object detection, offering potential benefits for marine applications and aquaculture management.
    Keywords: Detection; Image data; Convolutional neural network Confusion matrix; YOLO network; recurrent neural network.
    DOI: 10.1504/IJCNDS.2025.10062690
  • Context-aware enhancement of buffer utilization in MQTT-based IoT communication   Order a copy of this article
    by P.S. Akshatha, S.M. Dilip Kumar 
    Abstract: This paper explores Internet of Things (IoT) communication and the crucial role of buffer utilization in enhancing the Message Queuing telemetry Transport (MQTT) protocol. Unlike traditional approaches that highlight the benefits of buffering, this study takes a distinctive perspective by addressing the limitations of buffer usage in IoT communication. The research introduces a context-aware strategy to employ buffers judiciously, considering specific data requirements and network connectivity scenarios. Experimental setups involving Node-RED, Wireshark, and prominent MQTT brokers (HiveMQ, EMQx, and Mosquitto) facilitate comprehensive performance analysis. Parameters such as connection setup time, subscription time, mean delay, mean jitter, and bandwidth consumption are evaluated. The findings consistently demonstrate performance degradation after broker reconnection, with more prolonged network failures leading to more significant degradation. The study emphasizes the importance of using buffers wisely, especially for prioritizing critical messages, to ensure reliability and enhance overall MQTT network performance.
    Keywords: IoT; Internet of Things; MQTT; message queuing telemetry transport; Node-RED; MQTT broker; buffer; QoS levels.
    DOI: 10.1504/IJCNDS.2025.10062897
  • Low complexity IAOR signal detection for uplink GSM - massive MIMO systems   Order a copy of this article
    by Seema Hanchate, Shikha Nema 
    Abstract: Massive multiple input multiple output (Mamimo) is a high-speed wireless communication that uses more antennas at the receiver base station. When more antennas are utilised, the channel matrix gets larger. As a result of the inversion channel matrix, the complexity of linear signal detection grows. Mamimo consumes more power due to radio-frequency (RF) chains. The channel magnitude and correlation are used to implement the antenna selection process. The antenna selection method reduces the number of RF chains and improves BER performance. To avoid expensive matrix inversion, the IAOR (Improved accelerated over relaxation) signal detection algorithm is presented. For various antenna designs, the bit error rate is calculated. According to the result of MATLAB simulation, the performance of the standard minimum mean square error (MMSE) detection and the proposed method are approximately equal. The proposed IAOR signal detection method improves the overall performance and energy efficiency and also reduces computational complexity.
    Keywords: massive MIMO; MMSE signal detection; accelerated over-relaxation; channel correlation; computational complexity; uplink transmission.
    DOI: 10.1504/IJCNDS.2024.10063090
  • Addressing escalating threats: a secret image sharing scheme with adjustable threshold resilience against external adversaries and colluding participants   Order a copy of this article
    by Krishnaraj Bhat, Devesh Jinwala, Yamuna Prasad, Mukesh A. Zaveri 
    Abstract: We propose a novel Threshold Changeable Secret Image Sharing (TCSIS) scheme based on univariate and asymmetric bivariate polynomials for securing greyscale and colour secret images in the semi-honest model. The proposed scheme supports increasing the threshold number of shares needed to reveal the secret image using the share update mechanism. Unlike the existing TCSIS schemes, the proposed scheme can prevent the revealing of a secret image before the end of its lifespan. This revelation is possible due to the increasing capabilities of an external adversary and the increasing number of colluding participants. Furthermore, in contrast to some existing TCSIS schemes, each share generated using the proposed scheme does not leak visual information about the secret image. We prove the properties of the proposed scheme using theoretical analysis. We also provide experimental results supporting the implications of theoretical analysis corresponding to the execution time and the randomness of shares.
    Keywords: image security; secret image; TCSIS; threshold changeable secret image sharing; external adversary; colluding participants; information leakage; univariate polynomial; asymmetric bivariate polynomial.
    DOI: 10.1504/IJCNDS.2025.10063445
  • An innovative approach based on clustering and digital signature to prevent black hole attack from vehicular ad-hoc network   Order a copy of this article
    by Shahjahan Ali, Parma Nand, Shailesh Tiwari 
    Abstract: Due to broad development in wireless technology, the vehicular ad-hoc networks (VANETs) came into existence which can reduce the road accident, traffic jam and can increase the road safety. Because of dynamic topology, wireless medium, decentralised infrastructure, VANET is much more suspected towards various security attacks such as black hole in which control or data packets can be dropped by misbehaving vehicle, by which the safe path/link becomes compromised. In this research paper an innovative approach based on clustering and digital signature (CDS) is proposed to prevent black hole attack on reactive routing, i.e., ad-hoc on demand distance vector (AODV) and dynamic source routing (DSR) of VANET. The proposed approach is implemented and evaluated in SUMO-0.32.0 and NS-3.24.1 simulators. The novelty of this research work is that till now there is no approach (based on CDS) existed to prevent the black hole assault (BHA) from reactive routing in VANET.
    Keywords: VANET; vehicular ad-hoc network; routing; AODV; ad-hoc on demand distance vector; DSR; dynamic source routing; black hole; SUMO-0.32.0; NS-3.24.1; digital signature.
    DOI: 10.1504/IJCNDS.2025.10063476
  • Blocking performance comparison under hard handoff constraint using optimal guard channel in GSM standards   Order a copy of this article
    by Promod Kumar Sahu, Hemanta Kumar Pati, Sateesh Kumar Pradhan 
    Abstract: In the current mobile networks voice service in 2G coexists with voice over long term evolution (VoLTE) in 4G and voice over new radio (VoNR) in 5G. In wireless networks usually handoff call (HC)s receive higher priority than new call (NC)s. So, some radio resources may be reserved in each cell to handle HCs. If more channels are reserved for HCs, then the handoff call dropping probability (HCDP) will be decreased and at that time the new call blocking probability (NCBP) will be increased. Instead, if channels will be reserved for HCs by considering the target HCDP, then HCDP will be below the target and will incur minimum NCBP. In this paper, we proposed an optimal channel reservation (OCR) policy to reserve guard channels according to the given target HCDP. Further, we have made a comparison study of optimal blocking performances applying this OCR policy on different GSM standards.
    Keywords: global system for mobile communication; handoff call dropping; mobile cellular network; new call blocking; optimal channel.
    DOI: 10.1504/IJCNDS.2025.10063481
  • Self energised UAV-assisted wireless communication using NOMA over Nakagami-m fading channel   Order a copy of this article
    by G. Sivakannu, R.S. Anju, J. Anandpushparaj, P. Muthuchidambaranathan 
    Abstract: In a cooperative relay network, replacing the relay with an unmanned aerial vehicle (UAV) offers several advantages. In this work, a UAV-assisted communication network based on non orthogonal multiple access (NOMA) system that incorporates simultaneous wireless information and power transfer (SWIPT) technique is investigated. The performance of the proposed system is analysed by deriving the closed form expression for performance metrics like outage probability (OP), throughput and bit error rate (BER) under imperfect successive interference cancellation (SIC) with selection combining (SC) diversity technique at the receiver. In addition to that, a Multiple UAV based system model is considered with relay selection algorithms like max-min selection and the variation in the outage probability performance is also studied. The analytical expressions are also validated using Monte Carlo simulation. The results show that the proposed system has better performance even under imperfect SIC and reduces the wastage of resources.
    Keywords: NOMA; non orthogonal multiple access; cooperative relaying system; SWIPT; simultaneous wireless information and power transfer; time splitting; SIC; successive interference cancellation; selection combining; outage probability; BER; bit error rate.
    DOI: 10.1504/IJCNDS.2025.10063634
  • Secure emergency MAC protocol for wireless body area networks   Order a copy of this article
    by Bhavana Alte, Amarsinh Vidhate 
    Abstract: Wireless body area networks (WBANs) connect many small body sensors for Internet of Things healthcare applications. In vivo and on-body sensor nodes allow WBANs to detect and gather biometric data on bodily changes. Wireless transmission sends observed data. This information can help patients in critical condition or who cannot reach to hospitals due to physical handicap, traffic, and receive immediate care. Another crucial requirement for WBANs is capacity to provide quality of service (QoS) for different traffic data. Security and privacy are needed for healthcare professionals to use and store patient records securely. It is crucial for WBANs to address privacy and security concerns. The proposed method introduces the emergency MAC (E-MAC) super-frame architecture, enabling QoS. E-MAC accelerates and reliably transmits emergency data via an emergency information management system. To address security concerns, the approach is protected using elliptic curve cryptography. Results show that E-MAC outperforms IEEE 802.15.6.
    Keywords: WBAN; wireless body area network; ECC; elliptic curve cryptography; MAC protocols; emergency traffic; duty-cycle MAC.
    DOI: 10.1504/IJCNDS.2025.10064449
  • Blockchain-based privacy-preserving technology to secure shared data in vehicular communication   Order a copy of this article
    by Omessaad Slama, Walid Dhifallah, Salah Zidi, Jaime Lloret , Bechir Alaya, Mounira Tarhouni 
    Abstract: In vehicular ad-hoc networks (VANETs), securely exchanging sensitive data like misbehaviour detection models faces significant security and privacy hurdles. Our solution, machine learning model blockchain-based privacy-preserving (MBPP), combines Blockchain technology and advanced cryptography to tackle this. MBPP ensures data confidentiality and integrity while improving detection model reliability. It involves securely storing ML models on the blockchain using cryptographic hash functions. Our study meticulously evaluates transactional time and computational costs, vital for smooth blockchain transactions. This research not only presents a conceptual framework for blockchain use in VANETs but also offers insights into managing transactions via smart contracts, addressing VANETs' security and privacy challenges effectively.
    Keywords: blockchain; smart contract; computational costs; artificial intelligence algorithms; VANETs; vehicular ad-hoc networks; data sharing; privacy preservation; cryptography hash function.
    DOI: 10.1504/IJCNDS.2025.10064597
  • Harnessing machine learning for dynamic defence in the battle against 5G cybersecurity threats   Order a copy of this article
    by V. Aanandaram , P. Deepalakshmi 
    Abstract: The evolution mobile network highlighted by means of 5G networks, has caused advanced cyber threats necessitating modern security features. The adaptive multi-layer threat defence machine addresses these threats with machine getting to know (ML), presenting robust resilience. It surpasses traditional strategies via deploying ML algorithms throughout more than one network layers. Network behaviour profiling (NBP) establishes baselines for customers/gadgets, detecting deviations as early malicious signs. Intent prediction (IP) visually anticipates person purpose, while anomaly detection (AD) identifies subtle anomalies. The systems centre, decentralised associative learning (federated learning), keeps confidentiality and model integrity. Continuous Threat Intelligence Integration (TII) permits proactive responses to rising threats. This integrated approach provides better protection for 5G networks, creating an adaptive defence via profiling, prediction and anomaly detection. The adaptive multi-layer threat defence system, combining flexibility, privacy, and scalability, ushers in a generation in which ML supports technological development.
    Keywords: AML-TDS; adaptive multi-layered threat defence system; threat intelligence; anomaly detection; privacy preservation; 5G network security; NBP; network behaviour profiling; cyber threats.
    DOI: 10.1504/IJCNDS.2025.10065033
  • A linear regression based prediction model for load distribution and quality of service improvement with different resource utilisation in cloud environment   Order a copy of this article
    by Gopa Mandal, Santanu Dam, Kousik Dasgupta, Paramartha Dutta 
    Abstract: Cloud computing is a delivery-based consumption model rely over the internet Uses of cloud enabled devices increasing rapidly So, to maintain quality of service (QoS), throughput of the entire system with service level agreements(SLA) is major concern between the service providers and the end users Alternative techniques for virtual machine (VM) consolidation and proper workload allocation may beneficial This study proposes a linear regression-based prediction model for load distribution and QoS improvement The model aims to enhance system throughput and QoS by predicting resource utilization levels using historical consumption data Experiments conducted using CloudSim and CloudAnalyst platforms demonstrate positive results, outperforming existing methodologies The study also evaluates Service Level Agreement Violation (SLAV) and delays to assess the QoS provided by the CSP Overall, this research contributes to the enhancement of QoS in cloud and cloud enabled systems like IoT, CoT, addresses the challenges of optimize resource utilization while ensuring QoS.
    Keywords: CoT; cloud of thing; IoT; Internet of Things; VM consolidation; cloud computing; QoS; quality of service; CloudSim; CloudAnalyst; linear regression.
    DOI: 10.1504/IJCNDS.2025.10065020
  • Ultra-scalable ensemble clustering with simulated annealing based coot bird routing protocol for WSN   Order a copy of this article
    by Robin Abraham, M. Vadivel 
    Abstract: Energy proficiency is the main restriction in wireless sensor network (WSN) that affects the network life cycle. Therefore, opposition learning-based flamingo search algorithm is utilised to select the cluster head (CH) of ultra-scalable ensemble clustering. The distance to neighbours, residual energy, and distance to BS are used to optimise the CH selection. The main goal of this paper is to propose a novel energy efficient cluster-based routing protocol to improve the WSN lifespan and minimise power consumption. The experimental results are analysed for the proposed and existing algorithms in terms of a live nodes, end-to-end delay, throughput, rounds for half nodes die, last node die, and first node die, and packet delivery (PDR). The experimental results show that the proposed approach can perform better than existing protocol. The obtained PDR is 85% in the first scenario, which is greater than what exists already.
    Keywords: wireless sensor network; WSN; ultra-scalable ensemble clustering; simulated annealing; SA; based coot bird meta-heuristic optimisation; and opposition based learning; OBL based flamingo search algorithm; FSA.
    DOI: 10.1504/IJCNDS.2024.10059914
  • Metaheuristic based segment routing for hybrid software-defined network under heterogeneous environment   Order a copy of this article
    by Deepak Bishla, Brijesh Kumar 
    Abstract: Software-defined networking (SDN) is a network framework that decouples the network's control from its data-forwarding operations, concentrates on intelligence, and isolates the network's fundamental architecture from various applications and services. With the help of a hybrid SDN framework, legacy and SDN protocols can coexist and function in the same setting. However, the hybrid structure makes managing traffic in the hybrid SDN difficult. Segment routing produces control overheads due to the incorporation of extra packet headers. Still, the network congestion, higher packet loss rate and energy usage make routing a challenging task. Hence, a novel segment routing using the proposed Gannet artificial humming optimisation (GAho) algorithm. The proposed GAho utilises the multi-objective fitness function based on link quality and flow features to make congestion-free routing. The performance analysis of GAho based segment routing using the delay, throughput, jitter, and packet drop acquired the values of 4.24 ms, 77.61%, 0.15 sec, and 1.82%, respectively.
    Keywords: segment routing; hybrid software-defined networks; traffic management; hybrid optimisation; heterogeneous; flow attributes; link quality.
    DOI: 10.1504/IJCNDS.2024.10060534
  • Robustness of complex networks considering load and cascading failure under edge-removal attack   Order a copy of this article
    by Peng Geng, Zixin Ye, Huizhen Hao, Annan Yang, Yan Liu 
    Abstract: This article challenges the conventional wisdom that edges with larger degrees are more important in complex networks. Through simulation analysis on the BA scale-free and WS small-world networks, we investigate edge-removal attack strategies, taking into account edge load and cascading failure. Specific attacks include high load edge-removal attacks (HLEA) and low load edge-removal attacks (LLEA). Our results demonstrate that the importance of edges is closely tied to the load parameter δ. When 0 < δ < 1, attacking edges with smaller degrees leads to greater cascading failures, rendering low-degree edges more important under these conditions. Conversely, when δ > 1, high-degree edges are more critical due to their ability to cause greater cascading failure upon removal. When δ = 1, cascading failure becomes independent of the degree of the removed edge. These findings underscore the need for considering edge loads and specific network conditions when assessing the importance of edges in complex networks.
    Keywords: complex networks; edge load; cascading failure; edge-removal attack; high load edge-removal attacks; HLEA; low load edge-removal attacks; LLEA.
    DOI: 10.1504/IJCNDS.2024.10058708
  • A low complexity enhanced squirrel search algorithm for reduction of peak to average power ratio in OFDM systems   Order a copy of this article
    by R. Anil Kumar 
    Abstract: Future wireless networks: smarter, faster, and more efficient; user equipment gains features for diverse applications and demands. OFDM is widely used in Wi-Fi, WiMAX, and LTE for spectrum efficiency but can degrade power amplifier performance due to high peak amplitudes, affecting BER. PTS reduces OFDM PAPR but adds computational complexity due to the search for optimal phase factors. In this article, we combined PTS with the proposed novel enhanced squirrel search algorithm (ESSA) to obtain an optimum random phase sequence matrix (RPSM). This scheme reduces the PAPR, reduces the computational complexity (CC) of the OFDM system, and provides a faster convergence rate. This paper presents the closed-form mathematical expressions of PAPR, computational complexity, and input and output backoffs of the power amplifier. Performance validation includes PAPR and BER for various subcarriers, subblock sizes, and trade-off factors in the system. MATLAB simulated results compared proposed PAPR reduction scheme with various existing schemes for OFDM systems.
    Keywords: bit error rate; BER; enhanced squirrel search algorithm; ESSA; orthogonal frequency division multiplexing; OFDM; PAPR; partial transmit sequence; PTS; random phase sequence matrix; RPSM.
    DOI: 10.1504/IJCNDS.2024.10059468
  • Energy efficient and lifetime aware clustering and routing using improved rabbit optimisation algorithm in WSN   Order a copy of this article
    by Roma Saxena, Akhtar Husain 
    Abstract: One of the most difficult tasks when building a routing model for a wireless sensor network (WSN) is energy efficiency. However, the sensor node only uses a small amount of energy when sending data to the sink node. The suggested method makes use of an efficient technique to increase energy efficiency and extend the network life cycle. To select the optimal cluster head, the improved rabbit optimisation algorithm (IROA) is initially used. Levy flight updation is used in this instance to enhance the conventional ROA method. Next, the secondary cluster head is chosen to improve the network's energy efficiency based on weight of sensor node. Finally, the improved rabbit optimisation algorithm (IROA) chooses the best route. In terms of energy efficiency, network lifetime, delivery ratio, and throughput the suggested scheme's performance is evaluated. The average performance metrics obtained by the suggested method are 79% of delivery ratio, 56.8 kbps of throughput, 43.6J of energy, and 6.4 hours of network life.
    Keywords: wireless sensor networks; WSNs; rabbit optimisation algorithm; ROA; levy flight; delivery ratio; throughput; energy consumption and network life time.
    DOI: 10.1504/IJCNDS.2024.10060818
  • Elastic demand network slicing based on fuzzy multi-criteria   Order a copy of this article
    by Matheus M. Silveira, Maria C.M.M. Ferreira, Rafael L. Gomes 
    Abstract: The internet serves as the primary means of communication and supports numerous essential services. Nevertheless, it faces certain limitations that directly impact the quality of service (QoS) and quality of experience (QoE) for users. To address this, internet service providers (ISPs) are implementing innovative technologies and network management strategies, including network slicing. This approach involves dividing network resources among clients and services, making the allocation algorithm for these network slices critical, especially in scenarios where resource demands fluctuate throughout the day. In this scenario, this article focuses on introducing the fuzzy multi-criteria (FUMU) algorithm, which aims to establish network slicing using various network metrics while being adjustable to the network administrator's specifications. The outcomes of the conducted experiments indicate that FUMU outperforms existing methods by reaching a superior balance between utilising provider resources and meeting customers' QoS requirements.
    Keywords: edge network; access network; network management; multi-criteria.
    DOI: 10.1504/IJCNDS.2024.10061048