Forthcoming Articles

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 (14 papers in press)

Regular Issues

  • Hybrid optimisation with multi-objective fitness for CH selection and effectual routing in WSN   Order a copy of this article
    by Asha Rawat, Harsh Namdev Bhor, Mukesh Kalla, Manish Subhash Gardi, Sudhir Ramrao Rangari, Suvarna Prabhuappa Bhatsangave 
    Abstract: The wireless sensor network (WSN) contains a huge number of cost-effective and small energy-constrained nodes for network communication. Moreover, the clustering is considered as a major part of WSNs routing. Hence, this paper develops the Cosine Lotus Effect Algorithm (CLEA) for Cluster Head (CH) selection, and the Fractional Cosine Lotus Effect Algorithm (FCLEA) for routing. Initially, the network simulation is carried out, and the CH is done using the proposed CLEA with the fitness components such as Link Lifetime (LLT), delay, inter, and cluster distance, trust factor, and energy, in which, the Radial Basis Function Network (RBFN) is employed for energy prediction. The proposed FCLEA is utilized for routing, where fitness factors such as energy, delay, distance, and trust factors are utilized. Moreover, the FCLEA-based routing obtained the better average residual energy, distance, and throughput of 1.719 J, 7.068m, and 431.8.
    Keywords: LEO; lotus effect optimisation; WSNs; wireless sensor networks; FC; fractional calculus; SCA; sine cosine algorithm; RBFN; radial basis function network.
    DOI: 10.1504/IJCNDS.2026.10072516
     
  • Comparative study of VNS and hybridised PSO for resource allocation in V2X communications   Order a copy of this article
    by Ibtissem Brahmi, Souhir Elleuch, Emna Hajlaoui, Monia Hamdi, Faouzi Zarai 
    Abstract: Exploration into cooperative intelligent traffic systems has yielded improvements in ground transportations efficiency, safety, and comfort. This work focuses on the resource allocation challenge within Vehicle-to-Everything communications. To address this problem, we suggested and compared the performance of two distinct meta-heuristic algorithms. The first technique, variable neighbourhood search (VNS), belongs to the category of solution-based meta-heuristics. The second technique hybridises particle swarm optimisation (PSO),a population-based meta-heuristic, with a proposed local search approach, trying to leverage the strengths and mitigate the weaknesses of both algorithms. The two proposed methods seek to optimise the systems overall throughput while ensuring minimal latency and reliability for both cellular user equipment (CUEs) and vehicle user equipment (VUEs). The algorithms proposed in this paper improve the system throughput and demonstrate its feasibility and utility for V2X communications.
    Keywords: resource allocation; meta-heuristic algorithms; VNS; variable neighbourhood search; PSO; particle swarm optimisation.
    DOI: 10.1504/IJCNDS.2026.10073223
     
  • Velocity-based user splitting and resource allocation for downlink fifth generation vehicle-to-everything communication   Order a copy of this article
    by Amit Kumar, Krishnan B. Iyengar, Raghavendra Pal, Abhilash S. Mandloi 
    Abstract: Fifth Generation (5G) Vehicle-to-Everything (V2X) communication requires efficient allocation of resource blocks (RBs) by a base station (BS) to the vehicles it is serving. To that end, this work presents a resource allocation algorithm that exploits the fact that vehicles in an environment typically have different velocities and velocity distributions. The algorithm uses a Velocity Based User Splitting approach that partitions users into discrete (low/high) velocity categories to utilise the difference in coherence intervals between the different vehicles. The channel conditions of low velocity users remain constant for longer than those of high velocity users, and the algorithm uses this difference to perform optimal RB allocation to maximise capacity. The performance of the algorithm is evaluated with respect to many parameters and factors including transmitted power, number of RBs, and channel conditions. The results are compared against random allocation and simple greedy allocation methods, and show a 5% improvement in low signal-to-noise ratio (SNR) conditions.
    Keywords: 5G; Cellular V2X; RA; resource allocation; downlink orthogonal frequency division multiple access; mobility.
    DOI: 10.1504/IJCNDS.2026.10073265
     
  • AI-based intrusion detection and adaptive access control for enhancing security in 6G network slicing   Order a copy of this article
    by R. Kanthavel , R. Dhaya  
    Abstract: As 6G networks become a reality, they will certainly usher in new security challenges that will need to be addressed, particularly due to network slicing in multi-tenant environments. In this work, we proposed an AI-based framework consisting of: (1) a deep learning-based intrusion detection system (AI-IDS), and (2) a reinforcement learning-based adaptive access control system (AACS) for slice-level security. The proposed system identifies threats (known and unknown), dynamically develops, and enforces access policies based on normal user behaviour. The framework was evaluated using various benchmark datasets in a simulated 6G slicing environment. Overall, the proposed AI framework achieved ~93% detection accuracy, low false positive rates (~4%), and reasonably rapid response times (~75 ms). Results showed the proposed framework provided higher adaptability and accuracy over traditional fixed security mechanisms.
    Keywords: 6G network slicing; AI-based intrusion detection; AACS; adaptive access control system; RL; reinforcement learning; DL; deep learning; cybersecurity in multi-tenant networks.
    DOI: 10.1504/IJCNDS.2026.10073797
     
  • A novel approach based on multi-level blockchain framework for securing clustered VANET’s routing from wormhole assault   Order a copy of this article
    by Shahjahan Ali, Parma Nand, Shailesh Tiwari 
    Abstract: Available research signifies that CB-MAC (Cluster-based Medium Access Control) protocols do good work for managing & controlling Vehicular Ad-hoc Network (VANET), but it wants to ensure improved privacy & security preserving authentication procedure. The VANET is wireless in nature, due to which it is much more sensitive to various security assaults i.e. wormhole, block hole, gray hole etc. The wormhole assault is very severe assault in VANET, which interrupt the routing mechanism of any routing protocol (i.e. AODV). In this research paper a privacy-preserving authentication protocol based on multi-level blockchain is proposed to stave off the wormhole assault from clustered VANET’s routing. Moreover, formation of vehicle registration centres, authentication centres and key creation procedures, are explained thoroughly. From results it is clear that proposed approach is more efficient in terms of storage and time as compare to existed approaches. The proposed approach based on CB-MAC & Blockchain is simulated with the help of SUMO 0.32.0 and NS-2.35 simulators.
    Keywords: VANET; vehicular ad-hoc network; security; wireless; wormhole; routing protocol; blockchain; MAC; medium access control; SUMO 0.32.0; NS-2.35; throughput.
    DOI: 10.1504/IJCNDS.2026.10075417
     
  • Intelligent early intrusion prediction and route migration framework for secure data transmission   Order a copy of this article
    by S. Kranthi, M. Kanchana, M. Suneetha 
    Abstract: A method of managing resources for networks that makes use of dynamic software-defined networking (SDN) that allows administrators to regulate resources in real-time. However, traditional models have met challenges, including high packet drop, energy consumption, and low performance. To overcome these challenges, a novel solution called hyena sequence intrusion detection (HSID) is proposed. This involves the creation of required nodes in the network, and the hyena function continually monitors node status. It effectively eliminates high-energy nodes, ensuring the sustainability of the routing process. The framework is implemented and rigorously tested in the Python platform, with a thorough evaluation of network efficiency parameters. In comparison, various metrics are considered, including energy consumption, throughput, packet drop, detection accuracy, and confidentiality rate. The results demonstrate higher performance satisfaction with the proposed model, emphasising its effectiveness in addressing the identified challenges and enhancing overall network security and efficiency.
    Keywords: network efficiency; throughput; detection accuracy; confidentiality rate; network security.
    DOI: 10.1504/IJCNDS.2026.10075420
     
  • Joint association management and contiguous channel bonding for coexisting high throughput users and legacy users   Order a copy of this article
    by Babul P. Tewari, Poulomi Mukherjee 
    Abstract: Channel bonding in high throughput (HT) Wi-Fi networks facilitates higher data rate but may restrict the number of non-overlapping channels. This also restricts spatial reuse. The assignment of channels becomes further complicated in coexisting network of HT and legacy g users. In this mixed contention scenario, a judicious bonded channel assignment strategy is proposed to facilitate a high data rate to the HT users and fair service coverage to legacy users. An integrated model based on integer linear programming has been formulated with an elegant greedy approach to address a suitable bonded channel assignment strategy. Extensive simulations were conducted for a comparative analysis with contemporary works, focusing on channel bonding and association management. The results demonstrate that prioritising either bonded channels exclusively or basic 20 MHz channels can result in suboptimal performance. The proposed approach successfully removes constraints on Access Points (APs), enabling them to serve users of different types.
    Keywords: 802.11ac WLAN; channel bonding; heterogeneous users; association management; interference management; legacy users; HT users.
    DOI: 10.1504/IJCNDS.2026.10075455
     
  • A novel multi-hop distributed clustering-based routing protocol for underwater wireless sensor networks   Order a copy of this article
    by V. Kiruthiga, V. Narmatha 
    Abstract: Underwater wireless sensor networks (UWSNs) face challenges due to limited battery resources that cannot be easily recharged or replaced. To address this, a novel multi-hop distributed clustering-based routing protocol (MH-DCRP) is proposed. This protocol operates in three phases: Location Broadcasting, Cluster Formation, and Data Forwarding. In the first phase, location data is gathered from neighbouring nodes to form clusters. The second phase optimises cluster formation based on distance and energy. After clusters are formed, cluster heads are selected to route data packets to monitoring stations via sonobuoys. In the final phase, data packets are transmitted to the sonobuoys through intra- and inter-cluster routing. The performance of MH-DCRP is evaluated through simulations in both dense and sparse environments, demonstrating superior results in terms of packet delivery ratio, network lifetime, residual energy, and reduced end-to-end delay compared to existing routing schemes. This makes MH-DCRP a more efficient solution for UWSNs.
    Keywords: UWSNs; underwater wireless sensor networks; multipath distributed routing; broadcasting phase; data transmission phase; group clustering mechanism; performance metrics.
    DOI: 10.1504/IJCNDS.2026.10075502
     
  • Cooperative spectrum sensing and routing related security vulnerabilities in cognitive radio networks: issues, solutions and future challenges   Order a copy of this article
    by Prathana Saikia, Sanjib K. Deka, Monisha Devi 
    Abstract: Cognitive Radio (CR) is an emerging solution to spectrum scarcity caused by rapid telecommunication growth. This technology operates in frequency bands unused by primary users (PUs), enhancing overall spectrum utilisation. In cognitive radio networks (CRNs), the unused spectrum bands, also called as spectrum holes, are assigned to secondary users (SUs) to attain effective communication amongst SUs. CRNs spectrum sensing, essential for identifying spectrum gaps, is prone to security risks. Moreover, routing in the network layer relies on accurate physical-layer sensing, which is compromised by these vulnerabilities. Ensuring secure spectrum sensing and routing is vital, as their compromise can affect overall CRN performance. Both traditional wireless network vulnerabilities and CRN-specific vulnerabilities can affect CRNs. In light of this, this paper provides a comprehensive survey of current vulnerability problems and related defences for cooperative spectrum sensing (CSS) and CR routing, as well as important unaddressed research challenges that require further investigation.
    Keywords: CRN; cognitive radio network; CSS; cooperative spectrum sensing; cognitive radio network routing; attacks; security issues.
    DOI: 10.1504/IJCNDS.2026.10076031
     
  • Network intrusion detection enhancement system through machine learning algorithms   Order a copy of this article
    by Nour Kadhim Hadi  
    Abstract: In today’s digitally driven landscape, network security is critical as decision-making relies heavily on reliable, high-quality data. This study utilises the network security laboratory-knowledge discovery data mining (NSL-KDD) dataset to improve traffic classification and data quality evaluation through state-of-the-art techniques. By employing advanced methods such as feature engineering, ensemble learning, and machine learning (ML) algorithms, the research enhances classification precision and accuracy. The primary goal is to develop an optimised classifier capable of detecting anomalous network traffic indicative of security intrusions. Using a preprocessed dataset, the study identifies significant features and optimises hyperparameters to refine performance. A decision tree classifier was evaluated using unseen data, integrating stages of data preparation, anomaly detection, training, and visualisation. The resulting model demonstrated high effectiveness for intrusion detection systems, achieving an accuracy of 95.36%, alongside 97% precision, a 95% F1-score, and 95% recall. This comprehensive approach ensures robust detection of potential network threats.
    Keywords: machine learning; intrusion detection; decision tree; NSL-KDD; feature importance; performance metrics.
    DOI: 10.1504/IJCNDS.2026.10076268
     
  • Lightweight blockchain-integrated IoT framework: a layered architecture for enhanced security and privacy   Order a copy of this article
    by Sumita Kumar, Vidhate Amarsinh, Puja Padiya 
    Abstract: The Internet of Things (IoT) enables devices embedded with sensors and communication capabilities to continuously sense and transmit environmental data, enhancing automation, efficiency, and quality of life. However, large-scale IoT deployments face significant challenges related to security, privacy, and cyber threats. This paper proposes a generic lightweight blockchain-based framework to strengthen IoT security and privacy. The framework distributes blockchain operations across multiple IoT layers and employs elliptic curve cryptography (ECC) for lightweight encryption and digital signatures, along with streamlined consensus mechanisms suitable for resource-constrained environments. A DAG based lightweight structure, fine-tuned load balancing, and memory pooling improve performance and resilience against attacks. Smart contracts deployed at the dew and cloudlet layers enable real-time operations and adaptability in dynamic IoT scenarios. The framework is validated against major cyber threats, including intrusion, man-in-the-middle, replay, and eavesdropping attacks. Performance evaluations based on throughput, latency, and scalability confirm its effectiveness for secure, scalable, and high-performance IoT deployments.
    Keywords: IoT; Internet of Things; blockchain; smart contract; cryptography; security; privacy.
    DOI: 10.1504/IJCNDS.2026.10076366
     
  • A comprehensive review of MIMO-NOMA systems for performance enhancement in future wireless network: current status and open research challenges   Order a copy of this article
    by G. Prasanna Kumar, K. Ramesh Chandra, Kothapalli Phani Varma, S.V. Kiranmayi Sridhara , Abdul Rahaman Shaik 
    Abstract: Non-orthogonal multiple access (NOMA) is a promising multiple access technique for 5G and beyond 5G mobile networks. Integration of NOMA with multiple input multiple output (MIMO) technology improves spectral efficiency and user services. This paper provides a comprehensive review of the MIMO-NOMA system in future wireless networks. Initially, the basic concepts of the MIMO-NOMA system are explained, then reviewed single and multi-user MIMO-NOMA systems along with their limitations. The other enabling technologies of the MIMO-NOMA system, such as backscatter communication, mobile edge computing, intelligent reflecting surfaces, integrated terrestrial satellite networks, and underwater communication, were also investigated. Finally, discussed future research directions of the proposed review, such as integration of better signal processing techniques, optimal resource management, analyse security and privacy in MIMO, etc.
    Keywords: NOMA; non-orthogonal multiple access; MIMO; multiple input multiple output; TDMA; time division multiple access; FDMA; frequency division multiple access; CDMA; code division multiple access; NAICS; network-assisted interference cancellation and suppression.
    DOI: 10.1504/IJCNDS.2026.10076427
     
  • Trust-aware buffer management for reliable communication in opportunistic IoT networks using indirect evidence and congestion prediction   Order a copy of this article
    by S. Gopinathan, S. Babu 
    Abstract: The Opportunistic Internet of Things Network (OppIoTNet) is unsteady and is prone to inactivity, resembling poor communication. Due to the vitality of this network, it is crucial to introduce an approach for effective buffer management by identifying the congestion points in the network. This paper presents a trustaware buffer management system for reliable communication in OppIoTNets. The system has three fundamental elements: evidence creation, blackhole detection and buffer management. It actively detects the message forwarding patterns to build trust evidence, which are categorised as cooperative or malicious with the Incremental 1D Transformer (I1D-XFormer). This real-time model uses attention mechanisms to learn temporal trends and filters out the untrustworthy nodes efficiently. Also, the system uses an extended Kalman filter with nonlinear operation (EKF-NLF) to anticipate the possible congestion points prior to contacts. The given system has an accuracy of 99.95 and F-measure, recall, and precision of 0.9996, 0.9995, and 0.9997, respectively.
    Keywords: indirect evidence; blackhole detection; buffer management; congestion prediction; I1D-XFormer; incremental 1D transformer; EKF-NLF; extended Kalman filter with nonlinear function.
    DOI: 10.1504/IJCNDS.2026.10076982
     
  • Research on cross layer robustness of coupled urban public utility networks   Order a copy of this article
    by Lv Jiao , Liu Yan , Bektur Azimov , Yang Haojie , Geng Peng , Zhao Xiaoyan  
    Abstract: This study investigates cascading failure risks in interdependent urban infrastructure by developing a multi-layer economic coupling model that integrates power, gas, water, metro, and heating systems. A comparative framework is established to examine robustness variations between large and small/medium cities based on coupling strength differentials. Vulnerability is assessed under three attack strategies random, betweenness-based, and weighted out-degree-based with cascading impacts quantified by the proposed dynamic propagation loss index (DPLI). Results demonstrate that weighted out-degree attacks induce 43.92% greater systemic degradation than betweenness-based strategies (p < 0.01). The local degree allocation (LDA) protection strategy improves network survivability by 14.32% over Resource Allocation (RA) under targeted attacks. An adaptive edge-enhancement strategy incorporating real-time network dynamics further enhances chained fault containment by 9.9% compared to static models. These findings provide theoretical foundations and practical guidelines for resilient urban infrastructure design under diverse attack scenarios.
    Keywords: cross layer robustness; complex networks; public utility networks; coupling; robustness; protection strategies.
    DOI: 10.1504/IJCNDS.2026.10076997