International Journal of Autonomous and Adaptive Communications Systems (9 papers in press)

Regular Issues

• ONCP: An Optimised Node Clustering Protocol using PSO for Enhanced Multimedia IoT Network Performance  
  by Prakruti Kulkarni, S.S. Lokhande 
  Abstract: High-performance and reliable multimedia communication is critical for modern IoT applications such as smart healthcare, wearables, homes, and industrial automation. Cross-layer protocol designs have emerged to improve network performance by enabling coordination across protocol layers. The IoMT protocol applies cross-layer optimisation to reduce energy usage and latency but faces scalability and real-time issues in dense networks due to increased computational complexity. To address this, enhancements like directional antennas and the Dual Sensing MAC (DSDMAC) protocol were introduced at the MAC layer to improve channel access and reduce hidden terminal issues, forming the basis for the MCROSS protocol. Building on this, the Optimised Node Clustering Protocol introduces a modified PSO-based clustering method for intelligent selection of cluster heads and relay nodes. It uses a fitness function that considers multiple parameters (PFR, RER, CR), resulting in improved energy efficiency, load balancing, and reliability. Comparative analysis confirms ONCP's superior performance across diverse metrics.
  Keywords: IoT; cross-layer protocol; IoMT; MCROSS; ONCP; DSDMAC; Particle Swarm Optimisation; cluster head selection; adaptive clustering.
  DOI: 10.1504/IJAACS.2026.10073918
   
  
• Automatic Monitoring Approach for Continuous Usability Evaluation  
  by Mouna Jarraya, Faouzi Moussa, Meriem Riahi 
  Abstract: Resilience engineering aims to embed resilience into socio-technical systems by addressing unforeseen situations and ensuring that systems can operate effectively under both expected and unexpected conditions. To this end, we propose an automatic monitoring approach for continuous usability evaluation, designed to detect and alert users to potential risks arising from usersystem interactions. In our study, a proxy is integrated into an academic simulator of an onboard automated car system to monitor user actions through the generation of a Petri net-based activity trace. Usability evaluation is then carried out by comparing this trace with a real-time deduced task model in order to identify deviations from expected interaction patterns. Furthermore, machine learning techniques are employed to analyse the current situational context and to determine which tasks are permissible and which should be restricted. The overarching objective is to enhance system resilience by proactively monitoring user deviations and anticipating unexpected situations.
  Keywords: Usability evaluation; Human-Computer interaction; Task modelling; Monitoring; Petri net.
  DOI: 10.1504/IJAACS.2026.10074890
   
  
• New Relaxed Conditions of Continuous Delayed Takagi-Sugeno Positive Systems Controlled by State Feedback and Memory State Feedback by LP Approach: Application to Buck Converter T-S Model  
  by Rkia Oubah, Ouahiba Benmessaouda, Layla Wakrim 
  Abstract: This paper investigates the new relaxed stability conditions in open loop and closed loop of time-varying delay Takagi-Sugeno models while maintaining positivity within closed loop. New delay-dependent conditions of stabilization in terms of LP approach will be derived by using a Lyapunov-Krasovskii Functional (LKF). The proposed stabilization conditions are less restrictive than some major published stabilization conditions. Memoryless state feedback control is also employed in cases when the system in open loop is not positive (for example an electrical system where either a positive or negative input current is possible), that in feedback is necessary to make stable and positive. The benefits of the suggested stabilization conditions will be demonstrated with a numerical and practical (Buck Converter) examples.
  Keywords: LP approach; Lyapunov-Krasovskii Functional; Fuzzy Takagi-Sugeno system; Time-varying delay; Positive systems; State feedback; Memory state feedback; Buck Converter.
  DOI: 10.1504/IJAACS.2026.10074989
   
  
• A QR Code Secret Sharing Scheme Based on Extended Hamming Code  
  by Xuehua Cao, Xinwei Zhong, Genlin Ji 
  Abstract: Secret sharing, as a crucial method for privacy protection, has seen rapid development in fields such as cloud computing and the Internet of Things in recent years. As a very popular information cover at present, QR code is used far more frequently than traditional images, so the application of secret sharing in QR code has highly promising. However, because the QR code is often presented in paper form, it is easy to be stained or damaged; At the same time, stego-QR codes may be tampered with by attackers during transmission. These issues will inevitably lead to bit errors in stego-QR code, and the existing research schemes are unable to recover the secret losslessly. To address this, this paper proposes a QR code secret sharing scheme based on Extended Hamming Code. This scheme not only ensures high embedding capacity but also implements error correc tion capability of stego-QR codes, which can accurately detect and correct bit errors in the stego-QR code, and then recover the secret. Both theoretical analysis and experimental results demonstrate the effectiveness and practicality of this scheme.
  Keywords: secret sharing; QR code; bit errors; Extended Hamming Code; error correction.
  DOI: 10.1504/IJAACS.2026.10075089
   
  
• A robust generative coverless co-steganography method of text and image  
  by Yuxi Deng, Yun Tan, Le Mao, Xuyu Xiang 
  Abstract: Most existing coverless image steganography methods based on image generation suffer from insufficient hiding capacity. To address this, a generative coverless co-steganography method of text and images is proposed. Secret text is first converted into noise vectors using convolutional error-correcting codes, then a container image is generated using a self-attention generative adversarial network (SAGAN). The secret image is converted into a binary sequence through pixel encoding, and a style image containing the secret information is generated by an encoder. These images are then input into the generator to produce two sets of generative stego images for transmission. The secret text is recovered using a gradient descent method based on the simulated annealing algorithm, while the secret image is recovered through the decoder. The proposed method is evaluated on CelebA and Fashion MNIST datasets. Compared to existing methods, the proposed method significantly improves capacity and efficiency, increasing hiding capacity by 1.6 times.
  Keywords: coverless steganography; co-steganography of text and image; generative adversarial network; style transfer.
  DOI: 10.1504/IJAACS.2025.10071727
   
  
• An efficient natural language watermarking method via robust-word substitution  
  by Lingyun Xiang, Chenling Zhang, Minghao Huang, Jinghan Zhou 
  Abstract: Current modification-based natural language watermarking methods often face limitations in extraction efficiency and resilience against text editing attacks. To tackle these issues, this paper proposes a Robust Word Substitution Watermarking (RWSW) method, which enhances robustness while preserving the original text's fluency and quality. RWSW embeds watermarks at the sentence level by substituting robust words, drawing on complex sentence simplification insights. A robust word recognizer, trained via an encoder-decoder framework, identifies words unchanged in normal editing. For optimal substitutions, a BiLSTM network and Transformer predict suitable replacements, ensuring natural integration. Watermark info is redundantly embedded by replacing multiple sentence-level robust words with the same bit, boosting resistance to perturbations. Extraction decodes values and uses majority voting for high-accuracy recovery. Experiments show RWSW generates high-quality watermarked texts, with superior robustness over existing methods and high extraction accuracy under common editing attacks.
  Keywords: natural language watermarking; robust words; word prediction model; word substitution.
  DOI: 10.1504/IJAACS.2025.10074583
   
  
• Efficient multi-path routing in 5G using Eel-grouper flamingo search in software defined networking  
  by Harsh Namdev Bhor, Madhuri Pagale, Jaydeep Narayan Kale, Jyoti Ganesh Wadmare, Reena Lokare, Rashmi Malvankar 
  Abstract: The 5G mobile communication networks are designed to allow new user experience for multimedia streaming services, which provides maximum data rates and minimum latency. However, existing multimedia service approaches in software defined networking (SDN) suffer from high delay, inefficient energy usage, and limited adaptability in dynamic network conditions, resulting in degraded quality of experience (QoE). The emerging architecture SDN offers flexibility, manageability and responsibility for rapid changes in traffic requirements. Hence, this research proposed a multimedia service approach in a 5G network-enabled Eel and Grouper Flamingo Search Algorithm (EGFSA). Firstly, the SDN simulation is executed through OpenFlow and Mininet as well as the energy model is performed. Secondly, the multi-path routing is efficiently done with the help of a new hybrid optimisation framework named EGFSA. The EGFSA model obtained delay, energy, bit error rate (BER), fitness and throughput of values 0.680 s, 37.270 J, 0.002, 0.872 and 32.477 Mbps, respectively.
  Keywords: multimedia service; 5G network; SDN; software defined networking; multi-path routing; Eel and grouper optimiser.
  DOI: 10.1504/IJAACS.2025.10074550
   
  
• Cluster head selection and routing using fractional deep deterministic policy gradient in FANET  
  by Kathuroju Srinivas, Malaiyappan Nandhini 
  Abstract: Deep learning (DL) offers significant advancements in the selection and routing of cluster heads (CHs), which are characterised by their dynamic environments and high mobility. By utilising supervised learning, drones can be classified based on battery life, communication range, and historical performance. Here, a fractional deep deterministic policy gradient (FDDPG) enabled multi-agent actor-critic network is devised for CH selection and routing in flying ad hoc networks (FANETs). At first, a FANET simulation is conducted. Then, flying node metrics computation for every node is conducted based on multi-objective parameters. Multi-agent actor-critic Network is employed to select CH and to determine the routing protocol, where the training is conducted using FDDPG approach, which is the integration of fraction calculus (FC) and deep deterministic policy gradient (DDPG). It is recognised that the developed model attained energy consumption of 55.596 J, a distance of 73.293 m, a delay of 0.489 ms, and a trust of 0.879.
  Keywords: FANET; flying ad hoc network; UAVs; unmanned aerial vehicles; cluster head selection; routing; DDPG; deep deterministic policy gradient.
  DOI: 10.1504/IJAACS.2025.10074565
   
  
• Development of hybrid coyote-salp swarm optimisation for optimal routing in cognitive radio ad-hoc network  
  by B. Rajendra Prasad Babu, R. Rajeswara Rao 
  Abstract: This work is planned to design and develop a novel hybrid meta-heuristic algorithm with hybrid coyote salp swarm optimisation (HCSSO) for the routing of cognitive radio ad hoc network (CRAHN). The initial process of the proposed protocol is the selection of the source node and the destination node. Once these are selected, the proposed HCSSO is used for optimal routing of CRAHN by solving a multi-objective function. The constraints selected for deriving the multi-objective function are the distance between nodes, quality of service (QoS), energy consumption, packet loss ratio, power consumption, signal to interference, and noise ratio (SINR), and expected transmission time (ETT). Finally, the results expose that the designed algorithm outperforms better over conventional models.
  Keywords: optimal routing in cognitive radio ad-hoc network; HCSSO; hybrid coyote salp swarm optimisation; multi-objective function-based optimal routing; ETT; expected transmission time; signal to interference and noise ratio; energy consumption.
  DOI: 10.1504/IJAACS.2025.10074273