International Journal of Ad Hoc and Ubiquitous Computing (19 papers in press)

Regular Issues

• A Trusted and Adaptive Security Mechanism for Wearable E-Healthcare Systems  
  by Geetanjali Rathee, Hemraj Saini, Shishir K. Shandilya, S. Rajasoundaran 
  Abstract: The wearable e-healthcare systems are a critical IoT mission having wearable sensors, wireless devices and intelligent monitoring of surroundings. The ultimate goal of e-healthcare systems is to identify or diagnose the patients by recognising their various features that are correlated among each other. The involvement of several malicious objects may try to hide the actual recognition of wearable objects for benefiting their own purposes. Though various researchers have proposed various security and efficient schemes, however, it may lead to several computations, management overhead. The aim of this paper is to propose a trusted and efficient e-healthcare communication mechanism while recognising the exact identification of wearable objects. In addition, the proposed mechanism is associated with blockchain mechanism to ensure the transparency and security inside the network while sharing the information. The proposed mechanism is further validated over several security threats against number of security parameters.
  Keywords: wearable devices; AHP; security mechanism; analysis process; secure e-healthcare systems.
  DOI: 10.1504/IJAHUC.2023.10052372
   
  
• Ubiquitous monitoring of liver transplantation patients  
  by Javier Navarro-Alaman, Raquel Lacuesta, Jose M. Jimenez, Jaime Lloret Mauri, Iván García-Magariño, Trinidad Serrano 
  Abstract: Currently, liver transplantation is the most effective treatment available for patients with end-stage liver disease. Patients, after being transplanted, require immunosuppressive treatment that must be monitored. mHealth systems reduce costs and increase the effectiveness of monitoring. Wireless body sensor networks are used to connect personal monitoring devices in the health environment. In this work, we present a system with a specific software application to monitor liver transplant patients remotely through the data gathered from a body sensor network. The main objective of the application is to carry out the out-of-hospital follow-up of patients who are receiving postoperative treatment. The application also provides a forum, frequently asked questions, and direct communication with health specialist personnel. We have observed that the degree of activity and the emotions of the patients are related to the information provided by the collected parameters through the devices of the body sensor network.
  Keywords: mHealth; app; wearable devices; monitoring; liver; transplantation.
  DOI: 10.1504/IJAHUC.2023.10052490
   
  
• DATA SECURITY ENHANCEMENT IN INTERNET OF THINGS USING OPTIMIZED HASHING ALGORITHM  
  by Arun Kumar Udayakumar, Premkumar R, Sivakumar S. A, Maruthi Shankar B, Mahendran G 
  Abstract: The internet of things (IoT) has advanced quickly, providing customers with significant convenience in a variety of areas, including smart homes, smart transportation, and more. It might potentially pose security issues too. Significant security difficulties for the communications between such devices are brought on by the development of smart devices in IoT networks. As the IoT ecosystems develop, blockchain will become a platform for their security. Blockchain is a decentralised, distributed technology that may be able to address the IoT network security issues. Blockchain can address IoT restrictions on privacy and data protection. IoT is not a good fit for blockchain because of its high computing complexity, limited scalability, significant bandwidth overhead, and latency. This study develops an effective blockchain paradigm to address IoT requirements. Initially, the dataset is collected from the IoT sensors and pre-processed using the normalisation method. The pre-processed data is validated using smart contracts and stored in the blockchain network. Proof of work (PoW) consensus protocol is employed for the validation of the blocks. We propose an optimal key search fuzzy hashing algorithm (OKSFHA) for enhancing the security of the data. To optimise the security enhancement Spider monkey optimisation (SMO) is employed. The proposed algorithm is compared with traditional algorithms to prove the efficiency of the suggested system.
  Keywords: internet of things; IoT; blockchain; smart contracts; proof of work; PoW; optimal key search fuzzy hashing algorithm; OKSFHA; spider monkey optimisation; SMO.
  DOI: 10.1504/IJAHUC.2023.10053339
   
  
• Reconfigurable Intelligent Surfaces with Hybrid Wind, Solar and RF Energy Harvesting  
  by Raed Alhamad 
  Abstract: This paper derives the throughput of wireless communications using reconfigurable intelligent surfaces (RIS) when the source harvests power from wind, radio frequency (RF) signals and the sun. The harvested power from wind is proportional to the power of three of wind speed and depends also on rotor radius r and air density. The harvested power from RF signals is proportional to the squared absolute value of channel coefficient. The harvested power from the sun uses a photo voltaic (PV) system and is proportional to radiation intensity. The radiation intensity is Gaussian and takes into account weather effects such as cloud occlusion. We show that hybrid energy harvesting using both the wind, RF signal, and solar energy offers the largest throughput.
  Keywords: wind energy harvesting; RF signals; solar energy harvesting; reconfigurable intelligent surfaces; RIS; throughput analysis; Rayleigh channels.
  DOI: 10.1504/IJAHUC.2023.10055783
   
  
• Relay-based Spectrum Sensing with Wind Energy Harvesting  
  by Majed Abdouli 
  Abstract: In this paper, we derive the detection probability when primary user (PU) and relay nodes harvest energy from wind using a rotor of radius r. There are three phases in the network model. In the first one, PU and relays harvest power from wind over T seconds where 0 < < 1 and T is frame duration. Then, PU sends its signal over (1 )T/2 seconds. In the last phase, the best relay amplifies the PU signal to a fusion node (FN) where spectrum sensing is performed using the energy detector (ED). We derive an upper bound of the detection probability and study the effects of the number of relays K, the number of symbols M used by the ED, the false alarm probability Pf and the average wind speed
  Keywords: wind energy harvesting; spectrum sensing; relay nodes; Rayleigh channels.
  DOI: 10.1504/IJAHUC.2023.10057112
   
  
• Consumer IoT Device Deployment Optimization through Deep Learning: A CNN-LSTM Solution for Traffic Classification and Service Identification  
  by Imane CHAKOUR, Sajida Mhammedi, Cherki DAOUI, Mohamed BASLAM 
  Abstract: The internet of things (IoT) has revolutionised our world, connecting devices and creating a more intelligent and interconnected environment. However, managing and utilising the vast amount of data generated by these devices is a major challenge. To address this, we propose a novel approach in this article that combines convolutional neural networks (CNNs) with long short-term memory (LSTM) networks to optimise IoT device deployment. The process involves data preparation, defining and training a deep learning model on preprocessed data, and using the trained model to categorise network traffic from IoT devices. Our experimental results demonstrate exceptional accuracy of over 99.99%. We evaluate the models performance using classification metrics and compare it with commonly used traffic predictive models. Additionally, our approach provides valuable insights into the services offered by IoT devices by analysing their traffic patterns, distinguishing between monitoring, home automation, and appliance usage.
  Keywords: Consumer Internet of Thing (IoT) devices; Convolutional Neural Network(CNN); Long Short-Term Memory (LSTM); IoT Traffic Classification; and Traffic analysis.
  DOI: 10.1504/IJAHUC.2023.10057217
   
  
• Secure Proof of the Sum of all the Elements of a Matrix of Finite Field Elements in Zero-Knowledge  
  by Amalan Joseph Antony, Kunwar Singh 
  Abstract: Privacy preserving analysis on encrypted data requires that information be extracted from encrypted data. Interactive zero-knowledge arguments for some fundamental linear algebraic operations have been formulated. Using those proofs for certain operations that involve vectors or matrices requires certain additional reductions and additional communication rounds. In this paper, we explore the possibility of using various Discrete Mathematical principles to reduce the matrices to an operable form, and formulate a method for a prover to securely prove to the verifier that he knows the sum of all the elements of a matrix, while both the sum and the original matrix remain unknown to the verifier.
  Keywords: Cryptography; Matrix; Pedersen commitment; Zero-knowledge proof.
  DOI: 10.1504/IJAHUC.2023.10057221
   
  
• Merit: An On-demand IoT Service Delivery and Resource Scheduling Scheme for Federated Learning and Blockchain Empowered 6G Edge Networks With Reduced Time and Energy Cost  
  by Mahfuzul H. Chowdhury  
  Abstract: Federated learning (FL) can improve the privacy-preserving issue of users’ IoT devices, in which users complete the local training and transfer the updated model data to the central server for a global update. Due to high latency, the central server-based FL may suffer from huge energy loss at local user devices. MEC-based FL can improve the model accuracy and energy consumption at user devices via edge server-based task execution. Along with FL, blockchain can improve data security via permission-based access. Existing works explored only single type of IoT task without any appropriate resource scheduling for multiple tasks with different preferences, FL, and blockchain operations. This paper provides a merit-based resource scheduling scheme for different tasks with preferences, blockchain, and FL operations by checking resources, deadlines, delays, and resource costs. The simulation results verify that 45% running time and 53% cost gain is achieved in proposed scheme over the baseline schemes.
  Keywords: blockchain; BC; federated learning; FL; resource scheduling; mobile edge computing; MEC; multi-task execution; task running time.
  DOI: 10.1504/IJAHUC.2023.10057229
   
  
• Joint Resource Allocation and Cluster-Head Selection for Energy Aware D2D Multicasting.  
  by Poulomi Mukherjee, Babul P. Tewari, Tanmay De 
  Abstract: This work addresses an energy aware D2D multi-casting through a combined approach of appropriate cluster-head (CH) selection and efficient resource block (RB) allocation. The objective is to minimise the consumed energy of the formulated clusters while respecting the interference constraints of the network. An integer linear programming based on the proposed integrated approach has been formulated and an analytical model for interference analysis has been presented. We have developed an appropriate greedy algorithm to solve the joint problem. Extensive simulations have been performed using network simulator 2 (NS2) to evaluate the performance of the proposed approach. It has been shown that the proposed approach outperforms some well known approaches and results in more than 90% service coverage with reasonably higher individual data rate of 25.80 Mbps and minimum individual power consumption of 5.1 Joules/Kbits. Finally, uncertainty analysis on the experimental data and sensitivity analysis of the proposed approached are presented.
  Keywords: 5G D2D communications; multi-casting; energy consumption; RB allocation; interference management.
  DOI: 10.1504/IJAHUC.2023.10057270
   
  
• Quantum Simulation Scenarios and Disease Classification Behaviour on Diabetes Data  
  by AJEET SINGH, N.D. Patel 
  Abstract: In quantum mechanics, the state of a particle can be fully characterised for all future periods based on the beginning conditions and knowledge of the potential occupied by the particle. This paper presents an overview of the integration of statistical machine learning and quantum mechanics. Furthermore, we provide simulation scenarios, classification behaviour, and empirical observations on healthcare data through the utilisation of Feynman diagrams (Feynman et al., 2010) and QLattice (Abzu, 2022). The experimental simulation is carried out in the following instances: 1) changing the number of updating loops; 2) calling the qgraph.fit function multiple times before updating the QLattice; 3) fitting and selecting graphs according to different loss functions; 4) setting the graphs max depth to comparatively higher or smaller values. The paper concludes by summarising the observations made throughout the study and discussing the potential for future work in this field.
  Keywords: path integral formulation; quantum machine learning; QGraph; registers; interactions; binary classification; simulation; healthcare.
  DOI: 10.1504/IJAHUC.2023.10057477
   
  
• NEAT Activity Detection using Smartwatch  
  by Ankita Dewan, Viswanath Gunturi, Vinayak Naik 
  Abstract: This paper presents a system for distinguishing non-exercise activity thermogenesis (NEAT) and non-NEAT activities at home. NEAT includes energy expended on activities apart from sleep, eating, or traditional exercise. Our study focuses on specific NEAT activities like cooking, sweeping, mopping, walking, climbing, and descending, as well as non-NEAT activities such as eating, driving, working on a laptop, texting, cycling, and watching TV/idle time. We analyse parameters like classification features, upload rate, data sampling frequency, and window length, and their impact on battery depletion rate and classification accuracy. Previous research has not adequately addressed NEAT activities like cooking, sweeping, and mopping. Our study uses lower frequency data sampling (10 Hz and 1 Hz). Findings suggest using statistical features, sampling at 1 Hz, and maximising upload rate and window length for optimal battery efficiency (33,000 milliamperes per hour, 87% accuracy). For highest accuracy, use ECDF features, sample at 10 Hz, and a window length of six seconds or more (37,000 milliamperes per hour, 97% accuracy).
  Keywords: non-exercise activity thermogenesis; NEAT; smartwatch; activity recognition; battery.
  DOI: 10.1504/IJAHUC.2023.10057574
   
  
• Computational Offloading in Vehicular Edge Computing using Multiple Agents based Deterministic Policy Gradient Algorithm and Generative Adversarial Networks (DPG-GAN)  
  by Shabariram C. P, Shanthi N, PriyaPonnusamy P 
  Abstract: The development of the intelligent connected vehicles and internet of vehicles as an evolving technology has changed the vehicular edge computing. Computational offloading is the primary challenge. Although numerous offloading algorithms are proposed to achieve computing performance, the mobility, priority of offloading and offloading failure are rarely considered for optimisation and it remains challenging. To address the challenge, this paper presents computational offloading using multiple agent-based deterministic policy gradient-generative adversarial networks (DPG-GAN) and increases the number of offloading executions with a minimum number of edge servers. The system overhead is minimised by 50% while the learning rate is 6e-6. The GAN in the actor-critic network increases the learning rate and efficiency. The energy utilisation is 15 to 25 J which is two times better than LSTM. Simulation and its results show the system gives minimal system overhead from 210 episodes and subject to processing time delay and energy utilisation.
  Keywords: multiple agents; deep reinforcement learning; internet of vehicles; IoV; computation offloading; vehicular edge computing; deterministic policy gradient; DPG; generative adversarial networks; GAN.
  DOI: 10.1504/IJAHUC.2023.10057819
   
  
• Icon: An Intelligent Resource Slicing and Task Coordination Framework For Web 3.0 and Metaverse Based Service Execution Over 6G Based Immersive Edge Computing Network  
  by Mahfuz Ul Hoq Chowdhury  
  Abstract: Web 3.0 is immersive web technology in which human users can use metaverse platforms and experience digital realities for work, play, socializing, and learning activities Metaverse is considered a virtual world in which users can interact with other users and services in an immersive manner The existing research articles did not provide any unified service coordination framework for different web 3.0 and metaverse-based task execution by taking intelligent resource slicing, work node selection, task, and resource coordination into account To address these issues, this paper yields an intelligent resource slicing-based unified framework for metaverse and web 3.0-based task execution over 6G enhanced immersive networks by scrutinizing resource device status, different current and previous generation tasks with requirements, time, energy, and economic gain, into account The experimental results notified that 59 90% delay and 78% utility gain is attained in the proposed scheme over the benchmark scheme.
  Keywords: Metaverse; Web 3.0; Resource Slicing; Task Coordination; Digital Twin; Service Realization Delay; Blockchain; Users Economic Cost; Utility; Dissipated Energy Value; Mobile Edge Computing.
  DOI: 10.1504/IJAHUC.2023.10058084
   
  
• Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surfaces (STAR-RIS) with Multi-antenna Energy Harvesting and Adaptive Power  
  by RAED ALHAMAD 
  Abstract: This paper computes the secondary throughput of Cognitive Radio Networks (CRN) where the Secondary Source SS harvests energy from the Radio Frequency (RF) signal of node A received over nr antennas. Then, SS adapts its power to control the interference level at Primary Destination (PD). The secondary signal is transmitted to users Ur and Ut located in the reflection and transmission space of STAR-RIS. We show that when the number of STAR-RIS elements is doubled, we obtain 15 dB gain. STAR RIS is a good candidate for next generation of wireless communications such as 6G and beyond as it offers a large throughput.
  Keywords: STAR-RIS; 6G; CRN; Adaptive power.
  DOI: 10.1504/IJAHUC.2023.10058370
   
  
• Simple Design of QCA-based T-flipflop with Energy Dissipation Analysis for Nanocomputing  
  by Angshuman Khan, Sikta Mandal, Rajeev Arya 
  Abstract: One of the emerging nano-technologies that might one day replace traditional transistor-based technologies is quantum-dot cellular automata (QCA). An effective elementary T flipflop based on the QCA is proposed here. There is no need to cross wires across layers, so the suggested gates may be realized with single-layer majority gates. QCADesigner 2.0.3 is used to create and test circuit layouts. The simulation outcome discredits the superiority of the existing designs. When the suggested design is compared to the best T-flipflop currently available, cell complexity and cell area needed are decreased by 9.3% and 7.7%, respectively. The energy loss of the proposed block has also been estimated using the QCAPro and QCADesigner-E (QDE) tools. According to QCAPro, there is a 12% improvement in energy dissipation at ?=1.5EK over the best available design.
  Keywords: flipflop; nanocomputing; T-flipflop; quantum dot cellular automata; QCA.
  DOI: 10.1504/IJAHUC.2023.10058705
   
  
• Performance Evaluation of Strapdown Inertial Navigation and Beidou Satellite Navigation System Based on Intelligent Image Processing Technology  
  by Jianzhong Wang, Lijun Huang 
  Abstract: This paper proposes image processing technology and Beidou/SINS compact integrated navigation system, and analyses its performance. The experimental results show that in terms of attitude angle accuracy, the attitude data output by the integrated navigation system in the static state is stable, and the root mean square error is less than 0.6
  Keywords: Beidou satellite navigation; image processing technology; strapdown inertial navigation; compact integrated navigation; digital image processing.
  DOI: 10.1504/IJAHUC.2024.10058860
   
  
• A Hybrid Channel Transmission Method for Effective Spectrum Access in Cognitive Radio Networks  
  by S.K. Dhurandher, Bhoopendra Kumar, Isaac Woungang, Han-Chieh Chao Han-Chieh Chao 
  Abstract: Cognitive radio is considered as a very influencing technique and has the great potential to solve the problem of shortage of the radio spectrum. A secondary user also called as a cognitive user may access the primary channel(s) with a certain restrictions in a cognitive radio network. Spectrum sensing is a very important activity during the process of spectrum access. This paper proposes a Markov chain-based proactive hybrid spectrum access method for maximizing the radio spectrum usage by optimizing the channel sensing process and establishing the channel switching conditions. Using the OMNeT++ simulator, the proposed method (proactive hybrid access) is compared against that of the conventional (reactive hybrid access), overlay, and underlay access methods, showing its superiority by about 20% in terms of performance improvement with respect to throughput, service delay, and PU detection probability.
  Keywords: Radio Spectrum; Cognitive Radio; Spectrum Sensing; Hybrid Spectrum Access; Markov Chain; OMNeT++.
  DOI: 10.1504/IJAHUC.2023.10058936
   
  
• Lightweight and Personalized E-commerce Recommendation based on Collaborative Filtering and LSH  
  by Dejuan Li, James A. Esquivel 
  Abstract: Nowadays, e-commerce has become one of the most popular shopping ways for worldwide customers especially after the outbreak of COVID-19 worldwide. To aid the scientific shopping decision-makings of customers, collaborative filtering is often used to discover similar customers as well as their common shopping preferences. However, traditional collaborative filtering methods often need to read massive shopping records of customers, which usually consumes much time for discovering the customer preferences and consequently, leads to a slow response and decreases customers' shopping quality of experiences. Moreover, traditional collaborative filtering methods cannot always guarantee to discover similar customers as well as their common shopping preferences especially when different customers share few commonly-bought commodities. Motivated by the above two limitations, locality-sensitive hashing used widely in information retrieval domain is recruited in this paper to aid e-commerce platforms to make accurate and scientific shopping decisions for the customers of the platforms. The advantage of our solution is that it can help to improve the response efficiency of e-commerce platforms and provide lightweight and personalised e-commerce recommendation strategies especially when the shopping records of customers are both massive and sparse. We prove the innovations of our algorithm with multiple sets of experiments.
  Keywords: e-commerce recommender system; lightweight; personalisation; collaborative filtering; locality-sensitive hashing.
  DOI: 10.1504/IJAHUC.2024.10059174
   
  
• Throughput optimization with Wind Energy harvesting  
  by Faisal Alanazi 
  Abstract: In this paper, we optimise the instantaneous and average throughput of wireless communications when the source harvests power from wind. We select the value of packet length to optimise the instantaneous or average throughput. Instantaneous throughput optimisation offers up to 5 dB gain versus average throughput optimisation. Average throughput optimisation offers a larger throughput than any packet length. We also study the effects of average wind speed and the results are obtained for Rayleigh channels. We derive the SNR statistics when the source harvests power from wind. Our derivations are valid for any position of nodes and any average wind speed. Average throughput optimisation offers a larger throughput than any packet length as suggested in the literature. We obtained up to 1.5 dB gain using average throughput optimisation when compared to packet length N = 200, 500. Instantaneous throughput optimisation allows up to 5 dB gain versus average throughput optimisation.
  Keywords: wind energy harvesting; average and instantaneous throughput optimisation; Rayleigh channels; Nakagami channels; optimal packet length.
  DOI: 10.1504/IJAHUC.2023.10059176