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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 (26 papers in press)

Regular Issues

  •   Free full-text access Open AccessSubcarrier power control for URLLC communication system via multi-agent deep reinforcement learning in IoT network
    ( Free Full-text Access ) CC-BY-NC-ND
    by Haiyan Wang, Xinmin Li, Feiying Luo, Jiahui Li, Xiaoqiang Zhang 
    Abstract: Designing an intelligent resource allocation scheme to achieve the performance requirements of internet of things (IoT) devices for the future ultra-reliable low-latency communication (URLLC) network is a challenging task. In this paper, we formulate a joint blocklength allocation and power control optimisation problem to maximise the sum-rate performance with the short data packet in an uplink URLLC communication system. To alleviate this non-convex optimisation problem under the subcarrier power, blocklength and rate constraints, we firstly transfer it into a multi-agent reinforcement learning (RL) problem, in which each subcarrier works as the agent to decide its own power intelligently. Then a distributed blocklength allocation and power control scheme is proposed based on deep Q-network (DQN). To improve the rate performance in the dynamic communication environment, we design the segmented reward function depending on the communication rate and blocklength under different conditions, and adopt the experience replay strategy to avoid the dependency of training data. Finally, the simulation results show that the proposed scheme achieve the effectiveness and convergence under different settings compared to benchmark schemes.
    Keywords: ultra-reliable low-latency communication; URLLC; blocklength allocation; power control; deep reinforcement learning.
    DOI: 10.1504/IJCNDS.2024.10062215
  • STAGNN: A Spatial-Temporal Attention Graph Neural Network for Network Traffic Prediction   Order a copy of this article
    by Yonghua Luo, Qian Ning, Bingcai Chen, Xinzhi Zhou, Linyu Huang 
    Abstract: Accurate and real-time traffic prediction can reasonably allocate the resources of communication networks and effectively improve the communication quality of networks. However, the complex topology and highly dynamic nature of communication networks pose new challenges for traffic prediction. To be able to effectively obtain the temporal correlation and spatial dependency of network traffic and mask the redundant traffic features, we propose a spatial-temporal attention graph neural network (STAGNN). The STAGNN combines the graph attention network (GAT) and the time series model informer, where GAT is used to learn the complex spatial dependencies of network topology and informer is used to learn the dynamic temporal correlation of network traffic. Also in learning, we introduce the multi-headed attention mechanism enabling STAGNN to quickly select high-value network traffic information using limited attention resources. The experimental results demonstrate that STAGNN has better prediction performance compared with other existing methods.
    Keywords: network traffic prediction; attention mechanism; temporal correlation; spatial dependency.
    DOI: 10.1504/IJCNDS.2024.10056816
  • A survey on security threats in cognitive radio networks based on cooperative spectrum sensing   Order a copy of this article
    by Flavien Donkeng Zemo, Sara BAKKALI 
    Abstract: Cognitive radio networks (CRNs) are a technological revolution that allows unlicensed users (SUs) to opportunistically use the freely licensed spectrum bands of a primary user (PU). To avoid interference with the PU, SUs need to do accurate spectrum sensing. Spectrum sensing (SS) by a single SU user can be inaccurate in deep fading and multi-path environments. Cooperative spectrum sensing (CSS) is a technology implemented in CRNs to improve the results of SS in deep fading environments. But only the success of CSS is threatened by new forms of attacks on the physical layer, the main ones being the spectrum sensing data falsification attack (SSDF) and the primary user emulation attack (PUEA). In our paper, we present the CSS in detail. Subsequently, a relevant study on SSDF and PUEA attacks is carried out, and depending on the approach exploited, different research works to defend the CSS against these attacks are presented.
    Keywords: cognitive radio networks; CRNs; cooperative spectrum sensing; CSS; spectrum sensing data falsification attack; SSDF; primary user emulation attack; PUEA.
    DOI: 10.1504/IJCNDS.2024.10057458
  • Secure Key Exchange Protocol using Graph and Trusted Third Party   Order a copy of this article
    by Maroti Deshmukh, Arjun Rawat 
    Abstract: The exchange of cryptographic keys poses a challenge due to the need for secure communication channels. This paper presents an algorithm that employs a random complete graph, a trusted third party, and a circuit to ensure secure key transmission. The trusted third party generates a graph and uses a circuit (a path from sender to receiver) to transmit the key alongside the message. This process enhances security by making key tracing difficult. The proposed scheme generates a common session key through a graph permutation, outperforming existing schemes in terms of key size. It accommodates varying key sizes, making it adaptable to different scenarios. Moreover, the approach minimises computation and communication overhead by utilising a limited number of steps, graph weights, permutations, and multiplications, while involving a trusted third party.
    Keywords: key exchange protocol; asymmetric key cryptography; complete graph; key distribution; trusted third party; TTP.
    DOI: 10.1504/IJCNDS.2024.10057678
    by Sarandis Mitropoulos 
    Abstract: Large-scale distributed system management is an emerging task for all modern networked organisations. In this direction, corporate management systems are usually organised into domains, which specify the borders for policy applicability. Due to the complexity of such a task, techniques must be developed for resolving conflicts and optimising the management structures and performance. In this paper, after brief providing an overview of the related topics on policy-based system management, we propose mechanisms for consistency and minimisation of policy sets, and finally for optimisation in management structures adopting parallel processing techniques.
    Keywords: distributed system management; management domain structures; management policy hierarchies; optimisation; parallel processing.
    DOI: 10.1504/IJCNDS.2024.10057839
  • 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
  • Extended Diffie Hellman Protocol Based on Exponential and Multiplication Operation Over Modular Arithmetic   Order a copy of this article
    by Sandeep Chand Kumain, Maroti Deshmukh, Maheep Singh 
    Abstract: In this modern digital world, a huge volume of data is transmitted over the internet. This data transmission is done through the communication channel and the communication channel might be insecure. The unauthorised disclosure and tempering of data is a threat to the integrity of the message in network security, hence security is required during the data transmission between two or more parties. Diffie-Hellman is the first key exchange protocol proposed for this purpose. However, there are several attacks are possible in this scheme. In this research article, the authors of this study providing the solution for passive attack and increase the Diffie-Hellman algorithm’s security against potential passive attacks even the mod value is small. In this extended improved version of Diffie-Hellman, the final key does not rely directly on mod value which makes the passive attack more complex as compared to the original Diffie-Hellman.
    Keywords: key exchange protocol; key agreement protocol; passive attack; Diffie-Hellman; modular arithmetic; exponentiation operation.
    DOI: 10.1504/IJCNDS.2024.10058942
  • 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 ANIL KUMAR R.  
    Abstract: Future wireless networks: smarter, faster, 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.
    DOI: 10.1504/IJCNDS.2024.10059468
  • A Secured lightweight Authentication Protocol for Vehicular Adhoc Network (VANET) using Blind Signature   Order a copy of this article
    by Kalpana Samal, Shanta Kumari Sunanda, Debasish Jena, Srikanta Patnaik 
    Abstract: Malicious attacks on vehicular ad hoc networks (VANET) can cause serious harm, including vehicle accidents. This paper suggests a secure protocol for the authentication of Vehicles with roadside units (RSU) in VANET and secure protocols for the online registration of vehicles and RSU with the transport authority (TA). A strategy is also presented for preserving vehicle and traveller privacy during communications with the TA and RSU. The proposed protocol prevents attacks like replay, impersonation, and man-in-the-middle attacks. Lightweight components like XOR and hash functions are used for the authentication of vehicles with the RSU, which makes the protocol faster than the existing protocols. Automated validation of internet security protocols and applications (AVISPA) is used to verify the proposed protocol. The proposed protocol is compared with well-known current approaches, and it is found that the technique used in the proposed protocol overcomes other existing protocols.
    Keywords: vehicular ad hoc network; VANET; security; privacy; blind signature; authentication; secure protocol; AVISPA.
    DOI: 10.1504/IJCNDS.2024.10059913
    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.
    DOI: 10.1504/IJCNDS.2024.10059914
  • Metaheuristic Based Segment Routing for Hybrid Software-Defined Network (SDN) 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 4.24ms, 77.61%, 0.15sec, 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
  • 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 Multicriteria   Order a copy of this article
    by Matheus Silveira, Maria Clara Mesquita, Rafael Gomes 
    Abstract: 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 FUMU (FUzzy MUlticriteria) 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 utilizing provider resources and meeting customers' QoS requirements.
    Keywords: Multicriteria; Network Management; Internet Service Provider.
    DOI: 10.1504/IJCNDS.2024.10061048
  • 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
  • Applications of Bluetooth and Wi-Fi-Direct for local communication and their performance evaluation   Order a copy of this article
    by Yugbhanu Rajwade, Divy Arpit, K. Jairam Naik 
    Abstract: Wireless connectivity may not be available in congested locations (such as concerts or conference-halls) or may be interrupted by infrastructure outages caused by earthquakes and tsunamis. They are the great boon when it comes to device-to-device communication based on technologies like Wi-Fi-Direct and Bluetooth. However, no existing research builds a fully functional communication system which is local in nature, nor does it consider how the user mobility can be supported. A fuzzy logic-based normalised quantitative decision (FNQD) approach was proposed by the recent researchers, but it is suffering with the distance coverage among the communicating devices. We put forward an intragroup communication solution for local setup without the interference of any external network support. We propose a Bluetooth and Wi-Fi-Direct (Wifi_BL) system that improves the distance coverage obtained from the existing fuzzy logic-based normalised quantitative decisions. The proposed Wifi_BL system attains better distance coverage over the existing FNQD.
    Keywords: local communication; Bluetooth; Wi-Fi-Direct; distance coverage; fuzzy logic.
    DOI: 10.1504/IJCNDS.2024.10056567
  • A critical review of feature selection methods for machine learning in IoT security   Order a copy of this article
    by JingJing Li, Mohd Shahizan Othman, Hewan Chen, Lizawati Mi Yusuf 
    Abstract: In the internet of things (IoT) era, the security of connected devices and systems is critical. Machine learning models are commonly used for IoT attack detection, where feature selection (FS) plays an important role. However, FS for IoT security differs from traditional cybersecurity due to the uniqueness of IoT systems. This paper reviews FS methods for effective machine learning-based IoT attack detection. We identify five research questions and systematically review 1,272 studies, analysing 63 that meet inclusion criteria using the preferred reporting items for systematic review and meta-analysis (PRISMA) guidelines. We categorised the studies to address the research questions regarding FS methods, trends, practices, datasets and validation used. We also discussed FS limitations, challenges, and future research directions for IoT security. The review can serve as a reference for researchers and practitioners seeking to incorporate effective FS into machine learning-based IoT attack detection.
    Keywords: internet of things; IoT; feature selection; IoT dataset; attack detection; classification; IoT security; systematic literature review; SLR; machine learning; deep learning.
    DOI: 10.1504/IJCNDS.2024.10057332
  • An objective comparison of two prominent virtual actor frameworks: Proto.Actor and Orleans   Order a copy of this article
    by Edward R. Sykes, Alec DiVito 
    Abstract: Recently there has been a significant increase in developing distributed systems easily and rapidly. Driven by the demand of software communities, developers seek tools and frameworks that abstract away low-level details of the underlying distributed system and the need to understand complex details on how the system works. Researchers have explored serverless frameworks, distributed key value stores, distributed stream processing frameworks and distributed actor frameworks. Currently, stateful serverless applications and distributed actor models may be the answer to what developers need. In this paper, we present a review of stateful distributed computing frameworks, and the results of experiments that compare Orleans and Proto.Actor - two popular actor model frameworks - running on Kubernetes. We discovered that the Proto.Actor performs at least two times faster than Orleans, but is more complex to learn. We present the results of these tests, and provide a discussion of future research opportunities highlighting virtual actor model frameworks.
    Keywords: actor model; distributed computing; microbenchmark tests; serverless computing; virtual actor frameworks.
    DOI: 10.1504/IJCNDS.2024.10057792
  • Searchlight: a novel data delivery cost-aware multi-mode data transmission scheme with best-fit resource allocation for 6G underwater sensor networks applications   Order a copy of this article
    by Mahfuzulhoq Chowdhury 
    Abstract: With the huge developments of underwater communication technologies, the UWSNs have played a significant role to realise profitable sea and water resource discovery/management applications. The existing UWSN works do not investigate data delivery cost-aware multi-mode data transmission by considering different communication links, forwarding nodes, networking devices, and resource allocation. Another crucial challenge is the selection of cluster-head and forwarding nodes. A majority of existing works investigate only underwater sensors' cluster head selection rather than both cluster head and forwarding nodes. This paper comes up with a data delivery cost-aware scheme with a best-fit resource allocation for UWSNs. This paper provides an integrated network model by coordinating terrestrial, non-terrestrial, and underwater networks. This paper yields a numerical model that includes finish time, energy depletion cost, network survivability, throughput, and utility metrics. The results of the proposed scheme achieve at least 45% utility gain than the traditional schemes.
    Keywords: underwater sensor networks; UWSNs; best-fit resource allocation; energy utility; cluster head and forwarding node selection; throughput; network survivability.
    DOI: 10.1504/IJCNDS.2024.10057140