Broken Links Research Articles

Latency‐Sensitive Service Function Chains Intelligent Migration in Satellite Communication Driven by Deep Reinforcement Learning

ABSTRACTSatellite communication technology solves the problem that the traditional wired network infrastructure is difficult to achieve global communication coverage. However, factors such as satellite orbits introduce frequent changes to the network topology, and challenges like satellite failures and communication link interruptions are prevalent. In the face of these issues, service function chain (SFC) migration becomes a crucial method for swiftly adjusting SFCs during faults, maintaining service continuity and availability. This article proposes a latency‐sensitive SFC migration algorithm tailored to satellite networks. The algorithm first models the satellite network as a multi‐domain virtual network, capturing the constraints faced during SFC migration. Subsequently, a deep reinforcement learning algorithm integrated attention mechanism is designed to more accurately capture and understand the complex network environment and dynamic satellite network topology and derive optimal SFC migration strategies for superior performance. Finally, through experimentation and evaluation of the deep reinforcement learning‐driven latency‐sensitive service function chain intelligent migration algorithm (LS‐SFCM) in satellite communication, this study validates the effectiveness and superior performance of the algorithm in latency‐sensitive scenarios. It provides a new avenue for enhancing the service quality and efficiency of satellite communication networks.

A comprehensive review of existing corpora and methods for creating annotated corpora for event extraction tasks

Abstract Purpose The purpose of this study is to serve as a comprehensive review of the existing annotated corpora. This review study aims to provide information on the existing annotated corpora for event extraction, which are limited but essential for training and improving the existing event extraction algorithms. In addition to the primary goal of this study, it provides guidelines for preparing an annotated corpus and suggests suitable tools for the annotation task. Design/methodology/approach This study employs an analytical approach to examine available corpus that is suitable for event extraction tasks. It offers an in-depth analysis of existing event extraction corpora and provides systematic guidelines for researchers to develop accurate, high-quality corpora. This ensures the reliability of the created corpus and its suitability for training machine learning algorithms. Findings Our exploration reveals a scarcity of annotated corpora for event extraction tasks. In particular, the English corpora are mainly focused on the biomedical and general domains. Despite the issue of annotated corpora scarcity, there are several high-quality corpora available and widely used as benchmark datasets. However, access to some of these corpora might be limited owing to closed-access policies or discontinued maintenance after being initially released, rendering them inaccessible owing to broken links. Therefore, this study documents the available corpora for event extraction tasks. Research limitations Our study focuses only on well-known corpora available in English and Chinese. Nevertheless, this study places a strong emphasis on the English corpora due to its status as a global lingua franca, making it widely understood compared to other languages. Practical implications We genuinely believe that this study provides valuable knowledge that can serve as a guiding framework for preparing and accurately annotating events from text corpora. It provides comprehensive guidelines for researchers to improve the quality of corpus annotations, especially for event extraction tasks across various domains. Originality/value This study comprehensively compiled information on the existing annotated corpora for event extraction tasks and provided preparation guidelines.

Web reference decay: Passing the HTTP errors instead of quality information

Web resource links routinely fail, and the content of links might change suddenly and without notice. When referrals to online sites offer proof or supporting data, these web dynamics are harmful. Any hyperlink’s final content is susceptible to two phenomena: the link breaks (link rot) and the content changes from its original state (content drift). The combination of both effects is referred to as reference rot. This paper aims to determine the application of online citations, the number of lost web citations, and the process of recovering missing web citations through the application of the Internet Archive’s Wayback Machine. According to the analysis, the Webology journal published 428 research articles between 2004 and 2020 that had 2,273 online citations. There are 1,260 (55.43%) accessible web citations out of the mentioned ones, whereas 1,013 (44.57%) are missing. There are 1,856 (81.65%) active web citations, up from 1,260 (55.43%) after an effort was made to retrieve 596 lost web citations using the Wayback Machine tool. That meant that the overall increase of the active URLs was 26.22%. The article presents a method for creating specific collections for online archiving in the future, even though web-archiving tools now take snapshots of websites in real time. The paper recommends that future curation standards for real-time web archiving shall include platform dynamics and cultural variations in link-sharing habits.

An Audit Of Health And Ageing Online Resources: Evaluating Information On Periodontitis And Cardiovascular Disease Associations

Abstract Background In 2019 the European Federation of Periodontology (EFP) and the World Heart Federation (WHF) organized a review of the literature concerning periodontal disease (PD) and cardiovascular disease (CVD). This was to update the existing evidence from a 2012 review. The consensus report established a strong link between severe PD and CVD, however, this vital information may not be reaching the public who stand to benefit from it. Methods A web-based audit to assess the dissemination of information on the PD-CVD association was conducted. Ninety English language websites of foundations, health authorities, and associations focused on aging (54), CVD (21), and general health (15) were included. Dental organisations were excluded. Using Boolean search criteria, websites were examined for webpages informing of the PD-CVD link published in 2019 or later. Pages with the information published before 2019 were also recorded separately. Broken links, paywalled content, and information solely on infective endocarditis were excluded. Pages without metadata on publishing dates were considered older than five years. Results Only 8 (8.8%) sites contained information on the PD-CVD link within the past five years of which 5 (5.5%) gave actionable guidance on how to improve oral health. An additional 9 sites (10%) offering the information were recorded but were older than five years. Conclusion This study reveals a concerning gap in translating research findings from the highest levels of evidence to online resources accessible to the public. This highlights a missed opportunity to empower individuals. The siloed nature of dentistry, with limited collaboration between dental professionals and other health care providers, might be a contributing factor. These findings highlight the need for improved communication strategies and collaborative efforts to bridge this knowledge gap and empower individuals to make informed decisions about their oral and overall health.

Enhancing Reliability and Stability of BLE Mesh Networks: A Multipath Optimized AODV Approach.

Bluetooth Low Energy (BLE) mesh networks provide flexible and reliable communication among low-power sensor-enabled Internet of Things (IoT) devices, enabling them to communicate in a flexible and robust manner. Nonetheless, the majority of existing BLE-based mesh protocols operate as flooding-based piconet or scatternet overlays on top of existing Bluetooth star topologies. In contrast, the Ad hoc On-Demand Distance Vector (AODV) protocol used primarily in wireless ad hoc networks (WAHNs) is forwarding-based and therefore more efficient, with lower overheads. However, the packet delivery ratio (PDR) and link recovery time for AODV performs worse compared to flooding-based BLE protocols when encountering link disruptions. We propose the Multipath Optimized AODV (M-O-AODV) protocol to address these issues, with improved PDR and link robustness compared with other forwarding-based protocols. In addition, M-O-AODV achieved a PDR of 88%, comparable to the PDR of 92% for flooding-based BLE, unlike protocols such as Reverse-AODV (R-AODV). Also, M-O-AODV was able to perform link recovery within 3700 ms in the case of node failures, compared with other forwarding-based protocols that require 4800 ms to 6000 ms. Consequently, M-O-AODV-based BLE mesh networks are more efficient for wireless sensor-enabled IoT environments.

A lightweight deep learning architecture for automatic modulation classification of wireless internet of things

AbstractThe wireless Internet of Things (IoT) is widely used for data transmission in power systems. Wireless communication is an important part of the IoT. The existing modulation classification algorithms have low classification accuracy when facing strong electromagnetic interference, which causes decoding error link interruption and wastes wireless channel resources. Therefore, it is necessary to study signal modulation classification methods in a low signal‐to‐noise ratio (SNR) environment. In this paper, a lightweight Deep Neural Networks (DNNs) modulation classification method based on the Informer architecture classifier and two‐dimensional (2‐D) curves input of the spectral correlation function (SCF) is proposed, which uses in‐phase and quadrature (I/Q) signals to generate 2‐D cross‐section SCF curve first and then feeds the feature curve into the Informer network to classify the modulation method. This model can better learn the robustness characteristics in a long sequence. Through testing, the classification accuracy of the modulation signal is not much lower than that of the current good classification method when the SNR is 10 dB, and this method can still show higher accuracy when hardware resources are limited. It is a compact design of a modulation classification model and easy to deploy on low‐cost embedded platforms.

A broken link: Knowledge of carbohydrate requirements do not predict carbohydrate intake around competition in endurance athletes.

Endurance athletes fail to meet carbohydrate (CHO) guidelines for competition, which may be due to limited knowledge. However, the relationship between knowledge and practice in this population is unknown. To investigate this, we assessed the dietary intake in 50 athletes (37 females) who completed endurance events ≥2.5h in duration and compared CHO intake against the carbohydrates for endurance athletes in competition questionnaire validated nutrition knowledge questionnaire, with specific questions related to CHO loading, pre-competition meal and during-competition intake. CHO-loading guidelines (10-12g·kg-1·day-1) were met in practice by n=5 (10%), but there was no relationship between identified requirements (range 0-12g·kg-1·day-1) and actual intake (rs=0.133, p=0.358), with the n=18 (36%) who correctly identified requirements, ingesting 6.1±1.9g·kg-1·day-1. CHO intake for pre-competition meal guidelines (1-4g·kg-1) was met in practice by n=40 (80%), but there was no relationship between identified requirements (range 0 to >4g·kg-1) and actual intake (rs=0.101, p=0.487), with n=19 (38%) who correctly identified guidelines requirements, ingesting 1.4±0.6g·kg-1. CHO intake during-competition guidelines (60-90g·h-1) was met in practice by n=18 (36%), but there was no relationship between the amounts of CHO required (range 30 to >90g/h) and actual intake (rs=0.028, p=0.849), with n=32 (64%) who correctly identified guidelines requirements, ingesting 56±20g·h-1. Results show no relationship between the knowledge of CHO recommendations and practice, suggesting that theoretical knowledge does not guarantee the achievement of best practice and other important factors may ultimately determine practice.

Pratiques spirituelles et prière incarnée chez Michel de Certeau

Abstract In recent years, numerous studies of prayer practices have been presented in the field of cultural and religious sciences. In his article on “L’homme en prière, cet ‘arbre de gestes’”, Michel de Certeau makes the gestures of prayer and the space inhabited by prayer the starting point for a fundamental approach to human existence. The following article builds on these reflections and, in the context of the ‘spacial turn’ in the cultural sciences, attempts to work out with Michel de Certeau the paths to an ‘intellectus fidei’ in these times of broken links with the ecclesial institution, when spirituality is gaining new importance, even in secular circles.

VANET cluster-based routing protocol with link breakage handling: introduction to hybrid optimization algorithm

VANET cluster-based routing protocol with link breakage handling: introduction to hybrid optimization algorithm

From mind‐deadness to mindedness, from collaboration to cooperation

AbstractLooking at the October 7, 2023, events in Israel, this paper suggests a unique configuration of Bion's minus links, called "broken links." The broken links not only represent a negation of a connection—but also a negation of the object. When the link of Love is broken, it is replaced by a unique formation of Love without an object, in which the lack‐of‐object installs itself as the sole object, replacing the work of mourning with pseudo, blank mourning. When the link of Hate is broken, the result is a murderous version of hatred, one that exceeds any proportion or context. When the link of Knowledge is broken, what ensues is a language that functions as a sealing material: instead of signifying and making differences, it drives to overgeneralize, erase differences, and remove distinctions, losing its metaphorical qualities and reducing to its literal meaning. These broken links lead to another twisted link: the link of solidarity, turning positive solidarity, which is based on cooperation—into negative solidarity, based on collaboration. The discussion suggests the shift from the state of mind‐deadness, characterizing broken links on both sides of the conflict, to the state of mindedness, in which the links are reclaimed and restored.

Network resilience of plant-bee interactions in the Eastern Afromontane Biodiversity Hotspot

Interaction network resilience can be defined as the ability of interacting organisms to maintain their functions, processes or populations after experiencing a disturbance. Studies on mutualistic interactions between plants and pollinators along environmental gradients are essential to understand the provision of ecosystem services and the mechanisms challenging their network resilience. However, it remains unknown to what level ecological changes along climatic gradients constrain the network resilience of mutualistic organisms, especially along elevation gradients. We surveyed bee species and recorded their interactions with plants throughout the four major seasons (i.e. long and short rainy, and long and short dry) on 50 study sites positioned along an elevation gradient (525 m to 2,530 m asl) in the Eastern Afromontane Biodiversity Hotspots in Kenya, East Africa. We calculated bee and plant network resilience using the network resilience parameter (βeff) and assessed changes in bee and plant network resilience along the elevation gradient using generalised additive models (gams). We quantified the effects of climate, bee and plant diversity, bee functional traits, network structure, and landscape configuration on bee and plant network resilience using a set of multi-model inference frameworks followed by structural equation models (SEM). We found that bee and plant species exhibited higher levels of network resilience at higher elevations. While bee network resilience increased linearly across the elevation gradient, plant network resilience increased exponentially from ∼1500 m and higher. Bee and plant network resilience increased in areas with reduced mean annual temperature (MAT) and decreased in areas with lower mean annual precipitation (MAP). Our SEM model showed that increasing temperatures indirectly influenced plant network resilience via network modularity and community assemblage of bees. We also found that MAP had a direct positive effect on plant diversity and network resilience, while the fragmentation of habitats reduced richness of plant communities and enhanced network modularity. In conclusion, we revealed that mutualistic networks showed higher network resilience at higher elevations. We also unveiled that climate and habitat fragmentation directly or indirectly influences the network resilience of plants and bees via the modulation of community assemblages and interaction networks. These influences are lower at higher elevations such that these systems seem better able to buffer against extinction cascades. We thus suggest that, management efforts should be geared at consolidating natural habitats. In contrast, restoration efforts should aim at mitigating climate change effects and harnessing the ability of mutualists to reconnect broken links to improve the network resilience and functioning of East-African montane ecosystems.

CO-19 PDB 2.0: A Comprehensive COVID-19 Database with Global Auto-Alerts, Statistical Analysis, and Cancer Correlations.

Biological databases serve as critical basics for modern research, and amid the dynamic landscape of biology, the COVID-19 database has emerged as an indispensable resource. The global outbreak of Covid-19, commencing in December 2019, necessitates comprehensive databases to unravel the intricate connections between this novel virus and cancer. Despite existing databases, a crucial need persists for a centralized and accessible method to acquire precise information within the research community. The main aim of the work is to develop a database which has all the COVID-19-related data available in just one click with auto global notifications. This gap is addressed by the meticulously designed COVID-19 Pandemic Database (CO-19 PDB 2.0), positioned as a comprehensive resource for researchers navigating the complexities of COVID-19 and cancer. Between December 2019 and June 2024, the CO-19 PDB 2.0 systematically collected and organized 120 datasets into six distinct categories, each catering to specific functionalities. These categories encompass a chemical structure database, a digital image database, a visualization tool database, a genomic database, a social science database, and a literature database. Functionalities range from image analysis and gene sequence information to data visualization and updates on environmental events. CO-19 PDB 2.0 has the option to choose either the search page for the database or the autonotification page, providing a seamless retrieval of information. The dedicated page introduces six predefined charts, providing insights into crucial criteria such as the number of cases and deaths', country-wise distribution, 'new cases and recovery', and rates of death and recovery. The global impact of COVID-19 on cancer patients has led to extensive collaboration among research institutions, producing numerous articles and computational studies published in international journals. A key feature of this initiative is auto daily notifications for standardized information updates. Users can easily navigate based on different categories or use a direct search option. The study offers up-to-date COVID-19 datasets and global statistics on COVID-19 and cancer, highlighting the top 10 cancers diagnosed in the USA in 2022. Breast and prostate cancers are the most common, representing 30% and 26% of new cases, respectively. The initiative also ensures the removal or replacement of dead links, providing a valuable resource for researchers, healthcare professionals, and individuals. The database has been implemented in PHP, HTML, CSS and MySQL and is available freely at https://www.co-19pdb.habdsk.org/. Database URL: https://www.co-19pdb.habdsk.org/.

SDN-based reliable emergency message routing schema using Digital Twins for adjusting beacon transmission in VANET

Digital Twin (DT) has revolutionized the contextualized digital environment. This advancement enables real-time monitoring and simulation of events, leading to more effective decision-making. In smart transportation, DT plays a crucial role in enhancing various aspects of road decision-making, including optimizing routing decisions for Emergency Message (EM) forwarding in Vehicular Ad hoc Networks (VANETs). In this study, DT has integrated with cutting-edge technologies such as Software-Defined-Network (SDN) and geographically distributed computing (fog computing) to elevate the position-based routing behavior in two directions: selecting the optimal next-hop and taking control of periodic messages (beacon transmission). The nature of routing decisions can be complex due to constant movement and frequent position changes of vehicles in the VANET system. Merely selecting the next-hop vehicle without considering its stability and predictability can result in suboptimal routing choices. To this end, SDN based on Reliable Emergency Message Routing Schema (SDN-REMR) is introduced. This schema utilizes DT and aims to leverage the behaviors of moving vehicles to enhance the delivery of EM by providing a reliable routing mechanism. To eliminate unstable neighbors from the list of potential next-hops, SDN-REMR forecasts the relative positions of surrounding vehicles using Euclidean distance and position information. Moreover, SDN-REMR uses the movement information collected from vehicles (such as position, speed, and power consumption) to reduce the possibility of a link disruption and select the best next-hop for reliable communication. SDN-REMR enables the Store-Carry-Forward (SCF) approach to ensure packets are successfully forwarded to the destination, even in challenging network conditions. This control strategy aims to strike a balance between maintaining reliable communication and minimizing congestion in the network. The experimental results prove that there are 42.6%, 76.22%, 76.22%, and 22.2% enhancement in terms of network throughput, total delivered packets, number of dropped packets, and routing overhead.

Enhanced Hybrid Routing Protocol for Energy-Efficient Multipath Routing in Manets

Mobile Ad Hoc Networks (MANETs) pose challenges in managing dynamic energy consumption and optimizing network lifetime. This study proposes an improved hybrid routing protocol by integrating situation-adaptive routing and energy-efficient multipath routing strategies. We identified two promising routing protocols, FF-AOMDV and STFDR. While FF-AOMDV minimizes energy consumption, it ignores loss of power, resulting in link failures and reduced MANET lifetime. To address this, we introduce PLA-AOMDV, which efficiently manages power loss and outperforms FF-AOMDV in experimental results. However, PLA-AOMDV needs enhancements in addressing link breakage and utilization. Thus, we propose ELA-AOMDV to maximize energy efficiency and load balancing, refining route selection for better outcomes. Experimental findings demonstrate ELA-AOMDV's superiority over PLA-AOMDV in throughput, packet dropping rate, energy consumption, and network lifetime. Additionally, we present an Improved Hybrid Routing Protocol (IHRP), which combines DMR, AOMDV, OLSR, and AODV. Leveraging the strengths of these protocols, IHRP exhibits superior performance compared to AOMDV, ZRP, AODV, and OLSR. It proposed enhanced hybrid routing protocol effectively addresses the challenges of dynamic energy consumption and efficient multipath routing in MANETs, improving network performance and lifetime.

Performance Analysis of Non-Realistic Routing Protocol using Random Waypoint Model in MANET

A mobile ad hoc network (MANET) is a collection of wireless nodes connected via wireless networks and has no set structure. MANETs feature a self-organized routing topology in which mobile nodes are free to move, making it difficult and crucial to construct a stable and reliable network. Thus, failure of the route is also regarded as a prime factor affecting the efficiency of any MANET routing protocol. The breaking of the connection between two routes or more nodes will cause the failure of the route specifically in the non-realistic routing protocol. In a network of mobile nodes, the link break is mainly based on the mobility of individual nodes. Therefore, the objective of this research is to investigate the performance of proactive DSDV and reactive AODV routing protocol using the Random Waypoint(RWP) mobility model in MANET. NS-2 network simulator is used to simulate the MANET environment and BonnMotion is to create a movement of mobile nodes that integrate with the routing protocol. The network performance metrics used are throughput, packet delivery ratio, and average end-to-end delay. In addition, three simulation scenarios have been conducted to compare AODV and DSDV routing protocols with varying numbers of nodes, a comparison of AODV and DSDV routing protocols with varying pause time, and a comparison of AODV and DSDV routing protocols with varying mobility speed. The result from the three scenarios analysed and concluded that the RWP mobility model with AODV gives a better performance of throughput with 869.69 kbps and Packet Delivery Ratio (PDR) with 83.00% meanwhile, RWP with DSDV is better for the average end-to-end delay(EED) with 212.970 bps.

Curving THz wireless data links around obstacles

A key challenge in millimeter-wave and terahertz wireless networks is blockage of the line-of-sight path between a base station and a user. User and environmental mobility can lead to blockage of highly directional beams by intervening people or objects, yielding link disruptions and poor quality of service. Here, we propose a solution to this problem which leverages the fact that, in such scenarios, users are likely to be located within the electromagnetic near field of the base station, which opens the possibility to engineer wave fronts for link maintenance. We show that curved beams, carrying data at high bit rates, can realize a link by curving around an intervening obstacle. We develop a model to analyze and experimentally evaluate the bandwidth limitations imposed by the use of self accelerating beams. We also demonstrate that such links employ the full aperture of the transmitter, even those portions which have no direct line of sight to the receiver, emphasizing that ray optics fails to capture the behavior of these near-field wave fronts. This approach, which is ideally suited for use at millimeter-wave and terahertz frequencies, opens vast new possibilities for wave front management in directional wireless networks.

The broken link: Learning habitus of rural students in county key high schools during COVID-19 related school closure in China

School closures and remoted learning during the COVID-19 pandemic have negatively affected students worldwide, particularly those from disadvantaged families. This study examines the experiences of remote learning in county key high schools in China, which link selected rural students with urban educational resources and future social mobility. Our qualitative data suggest that during the school closure, the cultivation of a learning habitus of hardworking sprits and aspiration of upward mobility at school was disrupted, despite the devoted efforts of teachers and staff, and the students largely felt lost in their home environment in rural villages. Only a few of the students were pulled back to the school learning habitus by committed teachers, educated family members, or self-disciplining, combating the adverse impacts of COVID-19 related school closures. Implications for habitus change, remote learning, county key high schools, and educational development in rural China are also discussed.

SDG 4 mid-point challenge: Fixing the broken interlinkages between education and gender equality

While the UN's SDG Summit 2023 marks the midpoint of the 2030 Agenda, many of the SDGs are moderately to severely off-track. In this commentary, we place emphasis on addressing hidden quality gaps that can help fix broken interlinkages, and in turn create positive correlations and harness untapped synergies, across goals. To illustrate broken interlinkages between SDGs 4 and 5, we focus on the puzzle of “education without employment” in South Asia. We argue that a hidden form of gender inequality in education quality -- gender stereotypes in learning materials – potentially undermines interlinkages between SDG targets in the region, among other factors. If gender inequality in educational production is overlooked, a focus on enrolling more girls will not fix the broken links between SDGs 4 and 5. Addressing hidden gaps in public service quality should be a priority during the final half of the SDG campaign.

SCFS-securing flying ad hoc network using cluster-based trusted fuzzy scheme

AbstractFlying Ad hoc Networks have emerged as a promising technology for number of real-time applications. However, the flexible and unstructured characteristics of these networks make them vulnerable to security threats posed by malicious nodes, such as denial of service attacks, node impersonation, and information breaches. Another major issue is the consideration of those nodes being unable to prove their trustworthiness due to factors like hardware or software failure, or by link interruptions, during the processing of detection of false nodes in the network. The existing mechanisms encompassing encryption, authentication, and intrusion detection highlight limitations to secure real-time applications and services due to the high speed of flying nodes and the absence of fixed network structures. To overcome these constraints, this research paper incorporates a novel framework for evaluating and improving the security of network by introducing an innovative cluster-based approach. Moreover, it presents a fuzzy model that dynamically estimates the trust levels of both individual nodes and clusters, by assigning weight to the parameters to address vulnerabilities. Additionally, a trust reconfiguration mechanism is further proposed to address the issue of nodes unable to substantiate their trust by providing them with additional chances based on the collective trust from previous evaluations. Further, the paper incorporates a dynamic reputation system to proficiently identify and separate malicious and selfish nodes from the network. Simulation results indicate a significant improvement in performance metrics, with a considerable reduction in delay and drop ratio by 41.46% and 36.37%, respectively, while the sufficient rise of 54.71% and 46.05% in throughput and coverage, respectively, comparing with the considered state-of-art.

Centralized multicasting AODV routing protocol optimized for intermittent cognitive radio ad hoc networks

The advancement of wireless technology is affected by Spectrum scarcity and the overcrowding of free spectrum. Cognitive Radio Ad Hoc Networks (CRAHNs) have emerged as a possible solution to both the scarcity and overcrowding challenges of the spectrum. The CRAHNs ensure that the Secondary Users (SUs) do co-exist with Primary Users (PUs) in a non-interfering manner. The SUs access the licensed spectrum opportunistically when they are idle. CRAHNs have many use cases which include intermittent networks here referred to as intermittent CRAHNs (ICRAHNs). For example, the Military (MCRAHNs). MCRAHN is complex and characterized by a dynamic topology which is subject to frequent partitioning and route breakages due to attacks and destruction in combat. This study optimizes the routing protocols for intermittent networks such as the MCRAHNs. ICRAHN routing is a challenge due to the network’s intermittent attribute, which is subject to destruction in the case of MCRAHN which is characterized by frequent link breakages. To better understand the routing in this network scenario, this paper presents two analytic models for the AODV and MAODV protocols based on queuing theory. The analytic models simulate unicast and multicast AODV in terms of factors such as queuing delay, throughput, and network scalability. Numerical analysis shows that MAODV outperforms AODV. Furthermore, the suggested routing protocols' performance was tested using network simulations utilizing the following metrics: throughput, Routing Path delay, Node Relay delay, and Spectrum Mobility delay. The simulation findings suggest that the MAODV protocol outperforms the AODV protocol.