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The 6TiSCH protocol (IEEE 802.15.4e) is crucial for the Industrial Internet of Things (IIoT), utilizing a time-slotted channel hopping (TSCH) mode based on node distribution. In this study, we propose an innovative cell allocation strategy based on node position clustering using the K-means algorithm, specifically designed to address congestion and optimize resource distribution in the 6TiSCH network. Our mechanism effectively groups nodes into clusters, allowing for dynamic adjustment of cell capacities in congested areas by analyzing traffic patterns and the spatial distribution of nodes. This clustering approach enhances the efficiency of slot frame utilization and minimizes communication delays by reducing interference and improving routing stability. The proposed strategy leverages the clustering results to improve cell usage efficiency and reduce communication latency between nodes. By tailoring cell allocation to the specific traffic needs of each cluster, we significantly reduce packet loss, manage congestion more effectively, and enhance data transmission reliability. We evaluated the clustering method using the K-means algorithm through experiments with the 6TiSCH simulator. Additionally, we considered using objective functions in Routing Protocol for Low-Power and Lossy Networks (RPL), such as OF0 and MRHOF, to assess clustering results and their impact on throughput and packet delivery. Our method resulted in significantly improved average performance metrics. Under the OF0 routing protocol, we achieved a 30.01% latency reduction, a 15.95% faster joining time, an 8% higher packet delivery ratio, and a 13.82% throughput increase. Similarly, we observed a 12.34% improvement in packet delivery ratio, 21.06% latency reduction, 12.68% faster joining time, and 25.97% higher throughput speed with the MRHOF routing protocol. These findings highlight the effectiveness of the improved cell allocation strategy in congested 6TiSCH environments, offering a better solution for enhancing network performance in IIoT applications. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) play a pivotal role within the Internet of Things (IoT) framework by seamlessly integrating sensor node functionalities with wireless connectivity. A critical research area regarding WSNs revolves around mitigating the constraints imposed by sensor node power consumption. Consequently, the estimation of a sensor node’s location via optimal power has emerged as a significant focus in WSN research. The range-free estimation method is particularly suitable because of its simplicity and lack of reliance on additional hardware or excessive power consumption. It hinges solely on the hop count, which is defined as the number of hops traversed. An early pioneering work in this domain is the Distance Vector-Hop (DV-Hop) localization algorithm, which accurately determines the locations of unknown nodes without requiring specific coverage areas covered by anchor nodes. However, the accuracy of this method depends upon several factors, including node density and the connectivity status of individual sensor nodes, resulting in low accuracy. Thus, this research introduces an algorithm that estimates the distance between a pair of sensor nodes by leveraging the relationship between the distance and the number of sensor nodes present in the intersection area between the pair. Furthermore, the connectivity status of each sensor node within this intersection area is accounted for to increase the precision of distance estimation. To assess the effectiveness of the proposed scheme, the simulation results are compared against those obtained via other recent localization algorithms, which are based on hop counts, namely, DV-Hop, DV-maxHop, GAPSODV-Hop, DECHDV-Hop, and PM.

Wireless Multimedia Sensor Networks (WMSNs) have been an essential part of our lives, with various applications from disaster assistance to medical services. As a result, the lifetime and energy consumption of WMSNs have become challenging research issues. In the previous decades, a large number of protocols have been established to improve the energy efficiency of WMSNs. One of the proposed solutions is clustering. The cluster head selection criteria, network architecture, and heterogeneity are mostly addressed in these protocols. In this paper, we proposed an Energy-Efficient Multipath Clustering with Load Balancing Routing Protocol for Wireless Multimedia Sensor Networks (EEMCL). In the proposed protocol, the main cluster heads (MCHs) are preselected in each cluster in the network field with more energy than normal sensor nodes. The selection of two secondary cluster heads (SCHs) by the main cluster heads algorithm is used in which nodes have higher energy will be chosen as SCHs. Moreover, inter-cluster multi-hop routing with the help of MCHs can enhance the network lifetime when the sink is located at the corner of the network area. The MATLAB simulation tool is used to investigate the performance of the proposed protocol EEMCL. The results have been shown that the best position of the base station (BS) is at the center of the network area which can prolong the lifetime of sensor nodes, and random distribution of the sensor nodes gives better performance relating to the residual energy and the nodes still alive than static distribution. [ABSTRACT FROM AUTHOR]

Community detection in complex networks has become an important step in understanding the structure and behaviour of networks in many fields. However, both standard node clustering and the relatively new link clustering methods have problems that make it hard to find combined clusters. Networks have been used to depict many types of real-world systems, such as those involving the transmission of information, the movement of funds, and biological processes. Communities are key structures for comprehending the structure of actual networks. The purpose of community detection is to identify meaningful subsets of these networks. Mesoscopically, a community consists of highly interconnected nodes within each subcommunity yet less strong connections across subcommunities. Communities can share a node or numerous nodes with overlapping. Evaluating the performance of a community detection method is crucial. Grouping the network's nodes into a family of subsets called clusters such that each cluster comprises similar nodes concerning the overall network structure is the problem of detecting overlapping communities in a network. Meanwhile, it has been shown that many methods for finding cluster centers have inherent flaws. Most methods are vulnerable to initial seeding and built-in variables, while others fail to highlight substantial overlaps. This article proposes the Structural Centrality Approach for Local Overlapping Community Detection (SCA-LOCD). It provides a novel approach to regional development that emphasizes the role of systems in identifying cluster centers. The fundamental concept behind this strategy is to identify structural centers in societies with coherent structures and then increase these centers using weighted methods and search engine techniques. Experimental results on synthetic and network systems show that the suggested technique is efficient and fascinating for detecting overlapped communities. It shows the success of regional extension strategies in identifying coherent groups and producing reliable classification results. [ABSTRACT FROM AUTHOR]

Achieving interpretable embedding of real network has a significant impact on network analysis tasks. However, majority of node embedding-based methods seldom consider the rationality and interpretability of node embedding. Although graph attention networks-based approaches have been employed to improve the interpretability of node embedding, they are implicitly specifying different weights to different nodes in a neighborhood. In this study, we present node embedding with capsule generation-embedding network(CapsGE), which is a novel capsule network-based network architecture, and uses node density based on the definition of uncertainty of node community belongings to explicitly assign different weights to different nodes in a neighborhood. In addition, this model uses the proposed cognitive reasoning mechanism for the weighted features to achieve rational and interpretable embedding of nodes. The performance of the method is assessed on node classification task. The experimental results demonstrate its advantages over other methods. [ABSTRACT FROM AUTHOR]

In a real-world, networked system, the ability to detect communities or clusters has piqued the concern of researchers in a wide range of fields. Many existing methods are simply meant to detect the membership of communities, not the structures of those groups, which is a limitation. We contend that community structures at the local level can also provide valuable insight into their detection. In this study, we developed a simple yet prosperous way of uncovering communities and their cores at the same time while keeping things simple. Essentially, the concept is founded on the theory that the structure of a community may be thought of as a high-density node surrounded by neighbors of minor densities and that community centers are located at a significant distance from one another. We propose a concept termed "community centrality" based on finding motifs to measure the probability of a node becoming the community center in a setting like this and then disseminate multiple, substantial center probabilities all over the network through a node closeness score mechanism. The experimental results show that the proposed method is more efficient than many other already used methods. [ABSTRACT FROM AUTHOR]

Wireless Sensor Networks (WSN) have widely grown worldwide and are utilized in all innovative applications, yet there are problems such as data overloading, packet drop, and lower data transmission rate. All these issues have been engendered due to the high energy consumption problem. The node consumes more energy and has less lifetime that might be disabled during the data transmission. To address these problems, a novel Wolf Fuzzy-based Aggregator Node selection (WFbANS) protocol is designed for the WSN environment. Initially, the node's parameters were validated and selected for the cluster hub. Consequently, the workless node has been identified to enable the sleep state. Furthermore, the planned energy-optimized model is tested in the MATLAB environment. Finally, the data was transferred, and the communication parameters were noted and compared with other models. The presented model has recorded the finest throughput rate of 350 Kbps, a data transfer rate of 99.7%, less energy consumption of 0.7 J, less packet drop of 2%, and a minor communication delay of 90 ms. [ABSTRACT FROM AUTHOR]

Vehicular ad hoc Network (VANET) is one of the recently growing trends which motivate the provision of several service providers in the urban areas. In VANETs, the vehicles represent the nodes in the network topology that needs to guarantee better cooperation when there is a higher node density. Moreover, the problem of determining an optimal route and achieving network scalability is a herculean task. In this context, the incorporation of a potential clustering algorithm has the possibility of improving the road safety and facilitating a reliable option of promoting message routing. The clustering protocols are determined to be the ideal candidate for solving the problems of network scalability to guarantee reliable data dissemination. In this paper, Remora optimization algorithm-based Optimized Node Clustering (ROAONC) Technique is proposed for node clustering in VANETs to achieved optimal CH selection process. This ROAONC scheme was proposed for minimizing network overhead in the scenarios of unpredictable node density. The simulation results of this ROAONC scheme confirmed better performance in terms of transmission range, node density, network area and number of clusters compared to the competitive ant colony, grey wolf, grasshopper, and dragonfly optimization algorithm-based clustering protocols.

Long Range (LoRa) is an interference-free, single-hop, low-power wide area network (LPWAN) technology. LoRa offers customization of its physical layer parameters like spreading factor, coding rate, bandwidth, and transmission power to achieve high network coverage. Requirements for high coverage precipice the problem of high energy consumption. As a solution, our article presents an energy-efficient data packet aggregation scheme for LoRa communication to reduce high energy consumption. We propose a load balancing algorithm that yields better results in network communication. On comparing data aggregation strategy in LoRa with conventional star connected LoRa communication, and with other existing protocols our approach shows significant improvement in performance and energy saving. By adopting our strategy, conventional LoRa networks can achieve a longer lifetime and network stability. [ABSTRACT FROM AUTHOR]

Sensors in underwater wireless sensor networks (UWSNs) can drift up to 3 m/s due to ocean currents, marine organisms, or passing vessels. In existing node deployment and localization techniques, node mobility and network disconnections are not taken into account. This article proposes a dynamic topology control algorithm for node deployment (DTCND) in mobile UWSN. This work aims to monitor the node mobility to predict nodes' location for ensuring coverage and connectivity. The sensor nodes are deployed randomly at different depths. The anchor nodes observe the signal quality index, energy drain rate, and node density at every time interval and detect node disconnections based on the variations in these observed metrics. After receiving the beacon messages from the anchor nodes, the courier nodes incline to move toward the target region for satisfying the coverage and connectivity constraints. Simulation results show that the proposed algorithm attains 5% higher connectivity when compared to energy‐efficient localization algorithm (EELA) and 9% higher connectivity when compared to adaptive triangular deployment algorithm (ATDA). The residual energy is also higher by 3% and 18% when compared to EELA and ATDA, respectively. The deployment cost and delay of DTCND also decrease when compared to EELA and ATDA, which results into efficient data collection. [ABSTRACT FROM AUTHOR]

In mobile adhoc networks (MANETs), the most essential problem is to ensure the quality-of-service (QoS) during data transmission via multiple paths from a source to the destination node. To tackle this problem, a topological change adaptive adhoc on-demand multipath distance vector (TA-AOMDV) routing protocol was developed, which ensures QoS according to the different parameters for high-speed node mobility. But, it did not consider the path stability related to the node density, which also affects the routing efficiency. Hence, this paper develops a reliable and stable TA-AOMDV (RSTA-AOMDV) routing protocol that applies a new forwarding strategy to enhance the path reliability and stability for data transmission. In this protocol, every origin node relays data packets to the target in a hop-by-hop manner depending on local information gathered from its one-hop adjacent during the forwarding phase. Also, two different metrics are considered: (i) destination region selection (DRS) and (ii) weighted closeness and connectivity (WCC) to find the stable path from the source to the destination node. During the adjacent finding phase, a forwarding node self-selection mechanism is introduced to reduce the communication overhead due to the high node density and severe congestion. Finally, this protocol is simulated for 2 different cases: (1) a varying node mobility and (2) varying number of nodes. In the case of high-speed node mobility, i.e. 50m/s, the RSTA-AOMDV protocol achieves a 50.7 % packet delivery ratio (PDR), 109.4ms end-toend delay (E2E-D), 158.51Kbps throughput, 73.4 % normalized routing overhead (NRO) and 11J mean energy consumption (MEC) compared to other existing protocols. Similarly, in the case of high node densities, i.e. when the number of nodes is 100, the RSTA-AOMDV protocol achieves a 66.5 % PDR, 1485.74ms mean E2E-D, 639.7Kbps throughput, 15 % NRO and 22.7J MEC compared to the existing protocols. [ABSTRACT FROM AUTHOR]

Vehicular ad hoc Network (VANET) is one of the recently growing trends which motivate the provision of several service providers in the urban areas. In VANETs, the vehicles represent the nodes in the network topology that needs to guarantee better cooperation when there is a higher node density. Moreover, the problem of determining an optimal route and achieving network scalability is a herculean task. In this context, the incorporation of a potential clustering algorithm has the possibility of improving the road safety and facilitating a reliable option of promoting message routing. The clustering protocols are determined to be the ideal candidate for solving the problems of network scalability to guarantee reliable data dissemination. In this paper, Remora optimization algorithm-based Optimized Node Clustering (ROAONC) Technique is proposed for node clustering in VANETs to achieved optimal CH selection process. This ROAONC scheme was proposed for minimizing network overhead in the scenarios of unpredictable node density. The simulation results of this ROAONC scheme confirmed better performance in terms of transmission range, node density, network area and number of clusters compared to the competitive ant colony, grey wolf, grasshopper, and dragonfly optimization algorithm-based clustering protocols. [ABSTRACT FROM AUTHOR]

LoRaWAN is one of the leading low power wide area network (LPWAN) technologies that compete for the formation of big scale Internet of Things (IoT). It uses LoRa (Long Range) protocol to achieve long range, low bit rate and low power communication. Large scale LoRaWAN based IoT deployments can consist of battery powered sensor nodes. Therefore, the energy consumption and efficiency of these nodes are crucial factors that can influence the lifetime of the network. However, there is no coherent experimental based research which identifies the factors that influence the LoRa energy efficiency at various nodes density. In this paper, results on measuring the packet delivery ratio, packet loss, data rate and energy consumption ratio (ECR) to gauge the energy efficiency of LoRa devices at various nodes density are presented. It is shown that the ECR of LoRa is inversely proportional to the node's density and that the ECR of the network is smaller at higher traffic indicating better network energy efficiency. It is also demonstrated that at high node density, spreading factor SF of 7 and 9 can improve the energy efficiency of the network by 5 and 3 times, respectively, compare to SF 11. [ABSTRACT FROM AUTHOR]

Remote sensor systems experience basic investigation of network security because of inexplicable operational imperatives. The challenge flinches with the fragment of worms in the remote system. A solitary contaminated hub is adequate to spread the worms over the entire system. The tainted hub hastily contaminates the contiguous hubs in a relentless way. In this paper, a scientific model depending on pandemic hypothesis is proposed which is an enhancement of the SIRS, SEIS, SEIRS models. SEIQRV (susceptible-exposed-infectious-quaraintain-recovered-vaccinated) model enriched with the additive white noise conquers the hindrances of existing models. Using Routh-Hurwitz criteria, reproduction number, existence of steady states, and stability about endemic steady state are analyzed. The proposed system's stability is substantiated varying for different values of communication radii and node densities. The additional constituent to the proposed model is the stochastic fluctuation implemented and the examination of the stochastic variations. This model incorporates a limited correspondence span and the related hub thickness. The assessment of the proposed model with other existing models are presented and analyzed based on different executions. [ABSTRACT FROM AUTHOR]

Multiple-input multiple-out (MIMO) equipment improves the spectral efficiency of wireless local area network (WLAN) systems. However, in a large-scale or dense MIMO WLANs, overlapping radio cells or basic service sets (BSSs) are inherent. This prevents multiple concurrent transmissions and degrades spatial reuse. The inability to separate multiple simultaneous transmissions in space is detrimental to overall system performance. The carrier sense multiple access collision avoidance (CSMA/CA) protocol uses the physical carrier sensing (PCS) threshold to determine channel state at the physical layer (PHY) and decide on the number of concurrent transmissions allowed per time slot. Since the PCS threshold determines the spatial reuse under the CSMA/CA protocol, which consequently determines the interference level and the network aggregate throughput, we address PCS threshold selection for dense uplink (UL) MIMO WLAN systems. A closed-form expression is derived for selecting the PCS threshold based on the fundamental parameters of the network where nodes are randomly placed according to a Poisson point process (PPP). We obtain the PCS threshold value that maximizes the spatial density of throughput (SDT) and study the effectiveness of the proposed framework under moderate to high node density. In addition, we analyze the effect of WLAN density on interference from concurrent transmitters. The key observation is that PCS threshold selection should take into account key network characteristics including node density, target SINR or threshold, path-loss exponent and antenna configuration.

Abstract- Efficient message delivery in city environment is required to ensure driver’s safety and passenger’s comfortability. In cities of developed nations, routing of data in vehicular Ad hoc Network (VANET) faces many challenges such as radio obstacles, mobility constraints and uneven nodes distribution. These factors primarily makes communication between vehicles complex. To overcome and transmit data traffic effectively in city environment in the presence of above-mentioned challenges, evaluation of some network parameters conducted. The selected metrics are packet delivery ratio (PDR), end-to-end delay and routing overhead. These are based on three performance of position-based routing protocols: Anchor–based Street and Traffic Awareness Routing (A-STAR), Greedy Perimeter Coordinator Routing (GPCR) and Contention Based Forwarding (CBF) with the help of Simulation of Urban Mobility (SUMO) to generates vehicle mobility in city environment and network simulator (OMNeT++) to creates and calculates needed components. The speed of the vehicles and node density were varied in this process, and the simulated results showed that CBF outperforms significantly than A-STAR and GPCR in terms of packet delivery ratio as the speed varied and with a better end-to-end delays and routing overhead at a lower speed. In addition, CBF performs better than A-STAR and GPCR in terms of packet delivery ratio as the node varied with a better end-to-end delay, and a better routing overhead at a lower node density.

Opportunistic communication between two encountered nodes is commonly established using a radio technology such as Wi-Fi or Bluetooth. One issue involved in the opportunistic communication is a trade-off between the connection time and probability with resource consumption. This paper includes a comprehensive study of density analyze for decentralized distributed opportunistic communications using Wi-Fi technology. We study and analyze the contact probability and energy efficiency of variant density in particular area. The contribution of this paper is to analyze the impact of density on the connection probability and resources. Furthermore, we present a simulation study framework to analyze the contact event with a view of energy consumption, the study gives a detailed contact information such as contact probability based on node density and transmission range in particular area, also, the beacon exchange process as an element of channel utilization and energy consumption. We present influence evaluation of various parameters on each other and finally on the system performance.

VANET is a critical and demanding mission. Numerous methods exist, but none profits in a distributed fashion from physical layer parameters. This paper describes a method that enables individual nodes to estimate node density, independent of beacon messages, and other infrastructure-based information, of their surrounding network. In this paper, a discrete simulator of events was proposed to estimate the average number of simultaneously transmitting nodes, a functional channel model for the VANETs system, and a method of estimating node density. Proposed based on some equations to allow individual nodes to estimate their surrounding node density in real-time Optimized Node Cluster Algorithm with Network Density in which the composition of a cluster is triggered adjacent, these traffic signals is the same and has been predicated mostly on the position a vehicle might well take after crossing. Additional Ordered Tracking with Particle -Filter Routing in which receives simultaneous signal intensity versus node transmission and node density transmission. Conduct multiple location-related analyzes to test the plausibility of the neighboring singlehop nodes on mobility data. The system is designed to operate in the most complex situations where nodes have little knowledge of network topology and the results, therefore, indicate that the system is fairly robust and accurate. [ABSTRACT FROM AUTHOR]

A reliable and effective packet delivery system is challenging issue due to VANET's intense characteristics. Broadcast nature of opportunistic routing makes it more effective than the traditional routing in packet delivery and improves the efficiency of sending packets. One of the main problems in VANETs is the packet loss due to collision. Because of the rapid movement of vehicles, frequent changes in topology and the occupancy of the channel by beacon packets, high number of collisions occur in VANETs. In this paper, a new collision-aware opportunistic routing protocol called SCAOR is proposed for highways. To reduce collisions, the design of the SCAOR protocol is composed of two phases. In the first phase, a new metric called QAD, is presented and it contains three parameters of link quality, packet advancement, and node density. In the second phase, a cluster-based scheduling algorithm called CSA is provided for sending periodic beacon packets to reduce the occupancy time of the channel. The QAD metric along with the CSA scheduling algorithm alleviate collisions and improve the efficiency of the SCAOR protocol with respect to the specific features of the VANETs. The performance of the SCAOR routing protocol is compared to the EXOR and LSGO opportunistic routing protocols. Experimental results show improved network performance in terms of packet delivery, end-to-end delay, packet loss and throughput. [ABSTRACT FROM AUTHOR]

Species‐specific diversification rates, or 'tip rates', can be computed quickly from phylogenies and are widely used to study diversification rate variation in relation to geography, ecology and phenotypes. These tip rates provide a number of theoretical and practical advantages, such as the relaxation of assumptions of rate homogeneity in trait‐dependent diversification studies. However, there is substantial confusion in the literature regarding whether these metrics estimate speciation or net diversification rates. Additionally, no study has yet compared the relative performance and accuracy of tip rate metrics across simulated diversification scenarios.We compared the statistical performance of three model‐free rate metrics (inverse terminal branch lengths; node density metric; DR statistic) and a model‐based approach (Bayesian analysis of macroevolutionary mixtures [BAMM]). We applied each method to a large set of simulated phylogenies that had been generated under different diversification processes. We summarized performance in relation to the type of rate variation, the magnitude of rate heterogeneity and rate regime size. We also compared the ability of the metrics to estimate both speciation and net diversification rates.We show decisively that model‐free tip rate metrics provide a better estimate of the rate of speciation than of net diversification. Error in net diversification rate estimates increases as a function of the relative extinction rate. In contrast, error in speciation rate estimates is low and relatively insensitive to extinction. Overall, and in particular when relative extinction was high, BAMM inferred the most accurate tip rates and exhibited lower error than non‐model‐based approaches. DR was highly correlated with true speciation rates but exhibited high error variance, and was the best metric for very small rate regimes.We found that, of the metrics tested, DR and BAMM are the most useful metrics for studying speciation rate dynamics and trait‐dependent diversification. Although BAMM was more accurate than DR overall, the two approaches have complementary strengths. Because tip rate metrics are more reliable estimators of speciation rate, we recommend that empirical studies using these metrics exercise caution when drawing biological interpretations in any situation where the distinction between speciation and net diversification is important. [ABSTRACT FROM AUTHOR]

Autonomous and self-organizing wireless ad-hoc communication networks for moving objects consist of nodes, which use no centralized network infrastructure. Examples of moving object networks are networks of flying objects, networks of vehicles, networks of moving people or robots. Moving object networks have to face many critical challenges in terms of routing because of dynamic topological changes and asymmetric networks links. A suitable and effective routing mechanism helps to extend the deployment of moving nodes. In this paper an attempt has been made to analyze the performance of the Greedy Decision method (position aware distance based algorithm) for geographic routing for network nodes moving according to the random waypoint mobility model. The widely used GPSR (Greedy Packet Stateless Routing) protocol utilizes geographic distance and position based data of nodes to transmit packets towards destination nodes. In this paper different scenarios have been tested to develop a concrete set of recommendations for optimum deployment of distance based Greedy Decision of Geographic Routing in randomly moving objects network

Resource Searching is one of the key functional tasks in large complex networks. With the P2P architecture, millions of peers connect together instantly building a communication pattern. Searching in mobile networks faces additional limitations and challenges. Flooding technique can cope up with the churn and searches aggressively by visiting almost all the nodes. But it exponentially increases the network traffic and thus does not scale well. Further the duplicated query messages consume extra battery power and network bandwidth. The blind flooding also suffers from long delay problem in P2P networks. In this paper, we propose optimal density based flooding resource discovery schemes. Our first model takes into account local graph topology information to supplement the resource discovery process while in our extended version we also consider the neighboring node topology information along with the local node information to further effectively use the mobile and network resources. Our proposed method reduces collision at the same time minimizes effect of redundant messages and failures. Overall the methods reduce network overhead, battery power consumption, query delay, routing load, MAC load and bandwidth usage while also achieving good success rate in comparison to the other techniques. We also perform a comprehensive analysis of the resource discovery schemes to verify the impact of varying node speed and different network conditions.