Non-uniform Node Distribution Research Articles

Distributed acoustical meshes on the Internet

An acoustical mesh distributed over the Internet is constructed of scattering junction nodes with bidirectional audio streaming between them. Components of common network music performance (NMP) applications like JackTrip can be adapted for experimentation with the concept. In the usual context of ensemble NMP, an audio hub server accepts bidirectional audio connections from multiple clients. The clients are located apart from each other physically and the hub server handles audio to and from the ensemble of sites, typically comprising a band or choir. The usual spoke and wheel topology (single hub server/mulitple hub clients) requires some modifications to run as a mesh of interconnected scattering juntions. The resulting waveguide mesh topology is explored for its properties, some of which resemble extensions of waveguide mesh physical model simulations of musical instruments and rooms. The acoustical medium that this creates is a live, vibrating acoustic mesh across Internet space. Unique properties, such as non-uniform distribution of nodes, are described in an experiment that explores analogies to plates and membranes and is characterized by the inherently anisotropic propagation of the network.

Analysis of the dynamic response for Kirchhoff plates by the element-free Galerkin method

Dynamic response analysis involves examining structural behavior under dynamic loading conditions. Transient dynamic analysis emerges as a method employed to assess the responses of deformable bodies. Due to the depth analysis of transient responses for thin plates, the associated error analysis work becomes particularly important. In this work, we conduct stability and convergence analysis of the element-free Galerkin (EFG) method for the dynamic response of Kirchhoff plate model. We start by discretizing the thin plate dynamics using the EFG method for the spatial domain and the central difference scheme for the temporal domain. Stability and convergence analysis for transient responses, including deflection and moment responses, are derived similarly to those in two-dimensional transient structural dynamic analysis. The key to the analysis is transforming the governing equations and clamped boundary conditions into a weak formulation with penalty terms using the penalty method. The main results demonstrate a significant correlation between the error estimate and both nodal spacing and time step size. Additionally, the continuity of the approximation functions and the selection of penalty factors significantly affect numerical accuracy. To validate the theoretical results, we conduct numerical experiments involving clamped square and L-shaped plates with uniform and nonuniform node distributions, as well as a perforated plate model. Furthermore, we investigate the impact of node influence domains and penalty factors on numerical accuracy, facilitating parameter selection for practical engineering applications.

Enhancing RBF-FD Efficiency for Highly Non-Uniform Node Distributions via Adaptivity

Enhancing RBF-FD Efficiency for Highly Non-Uniform Node Distributions via Adaptivity

Statistical properties and repetition rates for a quantum network with geographical distribution of nodes

Steady technological advances and recent milestones such as intercontinental quantum communication and the first implementation of medium-scale quantum networks are paving the way for the establishment of the quantum internet, a network of nodes interconnected by quantum channels. Here we build upon recent models for quantum networks based on optical fibers by considering the effect of a non-uniform distribution of nodes, more specifically based on the demographic data of the federal states in Brazil. We not only compute the statistical properties of this more realistic network, comparing its features with previous models but also employ it to compute the repetition rates for entanglement swapping, an essential protocol for quantum communication based on quantum repeaters.

Investigation and Analysis on Energy Efficient Stable Election Protocol (SEP) for WSN

Abstract: We study the impact of heterogeneity of nodes, in terms of their energy, in wireless sensor networks that are hierarchically clustered. In these networks some of the nodes become cluster heads, aggregate the data of their cluster members and transmit it to the sink. We assume that a percentage of the population of sensor nodes is equipped with additional energy resources—this is a source of heterogeneity which may result from the initial setting or as the operation of the network evolves. We propose SEP, a heterogeneous-aware protocol to prolong the time interval before the death of the first node (we refer to as stability period), which is crucial for many applications where the feedback from the sensor network must be reliable. SEP is based on weighted election probabilities of each node to become cluster head according to the remaining energy in each node. We show by simulation that SEP always prolongs the stability period compared to (and that the average throughput is greater than) the one obtained using current clustering protocols. We conclude by studying the sensitivity of our SEP protocol to heterogeneity parameters capturing energy imbalance in the network. We found that SEP yields longer stability region for higher values of extra energy brought by more powerful nodes. Sensor nodes usually have limited energy supply and they are impractical to recharge. How to balance traffic load in sensors in order to increase network lifetime is a very challenging research issue. Many clustering algorithms have been proposed recently for wireless sensor networks (WSNs). The use of mobile sinks has been shown to be an effective technique to enhance network performance features such as latency, energy efficiency, network lifetime, etc. In this paper, a modified Stable Election Protocol (SEP), which employs a mobile sink, has been proposed for WSNs with non-uniform node distribution. The decision of selecting cluster heads by the sink is based on the minimization of the associated additional energy and residual energy at each node. Besides, the cluster head selects the shortest path to reach the sink between the direct approach and the indirect approach with the use of the nearest cluster head. Simulation results demonstrate that our algorithm has better performance than traditional routing algorithms, such as LEACH and SEP.

Range-Free Localization Using Extreme Learning Machine and Ring-Shaped Salp Swarm Algorithm in Anisotropic Networks

Node localization is one of the basic requirements in various Internet of Things applications. Among a wide range of localization schemes, the range-free localization algorithm is promising as a cost-effective technique. However, the localization accuracy of this technique is susceptible to various anisotropy factors such as the existence of holes, non-uniform node distribution, and dynamic radio propagation pattern. To this end, an accurate range-free localization model using extreme learning machine and ring-shaped salp swarm algorithm is proposed for anisotropic wireless sensor networks. First, the integer hop count between two adjacent nodes is quantized as a real number according to the Jaccard coefficient of their shared neighbor nodes. Second, exploiting the strong generalization and fast learning speed of extreme learning machine, a distance mapping model based on the modified real hop count is developed for solving anisotropic signal attenuation. Third, the coordinate calculation of normal nodes is formulated as a minimum problem by taking into account the weighted squared error of estimated distance, and the bounding box method is utilized to initialize the possible location boundary area of normal nodes. Finally, the salp swarm algorithm based on the ring-shaped topology is designed to compute the coordinates of normal nodes. Extensive simulations on several network topologies are conducted with the effect of multiple anisotropic factors. Experimental results show that the proposed algorithm is superior to other developed ones not only in localization accuracy but also in robustness against network anisotropy.

Minimizing Energy Hole Problem Comparisons in Some Hierarchical WSN Routing Protocols

This paper study the efficient use of energy as a challenging task of designing these protocols. The energy holes are created due to non-uniform node distribution in the network when quickly drain the energy in a few nodes. It is studies removing energy holes by using sleep and awake mechanism for sensor nodes to save energy. This approach finds the maximum distance nodes to calculate the maximum energy for data. It intends to enumerate the dead nodes transmission, alive nodes, throughput, overhead and packet delivery ratio consumed by the entire network and affected by the network area changes. lastly, a brief performance analysis of Low Energy Adaptive Clustering Hierarchy (LEACH), Distributed Energy-Efficient Clustering (DEEC), Threshold sensitive Energy Efficient sensor Network protocol (TEEN) and Stable Election Protocol (SEP) is carried out considering metrics of the previous characteristics of wireless sensor network.

Influence of the Mesh Topology on the Accuracy of Modelling Turbulent Natural and Excited Round Jets at Different Initial Turbulence Intensities

The paper is aimed at an assessment of the importance of the coordinate system (Cartesian vs. cylindrical) assumed for simulations of free-round jets. The research is performed by applying the large eddy simulation method with spatial discretisation based on high-order compact difference schemes. The results obtained for natural and excited jets at three different turbulence intensity levels, Ti=0.01%,0.1% and 1.0%, are compared. In the case of the natural jet, it is found that both instantaneous and time-averaged results are significantly dependent on the coordinate system only for the lowest Ti. In this case, in the Cartesian coordinate system, the errors introduced by an azimuthal non-uniformity of the mesh seem to have a larger impact on the solutions than the disturbances generated at the nozzle exit. The azimuthal non-uniformity of the mesh also has a substantial influence on the results of the modelling of the excited jets. In this case, the excitation is introduced as time-varying forcing, with the frequency corresponding to half of the preferred mode frequency and the amplitude equal to 5% of the jet velocity. Such an excitation leads to the formation of the so-called side-jets being revealed as inclined streams of fluid ejected outside the main jet stream. Primary attention is paid to the mechanism of the formation of the side-jets, their number and location. The results obtained on Cartesian meshes show that for very low turbulence intensity levels (Ti=0.01%), the number and direction of the side-jets are dependent on the non-uniform distribution of the mesh nodes along the azimuthal direction of the jet. On the other hand, when the cylindrical coordinate system is used, the number of the side-jets and their locations are random and dependent only on inlet parameters. It has been demonstrated that the mechanism of side-jet formation is the same in both coordinate systems; however, its random nature can only be predicted when the cylindrical coordinate system is used.

Adaptive multi‐layer clustering strategies based on capacity weight for Internet of Things

SummaryDue to the requirements brought by diversification of IoT applications, differentiation of nodes' capability, dynamic communication environment and demands, the real‐time information of nodes (actual energy consumption, living nodes' density, pairwise nodes' communication radius) should be considered comprehensively for the clustering strategies of wireless sensor networks to achieve efficient, stable, and flexible performance with limited energy and different quality of service (QoS). This article proposes an improved dynamic multi‐layer clustering strategy for various IoT applications with heterogeneous nodes' energy, unpredictable or fast‐changing distribution of alive nodes, and dynamic scenarios. In addition, an adaptive adjustment strategy based on capability weight for multi‐layer clustering network is proposed to reduce the impact of unreasonable head selection cycle of clustering. By analyzing the node energy, the change of node locations and historical data transmission of cluster head, different capability weights are assigned to each node to adaptively re‐cluster the clusters with heavy load and poor performance, further make the network topology better match current situation and specified QoS requirements. Experimental results have demonstrated that proposed strategy can achieve less energy consumption, longer network lifetime, and better load balancing, especially for the cases with heterogeneous initial energy, nonuniform distribution, and higher density of nodes.

Leveraging Energy, Latency, and Robustness for Routing Path Selection in Internet of Battlefield Things

Internet of Battlefield Things (IoBT) connects massive tactical devices to collect battlefield situations and share perceived information. The IoBT can enhance the intelligent battlefield command, collaborative attack, and other applications, such as landmine trigger and post-war clearance. Existing routing path selection methods designed for wireless sensor networks (WSNs) are effective but still face challenges in IoBT scenarios. First, tactical devices follow nonuniform distributions with high density on boundaries in IoBT to prevent the location of devices from being speculated and protect strategic positions, which results in unbalanced energy consumption. Second, increasing latency in IoBT is caused by various data generation probabilities of tactical devices. Third, the military task features, such as landmine explosion, disconnection, and failure of tactical devices, may put forward special requirements on network robustness. To this end, we propose a routing path selection method with joint optimization in IoBT based on nonuniform node distributions and location-related data generation probabilities. Specifically, we first investigate and formulate the distribution and data generation probability of tactical devices. Based on the special features, energy consumption, latency, and network robustness are analyzed during multihop communications in IoBT. Then, a joint optimization problem is formulated to minimize energy consumption and latency, while maximizing the network robustness simultaneously. Furthermore, two path assignment algorithms are developed to solve this optimization problem. Finally, our simulation results show that the proposed routing path selection method can reduce energy consumption and latency with the guaranteed robustness of IoBT.

A cryptographic approach to prevent network incursion for enhancement of QoS in sustainable smart city using MANET

A city-wide communication network capable of supporting a range of applica- tions should be established through the use of wireless sensor networks that collect, analyze, and act on data in order to provide solutions for smart city im- plementation. A smart city network confronts a number of obstacles, including changing the network's coverage area to accommodate different applications, non-uniform node distribution, an increase in message volume, the use of multi- ple communication technologies, and node and message heterogeneity. Numer- ous aspects of smart cities are being investigated, with a few applications being developed in each. This article conducts a survey to describe various sensor network choices for smart cities. The research explores message transmission challenges via the lens of applications such as taxi sharing, ambulance services, and other emergency services that rely on real-time traffic data provided by the smart traffic domain to work successfully. Mobile Ad Hoc Networks (MANETs) are employed in a range of areas due to its advantage in rapidly establishing networks. The network will perform ideally if mobile nodes collaborate and trust one another; hence, message transmission for this service, as well as the utility of MANET routing algorithms, are examined.

Modeling and Analysis of HetNets With Interference Management Using Poisson Cluster Process

In typical wireless heterogeneous networks (HetNets), users are clustered around known hotspots, e.g., shopping centers or schools, but such a non-uniform distribution of nodes is difficult to analyze. This paper explicitly models this scenario, with macro base stations (MBSs) modeled by a homogeneous Poisson point process (PPP), and millimeter-wave small base stations (mmWave SBSs) and users clustered around the hotspot centers, forming two Poisson cluster processes (PCPs), respectively. Fractional frequency reuse (FFR) and coordinated multi-point transmission (CoMP) are assumed since they help to limit the co-tier interference and enhance the coverage and capacity of the network. We present a distance-based approach for grouping macro user equipments (MUEs) from the cell center (CC) and cell edge (CE) regions for FFR analysis. We first derive some distance distributions, including joint distance distribution from the typical user to the cooperative open-access mmWave SBS and distance distribution from the typical user to the non-cooperative open-access mmWave SBS. We obtain expressions for various performance metrics, including association probability, signal to interference-plus-noise ratio (SINR) coverage probability, and ergodic capacity, under these conditions. Due to the complexity of the exact expressions, we derive novel approximations, using Alzer's lemma, to obtain the lower bounds on coverage and ergodic capacity, which are shown to be accurate through Monte Carlo simulation. Simulation results analyze the effect of different parameters on the network performance to give some guidance for the design of future networks. Numerical optimization of a key parameter, in terms of association probability, coverage probability, and ergodic capacity, is enabled by our analysis.

A Novel Static Cluster-Based Hierarchical Protocol for Wireless Sensor Networks

Wireless sensor networks have recently gained a lot of attention from the scientific community due to their very wide spectrum of applications. In such networks, the sensor nodes have limited resources. These constraints impose many challenges to the design of related protocols. Especially, routing protocols should be energy-efficient for the prolonged network lifetime. The LEACH protocol is the most popular energy-efficient hierarchical clustering protocol for WSNs that was proposed for reducing power consumption. However, LEACH suffers from several drawbacks such as the non uniform distribution of Cluster Head nodes, the possibility of choosing a low energy node as Cluster Head, etc. In this paper, an attempt is made to overcome this shortcoming by introducing a new hierarchical clustering protocol, called SCHP (Static Cluster-based Hierarchical Protocol). The SCHP protocol is based on a static cluster creation and an optimal cluster head selection. Simulation results show that the proposal guarantees better performance than the LEACH Protocol that is considered as the baseline in the literature. We used many metrics, as packet loss rate, end-to-end delay, and energy consumption to evaluate the efficiency of our proposal. We show also that the SCHP protocol can improve the network lifetime.

Distributed consensus‐based routing protocol with multiple mobile sinks support for wireless sensor network

Non-uniform node distribution in a randomly deployed network causes inefficient routing when some abnormality or events at certain parts of the network cannot be detected due to a coverage hole problem. Existing works to improve routing efficiency in randomly deployed network utilise mobile sink to prolong nodes lifetime is either centred around the static sink or movement through random patterns. Few works had considered multiple mobile sinks to route packets in such network distribution. In fact, important aspect such as collaborations among mobile sinks is not well considered, where the decision made by each mobile sink in most existing approaches tend to maximise the individual sink's utility rather than benefiting wider parts of the network. Thus, a decision based on consensus may benefit more parties and eventually lead to better decision. A distributed collaboration mechanism may assist nodes mobility in improving routing efficiency. Thus, the authors proposed the consensus-based routing protocol, which aims to improve routing efficiency in randomly deployed network, by deciding relocation of mobile sinks based on coverage factor, in order to reduce energy consumption, providing more balance sinks distribution and better network coverage. Simulation results show good performances of proposed approach in terms of nodes lifetime, energy consumption, delay, packet delivery ratio and coverage hole, compared to other existing protocols.

Scaling Performance Analysis and Optimization Based on the Node Spatial Distribution in Mobile Content‐Centric Networks

Content‐centric networks (CCNs) have become a promising technology for relieving the increasing wireless traffic demands. In this paper, we explore the scaling performance of mobile content‐centric networks based on the nonuniform spatial distribution of nodes, where each node moves around its own home point and requests the desired content according to a Zipf distribution. We assume each mobile node is equipped with a finite local cache, which is applied to cache contents following a static cache allocation scheme. According to the nonuniform spatial distribution of cache‐enabled nodes, we introduce two kinds of clustered models, i.e., the clustered grid model and the clustered random model. In each clustered model, we analyze throughput and delay performance when the number of nodes goes infinity by means of the proposed cell‐partition scheduling scheme and the distributed multihop routing scheme. We show that the node mobility degree and the clustering behavior play the fundamental roles in the aforementioned asymptotic performance. Finally, we study the optimal cache allocation problem in the two kinds of clustered models. Our findings provide a guidance for developing the optimal caching scheme. We further perform the numerical simulations to validate the theoretical scaling laws.

Toward green computing in wireless sensor networks: prediction-oriented distributed clustering for non-uniform node distribution

Recently, researchers and practitioners in wireless sensor networks (WSNs) are focusing on energy-oriented communication and computing considering next-generation smaller and tiny wireless devices. The tiny sensor-enabled devices will be used for the purpose of sensing, computing, and wireless communication. The hundreds/thousands of WSNs sensors are used to monitor specific activities and report events via wireless communication. The tiny sensor-enabled devices are powered by smaller batteries to work independently in distributed environments resulting in limited maximum lifetime of the network constituted by these devices. Considering the non-uniform distribution of sensor-enabled devices in the next-generation mobility centric WSNs environments, energy consumption is imbalanced among the different sensors in the overall network environments. Toward this end, in this paper, a cluster-oriented routing protocol termed as prediction-oriented distributed clustering (PODC) mechanism is proposed for WSNs focusing on non-uniform sensor distribution in the network. A network model is presented, while categorizing PODC mechanism in two activities including setting cluster of nodes and the activity in the steady state. Further cluster set up activity is described while categorizing in four subcategories. The proposed protocol is compared with individual sensor energy awareness and distributed networking mode of clustering (EADC) and scheduled sensor activity-based individual sensor energy awareness and distributed networking mode of clustering (SA-ADC). The metrics including the overall lifetime of the network and nodes individual energy consumption in realistic next-generation WSNs environments are considered in the experimental evaluation. The results attest the reduced energy consumption centric benefits of the proposed framework PODC as compared to the literature. Therefore, the framework will be more applicable for the smart product development in the next-generation WSNs environments.

Centroid-Based Routing protocol with moving sink node for uniform and non-uniform distribution of wireless sensor nodes

A routing protocol called ‘Centroid-Based Routing (CBR)’ is proposed to optimize the total system energy for a given wireless sensor network. We have designed the CBR protocol to optimize the battery life of the sensor nodes, by using a mobile Sink Node (SN). In CBR, several clusters are formed for the sensor nodes and each cluster is assigned a ‘Cluster Head (CH)’ node, and these CHs act as a local Base Station. The SN moves to a coordinate point (Xc, Yc) which we call a ‘Centroid Point (CP)’ to collect data from the CH nodes. This ‘CP’ is dependent on the coordinates of all the CHs and also on their residual or remaining energy left over at any given round. This way the CH nodes have to pump a balanced amount of energy to send and receive data from SN, which makes the nodes last for a longer period. The simulation results imply that the CBR model is much efficient compared to other existing models in terms of energy utilization and network lifetime for the non-uniformly distributed sensor nodes in a given network area.

Algorithm for fairness in schedule lengths of sink-rooted trees in multi-sink heterogeneous wireless sensor networks

Sensor networks are used for observing some region of interest. Sensors sense different physical quantities and send to base station or sink. The tree based networks with TDMA as MAC protocol are preferable because of simplicity of tree and guaranteed data access in TDMA. Often sensor networks are multi-sink and multi-attribute networks. Multi-sink network means more than one sinks are present and so multiple sink-rooted trees are formed. When more than one types of nodes are deployed in the network, the network is known as heterogeneous network or multi-attribute network. Sometimes node density or heterogeneity is not uniform across entire network. As a result of non-uniform node distribution or non-uniform heterogeneity distribution, schedule lengths of sink-rooted trees are very different. Nodes part of trees with small schedule length will get more frequent transmission turns compared to those which belong to trees with large schedule length. To ensure fairness in terms of transmission opportunities, it is desired that schedule lengths should be balanced. In this work, an algorithm named as Schedule Length Balancing for Multi-sink HeTerogeneous networks (SLBMHT) is presented to balance schedule lengths. The SLBMHT algorithm is evaluated through simulations. It is found that the SLBMHT algorithm results in 8–56% reduction in schedule length difference of trees. It also results in 2–17% energy savings during data transmission phase. Only demerit is increase in control overhead. But as resulting increase in energy consumption is not much, it is overcome by savings in data energy consumption. Thus network lifetime is likely to increase.

Enhanced Sleep/Awake Schedule with Multi-Hop Hierarchical Routing Algorithm for Wireless Sensor Networks

Non-uniform deployment of sensor nodes, energy constraints, dead nodes, interference links are the major limitations of WSN performance. Energy consumption, life time improvement are the key parameters to increase the throughput of WSN. For limiting the energy consumption of sensor nodes, they are driven into sleep mode after they ends sensing. Efficient utilization of energy resources by clustered nodes is heavily affected by cluster head selection. This work focuses on reducing the energy consumption by proposing an efficient enhanced energy aware multi-hop hierarchical routing algorithm. In order to overcome energy holes drainage problem due to non-uniform node distribution in the network, an energy hole removing mechanism keeps a node into sleep mode if the node energy is less than the threshold. The comparison results shows proposed algorithm is more efficient than other existing algorithms.

Efficient parent selection for RPL using ACO and coverage based dynamic trickle techniques

Routing protocol for low-power and lossy networks (RPL) plays a vital role in the architecture of the IoT. The RPL follows the trickle algorithm and the distance based parent node selection. The trickle algorithm establishes a destination oriented directed acyclic graph (DODAG) with suppressed broadcasting. The broadcast suppression lacks in handling network coverage and load imbalance issues under the nonuniform node distribution. In addition, the DODAG construction exclusively depending on a single routing metric to identify an energy efficient and reliable routing paths. This article proposes an energy efficient RPL (E-RPL) protocol that consists of ACO based multi-factor optimization for parent selection and coverage based dynamic trickle algorithm for energy efficient DODAG construction without compromising network coverage and reliable data routing. The ACO considers the expected transmission count (ETX) and rank value as pheromone factors, whereas the residual energy and children count as heuristic factors. To balance the conflicting factors of ETX, rank, delay, and energy consumption, the E-RPL exploits the parent–child relationship factor as a pheromone evaporation factor. Moreover, the weight based algorithm is utilized to combine pheromone, heuristic, and pheromone evaporation factors towards a single objective function. To build an optimal DODAG structure with a reduced routing overhead, the E-RPL introduces concentric corona based network partition and decides the value of broadcast count dynamically concerning the node density and coverage. Finally, the performance of E-RPL is evaluated using Cooja simulator. The E-RPL attains 90% of the packet delivery ratio while spending 0.532 mJ over 30 node topology.