Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Calculating the number of cluster heads based on the rate-distortion function in wireless sensor networks.

ABSTRACT: Due to limited resources in wireless sensor nodes, energy efficiency is considered as one of the primary constraints in the design of the topology of wireless sensor networks (WSNs). Since data that are collected by wireless sensor nodes exhibit the characteristics of temporal association, data fusion has also become a very important means of reducing network traffic as well as eliminating data redundancy as far as data transmission is concerned. Another reason for data fusion is that, in many applications, only some of the data that are collected can meet the requirements of the sink node. In this paper, we propose a method to calculate the number of cluster heads or data aggregators during data fusion based on the rate-distortion function. In our discussion, we will first establish an energy consumption model and then describe a method for calculating the number of cluster heads from the point of view of reducing energy consumption. We will also show through theoretical analysis and experimentation that the network topology design based on the rate-distortion function is indeed more energy-efficient.

SUBMITTER: Yang M

PROVIDER: S-EPMC4102074 | biostudies-other | 2014

REPOSITORIES: biostudies-other

ACCESS DATA

Json Xml

Similar Datasets

Energy Efficient Cluster Based Scheduling Scheme for Wireless Sensor Networks.

Project description:The energy utilization of sensor nodes in large scale wireless sensor network points out the crucial need for scalable and energy efficient clustering protocols. Since sensor nodes usually operate on batteries, the maximum utility of network is greatly dependent on ideal usage of energy leftover in these sensor nodes. In this paper, we propose an Energy Efficient Cluster Based Scheduling Scheme for wireless sensor networks that balances the sensor network lifetime and energy efficiency. In the first phase of our proposed scheme, cluster topology is discovered and cluster head is chosen based on remaining energy level. The cluster head monitors the network energy threshold value to identify the energy drain rate of all its cluster members. In the second phase, scheduling algorithm is presented to allocate time slots to cluster member data packets. Here congestion occurrence is totally avoided. In the third phase, energy consumption model is proposed to maintain maximum residual energy level across the network. Moreover, we also propose a new packet format which is given to all cluster member nodes. The simulation results prove that the proposed scheme greatly contributes to maximum network lifetime, high energy, reduced overhead, and maximum delivery ratio.

| S-EPMC4606114 | biostudies-other

Distributed optimal power and rate control in wireless sensor networks.

Project description:With the rapid development of wireless sensor networks, reducing energy consumption is becoming one of the important factors to extend node lifetime, and it is necessary to adjust the launching power of each node because of the limited energy available to the sensor nodes in the networks. This paper proposes a power and rate control model based on the network utility maximization (NUM) framework, where a weighting factor is used to reflect the influence degree of the sending power and transmission rate to the utility function. In real networks, nodes interfere with each other in the procedure of transmitting signal, which may lead to signal transmission failure and may negatively have impacts on networks throughput. Using dual decomposition techniques, the NUM problem is decomposed into two distributed subproblems, and then the conjugate gradient method is applied to solve the optimization problem with the calculation of the Hessian matrix and its inverse in order to guarantee fast convergence of the algorithm. The convergence proof is also provided in this paper. Numerical examples show that the proposed solution achieves significant throughput compared with exiting approaches.

| S-EPMC4034712 | biostudies-other

Malware propagation model for cluster-based wireless sensor networks using epidemiological theory.

Project description:Due to limited resources, wireless sensor network (WSN) nodes generally possess weak defense capabilities and are often the target of malware attacks. Attackers can capture or infect specific sensor nodes and propagate malware to other sensor nodes in WSNs through node communication. This can eventually infect an entire network system and even cause paralysis. Based on epidemiological theory, the present study proposes a malware propagation model suitable for cluster-based WSNs to analyze the propagation dynamic of malware. The model focuses on the data-transmission characteristics between different nodes in a cluster-based network and considers the actual application parameters of WSNs, such as node communication radius, node distributed density, and node death rate. In addition, an attack and defense game between malware and defending systems is also established, and the infection and recovery rates of malware propagation under the mixed strategy Nash equilibrium condition are given. In particular, the basic reproductive number, equilibrium point, and stability of the model are derived. These studies revealed that a basic reproductive number of less than 1 leads to eventual disappearance of malware, which provides significant insight into the design of defense strategies against malware threats. Numerical experiments were conducted to validate the theory proposed, and the influence of WSN parameters on malware propagation was examined.

| S-EPMC8459781 | biostudies-literature

Data Aggregation Based on Overlapping Rate of Sensing Area in Wireless Sensor Networks.

Project description:Wireless sensor networks are required in smart applications to provide accurate control, where the high density of sensors brings in a large quantity of redundant data. In order to reduce the waste of limited network resources, data aggregation is utilized to avoid redundancy forwarding. However, most of aggregation schemes reduce information accuracy and prolong end-to-end delay when eliminating transmission overhead. In this paper, we propose a data aggregation scheme based on overlapping rate of sensing area, namely AggOR, aiming for energy-efficient data collection in wireless sensor networks with high information accuracy. According to aggregation rules, gathering nodes are selected from candidate parent nodes and appropriate neighbor nodes considering a preset threshold of overlapping rate of sensing area. Therefore, the collected data in a gathering area are highly correlated, and a large amount of redundant data could be cleaned. Meanwhile, AggOR keeps the original entropy by only deleting the duplicated data. Experiment results show that compared with others, AggOR has a high data accuracy and a short end-to-end delay with a similar network lifetime.

| S-EPMC5539569 | biostudies-other

Geographic wormhole detection in wireless sensor networks.

Project description:Wireless sensor networks (WSNs) are ubiquitous and pervasive, and therefore; highly susceptible to a number of security attacks. Denial of Service (DoS) attack is considered the most dominant and a major threat to WSNs. Moreover, the wormhole attack represents one of the potential forms of the Denial of Service (DoS) attack. Besides, crafting the wormhole attack is comparatively simple; though, its detection is nontrivial. On the contrary, the extant wormhole defense methods need both specialized hardware and strong assumptions to defend against static and dynamic wormhole attack. The ensuing paper introduces a novel scheme to detect wormhole attacks in a geographic routing protocol (DWGRP). The main contribution of this paper is to detect malicious nodes and select the best and the most reliable neighbors based on pairwise key pre-distribution technique and the beacon packet. Moreover, this novel technique is not subject to any specific assumption, requirement, or specialized hardware, such as a precise synchronized clock. The proposed detection method is validated by comparisons with several related techniques in the literature, such as Received Signal Strength (RSS), Authentication of Nodes Scheme (ANS), Wormhole Detection uses Hound Packet (WHOP), and Wormhole Detection with Neighborhood Information (WDI) using the NS-2 simulator. The analysis of the simulations shows promising results with low False Detection Rate (FDR) in the geographic routing protocols.

| S-EPMC4300191 | biostudies-literature

Efficient cluster-based routing protocol for wireless sensor networks by using collaborative-inspired Harris Hawk optimization and fuzzy logic.

Project description:In wireless sensor networks, the implementation of clustering and routing protocols has been crucial in prolonging the network's operational duration by conserving energy. However, the challenge persists in efficiently optimizing energy usage to maximize the network's longevity. This paper presents CHHFO, a new protocol that combines a fuzzy logic system with the collaborative Harris Hawks optimization algorithm to enhance the lifetime of networks. The fuzzy logic system utilizes descriptors like remaining energy, distance from the base station, and the number of neighboring nodes to designate each cluster head and establish optimal clusters, thereby alleviating potential hot spots. Moreover, the Collaborative Harris Hawks Optimization algorithm employs an inventive coding mechanism to choose the optimal relay cluster head for data transmission. According to the results, the network throughput, HHOCFR is 8.76%, 11.73%, 8.64% higher than HHO-UCRA, IHHO-F, and EFCR. In addition, he energy consumption of HHOCFR is lower than HHO-UCRA, IHHO-F, and EFCR by 0.88%, 39.79%, 34.25%, respectively.

| S-EPMC10997138 | biostudies-literature

Spatio-temporal functional data analysis for wireless sensor networks data.

Project description:A new methodology is proposed for the analysis, modeling and forecasting of data collected from a wireless sensor network. Our approach is considered in the framework of a functional data analysis paradigm where observed data is represented in a functional form. To reduce dimensionality, functional principal components analysis is applied to highlight important underlying characteristics and find patterns of variations. The principal scores are modeled with tensor product smooths that allow for smoothing over space and time. The model is then used for simultaneous spatial prediction at unsampled locations and to forecast future observations. We consider soil temperature data from a wireless sensor network of 50 sensor nodes in two different land types (grassland and forest) observed during 60 consecutive days in private property close to Yass, New South Wales, Australia.

| S-EPMC4493908 | biostudies-literature

Performance Analysis of Time Synchronization Protocols in Wireless Sensor Networks.

Project description:The time synchronization protocol is indispensable in various applications of wireless sensor networks, such as scheduling, monitoring, and tracking. Numerous protocols and algorithms have been proposed in recent decades, and many of them provide micro-scale resolutions. However, designing and implementing a time synchronization protocol in a practical wireless network is very challenging compared to implementation in a wired network; this is because its performance can be deteriorated significantly by many factors, including hardware quality, message delay jitter, ambient environment, and network topology. In this study, we measure the performance of the Flooding Time Synchronization Protocol (FTSP) and Gradient Time Synchronization Protocol (GTSP) in terms of practical network conditions, such as message delay jitter, synchronization period, network topology, and packet loss. This study provides insights into the operation and optimization of time synchronization protocols. In addition, the performance evaluation identifies that FTSP is highly affected by message delay jitter due to error accumulation over multi-hops. We demonstrate that the proposed extended version of the FTSP (E-FTSP) alleviates the effect of message delay jitter and enhances the overall performance of FTSP in terms of error, time, and other factors.

| S-EPMC6651869 | biostudies-literature

A wormhole attack detection method for tactical wireless sensor networks.

Project description:Wireless sensor networks (WSNs) are networks formed by organizing and combining tens of thousands of sensor nodes freely through wireless communication technology. WSNs are commonly affected by various attacks, such as identity theft, black holes, wormholes, protocol spoofing, etc. As one of the more severe threats, wormholes create passive attacks that are hard to detect and eliminate. Since WSN is often used in the tactical network field, a planned secure network is essential for military applications with high security. Guard nodes are traffic monitoring nodes used to supervise neighbors' data communication around the tactical networks. Therefore, this work proposes a Quality of Service (QoS) security mechanism to select multiple dual-layer guard nodes at different paths of the WSN based on the path qualities to detect wormholes. The entire network's links are categorized into high, normal, and low priority levels. As such, this study aimed to confirm the security of high priority nodes and links in the tactical network, avoid excessive overhead, and provide random security facilities to all nodes. The proposed measures of the QoS-based security provision, including link cluster formation, guard node selection, authenticated guard node identification, and intrusion detection, ensure economic and efficient network communication with different quality levels.

| S-EPMC10495966 | biostudies-literature

A Study on Wireless Charging for Prolonging the Lifetime of Wireless Sensor Networks.

Project description:Wireless charging is an important issue in wireless sensor networks, since it can provide an emerging and effective solution in the absence of other power supplies. The state-of-the-art methods employ a mobile car and a predefined moving path to charge the sensor nodes in the network. Previous studies only consider a factor of the network (i.e., residual energy of sensor node) as a constraint to design the wireless charging strategy. However, other factors, such as the travelled distance of the mobile car, can also affect the effectiveness of wireless charging strategy. In this work, we study wireless charging strategy based on the analysis of a combination of two factors, including the residual energy of sensor nodes and the travelled distance of the charging car. Firstly, we theoretically analyze the limited size of the sensor network to match the capability of a charging car. Then, the networked factors are selected as the weights of traveling salesman problem (TSP) to design the moving path of the charging car. Thirdly, the charging time of each sensor node is computed based on the linear programming problem for the charging car. Finally, a charging period for the network is studied. The experimental results show that the proposed approach can significantly maximize the lifetime of the wireless sensor network.

| S-EPMC5539798 | biostudies-other

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data