The Research of Data Gathering Protocol for Mobile Sensor Networks

2011 ◽  
Vol 216 ◽  
pp. 621-624
Author(s):  
Xin Lian Zhou ◽  
Jian Bo Xu
Keyword(s):  
Energy Efficient ◽  
Cluster Head ◽  
Mobile Sink ◽  
Mobile Node ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Node Mobility ◽  
Sink Node ◽  
Mobile Sensor ◽  
The Impact

This paper first proposed an energy-efficient distributed clustering technology for mobile sensor nodes and sink node mobility, select the higher residual energy and the nearest node from fixed nodes as cluster heads responsible for collecting sensed data, and all the fixed nodes form routing backbone to forward data, both can save energy and avoid cluster head away. Then, proposed a cross-layer scheduling mechanism to avoid the impact of mobile node and meet expectations cluster coverage. With energy-efficient clustering technology, efficient network topology control technology and mobile sink node, the data collection algorithm MSDBG, not only has considered mobility of nodes and energy saving, but also has achieved prolonging network lifetime.

Distributed Entropy Energy-Efficient Clustering algorithm for cluster head selection (DEEEC)

2020 ◽  
Vol 39 (6) ◽  
pp. 8139-8147
Author(s):  
Ranganathan Arun ◽  
Rangaswamy Balamurugan
Keyword(s):  
Energy Efficient ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Residual Energy ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Second Stage ◽  
Energy Efficient Clustering ◽  
Two Stages ◽  
Ch Selection

In Wireless Sensor Networks (WSN) the energy of Sensor nodes is not certainly sufficient. In order to optimize the endurance of WSN, it is essential to minimize the utilization of energy. Head of group or Cluster Head (CH) is an eminent method to develop the endurance of WSN that aggregates the WSN with higher energy. CH for intra-cluster and inter-cluster communication becomes dependent. For complete, in WSN, the Energy level of CH extends its life of cluster. While evolving cluster algorithms, the complicated job is to identify the energy utilization amount of heterogeneous WSNs. Based on Chaotic Firefly Algorithm CH (CFACH) selection, the formulated work is named “Novel Distributed Entropy Energy-Efficient Clustering Algorithm”, in short, DEEEC for HWSNs. The formulated DEEEC Algorithm, which is a CH, has two main stages. In the first stage, the identification of temporary CHs along with its entropy value is found using the correlative measure of residual and original energy. Along with this, in the clustering algorithm, the rotating epoch and its entropy value must be predicted automatically by its sensor nodes. In the second stage, if any member in the cluster having larger residual energy, shall modify the temporary CHs in the direction of the deciding set. The target of the nodes with large energy has the probability to be CHs which is determined by the above two stages meant for CH selection. The MATLAB is required to simulate the DEEEC Algorithm. The simulated results of the formulated DEEEC Algorithm produce good results with respect to the energy and increased lifetime when it is correlated with the current traditional clustering protocols being used in the Heterogeneous WSNs.

Quasi Oppositional Glowworm Swarm Optimization Algorithm for Energy Efficient Clustering in Wireless Sensor Networks

2020 ◽  
Vol 17 (12) ◽  
pp. 5447-5456
Author(s):  
R. M. Alamelu ◽  
K. Prabu
Keyword(s):  
Energy Efficient ◽  
Cluster Head ◽  
Residual Energy ◽  
Link Quality ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Node Degree ◽  
Swarm Optimization ◽  
Glowworm Swarm Optimization ◽  
Energy Efficient Clustering

Wireless sensor network (WSN) becomes popular due to its applicability in distinct application areas like healthcare, military, search and rescue operations, etc. In WSN, the sensor nodes undergo deployment in massive number which operates autonomously in harsh environment. Because of limited resources and battery operated sensor nodes, energy efficiency is considered as a main design issue. To achieve, clustering is one of the effective technique which organizes the set of nodes into clusters and cluster head (CH) selection takes place. This paper presents a new Quasi Oppositional Glowworm Swarm Optimization (QOGSO) algorithm for energy efficient clustering in WSN. The proposed QOGSO algorithm is intended to elect the CHs among the sensor nodes using a set of parameters namely residual energy, communication cost, link quality, node degree and node marginality. The QOGSO algorithm incorporates quasi oppositional based learning (QOBL) concept to improvise the convergence rate of GSO technique. The QOGSO algorithm effectively selects the CHs and organizes clusters for minimized energy dissipation and maximum network lifetime. The performance of the QOGSO algorithm has been evaluated and the results are assessed interms of distinct evaluation parameters.

Energy-Efficient Routing Protocol on Mobile Sink in Wireless Sensor Network

2013 ◽  
Vol 787 ◽  
pp. 1050-1055 ◽  
Author(s):  
Zhi Gui Lin ◽  
Hui Qi Zhang ◽  
Xu Yang Wang ◽  
Fang Qin Yao ◽  
Zhen Xing Chen
Keyword(s):  
Energy Consumption ◽  
Routing Protocol ◽  
Energy Efficient ◽  
Model Simulation ◽  
Cluster Head ◽  
Mobile Sink ◽  
High Energy ◽  
Residual Energy ◽  
Energy Efficient Routing ◽  
Simulation Results

To the disadvantages, such as high energy consumption and the energy consumption imbalance, we proposed an energy-efficient routing protocol on mobile sink (MSEERP) in this paper. In the MSEERP, the network is divided into several square virtual grids based on GAF, each grid is called a cluster, and the cluster head election method of GAF is improved. In addition, the MSEERP introduces a mobile sink in the network, the sink radios in limited number of hops and uses control moving strategy, namely the sink does not collect the information until it moves to a cluster with highest residual energy. We applied NS2 to evaluate its performance and analyze the simulation results by the energy model. Simulation results show that the MSEERP balances the energy consumption of the network, saves nodes energy and extends the network lifetime.

scholarly journals Qualification of Cluster Header and Cluster Member in Wireless Sensor Networks

2019 ◽  
Vol 8 (2S6) ◽  
pp. 101-105
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Transmission ◽  
Sensor Node ◽  
Data Transfer ◽  
Cluster Head ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sink Node

Many researches have been proposed for efficiency of data transmission from sensor nodes to sink node for energy efficiency in wireless sensor networks. Among them, cluster-based methods have been preferred In this study, we used the angle formed with the sink node and the distance of the cluster members to calculate the probability of cluster head. Each sensor node sends measurement values to header candidates, and the header candidate node measures the probability value of the header with the value received from its candidate member nodes. To construct the cluster members, the data transfer direction is considered. We consider angle, distance, and direction as cluster header possibility value. Experimental results show that data transmission is proceeding in the direction of going to the sink node. We calculated and displayed the header possibility value of the neighbor nodes of the sensor node and confirmed the candidates of the cluster header for data transfer as the value. In this study, residual energy amount of each sensor node is not considered. In the next study, we calculate the value considering the residual energy amount of the node when measuring the header possibility value of the cluster.

scholarly journals An Energy-Balanced Mechanism for Hierarchical Routing in Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Zhenjiang Zhang ◽  
Yanan Wang ◽  
Fuxing Song ◽  
Wenyu Zhang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Balance ◽  
Cluster Head ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sink Node ◽  
Hierarchical Routing ◽  
Cluster Heads

In wireless sensor networks (WSNs), energy-constrained sensor nodes are always deployed in hazardous and inaccessible environments, making energy management a key problem for network design. The mechanism of RNTA (redundant node transmission agents) lacks an updating mechanism for the redundant nodes, causing an unbalanced energy distribution among sensor nodes. This paper presents an energy-balanced mechanism for hierarchical routing (EBM-HR), in which the residual energy of redundant nodes is quantified and made hierarchic, so that the cluster head can dynamically select the redundant node with the highest residual energy grade as a relay to complete the information transmission to the sink node and achieve an intracluster energy balance. In addition, the network is divided into several layers according to the distances between cluster heads and the sink node. Based on the energy consumption of the cluster heads, the sink node will decide to recluster only in a certain layer so as to achieve an intercluster energy balance. Our approach is evaluated by a simulation comparing the LEACH algorithm to the HEED algorithm. The results demonstrate that the BEM-HR mechanism can significantly boost the performance of a network in terms of network lifetime, data transmission quality, and energy balance.

scholarly journals A Twofold Sink Based Data Collection for Continuous Object Tracking in Wireless Sensor Network

2017 ◽  
Author(s):  
Sajjad Hussain Chauhdary ◽  
Ali Hassan ◽  
Mohammed A Alqarni ◽  
Abdullah Alamri
Keyword(s):  
Object Tracking ◽  
Forest Fires ◽  
Life Time ◽  
Mobile Sink ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Sink Node ◽  
Network Nodes ◽  
Continuous Objects ◽  
Continuous Object

Continuous object tracking in WSNs, such as monitoring of mud-rock flows, forest fires etc., is a challenging task due to characteristic nature of continuous objects. They can appear randomly in the network field, move continuously, and can change in size and shape. Monitoring such objects in real-time generally require tremendous amount of messaging between sensor nodes to synergistically estimate object’s movement and track its location. In this paper, we propose a novel twofold-sink mechanism, comprising of a mobile and a static sink node. Both sink nodes gather information about boundary sensor nodes, which is then used to uniformly distribute energy consumption across all network nodes, thus helping in saving residual energy of network nodes. Numerous object tracking schemes, using mobile sink, have been proposed in the literature. However, existing schemes employing mobile sink cannot be applied to track continuous objects, because of momentous variation of network topology. Therefore, we present in this paper a mechanism, transformed from K-means algorithm, to find the best sensing location of the mobile sink node. It helps to reduce transmission load on the intermediate network nodes situated between static sink node and the ordinary network sensing nodes. The simulation results show that the proposed scheme can distinctly improve life time of the network, compared to one-sink protocol employed in continuous object tracking.

scholarly journals Levenberg–Marquart logistic deep neural learning based energy efficient and load balanced routing in MANET

2021 ◽  
Vol 23 (2) ◽  
pp. 1002
Author(s):  
A. Sangeetha ◽  
T. Rajendran
Keyword(s):  
Energy Efficient ◽  
Ad Hoc ◽  
New Technologies ◽  
Activation Function ◽  
Mobile Node ◽  
Residual Energy ◽  
Node Mobility ◽  
Mobile Nodes ◽  
Neural Learning ◽  
Load Balanced

As the advent of new technologies grows, the deployment of mobile ad hoc networks (MANET) becomes increasingly popular in many application areas. In addition, all the nodes in MANET are battery operated and the node mobility affects the path stability and creates excessive traffic leads to higher utilization of energy, data loss which degrades the performance of routing. So, in this paper we propose Levenberg–Marquardt logistic deep neural learning based energy efficient and load balanced routing (LLDNL-EELBR) which is a machine learning method to deeply analyze the mobile nodes to calculate residual load and energy and it also uses logistic activation function to select the mobile node having higher residual energy and residual load to route the data packet. Experimental evaluations of three methods (LLDNL-EELBR, multipath battery and mobility-aware routing scheme (MBMA-OLSR) and opportunistic routing with gradient forwarding for MANETs (ORGMA)) were done and the result reveals that LLDNL-EELBR method is able to increase the through put and minimizes the delay and energy consumption in MANET when compared to works under consideration.<br /><div> </div>

Research on Clustering Algorithm for Wireless Sensor Networks

2013 ◽  
Vol 380-384 ◽  
pp. 1231-1234
Author(s):  
Cheng Xu Feng ◽  
Zhong Liu ◽  
Zhi Kun Liu
Keyword(s):  
Clustering Algorithm ◽  
Cluster Head ◽  
Signal Strength ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sink Node ◽  
The Novel ◽  
Selection Mechanism ◽  
Energy Constrained

According to the problem that the sensor nodes are highly energy-constrained, a novel dynamic clustering algorithm for WSN, which is in application to object tracking, is proposed. The cluster head selection mechanism takes not only the distance between the cluster head and the sink node but also the received signal strength and the residual energy of nodes into consideration. The analysis result indicates that, the energy consumption of network communication is reduced and the cluster size is optimized. The simulation results show that the novel algorithm can efficiently prolong the lifetime of WSN, especially when the sink node is far from the network.

scholarly journals Energy-Efficient Clustering Multi-Hop Routing Protocol in a UWSN

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 627
Author(s):  
Nhat-Tien Nguyen ◽  
Thien T. T. Le ◽  
Huy-Hung Nguyen ◽  
Miroslav Voznak
Keyword(s):  
Energy Consumption ◽  
Network Lifetime ◽  
Routing Protocol ◽  
Energy Efficient ◽  
Cluster Head ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Depth Level ◽  
Large Numbers ◽  
Energy Efficient Clustering

Underwater wireless sensor networks are currently seeing broad research in various applications for human benefits. Large numbers of sensor nodes are being deployed in rivers and oceans to monitor the underwater environment. In the paper, we propose an energy-efficient clustering multi-hop routing protocol (EECMR) which can balance the energy consumption of these nodes and increase their network lifetime. The network area is divided into layers with regard to the depth level. The data sensed by the nodes are transmitted to a sink via a multi-hop routing path. The cluster head is selected according to the depth of the node and its residual energy. To transmit data from the node to the sink, the cluster head aggregates the data packet of all cluster members and then forwards them to the upper layer of the sink node. The simulation results show that EECMR is effective in terms of network lifetime and the nodes’ energy consumption.

scholarly journals A novel routing protocol for content-based publish/subscribe model in mobile sensor networks

2019 ◽  
Vol 15 (9) ◽  
pp. 155014771987904
Author(s):  
Lin Lin ◽  
Jinfu Chen ◽  
Patrick Kwaku Kudjo ◽  
Omari Michael
Keyword(s):  
Sensor Networks ◽  
Success Rate ◽  
Routing Protocol ◽  
Cluster Head ◽  
Mobile Sensor Networks ◽  
Sensor Nodes ◽  
Communication Process ◽  
Communication Overhead ◽  
Sink Node ◽  
Mobile Sensor

In the mobile sensor networks, the sink node registers its own events in the network, and when the sensor node finds an event of interest to the sink node, it sends a response message. The data traffic of the communication process in the application scenario has a bursting feature, and sometimes network congestion occurs. Therefore, when designing the data routing protocol, it is necessary to consider how to reduce the communication overhead in the network and improve the success rate of the query. To address this issue, this article proposes a routing protocol for content-based publish/subscribe, which is applicable in mobile sensor networks. The core idea of routing protocol for content-based publish/subscribe is that all sensor nodes in the network are divided into several clusters, and the transmission of sensing events is based on these clusters. The protocol consists of event publishing, subscription, matching, and unsubscribe. The inquirers send subscription information to the network, which are saved in the cluster head network. Published events are also transmitted to the cluster head network and the matching computation is performed. If the match is successful, events will be sent to subscribers, thus improving the success rate of queries. The simulations show that compared with existing methods, routing protocol for content-based publish/subscribe consumes lower matching events transmission energy to obtain a higher success rate. In the case of a large number of published events, the network lifetime of the routing protocol for content-based publish/subscribe protocol can be increased by 28%–54%, and the subscription success rate remains above 80%.

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