scholarly journals Energy Efficient Routing Protocall By One Way Multi-Hope Sensor Nodes

2021 ◽  
Vol 12 (7) ◽  
pp. 3401-3410
Author(s):  
Heba Hussain Hadi, Et. al.
Keyword(s):  
Data Transmission ◽  
Sensor Node ◽  
Cluster Head ◽  
Geographic Location ◽  
Life Time ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Energy Efficient Routing ◽  
Coverage Area ◽  
Aggregated Data

Multi-hope is widely used for data aggregation and transmission in various applications. The resource availability determines the life time of a WSN. Sensor nodes are powered by a tiny battery that supplies the required energy for the sensor and transmitter. The residual energy available at any moment decides the fitness of the sensor node. The sensor node senses the environment and transmits the data to the sink. Efficient data transmission and aggregation with less energy consumption can prolong the lifetime of the sensor network. The sensor node that is inside the coverage area of the sink can directly transmit the data to sink in a single-hop transmission. The sensor node that is not inside the coverage area should transmit the data to the neighbor node which is in the coverage area of the sink. The data is then turn transmitted by the node close to it fall in multi-hop transmission involving a number of intermediate nodes to forward the data to the sink and consumes extra energy for the forwarding process. The formation clusters and data transmission of data by Cluster Heads (CH) can eliminate many nodes involved in the transmission of same data. Clusters are a group of self-organized nodes in a geographic location that can communicate among them. A node in a cluster with higher residual energy will be acting as CH and all other nodes in the cluster transmit the data to the CH. The CH transmits the aggregated data to the sink. The CH transmits the data to the sink either in single-hop transmission or multi-hop transmission. The cluster head consumes more energy than other nodes in the cluster as it is involved in aggregation and transmission process.

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 Greedy Knapsack Based Energy Efficient Routing in WMSNS

2019 ◽  
Vol 8 (10) ◽  
pp. 1455-1461
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Sensor Node ◽  
Life Time ◽  
Residual Energy ◽  
Multimedia Data ◽  
Sensor Nodes ◽  
Wireless Multimedia ◽  
Energy Efficient Routing ◽  
Critical Situation

Managing the energy is very challenging in wireless multimedia sensor networks because of heavy consumption of energy by the sensor nodes. Multimedia data transmission contains heavy energy consumption operations such as sensing, aggregating, compressing and transferring the data from one sensor node to neighbour sensor node. Many routing techniques considers residual energy of a neighbour node to forward the data to that node. But, in reality a critical situation occurs where required energy is greater than individual neighbour node’s residual energy. In this situation it is not possible to select any neighbour node as a data forwarder. The proposed greedy knapsack based energy efficient routing algorithm (GKEERA) can address this critical situation very efficiently. And also a Two-in-One Mobile Sink (TIOMS) is used to provide the power supply and to collect the data from a battery drained sensor node. GKEERA improves the life time of a network by balancing the energy consumption between the neighbour nodes.

scholarly journals Performance Analysis of Q-Leach Algorithm in WSN

2020 ◽  
Vol 5 (10) ◽  
pp. 1-4
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Data Transmission ◽  
Short Range ◽  
Sensor Node ◽  
Life Time ◽  
Time Span ◽  
Sensor Nodes ◽  
Wireless Sensor

Sensor nodes are exceedingly energy compelled instrument, since it is battery operated instruments. In wsn network, every node is liable to the data transmission through the wireless mode [1]. Wireless sensor networks (WSN) is made of a huge no. of small nodes with confined functionality. The essential theme of the wireless sensor network is energy helpless and the WSN is collection of sensor. Every sensor terminal is liable to sensing, store and information clan and send it forwards into sink. The communication within the node is done via wireless network [3].Energy efficiency is the main concentration of a desining the better routing protocol. LEACH is a protocol. This is appropriate for short range network, since imagine that whole sensor node is capable of communication with inter alia and efficient to access sink node, which is not always correct for a big network. Hence, coverage is a problem which we attempt to resolve [6]. The main focus within wireless sensor networks is to increase the network life-time span as much as possible, so that resources can be utilizes efficiently and optimally. Various approaches which are based on the clustering are very much optimal in functionality. Life-time of the network is always connected with sensor node’s energy implemented at distant regions for stable and defect bearable observation [10].

scholarly journals Local Aggregation Scheme for Data Collection in Periodic Sensor Network

2019 ◽  
Vol 9 (2) ◽  
pp. 3583-3588
Keyword(s):  
Sensor Node ◽  
Cluster Head ◽  
Temporal Correlation ◽  
Sensor Nodes ◽  
Time Interval ◽  
Specific Time ◽  
Aggregated Data ◽  
Redundant Data ◽  
Local Aggregation ◽  
Local Outlier

Data aggregation is an important technique for data collection & aggregation in WSN where sensor nodes sense the raw data and sends the aggregated data to the sink node. In a cluster based periodic network, sensor node senses the data on a specific time interval, performs local aggregation and send aggregated data to Cluster Head (CH). Various Local aggregation algorithms are used to remove redundant data at sensor nodes but local outlier detection problem is still unsolved. Therefore, a local aggregation algorithm has been proposed which uses the temporal correlation property of WSN to eliminate redundant and local outlier data which improves the data sent ratio and data quality. Sensor measurement is collected at different time interval of a sensor, exhibits temporal correlation because measurements varies with small or same difference (δ) and measurements are treated as similar measurements. In proposed local aggregation approach, each sensor node finds similar measurements of sensors with their frequency (number of occurrence) in a specific time interval (Temporal correlation). Set having higher frequency is selected and transmitted the average values of measurements that lie in the selected set to the cluster head. If sensors don’t detect any reading between intervals it simple send a message ‘data not found’ instead of sending empty set. In this way we delete redundant and local outliers. The experimental result shows that algorithm improves the data quality and data sent ratio by eliminating redundant data and local outliers

scholarly journals Spatiotemporal correlation–based adaptive sampling algorithm for clustered wireless sensor networks

2018 ◽  
Vol 14 (8) ◽  
pp. 155014771879461 ◽  
Author(s):  
Wenyu Cai ◽  
Meiyan Zhang
Keyword(s):  
Spatial Correlation ◽  
Data Transmission ◽  
Adaptive Sampling ◽  
Cluster Head ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Sampling Algorithm ◽  
Sensory Data ◽  
Temporal Sampling ◽  
Redundant Data

Energy efficiency is one of the most crucial concerns for WSNs, and almost all researches assume that the process for data transmission consumes more energy than that of data collection. However, a few sophisticated collection processes of sensory data will consume much more energy than traditional transmission processes such as image and video acquisitions. Given this hypothesis, this article proposed an adaptive sampling algorithm based on temporal and spatial correlation of sensory data for clustered WSNs. First, according to spatial correlations between sensor nodes, a distributed clustering mechanism based on data gradient and residual energy level is proposed, and the whole network is divided into several independent clusters. Afterwards, each cluster head maintains an autoregressive prediction model for sensory data, which is derived from historical data in the temporal domain. With that, each cluster head has the ability of self-adjusting temporal sampling intervals within each cluster. Consequently, redundant data transmission is reduced by adjusting temporal sampling frequency while ensuring desired prediction accuracy. Finally, several distinct sampler collection sets are selected within each cluster following intra-cluster correlation matrix, and only one sampler collection needs to be activated at each round time. Sensory data of non-sampler can be substituted by those of sampler due to strong spatial correlation between them. Simulation results demonstrate the performance benefits of proposed algorithm.

scholarly journals A Research Protocol for Detection and Optimization of Overlapping Coverage in Wireless Sensor Networks

2019 ◽  
Vol 8 (6S) ◽  
pp. 1-6
Keyword(s):  
Human Life ◽  
Data Gathering ◽  
Fire Detection ◽  
Life Time ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Coverage Area ◽  
Random Manner ◽  
The Given

Wireless sensor network (WSN) is an emerging area in which numbers of sensor nodes are deployed in two ways random and deterministic for data gathering. WSNs have expedited human life in diverse emerging fields: military, agriculture, structural health, perimeter access control, forest fire detection. A physical stimulus such as pressure, sound, light act as an environmental parameter on which the system is design to monitor and detect it for controlling the coverage area for assigned task. The nodes are deployed in the random manner in the given area for gathering the information and they may be overlapped so that the total area may not be covered. The proposed protocol uses radius and the residual energy as a function to increase the total coverage area so that the whole coverage area may be achieved. It also increases the life time of the network using Sleep and Wakeup protocol. Therefore the overall life time of the network increases.

scholarly journals LOCATION AWARE CLUSTER BASED ROUTING IN WIRELESS SENSOR NETWORKS

2015 ◽  
pp. 36-41
Author(s):  
S. JERUSHA ◽  
K. KULOTHUNGAN ◽  
A Kannan
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Network ◽  
Network Lifetime ◽  
Minimum Distance ◽  
Sensor Node ◽  
Cluster Head ◽  
Residual Energy ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor

Wireless sensor nodes are usually embedded in the physical environment and report sensed data to a central base station. Clustering is one of the most challenging issues in wireless sensor networks. This paper proposes a new cluster scheme for wireless sensor network by modified the K means clustering algorithm. Sensor nodes are deployed in a harsh environment and randomly scattered in the region of interest and are deployed in a flat architecture. The transmission of packet will reduce the network lifetime. Thus, clustering scheme is required to avoid network traffic and increase overall network lifetime. In order to cluster the sensor nodes that are deployed in the sensor network, the location information of each sensor node should be known. By knowing the location of the each sensor node in the wireless sensor network, clustering is formed based on the highest residual energy and minimum distance from the base station. Among the group of nodes, one node is elected as a cluster head using centroid method. The minimum distance between the cluster node’s and the centroid point is elected as a cluster head. Clustering of nodes can minimize the residual energy and maximize the network performance. This improves the overall network lifetime and reduces network traffic.

scholarly journals Detection of Compromised Nodes in Wireless Sensor Networks using GPSR Protocol and Iterative Filtering Algorithm

2016 ◽  
Vol 1 (3) ◽  
pp. 141-148
Author(s):  
R. Ramalakshmi ◽  
S. Subash Prabhu ◽  
C. Balasubramanian
Keyword(s):  
Sensor Node ◽  
Cluster Head ◽  
Life Time ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Surrounding Area ◽  
Filtering Algorithm ◽  
Iterative Filtering ◽  
Time And Energy

The sensor network is used to observe surrounding area gathered and spread the information to other sink. The advantage of this network is used to improve life time and energy. The first sensor node or group of sensor nodes in the network runs out of energy. The aggregator node can send aggregate value to the base station. The sensor node can be used to assign initial weights for each node. This sensor node calculates weight for each node. Which sensor node weight should be lowest amount they can act as a cluster head. The joint node can send false data to the aggregator node and then these node controls to adversary. The dependability at any given instant represents an comprehensive behavior of participate to be various types of defects and misconduct. The adversary can send information to aggregator node then complexity will be occurred. These nodes are used to reduce the energy and band width.

scholarly journals Data Transmission Direction Based Routing Algorithm for Improving Network Performance of IoT Systems

2020 ◽  
Vol 10 (11) ◽  
pp. 3784
Author(s):  
Kyeong Mi Noh ◽  
Jong Hyuk Park ◽  
Ji Su Park
Keyword(s):  
Energy Efficiency ◽  
Routing Protocol ◽  
Data Transmission ◽  
Sensor Node ◽  
Network Performance ◽  
Cluster Head ◽  
Sensor Nodes ◽  
The Internet ◽  
Leach Protocol ◽  
Transmission Direction

With the continuous development of wireless communication technology, the Internet of Things (IoT) is being used in a wide range of fields. The IoT collects and exchanges large amounts of data with objects, either tangible or intangible, such as sensors or physical devices, connected to the Internet. Wireless sensor networks (WSNs) are components of IoT systems. WSNs are used in various IoT systems, such as monitoring, tracking, and detection systems, to extract relevant information and deliver it to users. WSNs consist of sensor nodes with low power, low cost, and multiple functions. Because sensor nodes have limited resources, such as power and memory, a reduction in the energy efficiency of the sensor nodes in WSNs will lead to a decrease in wireless network performance and an increase in packet loss, which affects IoT system performance. Therefore, this study aimed to find an energy-efficient routing method that extends the lifetime of WSNs by minimizing the battery use of sensor nodes to improve the network performance of IoT systems. Conserving energy from sensor nodes and increasing network throughput in WSNs involves having protocols. The low-energy adaptive clustering hierarchy (LEACH ) protocol is a well-known hierarchical routing protocol in WSNs that constructs clusters and transmits data. LEACH increases energy efficiency by transmitting data from sensor nodes to the base station (BS) through the cluster head. It is widely adopted in the WSN network field, and many protocols are being studied to improve cluster header selection and data transmission to increase the energy efficiency of sensor nodes. In this study, we attempted to improve energy efficiency by removing unnecessary energy from LEACH. In LEACH, when the sensor node is located between the BS and the cluster head, the sensor node transmits data to the cluster head in the opposite direction of the BS. The data sent to the cluster head are transmitted in the direction of the BS. Thus, transmission in the opposite direction consumes unnecessary energy and affects the WSN performance of IoT systems. In this study, we propose a D-LEACH (direction-based LEACH) protocol based on the received signal strength indicator (RSSI) that improves the efficiency of transmission energy considering the data transmission direction of sensor nodes. D-LEACH aims to balance the energy of the sensor nodes and improve the performance of WSNs in the IoT system by reducing unnecessary energy consumption caused by reverse transmission considering the data transmission direction of the sensor nodes. In the course of the paper, we refer to the routing protocol of WSNs to improve network performance and describe LEACH. We also explain the D-LEACH protocol proposed in this paper and confirm the performance improvement of WSNs in an IoT system through simulation.

ROUTING PATH OPTIMIZAION TO MAXIMIZE THE LIFETIME OF WIRELESS SENSOR NETWORK

2009 ◽  
Vol 16 (06) ◽  
pp. 509-520
Author(s):  
P. MANJUNATHA ◽  
A. K. VERMA ◽  
A. SRIVIDYA
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Lifetime ◽  
Sensor Node ◽  
Minimum Energy ◽  
Life Time ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Efficient Routing

Wireless sensor network (WSN) consists of a large number of sensor nodes which are able to sense their environment and communicate with each other using wireless interface. However these sensor nodes are constrained in energy capacity. The lifetimes of sensor node and sensor network mainly depends upon these energy resources. To increase the life time of sensor network, many approaches have been proposed to optimize the energy usage. All these proposed protocols mainly use minimum hop or minimum energy path. Continuously using the shortest path will deplete energy of the nodes at a much faster rate and causes network partition. This paper proposes an energy efficient routing protocol to extend the network lifetime for delay constrained network. Each sensor node selects the optimized path for forwarding packets to the base station based on routing metrics. Proposed studies and simulation results shows that the protocol put forward in the paper can achieve higher network lifetime by striking a balance between the delay and power consumption in comparison to other routing protocols.

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