scholarly journals Energy Efficient and Reliable Routing Algorithm for Wireless Sensors Networks

2020 ◽  
Vol 10 (5) ◽  
pp. 1885 ◽  
Author(s):  
Liangrui Tang ◽  
Zhilin Lu ◽  
Bing Fan
Keyword(s):  
Energy Efficient ◽  
Routing Algorithm ◽  
Evidence Theory ◽  
Fusion Rule ◽  
Residual Energy ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Entropy Weight ◽  
Reliable Routing ◽  
Index Value

In energy-constrained wireless sensor networks, low energy utilization and unbalanced energy distribution are seriously affecting the operation of the network. Therefore, efficient and reasonable routing algorithms are needed to achieve higher Quality of Service (QoS). For the Dempster–Shafer (DS) evidence theory, it can fuse multiple attributes of sensor nodes with reasonable theoretical deduction and has low demand for prior knowledge. Based on the above, we propose an energy efficient and reliable routing algorithm based on DS evidence theory (DS-EERA). First, DS-EERA establishes three attribute indexes as the evidence under considering the neighboring nodes’ residual energy, traffic, the closeness of its path to the shortest path, etc. Then we adopt the entropy weight method to objectively determine the weight of three indexes. After establishing the basic probability assignment (BPA) function, the fusion rule of DS evidence theory is applied to fuse the BPA function of each index value to select the next hop. Finally, each node in the network transmits data through this routing strategy. Theoretical analysis and simulation results show that DS-EERA is promising, which can effectively prolong the network lifetime. Meanwhile, it can also reach a lower packet loss rate and improve the reliability of data transmission.

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.

Energy Efficient Clustering and Routing Algorithm for WSN

2019 ◽  
Vol 12 ◽  
Author(s):  
Mohit Kumar ◽  
Sonu Mittal ◽  
Md. Amir Khusru Akhtar
Keyword(s):  
Energy Consumption ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Hot Spot ◽  
Routing Algorithm ◽  
Relay Node ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Efficient Clustering ◽  
Hot Spot Problem

Background: This paper presents a novel Energy Efficient Clustering and Routing Algorithm (EECRA) for WSN. It is a clustering-based algorithm that minimizes energy dissipation in wireless sensor networks. The proposed algorithm takes into consideration energy conservation of the nodes through its inherent architecture and load balancing technique. In the proposed algorithm the role of inter-cluster transmission is not performed by gateways instead a chosen member node of respective cluster is responsible for data forwarding to another cluster or directly to the sink. Our algorithm eases out the load of the gateways by distributing the transmission load among chosen sensor node which acts as a relay node for inter-cluster communication for that round. Grievous simulations show that EECRA is better than PBCA and other algorithms in terms of energy consumption per round and network lifetime. Objective: The objective of this research lies in its inherent architecture and load balancing technique. The sole purpose of this clustering-based algorithm is that it minimizes energy dissipation in wireless sensor networks. Method: This algorithm is tested with 100 sensor nodes and 10 gateways deployed in the target area of 300m × 300m. The round assumed in this simulation is same as in LEACH. The performance metrics used for comparisons are (a) network lifetime of gateways and (b) energy consumption per round by gateways. Our algorithm gives superior result compared to LBC, EELBCA and PBCA. Fig 6 and Fig 7 shows the comparison between the algorithms. Results: The simulation was performed on MATLAB version R2012b. The performance of EECRA is compared with some existing algorithms like PBCA, EELBCA and LBCA. The comparative analysis shows that the proposed algorithm outperforms the other existing algorithms in terms of network lifetime and energy consumption. Conclusion: The novelty of this algorithm lies in the fact that the gateways are not responsible for inter-cluster forwarding, instead some sensor nodes are chosen in every cluster based on some cost function and they act as a relay node for data forwarding. Note the algorithm does not address the hot-spot problem. Our next endeavor will be to design an algorithm with consideration of hot-spot problem.

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.

scholarly journals An Efficient Leader Node Selection for Movable Nodes in WSN using PSO Technique

2019 ◽  
Vol 8 (6) ◽  
pp. 5072-5078
Keyword(s):  
Energy Efficient ◽  
Network Performance ◽  
Clustering Algorithm ◽  
Group Formation ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Delivery Ratio ◽  
Efficient Prediction ◽  
The Stability ◽  
Effective Group

Wireless Sensor Networks (WSN) is a group of sensor devices, which are used to sense the surroundings. The network performance is still an issue in the WSN and an efficient protocol is introduced such as LEACH. To improve the stability, LEACH with fuzzy descriptors is used in preceding research. However the existing has drawback with effective group formation in heterogeneous WSN and also it is not achieved the Super Leader Node (SLH). To overcome the above mentioned issues, the proposed system enhances the approach which is used for increasing the energy consumption, packet delivery ratio, and bandwidth and network lifetime. The proposed paper contains three phases such as grouping formation, Leader Node (LN) selection, SLN selection with three main objectives:(i) to acquire Energy-Efficient Prediction Clustering Algorithm (EEPCA) in heterogeneous WSN for grouping formation (ii)To design Low Energy Adaptive Clustering Hierarchy- Expected Residual Energy (LEACH-ERE) protocol for LN selection.(iii)To optimize the SCH selection by Particle Swarm Optimization (PSO) based fuzzy approach. The clustering formation is done by Energy-Efficient Prediction Clustering Algorithm (EEPCA) in heterogeneous WSN. It is used to calculate the sensor nodes which have shortest distance between each node. The LEACH-ERE protocol was proposed to form a Leader Node (LN) and all the nodes has to communicate with sink through LN only. New SLN is elected based on distance from the sink and battery power of the node.

scholarly journals Designing an Energy Efficient Clustering in Heterogeneous Wireless Sensor Network

2021 ◽  
Vol 13 (1) ◽  
pp. 75-92
Author(s):  
Lakshmi M ◽  
Prashanth C R
Keyword(s):  
Energy Efficient ◽  
Cluster Head ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Delivery Ratio ◽  
Mac Layer ◽  
Optimum Energy ◽  
Heterogeneous Wireless Sensor Network ◽  
Energy Efficient Clustering ◽  
Secured Data

Designing an energy-efficient scheme in a Heterogeneous Wireless Sensor Network (HWSN) is a critical issue that degrades the network performance. Recharging and providing security to the sensor devices is very difficult in an unattended environment once the energy is drained off. A Clustering scheme is an important and suitable approach to increase energy efficiency and transmitting secured data which in turn enhances the performance in the network. The proposed algorithm Energy Efficient Clustering (EEC) works for optimum energy utilization in sensor nodes. The algorithm is proposed by combining the rotation-based clustering and energy-saving mechanism for avoiding the node failure and prolonging the network lifetime. This shows MAC layer scheduling is based on optimum energy utilization depending on the residual energy. In the proposed work, a densely populated network is partitioned into clusters and all the cluster heads are formed at a time and selected on rotation based on considering the highest energy of the sensor nodes. Other cluster members are accommodated in a cluster based on Basic Cost Maximum flow (BCMF) to allow the cluster head for transmitting the secured data. Carrier Sense Multiple Access (CSMA), a contention window based protocol is used at the MAC layer for collision detection and to provide channel access prioritization to HWSN of different traffic classes with reduction in End to End delay, energy consumption, and improved throughput and Packet delivery ratio(PDR) and allowing the cluster head for transmission without depleting the energy. Simulation parameters of the proposed system such as Throughput, Energy, and Packet Delivery Ratio are obtained and compared with the existing system.

scholarly journals Green Data Gathering under Delay Differentiated Services Constraint for Internet of Things

2018 ◽  
Vol 2018 ◽  
pp. 1-23 ◽  
Author(s):  
Mingfeng Huang ◽  
Anfeng Liu ◽  
Tian Wang ◽  
Changqin Huang
Keyword(s):  
Energy Consumption ◽  
Internet Of Things ◽  
Energy Efficient ◽  
Data Gathering ◽  
Differentiated Services ◽  
Residual Energy ◽  
Energy Utilization ◽  
Sensitive Data ◽  
Delay Sensitive ◽  
Delay Tolerant

Energy-efficient data gathering techniques play a crucial role in promoting the development of smart portable devices as well as smart sensor devices based Internet of Things (IoT). For data gathering, different applications require different delay constraints; therefore, a delay Differentiated Services based Data Routing (DSDR) scheme is creatively proposed to improve the delay differentiated services constraint that is missed from previous data gathering studies. The DSDR scheme has three advantages: first, DSDR greatly reduces transmission delay by establishing energy-efficient routing paths (E2RPs). Multiple E2RPs are established in different locations of the network to forward data, and the duty cycles of nodes on E2RPs are increased to 1, so the data is forwarded by E2RPs without the existence of sleeping delay, which greatly reduces transmission latency. Secondly, DSDR intelligently chooses transmission method according to data urgency: the direct-forwarding strategy is adopted for delay-sensitive data to ensure minimum end-to-end delay, while wait-forwarding method is adopted for delay-tolerant data to perform data fusion for reducing energy consumption. Finally, DSDR make full use of the residual energy and improve the effective energy utilization. The E2RPs are built in the region with adequate residual energy and they are periodically rotated to equalize the energy consumption of the network. A comprehensive performance analysis demonstrates that the DSDR scheme has obvious advantages in improving network performance compared to previous studies: it reduces transmission latency of delay-sensitive data by 44.31%, reduces transmission latency of delay-tolerant data by 25.65%, and improves network energy utilization by 30.61%, while also guaranteeing the network lifetime is not lower than previous studies.

DSERR: Delay Sensitive Energy Efficient Reliable Routing Algorithm

2017 ◽  
Vol 97 (3) ◽  
pp. 3685-3704 ◽  
Author(s):  
D. Gosain ◽  
I. Snigdh ◽  
M. Sajwan
Keyword(s):  
Energy Efficient ◽  
Routing Algorithm ◽  
Reliable Routing ◽  
Delay Sensitive

Power Control DSR Routing in Tunnel Environment Monitoring

2012 ◽  
Vol 524-527 ◽  
pp. 815-818
Author(s):  
Deng Yuan Xu ◽  
Zhong Wei Hou
Keyword(s):  
Power Control ◽  
Routing Algorithm ◽  
Life Time ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Cross Layer Design ◽  
Transmission Power ◽  
Environment Monitoring ◽  
Time Data ◽  
Dynamic Source

As one of important technologies of IOT (Internet of Things), WSN (Wireless Sensor Networks) has been used in tunnel environmental monitoring. Tunnel environment monitoring has its particularity that WSN nodes show linear topologies. Traditional routing algorithms in WSN do not consider the linear topology of sensor nodes in tunnel and are difficult to realize long-time data transmission in limited battery power. In this paper, we propose Power Control Dynamic Source Routing algorithm (PC-DSR) by the thought of cross-layer design. Routing table is established according to the distance between nodes and the residual energy of nodes and optimum transmission power is calculated in order to save nodes’ power and prolong the life-time of the whole networks. Simulation results show that the novel algorithm can save node's transmission power, which increase the WSN lifetime of 12.3%.

An Energy Aware Routing Algorithm for WSNs Based on Semi-Static Clustering

2015 ◽  
Vol 752-753 ◽  
pp. 1413-1418
Author(s):  
Tao Du ◽  
Qing Bei Guo ◽  
Kun Zhang ◽  
Kai Wang
Keyword(s):  
Energy Efficiency ◽  
Large Scale ◽  
Routing Algorithm ◽  
Cluster Head ◽  
Residual Energy ◽  
Routing Algorithms ◽  
Sensor Nodes ◽  
Energy Aware ◽  
Hierarchical Routing ◽  
Static Clustering

Energy efficiency is a key factor to improve WSNs’ performance, and hierarchical routing algorithms are fitter in large scale networks and have more reliability, so they are mostly used to improve the nodes’ energy efficiency now. In this paper, mainly existing hierarchical routing algorithms are introduced, and based on these researches, a new energy efficient hierarchical routing algorithm designed based on energy aware semi-static clustering method is proposed. In this algorithm named EASCA, the nodes’ residual energy and cost of communication would both be considered when clustering. And a special packet head is defined to update nodes’ energy information when transmitting message; to rotate cluster head automatically, a member management scheme is designed to complete this function; and a re-cluster mechanism is used to dynamic adjust the clusters to make sensor nodes organization more reasonable. At last, EASCA is compared with other typical hierarchical routing algorithms in a series of experiments, and the experiments’ result proves that EASCA has obviously improved WSNs’ energy efficiency.

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