An Energy-Balanced Routing Algorithm in Wireless Seismic Sensor Network

2016 ◽  
Vol 13 (10) ◽  
pp. 6823-6833
Author(s):  
Xunqian Tong ◽  
Gengfa Fang ◽  
Diep Nguyen ◽  
Jun Lin ◽  
Emerson Cabrera
Keyword(s):  
Energy Consumption ◽  
Network Lifetime ◽  
Clustering Algorithm ◽  
Hamming Distance ◽  
Hot Spot ◽  
Routing Algorithm ◽  
Residual Energy ◽  
Data Collector ◽  
Energy Balanced Routing ◽  
Candidate Set

Due to unpredictable geological outdoor environments and imbalances in energy consumption of seismometer nodes in the wireless seismic sensor networks (WSSN), some seismometer nodes fail much earlier than others due to power loss. This would cause hot spot problems, network partitions, and significantly shorten network lifetime. In this paper, we designed an energy-balanced routing algorithm (EBRA) to ensure balanced energy consumption from all seismometer nodes in the WSSN and to enhance the connectivity and lifetime of the WSSN. By aiming at minimizing the imbalance in the residual energy, we divide the routing algorithm into two parts: clustering formation and inter-cluster routing. In clustering formation, we design an energy-balanced clustering algorithm, which selects the cluster head dynamically, based on residual energy, distance between the seismometer node and data collector. The clustering algorithm mitigates hot spot problems by balancing energy consumption among seismometer nodes. In regards to inter-cluster routing, we can relate it to the pareto-candidate set. To reduce the average multi-hop delay from cluster heads to the data collector, we optimize the pareto-candidate set by Hamming distance. In the design of EBRA, we consider minute details such as energy consumed by transmitting bits and impact of average multi-hop delay. This adds to the novelty of this work compared to the existing studies. Simulation results demonstrated a reduction in the average multi-hop delay by 87.5% with network size of 200 nodes in ten different data collector locations. Our algorithm also improves the network lifetime over the others three schemes by 7.8%, 23% and 45.4%, respectively.

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.

Type 2 Fuzzy Logic based Unequal Clustering algorithm for multi-hop wireless sensor networks

2020 ◽  
pp. 33-46
Author(s):  
A. Sariga ◽  
◽  
◽  
J. Uthayakumar
Keyword(s):  
Fuzzy Logic ◽  
Energy Consumption ◽  
Network Lifetime ◽  
Clustering Algorithm ◽  
Hot Spot ◽  
Wireless Sensor ◽  
Unequal Clustering ◽  
Clustering Protocols ◽  
Hot Spot Problem

Wireless sensor network (WSN) is an integral part of IoT and Maximizing the network lifetime is a challenging task. Clustering is the most popular energy efficient technique which leads to increased lifetime stability and reduced energy consumption. Though clustering offers several advantages, it eventually raises the burden of CHs located in proximity to the Base Station (BS) in multi-hop data transmission which makes the CHs near BS die earlier than other CHs. This issue is termed as hot spot problem and unequal clustering protocols were introduced to handle it. Presently, some of the clustering protocols are developed using Type-2 Fuzzy Logic (T2FL) but none of them addresses hot spot problem. This paper presents a Type-2 Fuzzy Logic based Unequal Clustering Algorithm (T2FLUCA) for the elimination of hot spot problem and also for lifetime maximization of WSN. The proposed algorithm uses residual energy, distance to BS and node degree as input to T2FL to determine the probability of becoming CHs (PCH) and cluster size. For experimentation, T2FLUCA is tested on three different scenarios and the obtained results are compared with LEACH, TEEN, DEEC and EAUCF in terms of network lifetime, throughput and average energy consumption. The experimental results ensure that T2FLUCA outperforms state of art methods in a significant way.

scholarly journals Implementation of Enhanced AODV based Self-Organized Tree for Energy Balanced Routing in Wireless Sensor Networks

2020 ◽  
Vol 9 (3) ◽  
pp. 1926-1933
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Data Transmission ◽  
Cluster Head ◽  
Residual Energy ◽  
Wireless Sensor ◽  
Self Organized ◽  
Energy Balanced Routing

Wireless sensor networks (WSN) are gaining attention in numerous fields with the advent of embedded systems and IoT. Wireless sensors are deployed in environmental conditions where human intervention is less or eliminated. Since these are not human monitored, powering and maintaining the energy of the node is a challenging issue. The main research hotspot in WSN is energy consumption. As energy drains faster, the network lifetime also decreases. Self-Organizing Networks (SON) are just the solution for the above-discussed problem. Self-organizing networks can automatically configure themselves, find an optimalsolution, diagnose and self-heal to some extent. In this work, “Implementation of Enhanced AODV based Self-Organized Tree for Energy Balanced Routing in Wireless Sensor Networks” is introduced which uses self-organization to balance energy and thus reduce energy consumption. This protocol uses combination of number of neighboring nodes and residual energy as the criteria for efficient cluster head election to form a tree-based cluster structure. Threshold for residual energy and distance are defined to decide the path of the data transmission which is energy efficient. The improvement made in choosing robust parameters for cluster head election and efficient data transmission results in lesser energy consumption. The implementation of the proposed protocol is carried out in NS2 environment. The experiment is conducted by varying the node density as 20, 40 and 60 nodes and with two pause times 5ms, 10ms. The analysis of the result indicates that the new system consumes 17.6% less energy than the existing system. The routing load, network lifetime metrics show better values than the existing system.

scholarly journals An Efficient Mobile Data Gathering Method with Tree Clustering Algorithm in Wireless Sensor Networks Balanced and Unbalanced Topologies

2021 ◽  
Author(s):  
Meriem MEDDAH ◽  
Rim HADDAD ◽  
Tahar EZZEDDINE
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Clustering Algorithm ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Mobile Data ◽  
Data Collector ◽  
Mobile Data Collector

Abstract Mobile Data Collector device (MDC) is adopted to reduce the energy consumption in Wireless Sensor Networks. This device travels the network in order to gather the collected data from sensor nodes. This paper presents a new Tree Clustering algorithm with Mobile Data Collector in Wireless Sensor Networks, which establishes the shortest travelling path passing throw a subset of Cluster Heads (CH). To select CHs, we adopt a competitive scheme, and the best sensor nodes are elected according to the number of packets forwarded between sensor nodes, the number of hops to the tree’s root, the residual energy, and the distance between the node and the closest CH. In simulation results, we adopt the balanced and unbalanced topologies and prove the efficiently of our proposed algorithm considering the network lifetime, the fairness index and the energy consumption in comparison with the existing mobile data collection algorithms.

scholarly journals Dynamic Multi-hop Routing Protocol Based on Fuzzy-Firefly Algorithm for Data Similarity Aware Node Clustering in WSNs

2018 ◽  
Vol 13 (1) ◽  
pp. 99
Author(s):  
Misbahuddin Misbahuddin ◽  
Anak Agung Putri Ratna ◽  
Riri Fitri Sari
Keyword(s):  
Network Lifetime ◽  
Routing Protocol ◽  
Clustering Algorithm ◽  
Hot Spot ◽  
Routing Algorithm ◽  
Base Station ◽  
Cluster Heads ◽  
Data Similarity ◽  
Fuzzy Aggregation ◽  
Node Clustering

In multi-hop routing, cluster heads close to the base station functionaries as intermediate nodes for father cluster heads to relay the data packet from regular nodes to base station. The cluster heads that act as relays will experience energy depletion quicker that causes hot spot problem. This paper proposes a dynamic multihop routing algorithm named Data Similarity Aware for Dynamic Multi-hop Routing Protocol (DSA-DMRP) to improve the network lifetime, and satisfy the requirement of multi-hop routing protocol for the dynamic node clustering that consider the data similarity of adjacent nodes. The DSA-DMRP uses fuzzy aggregation technique to measure their data similarity degree in order to partition the network into unequal size clusters. In this mechanism, each node can recognize and note its similar neighbor nodes. Next, K-hop Clustering Algorithm (KHOPCA) that is modified by adding a priority factor that considers residual energy and distance to the base station is used to select cluster heads and create the best routes for intra-cluster and inter-cluster transmission. The DSA-DMRP was compared against the KHOPCA to justify the performance. Simulation results show that, the DSA DMRP can improve the network lifetime longer than the KHOPCA and can satisfy the requirement of the dynamic multi-hop routing protocol.

Routing Algorithm based on Clustering for Increasing the Lifetime of Sensor Networks by Using Meta-Heuristic Bee Algorithms

2020 ◽  
Vol 10 (1) ◽  
pp. 25-36
Author(s):  
Mohammad Sedighimanesh ◽  
Hesam Zand Hesami ◽  
Ali Sedighimanesh
Keyword(s):  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Clustering Algorithm ◽  
Heuristic Algorithms ◽  
Routing Algorithm ◽  
Cluster Head ◽  
Cost Effective ◽  
Sensor Nodes ◽  
Wireless Sensor

Background: Nowadays, the use of wireless sensor networks is developing rapidly. these networks are applicable in many fields, including military, medical, and environment. these networks use hundreds or thousands of cheap sensor nodes with low power-low and low energy to perform large tasks. These networks have limitations that can lead to inefficiency or not cost - effective. Among these limitations, consumption of energy and issues related to the lifetime of the network. One of the solutions that can assist the load balancing between sensor nodes, increased scalability, improving energy consumption and consequently, increasing network lifetime, clustering of sensor nodes and placing a suitable cluster head in all clusters. Choosing the right cluster head, significantly reduces energy consumption in the network and increases network lifetime. Objective: The purpose of this paper is to increase network lifetime by using the efficient clustering algorithm, which is used in Meta-heuristic bee colony to select the cluster head. Simulation of this paper is performed by MATLB software and the proposed method is compared with LEACH and GACR approaches. Conclusion: The simulation findings in this study show that the intended study has remarkably increased the length of the network lifetime by LEACH and GACR algorithms. Due to the limitation of energy in the wireless sensor network such solutions and using Meta-heuristic algorithms can give rise a remarkable increasing in network lifetime.

scholarly journals Cluster Routing Algorithm for Ring Based Wireless Sensor Network Using Particle Swarm And Lion Swarm Optimization

2021 ◽  
Author(s):  
Huangshui Hu ◽  
Yuxin Guo ◽  
Jinfeng Zhang ◽  
Chunhua Yin ◽  
Dong Gao
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Hot Spot ◽  
Fitness Function ◽  
Routing Algorithm ◽  
Particle Swarm ◽  
Relay Node ◽  
Wireless Sensor ◽  
Swarm Optimization

Abstract In order to solve the problem of hot spot caused by uneven energy consumption of nodes in Wireless Sensor Networks (WSNs) and reduce the network energy consumption, a novel cluster routing algorithm called CRPL for ring based wireless sensor networks using Particle Swarm Optimization (PSO) and Lion Swarm Optimization (LSO) is proposed in this paper. In CRPL, the optimal cluster head (CH) of each ring are selected by using LSO whose fitness function is composed of energy,number of neighbor nodes, number of cluster heads and distance. Moreover, PSO with a multi-objective fitness function considering distance, energy and cluster size is used to find the next hop relay node in the process of data transmission, and the optimal routing paths are obtained, so as to alleviate the hot spot problem as well as decrease the energy consumption in the routing process. The simulation results show that, compared with some existing optimization algorithms, CRPL has better effects in balancing the energy consumption of the network and prolonging the life cycle of the network.

scholarly journals Energy Balance Routing Algorithm Based on Virtual MIMO Scheme for Wireless Sensor Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Jianpo Li ◽  
Xue Jiang ◽  
I-Tai Lu
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Balance ◽  
Network Lifetime ◽  
Routing Algorithm ◽  
Cluster Head ◽  
Wireless Sensor ◽  
Virtual Mimo ◽  
Head Node

Wireless sensor networks are usually energy limited and therefore an energy-efficient routing algorithm is desired for prolonging the network lifetime. In this paper, we propose a new energy balance routing algorithm which has the following three improvements over the conventional LEACH algorithm. Firstly, we propose a new cluster head selection scheme by taking into consideration the remaining energy and the most recent energy consumption of the nodes and the entire network. In this way, the sensor nodes with smaller remaining energy or larger energy consumption will be much less likely to be chosen as cluster heads. Secondly, according to the ratio of remaining energy to distance, cooperative nodes are selected to form virtual MIMO structures. It mitigates the uneven distribution of clusters and the unbalanced energy consumption of the whole network. Thirdly, we construct a comprehensive energy consumption model, which can reflect more realistically the practical energy consumption. Numerical simulations analyze the influences of cooperative node numbers and cluster head node numbers on the network lifetime. It is shown that the energy consumption of the proposed routing algorithm is lower than the conventional LEACH algorithm and for the simulation example the network lifetime is prolonged about 25%.

scholarly journals Zone-based Energy Efficient Routing Protocols for Wireless Sensor Networks

2019 ◽  
Vol 20 (1) ◽  
pp. 55-70
Author(s):  
Rajan Sharma ◽  
Balwinder Singh Sohi ◽  
Nitin Mittal
Keyword(s):  
Energy Consumption ◽  
Load Balancing ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Residual Energy ◽  
Total Energy Consumption ◽  
Energy Efficient Routing ◽  
Phase Zone ◽  
Zone Formation ◽  
Competitive Algorithms

This paper proposes a novel zone or grid-based network deployment framework for energy efficient selection and reselection process of Zone-Head (ZH) in the WSNs. The proposed zone head reselection process ensures energy efficiency, load balancing, and stability which further prolongs the network lifetime. Instead of carrying out periodic reselection of Zone-Head (ZH) that leads to extra energy consumption and network overhead, the protocol dynamically initiates the process of reselection based on residual energy level of ZH. In the proposed approach the process is segregated into four phases; deployment phase, the zone formation phase, zone head selection phase, data transmission phase and reselection phase. We implemented the proposed algorithm in MATLAB and its result outcomes reveal that the proposed method outperforms the competitive algorithms for parameters such as load balancing, total energy consumption and network lifetime.

scholarly journals Energy Efficient Cross Layer Based Multi-Hop Clustered Routing Protocol For Wireless Sensor Networks

2019 ◽  
Vol 8 (4) ◽  
pp. 11996-12003
Keyword(s):  
Energy Consumption ◽  
Network Lifetime ◽  
Routing Protocols ◽  
Cluster Head ◽  
High Energy ◽  
Residual Energy ◽  
Base Station ◽  
Wireless Sensor ◽  
Cross Layer ◽  
User Friendly

Wireless Sensor network becomes an essential part of Internet of things paradigm due their scalability, ease of deployment and user-friendly interface. However, certain issues like high energy consumption, low network lifetime and optimum quality of service requirement force researchers to develop new routing protocols. In WSNs, the routing protocols are utilized to obtain paths having high quality links and high residual energy nodes for forwarding data towards the sink. Clustering provide the better solution to the WSN challenges by creating access points in the form of cluster head (CH). However, CH must tolerate additional burden for coordinating network activities. After considering these issues, the proposed work designs a moth flame optimization (MFO) based Cross Layer Clustering Optimal (MFO-CLCO) algorithm to consequently optimize the network energy, network lifetime, network delay and network throughput. Multi-hop wireless communication between cluster heads (CHs) and base station (BS) is employed along with MFO to attain optimum path cost. The simulation results demonstrate that the proposed scheme outperforms existing schemes in terms of energy consumption, network lifetime, delay and throughput.

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