Local Load Balancing for Globally Efficient Routing in Wireless Sensor Networks

One of the limitations of wireless sensor nodes is their inherent limited energy resource. Besides maximizing the lifetime of the sensor node, it is preferable to distribute the energy dissipated throughout the wireless sensor network in order to minimize maintenance and maximize overall system performance. Any communication protocol that involves synchronization of peer nodes incurs some overhead for setting up the communication. We introduce a new algorithm, e3D (energy-efficient Distributed Dynamic Diffusion routing algorithm), and compare it to two other algorithms, namely directed, and random clustering communication. We take into account the setup costs and analyze the energy-efficiency and the useful lifetime of the system. In order to better understand the characteristics of each algorithm and how well e3D really performs, we also compare e3D with its optimum counterpart and an optimum clustering algorithm. The benefit of introducing these ideal algorithms is to show the upper bound on performance at the cost of astronomical prohibitive synchronization costs. We compare the algorithms in terms of system lifetime, power dissipation distribution, cost of synchronization, and simplicity of the algorithm. Our simulation results show that e3D performs comparable to its optimal counterpart while having significantly less overhead.

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A New Clustering Routing Algorithm for WSN Based on PSO

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.850-851.689 ◽

2013 ◽

Vol 850-851 ◽

pp. 689-692

Author(s):

Li Fu Wang ◽

Jian Ding ◽

Zhi Kong

Keyword(s):

Energy Consumption ◽

Clustering Algorithm ◽

Routing Algorithm ◽

Cluster Head ◽

Pso Algorithm ◽

Sensor Nodes ◽

Wireless Sensor ◽

Long Distance ◽

Wireless Sensor Nodes ◽

Spatially Distributed

A wireless sensor network (WSN) consists of spatially distributed wireless sensor nodes. The node power constrains the development of WSN. Employing techniques of clustering can reduce energy consumption of wireless sensor nodes and prolong the network lifetime. Therefore, in the study a new clustering routing algorithm is presented. The clustering algorithm uses the double-layer sensor nodes to communicate. And in order to optimize power energy consumption for WSN node energy, PSO algorithm is employed to find cluster head in each layer. Simulation results show that the algorithm not only can equal power energy of node, but also can reduce consumption in the long distance data transmission.

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Energy Efficient, Data Centric Routing Algorithm In Mobile Wireless Sensor Nodes (Energy Savings Quantification)

International Journal of Computer Sciences and Engineering ◽

10.26438/ijcse/v6i10.127135 ◽

2018 ◽

Vol 6 (10) ◽

pp. 127-135

Author(s):

Mohammed Nazeer ◽

Garimella Rama Murthy

Keyword(s):

Energy Efficient ◽

Energy Savings ◽

Routing Algorithm ◽

Sensor Nodes ◽

Wireless Sensor ◽

Wireless Sensor Nodes ◽

Mobile Wireless ◽

Efficient Data ◽

Mobile Wireless Sensor

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

International Journal of Sensors Wireless Communications and Control ◽

10.2174/2210327909666190129154802 ◽

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.

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Number of sensors versus time to detection in wildfires

International Journal of Wildland Fire ◽

10.1071/wf07137 ◽

2009 ◽

Vol 18 (7) ◽

pp. 825 ◽

Cited By ~ 5

Author(s):

Pablo I. Fierens

Keyword(s):

Probability Distribution ◽

Propagation Model ◽

Sensor Nodes ◽

Wireless Sensor ◽

Independent Random Variables ◽

Burned Area ◽

Wireless Sensor Nodes ◽

Time To Detection ◽

The Moment ◽

The Cost

The lack of extensive research in the application of inexpensive wireless sensor nodes for the early detection of wildfires motivated us to investigate the cost of such a network. As a first step, in this paper we present several results that relate the time to detection and the burned area to the number of sensor nodes in the region that is protected. We prove that the probability distribution of the size of the burned area at the moment of detection is approximately exponential, given that some hypotheses hold: the positions of the sensor nodes are independent random variables uniformly distributed and the number of sensor nodes is large. This conclusion depends neither on the number of ignition points nor on the propagation model of the fire.

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Improved Energy Efficient Wireless Sensor Networks Using Balanced Multi-Hop Routing Protocol

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i3.6.14927 ◽

2018 ◽

Vol 7 (3.6) ◽

pp. 24

Author(s):

C Sivakumar ◽

P Latha Parthiban

Keyword(s):

Routing Protocol ◽

Energy Efficient ◽

Routing Algorithm ◽

Mobile Network ◽

Base Station ◽

Sensor Nodes ◽

Wireless Sensor ◽

Dijkstra Algorithm ◽

Wireless Sensor Nodes ◽

Combined Technique

In this paper, consumption of energy by the sensor nodes in Wireless Sensor Nodes (WSNs) is been handled effectively using a combined technique. The objective of the paper is to increase the network lifetime with dynamic routing protocol. Here, the proposed routing algorithm, named Balanced Multi-Hop (BMH) protocol combines the multi-hop and direct transmission communication. This method further uses Dijkstra algorithm to route the packets between the sensor nodes and base station in mobile network. This method avoids the use of central router to control the other nodes. The results of the proposed method is tested against various result metrics. The evaluation over other existing methods prove that the BMH method achieves higher lifetime and high network throughput.

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Design Integration Method of Vibration Sensor and Sensing Circuit with Zero-power Charge Transfer for Millimeter-sized Wireless Sensor Nodes

IEEJ Transactions on Sensors and Micromachines ◽

10.1541/ieejsmas.141.7 ◽

2021 ◽

Vol 141 (1) ◽

pp. 7-13

Author(s):

Toshishige Shimamura ◽

Hiroki Morimura

Keyword(s):

Charge Transfer ◽

Integration Method ◽

Vibration Sensor ◽

Sensor Nodes ◽

Wireless Sensor ◽

Wireless Sensor Nodes ◽

Design Integration

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Design, Development and Realization of Flexible Programmable Low-cost Wireless Sensor Nodes for Industrial Application Using IOT

SSRN Electronic Journal ◽

10.2139/ssrn.3446544 ◽

2019 ◽

Author(s):

Anawarali Suthar ◽

Ravi Patel ◽

Pratik Patel

Keyword(s):

Industrial Application ◽

Low Cost ◽

Sensor Nodes ◽

Wireless Sensor ◽

Design Development ◽

Wireless Sensor Nodes

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Energy Efficient Clustering and Routing Algorithm for WSN

Recent Patents on Computer Science ◽

10.2174/2213275912666190716112254 ◽

2019 ◽

Vol 12 ◽

Cited By ~ 1

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.

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