scholarly journals PCA-Guided Routing Algorithm for Wireless Sensor Networks

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Gong Chen ◽  
Liansheng Tan ◽  
Yanlin Gong ◽  
Wei Zhang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Routing Algorithm ◽  
Principal Component ◽  
Wireless Sensor ◽  
Energy Dissipated ◽  
Sum Of Distances ◽  
Theoretical Analyses

An important performance concern for wireless sensor networks (WSNs) is the total energy dissipated by all the nodes in the network over the course of network lifetime. In this paper, we propose a routing algorithm termed as PCA-guided routing algorithm (PCA-RA) by exploring the principal component analysis (PCA) approach. Our algorithm remarkably reduces energy consumption and prolongs network lifetime by realizing the objective of minimizing the sum of distances between the nodes and the cluster centers in a WSN network. It is demonstrated that the PCA-RA can be efficiently implemented in WSNs by forming a nearly optimalK-means-like clustering structure. In addition, it can decrease the network load while maintaining the accuracy of the sensor measurements during data aggregating process. We validate the efficacy and efficiency of the proposed algorithm by simulations. Both theoretical analyses and simulation results demonstrate that this algorithm can perform significantly with less energy consumption and thus prolong the system lifetime for the networks.

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%.

An Energy Balancing Cross Layer Scheme for Long Lifetime Wireless Sensor Networks

2015 ◽  
Vol 764-765 ◽  
pp. 827-831
Author(s):  
Yung Fa Huang ◽  
Tan Hsu Tan ◽  
Yau Der Wang ◽  
Young Long Chen ◽  
Neng Chung Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Load Balancing ◽  
Network Lifetime ◽  
Routing Algorithm ◽  
Wireless Sensor ◽  
Cross Layer ◽  
Energy Balancing ◽  
Energy Aware

In this paper, we propose an improved routing algorithm to prolong network lifetime of wireless sensor networks (WSNs) by combining the shortest hop routing tree (SHORT) algorithm and the, turn off redundant node (TORN) MAC layer protocol to cross layer SHORTORN scheme. Moreover, to prolong the lifetime of the first node death (FND) in networks, the rate of energy consumption should be balanced for all nodes. Therefore, this paper further proposes a load balancing SHORTORN scheme by combining the weight and energy-aware, called energy-aware weight-based SHORTORN (EWSHORTORN). The proposed EWSHORTORN algorithm lets more nodes share the load of the leader and balances the opportunity of data relaying to all nodes. The proposed load balancing scheme allocates energy consumption load to be more uniformly among all nodes, thus the FNL can be prolonged evidently. Simulation results show that the proposed EWSHORTORN outperforms the SHORT scheme with double lifetime of FND.Keywords: wireless sensor networks, network lifetime, cross layer protocol, load balance.

QoS Aware Multi-hop Multi-path Routing Approach in Wireless Sensor Networks

2019 ◽  
Vol 9 (1) ◽  
pp. 43-52
Author(s):  
Omkar Singh ◽  
Vinay Rishiwal
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Life Time ◽  
Base Station ◽  
Environmental Data ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
End To End

Background & Objective: Wireless Sensor Network (WSN) consist of huge number of tiny senor nodes. WSN collects environmental data and sends to the base station through multi-hop wireless communication. QoS is the salient aspect in wireless sensor networks that satisfies end-to-end QoS requirement on different parameters such as energy, network lifetime, packets delivery ratio and delay. Among them Energy consumption is the most important and challenging factor in WSN, since the senor nodes are made by battery reserved that tends towards life time of sensor networks. Methods: In this work an Improve-Energy Aware Multi-hop Multi-path Hierarchy (I-EAMMH) QoS based routing approach has been proposed and evaluated that reduces energy consumption and delivers data packets within time by selecting optimum cost path among discovered routes which extends network life time. Results and Conclusion: Simulation has been done in MATLAB on varying number of rounds 400- 2000 to checked the performance of proposed approach. I-EAMMH is compared with existing routing protocols namely EAMMH and LEACH and performs better in terms of end-to-end-delay, packet delivery ratio, as well as reduces the energy consumption 13%-19% and prolongs network lifetime 9%- 14%.

scholarly journals Energy Aware Simple Ant Routing Algorithm for Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-11
Author(s):  
Sohail Jabbar ◽  
Rabia Iram ◽  
Muhammad Imran ◽  
Awais Ahmad ◽  
Anand Paul ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Large Scale ◽  
Routing Algorithm ◽  
Wireless Sensor ◽  
Route Discovery ◽  
Route Selection ◽  
Energy Aware ◽  
Forwarding Node

Network lifetime is one of the most prominent barriers in deploying wireless sensor networks for large-scale applications because these networks employ sensors with nonrenewable scarce energy resources. Sensor nodes dissipate most of their energy in complex routing mechanisms. To cope with limited energy problem, we present EASARA, an energy aware simple ant routing algorithm based on ant colony optimization. Unlike most algorithms, EASARA strives to avoid low energy routes and optimizes the routing process through selection of least hop count path with more energy. It consists of three phases, that is, route discovery, forwarding node, and route selection. We have improved the route discovery procedure and mainly concentrate on energy efficient forwarding node and route selection, so that the network lifetime can be prolonged. The four possible cases of forwarding node and route selection are presented. The performance of EASARA is validated through simulation. Simulation results demonstrate the performance supremacy of EASARA over contemporary scheme in terms of various metrics.

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 A PSO-Based Uneven Dynamic Clustering Multi-Hop Routing Protocol for Wireless Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 1835 ◽  
Author(s):  
Ruan ◽  
Huang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Routing Protocol ◽  
Cluster Head ◽  
Base Station ◽  
Wireless Sensor ◽  
Dynamic Clustering ◽  
Energy Efficient Routing

Since wireless sensor networks (WSNs) are powered by energy-constrained batteries, many energy-efficient routing protocols have been proposed to extend the network lifetime. However, most of the protocols do not well balance the energy consumption of the WSNs. The hotspot problem caused by unbalanced energy consumption in the WSNs reduces the network lifetime. To solve the problem, this paper proposes a PSO (Particle Swarm Optimization)-based uneven dynamic clustering multi-hop routing protocol (PUDCRP). In the PUDCRP protocol, the distribution of the clusters will change dynamically when some nodes fail. The PSO algorithm is used to determine the area where the candidate CH (cluster head) nodes are located. The adaptive clustering method based on node distribution makes the cluster distribution more reasonable, which balances the energy consumption of the network more effectively. In order to improve the energy efficiency of multi-hop transmission between the BS (Base Station) and CH nodes, we also propose a connecting line aided route construction method to determine the most appropriate next hop. Compared with UCCGRA, multi-hop EEBCDA, EEMRP, CAMP, PSO-ECHS and PSO-SD, PUDCRP prolongs the network lifetime by between 7.36% and 74.21%. The protocol significantly balances the energy consumption of the network and has better scalability for various sizes of network.

An Energy Aware Routing Based on Swarm Intelligence for Wireless Sensor Networks

2013 ◽  
Vol 706-708 ◽  
pp. 635-638
Author(s):  
Yong Lv
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Swarm Intelligence ◽  
Network Lifetime ◽  
Average Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Energy Efficient Routing

Wireless Sensor Networks consisting of nodes with limited power are deployed to collect and distribute useful information from the field to the other sensor nodes. Energy consumption is a key issue in the sensor’s communications since many use battery power, which is limited. In this paper, we describe a novel energy efficient routing approach which combines swarm intelligence, especially the ant colony based meta-heuristic, with a novel variation of reinforcement learning for sensor networks (ARNet). The main goal of our study was to maintain network lifetime at a maximum, while discovering the shortest paths from the source nodes to the sink node using an improved swarm intelligence. ARNet balances the energy consumption of nodes in the network and extends the network lifetime. Simulation results show that compared with the traditional EEABR algorithm can obviously improve adaptability and reduce the average energy consumption effectively.

Sign in / Sign up

Export Citation Format

Share Document