scholarly journals Prolonging the Lifetime of Wireless Sensor Networks Interconnected to Fixed Network Using Hierarchical Energy Tree Based Routing Algorithm

2014 ◽  
Vol 2014 ◽  
pp. 1-12
Author(s):  
M. Kalpana ◽  
R. Dhanalakshmi ◽  
P. Parthiban
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Routing Algorithm ◽  
Research Work ◽  
Product Evaluation ◽  
Wireless Sensor ◽  
Energy Efficient Routing ◽  
Data Packets ◽  
Fixed Network

This research work proposes a mathematical model for the lifetime of wireless sensor networks (WSN). It also proposes an energy efficient routing algorithm for WSN called hierarchical energy tree based routing algorithm (HETRA) based on hierarchical energy tree constructed using the available energy in each node. The energy efficiency is further augmented by reducing the packet drops using exponential congestion control algorithm (TCP/EXP). The algorithms are evaluated in WSNs interconnected to fixed network with seven distribution patterns, simulated in ns2 and compared with the existing algorithms based on the parameters such as number of data packets, throughput, network lifetime, and data packets average network lifetime product. Evaluation and simulation results show that the combination of HETRA and TCP/EXP maximizes longer network lifetime in all the patterns. The lifetime of the network with HETRA algorithm has increased approximately 3.2 times that of the network implemented with AODV.

An Energy Efficient Routing Protocol Based On New Variable Data Packet (VDP) Algorithm for Wireless Sensor Networks

2020 ◽  
Vol 13 (3) ◽  
pp. 353-361
Author(s):  
Veervrat Singh Chandrawanshi ◽  
Rajiv Kumar Tripathi ◽  
Rahul Pachauri ◽  
Nafis Uddin Khan
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Routing Algorithm ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Energy Efficient Routing ◽  
Data Packets ◽  
Variable Data

Background:Wireless Sensor Networks (WSNs) refer to a group of sensors used for sensing and monitoring the physical data of the environment and organizing the collected data at a central location. These networks enjoy several benefits because of their lower cost, smaller size and smarter sensors. However, a limited source of energy and lifetime of the sensors have emerged as the major setbacks for these networks.Methods:In this work, an energy-aware algorithm has been proposed for the transmission of variable data packets from sensor nodes to the base station according to the balanced energy consumption by all the nodes of a WSN.Results:Obtained simulation results verify that the lifetime of the sensor network is significantly enhanced in comparison to other existing clustering based routing algorithm.Conclusion:The proposed algorithm is comparatively easy to implement and achieves a higher gain in the lifetime of a WSN while keeping the throughput nearly same as LEACH protocol.

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 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.

scholarly journals An Intelligent Opportunistic Routing Algorithm for Wireless Sensor Networks and Its Application Towards e-Healthcare

Sensors ◽  
2020 ◽  
Vol 20 (14) ◽  
pp. 3887 ◽  
Author(s):  
Deep Kumar Bangotra ◽  
Yashwant Singh ◽  
Arvind Selwal ◽  
Nagesh Kumar ◽  
Pradeep Kumar Singh ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Routing Algorithm ◽  
Relay Node ◽  
Healthcare Services ◽  
Opportunistic Routing ◽  
Wireless Sensor ◽  
Energy Efficient Routing

The lifetime of a node in wireless sensor networks (WSN) is directly responsible for the longevity of the wireless network. The routing of packets is the most energy-consuming activity for a sensor node. Thus, finding an energy-efficient routing strategy for transmission of packets becomes of utmost importance. The opportunistic routing (OR) protocol is one of the new routing protocol that promises reliability and energy efficiency during transmission of packets in wireless sensor networks (WSN). In this paper, we propose an intelligent opportunistic routing protocol (IOP) using a machine learning technique, to select a relay node from the list of potential forwarder nodes to achieve energy efficiency and reliability in the network. The proposed approach might have applications including e-healthcare services. As the proposed method might achieve reliability in the network because it can connect several healthcare network devices in a better way and good healthcare services might be offered. In addition to this, the proposed method saves energy, therefore, it helps the remote patient to connect with healthcare services for a longer duration with the integration of IoT services.

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.

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