scholarly journals Autonomous Load Regulation Based Energy Balanced Routing in Rechargeable Wireless Sensor Networks

2019 ◽  
Vol 9 (16) ◽  
pp. 3251 ◽  
Author(s):  
Runze Wu ◽  
Haobo Guo ◽  
Liangrui Tang ◽  
Bing Fan
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Wireless Sensor ◽  
Regulation Mechanism ◽  
Wireless Charging ◽  
Routing Strategy ◽  
Load Regulation ◽  
Energy Balanced Routing ◽  
Balancing Efficiency

Recent progress in wireless charging technologies has greatly promoted the development of rechargeable wireless sensor networks (RWSN). The network lifetime of RWSN can be commonly extended through routing strategy and wireless charging technology. However, the node accepts the relay request of its neighbor unconditionally, and it cannot remove its overload on its own in a timely manner in traditional routing strategies. The energy balancing efficiency of the network may be limited by this passive mechanism, which poses a great challenge to obtaining optimal joint efficiency of routing and charging strategies. In this paper, we propose an autonomous load regulation mechanism-based energy balanced routing algorithm (ALRMR) for RWSN. In addition to an efficient framework of joint wireless energy transfer and multi-hop routing where the routing strategy is adapted to the charging scheme, an innovative load regulation mechanism is proposed. Under this mechanism, each node can actively adjust its own load by controlling its relay radius. The simulation demonstrates the advantages of our algorithm for energy balance efficiency and improving the network lifetime through the charging scheme and the innovative mechanism.

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.

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 Distributed and morphological operation-based data collection algorithm

2017 ◽  
Vol 13 (7) ◽  
pp. 155014771771759 ◽  
Author(s):  
Yalin Nie ◽  
Haijun Wang ◽  
Yujie Qin ◽  
Zeyu Sun
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Collection ◽  
Network Lifetime ◽  
Algorithm Analysis ◽  
Wireless Sensor ◽  
Morphological Operation ◽  
Event Monitoring ◽  
Binary Images ◽  
Structuring Element

When monitoring the environment with wireless sensor networks, the data sensed by the nodes within event backbone regions can adequately represent the events. As a result, identifying event backbone regions is a key issue for wireless sensor networks. With this aim, we propose a distributed and morphological operation-based data collection algorithm. Inspired by the use of morphological erosion and dilation on binary images, the proposed distributed and morphological operation-based data collection algorithm calculates the structuring neighbors of each node based on the structuring element, and it produces an event-monitoring map of structuring neighbors with less cost and then determines whether to erode or not. The remaining nodes that are not eroded become the event backbone nodes and send their sensing data. Moreover, according to the event backbone regions, the sink can approximately recover the complete event regions by the dilation operation. The algorithm analysis and experimental results show that the proposed algorithm can lead to lower overhead, decrease the amount of transmitted data, prolong the network lifetime, and rapidly recover event regions.

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 GAFOR: Genetic Algorithm Based Fuzzy Optimized Re-Clustering in Wireless Sensor Networks

Mathematics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 43
Author(s):  
Muhammad K. Shahzad ◽  
S. M. Riazul Islam ◽  
Mahmud Hossain ◽  
Mohammad Abdullah-Al-Wadud ◽  
Atif Alamri ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Smart Cities ◽  
Hot Spot ◽  
Time Instant ◽  
Wireless Sensor ◽  
Injection Attacks ◽  
Fixed Path

In recent years, the deployment of wireless sensor networks has become an imperative requisite for revolutionary areas such as environment monitoring and smart cities. The en-route filtering schemes primarily focus on energy saving by filtering false report injection attacks while network lifetime is usually ignored. These schemes also suffer from fixed path routing and fixed response to these attacks. Furthermore, the hot-spot is considered as one of the most crucial challenges in extending network lifetime. In this paper, we have proposed a genetic algorithm based fuzzy optimized re-clustering scheme to overcome the said limitations and thereby minimize the effect of the hot-spot problem. The fuzzy logic is applied to capture the underlying network conditions. In re-clustering, an important question is when to perform next clustering. To determine the time instant of the next re-clustering (i.e., number of nodes depleted—energy drained to zero), associated fuzzy membership functions are optimized using genetic algorithm. Simulation experiments validate the proposed scheme. It shows network lifetime extension of up to 3.64 fold while preserving detection capacity and energy-efficiency.

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