scholarly journals Adaptive Energy Balanced Routing Strategy for Wireless Rechargeable Sensor Networks

2019 ◽  
Vol 9 (10) ◽  
pp. 2133 ◽  
Author(s):  
Liangrui Tang ◽  
Zhiyi Chen ◽  
Jinqi Cai ◽  
Haobo Guo ◽  
Runze Wu ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Network Lifetime ◽  
Data Packets ◽  
Charging Time ◽  
Routing Strategy ◽  
Wireless Rechargeable Sensor Networks ◽  
Wireless Rechargeable Sensor Network ◽  
Energy Balanced Routing ◽  
Energy Consumption Rate ◽  
Charging Efficiency

The network lifetime of wireless rechargeable sensor network (WRSN) is commonly extended through routing strategy or wireless charging technology. In this paper, we propose an optimization algorithm from the aspects of both charging and routing process. To balance the network energy in charging part, node’s charging efficiency is balanced by dynamically planning charging point positions and the charging time is allocated according to the energy consumption rate of nodes. Moreover, the routing method is adapted to the node’s charging efficiency. The adaptive routing strategy assigns more forwarding tasks to nodes that can get more energy during the charging phase, and makes the data packets transmit farther away, thus reducing the average hops and energy consumption of the network. Finally, the simulation results reveal that the proposed algorithm has certain advantages in prolonging the network lifetime, reducing the average hop counts and balancing the energy of each node.

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.

Adaptive Duty Cycle Medium Access Control Protocol for Wireless Sensor Networks

2016 ◽  
Vol 5 (2) ◽  
pp. 79
Author(s):  
Anand Babu
Keyword(s):  
Energy Consumption ◽  
Network Lifetime ◽  
Duty Cycle ◽  
Consumption Rate ◽  
Medium Access Control Protocol ◽  
Sleep Mode ◽  
Medium Access ◽  
Low Energy Consumption ◽  
Idle Listening ◽  
Energy Consumption Rate

<p>To increase the network lifetime of WSNs is a major concern. Network lifetime can be increased by reducing energy consumptions through MAC protocols periodic and a- periodic sleep mode mechanisms. The short duty cycle makes sensors have low energy consumption rate but increases the transmission delay and long duty cycle makes the sensor to increase the energy consumption and reduce the delay. Duty cycle need to be adaptively varied to reduce the idle listening. In the proposed Adaptive Duty cycle MAC (ADMAC) protocol, duty cycle is varied by taking nodes rate of energy consumption and filled queue length in account. It reduces the delay and energy spent by reducing the idle listening. ADMAC is realized in NS2 and its performance is compared with SMAC.</p>

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.

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 A Safe Charging Algorithm Based on Multiple Mobile Chargers

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2937
Author(s):  
Wei Wang ◽  
Haoran Jing ◽  
Junhua Liao ◽  
Feng Yin ◽  
Ping Yuan ◽  
...  
Keyword(s):  
Electromagnetic Radiation ◽  
Radiation Safety ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Safety Level ◽  
Wireless Sensor Nodes ◽  
Charging Time ◽  
The One ◽  
Wireless Rechargeable Sensor Network ◽  
Charging Efficiency

A safe charging algorithm in wireless rechargeable sensor network ensures the charging efficiency and the electromagnetic radiation below the threshold. Compared with the current charging algorithms, the safe charging algorithm is more complicated due to the radiation constraint and the mobility of the chargers. A safe charging algorithm based on multiple mobile chargers is proposed in this paper to charge the sensor nodes with mobile chargers, in order to ensure the premise of radiation safety, multiple mobile chargers can effectively complete the network charging task. Firstly, this algorithm narrows the possible location of the sensor nodes by utilizing the charging time and antenna waveform. Secondly, the performance of non-partition charging algorithm which algorithm allow chargers to charge different sensors sets in a different cycle is evaluated against the one of partition charging which does not allow for charging different ones. The moving distance of the charger node will be reduced by 18%. It not only improves the safety level which is inversely proportional to electromagnetic radiation but also expands the application scope of the wireless sensor nodes.

scholarly journals An Online Charging Scheme for Wireless Rechargeable Sensor Networks Based on a Radical Basis Function

Sensors ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 205
Author(s):  
Jia Yang ◽  
Jian-Shuang Bai ◽  
Qiang Xu
Keyword(s):  
Neural Network ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Basis Function ◽  
Consumption Rate ◽  
Rbf Neural Network ◽  
Energy Hole ◽  
Wireless Rechargeable Sensor Networks ◽  
Energy Consumption Rate ◽  
Node Energy

The node energy consumption rate is not dynamically estimated in the online charging schemes of most wireless rechargeable sensor networks, and the charging response of the charging-needed node is fairly poor, which results in nodes easily generating energy holes. Aiming at this problem, an energy hole avoidance online charging scheme (EHAOCS) based on a radical basis function (RBF) neural network, named RBF-EHAOCS, is proposed. The scheme uses the RBF neural network to predict the dynamic energy consumption rate during the charging process, estimates the optimal threshold value of the node charging request on this basis, and then determines the next charging node per the selected conditions: the minimum energy hole rate and the shortest charging latency time. The simulation results show that the proposed method has a lower node energy hole rate and smaller charging node charging latency than two other existing online charging schemes.

scholarly journals A Joint Energy Replenishment and Data Collection Strategy in Heterogeneous Wireless Rechargeable Sensor Networks

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2930
Author(s):  
Mengqiu Tian ◽  
Wanguo Jiao ◽  
Yaqian Chen
Keyword(s):  
Sensor Networks ◽  
Data Collection ◽  
Network Lifetime ◽  
Selection Strategy ◽  
Data Loss ◽  
Remote Areas ◽  
Charging Time ◽  
Data Collection Strategy ◽  
Wireless Rechargeable Sensor Networks ◽  
Energy Replenishment

In wireless rechargeable sensor networks, mobile vehicles (MVs) combining energy replenishment and data collection are studied extensively. To reduce data overflow, most recent work has utilized more vehicles to assist the MV to collect buffered data. However, the practical network environment and the limitations of the vehicle in the data collection are not considered. UAV-enabled data collection is immune to complex road environments in remote areas and has higher speed and less traveling cost, which can overcome the lack of the vehicle in data collection. In this paper, a novel framework joining the MV and UAV is proposed to prolong the network lifetime and reduce data overflow. The network lifetime is correlated with the charging order; therefore, we first propose a charging algorithm to find the optimal charging order. During the charging period of the MV, the charging time may be longer than the collecting time. An optimal selection strategy of neighboring clusters, which could send data to the MV, was found to reduce data overflow. Then, to further reduce data overflow, an algorithm is also proposed to schedule the UAV to assist the MV to collect buffered data. Finally, simulation results verified that the proposed algorithms can maximize network lifetime and minimize the data loss simultaneously.

scholarly journals An On-Demand Charging for Connected Target Coverage in WRSNs Using Fuzzy Logic and Q-Learning

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5520
Author(s):  
Phi Le Nguyen ◽  
Van Quan La ◽  
Anh Duy Nguyen ◽  
Thanh Hung Nguyen ◽  
Kien Nguyen
Keyword(s):  
Fuzzy Logic ◽  
Network Lifetime ◽  
Sensor Nodes ◽  
Target Number ◽  
Q Learning ◽  
On Demand ◽  
Charging Time ◽  
Sufficient Power ◽  
Wireless Rechargeable Sensor Networks ◽  
Wireless Medium

In wireless rechargeable sensor networks (WRSNs), a mobile charger (MC) moves around to compensate for sensor nodes’ energy via a wireless medium. In such a context, designing a charging strategy that optimally prolongs the network lifetime is challenging. This work aims to solve the challenges by introducing a novel, on-demand charging algorithm for MC that attempts to maximize the network lifetime, where the term “network lifetime” is defined by the interval from when the network starts till the first target is not monitored by any sensor. The algorithm, named Fuzzy Q-charging, optimizes both the time and location in which the MC performs its charging tasks. Fuzzy Q-charging uses Fuzzy logic to determine the optimal charging-energy amounts for sensors. From that, we propose a method to find the optimal charging time at each charging location. Fuzzy Q-charging leverages Q-learning to determine the next charging location for maximizing the network lifetime. To this end, Q-charging prioritizes the sensor nodes following their roles and selects a suitable charging location where MC provides sufficient power for the prioritized sensors. We have extensively evaluated the effectiveness of Fuzzy Q-charging in comparison to the related works. The evaluation results show that Fuzzy Q-charging outperforms the others. First, Fuzzy Q-charging can guarantee an infinite lifetime in the WSRNs, which have a sufficient large sensor number or a commensurate target number. Second, in other cases, Fuzzy Q-charging can extend the time until the first target is not monitored by 6.8 times on average and 33.9 times in the best case, compared to existing algorithms.

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%.

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