scholarly journals A Topology Control with Energy Balance in Underwater Wireless Sensor Networks for IoT-Based Application

Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2306 ◽  
Author(s):  
Zhen Hong ◽  
Xiaoman Pan ◽  
Ping Chen ◽  
Xianchuang Su ◽  
Ning Wang ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Balance ◽  
Topology Control ◽  
Water Environment ◽  
Wireless Sensor ◽  
Underwater Wireless Sensor Networks ◽  
Network Failure ◽  
Application Fields

As part of the IoT-based application, underwater wireless sensor networks (UWSN), which are typically self-organized heterogeneous wireless network, are one of the research hot-spots using various sensors in marine exploration and water environment monitoring application fields, recently. Due to the serious attenuation of radio in water, acoustic or hybrid communication is a usual way for transmitting information among nodes, which dissipates much more energy to prevent the network failure and guarantee the quality of service (QoS). To address this issue, a topology control with energy balance, namely TCEB, is proposed for UWSN to overcome time-delay and other interference, as well as make the entire network load balance. With the given underwater network model and its specialized energy consumption model, we introduce the non-cooperative-game-based scheme to select the nodes with better performance as the cluster-heads. Afterwards, the intra-cluster and inter-cluster topology construction are, respectively, to form the effective communication links of the intra-cluster and inter-cluster, which aim to build energy-efficient topology to reduce energy consumption. With the demonstration of the simulation, the results show the proposed TCEB has better performance on energy-efficiency and throughput than three other representative algorithms in complex underwater environments.

scholarly journals An Uneven Node Self-Deployment Optimization Algorithm for Maximized Coverage and Energy Balance in Underwater Wireless Sensor Networks

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1368 ◽  
Author(s):  
Luoheng Yan ◽  
Yuyao He ◽  
Zhongmin Huangfu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Balance ◽  
Optimization Algorithm ◽  
Growth Ring ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Underwater Wireless Sensor Networks ◽  
Connected Network ◽  
Deployment Optimization

The underwater wireless sensor networks (UWSNs) have been applied in lots of fields such as environment monitoring, military surveillance, data collection, etc. Deployment of sensor nodes in 3D UWSNs is a crucial issue, however, it is a challenging problem due to the complex underwater environment. This paper proposes a growth ring style uneven node depth-adjustment self-deployment optimization algorithm (GRSUNDSOA) to improve the coverage and reliability of UWSNs, meanwhile, and to solve the problem of energy holes. In detail, a growth ring style-based scheme is proposed for constructing the connective tree structure of sensor nodes and a global optimal depth-adjustment algorithm with the goal of comprehensive optimization of both maximizing coverage utilization and energy balance is proposed. Initially, the nodes are scattered to the water surface to form a connected network on this 2D plane. Then, starting from sink node, a growth ring style increment strategy is presented to organize the common nodes as tree structures and each root of subtree is determined. Meanwhile, with the goal of global maximizing coverage utilization and energy balance, all nodes depths are computed iteratively. Finally, all the nodes dive to the computed position once and a 3D underwater connected network with non-uniform distribution and balanced energy is constructed. A series of simulation experiments are performed. The simulation results show that the coverage and reliability of UWSN are improved greatly under the condition of full connectivity and energy balance, and the issue of energy hole can be avoided effectively. Therefore, GRSUNDSOA can prolong the lifetime of UWSN significantly.

An Energy-Balance Based Distributed Topology Control Algorithm for Wireless Sensor Networks

2012 ◽  
Vol 490-495 ◽  
pp. 1392-1396 ◽  
Author(s):  
Chu Hang Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Topology Control ◽  
Control Algorithm ◽  
Path Loss ◽  
Network Connectivity ◽  
Premature Death ◽  
Residual Energy ◽  
Wireless Sensor

Topology control is an efficient approach which can reduce energy consumption for wireless sensor networks, and the current algorithms mostly focus on reducing the nodes’ energy consumption by power adjusting, but pay little attention to balance energy consumption of the whole network, which results in premature death of many nodes. Thus, a distributed topology control algorithm based on path-loss and residual energy (PRTC) is designed in this paper. This algorithm not only maintains the least loss links between nodes but also balances the energy consumption of the network. The simulation results show that the topology constructed by PRTC can preserve network connectivity as well as extend the lifetime of the network and provide good performance of energy consumption.

scholarly journals Hierarchical classification of time series data aggregation in underwater wireless sensor networks

2020 ◽  
Vol 37 (2) ◽  
pp. 53-64
Author(s):  
Durairaj Ruby ◽  
Jayachandran Jeyachidra
Keyword(s):  
Time Series ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Error Rate ◽  
Data Aggregation ◽  
Hierarchical Classification ◽  
Wireless Sensor ◽  
Underwater Wireless Sensor Networks

Environmental fluctuations are continuous and provide opportunities for further exploration, including the study of overground, as well as underground and submarine, strata. Underwater wireless sensor networks (UWSNs) facilitate the study of ocean-based submarine and marine parameters details and data. Hardware plays a major role in monitoring marine parameters; however, protecting the hardware deployed in water can be difficult. To extend the lifespan of the hardware, the inputs, processing and output cycles may be reduced, thus minimising the consumption of energy and increasing the lifespan of the devices. In the present study, time series similarity check (TSSC) algorithm is applied to the real-time sensed data to identify repeated and duplicated occurrences of data for reduction, and thus improve energy consumption. Hierarchical classification of ANOVA approach (HCAA) applies ANOVA (analysis of variance) statistical analysis model to calculate error analysis for realtime sensed data. To avoid repeated occurrences, the scheduled time to read measurements may be extended, thereby reducing the energy consumption of the node. The shorter time interval of observations leads to a higher error rate with lesser accuracy. TSSC and HCAA data aggregation models help to minimise the error rate and improve accuracy.

scholarly journals A Method for Energy Balance and Data Transmission Optimal Routing in Wireless Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 3017 ◽  
Author(s):  
Xuesong Liu ◽  
Jie Wu
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Balance ◽  
Energy Distribution ◽  
Data Transmission ◽  
Line Length ◽  
Wireless Sensor ◽  
Hop Count ◽  
Transmission Distance

Wireless sensor networks are widely used in many fields. Nodes in the network are typically powered by batteries. Because the energy consumption of wireless communication is related to the transmission distance, the energy consumption of nodes in different locations is different, resulting in uneven energy distribution of nodes. In some special applications, all nodes are required to work at the same time, and the uneven energy distribution makes the effective working time of the system subject to the node with the largest energy consumption. The commonly used clustering protocol can play a role in balancing energy consumption, but it does not achieve optimal energy consumption. This paper proposes to use the power supply line to connect the nodes to fully balance the energy. The connection scheme with the shortest power line length is also proposed. On the basis of energy balance, the method of transmitting data with the best hop count is proposed, which fully reduces the power consumption of the data transmission. The simulation results show that the proposed method can effectively reduce the energy consumption and prolong the lifetime of wireless sensor 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%.

scholarly journals A data forwarding algorithm based on Markov thought in underwater wireless sensor networks

2017 ◽  
Vol 13 (2) ◽  
pp. 155014771769198
Author(s):  
Dongwei Li ◽  
Jingli Du ◽  
Linfeng Liu
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Success Rate ◽  
Three Dimensional ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Underwater Wireless Sensor Networks ◽  
Data Forwarding ◽  
Bottom To Top

The underwater wireless sensor networks composed of sensor nodes are deployed underwater for monitoring and gathering submarine data. Since the underwater environment is usually unpredictable, making the nodes move or be damaged easily, such that there are several vital objectives in the data forwarding issue, such as the delivery success rate, the error rate, and the energy consumption. To this end, we propose a data forwarding algorithm based on Markov thought, which logically transforms the underwater three-dimensional deployment model into a two-dimensional model, and thus the nodes are considered to be hierarchically deployed. The data delivery is then achieved through a “bottom to top” forwarding mode, where the delivery success rate is improved and the energy consumption is reduced because the established paths are more stable, and the proposed algorithm is self-adaptive to the dynamic routing loads.

scholarly journals Maximizing Network Lifetime Operator for Wireless Sensor Networks

2013 ◽  
Vol 4 (2) ◽  
pp. 267-272
Author(s):  
Dr. Deepali Virmani
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Topology Control ◽  
Performance Metrics ◽  
Minimum Energy ◽  
Energy Utilization ◽  
Wireless Sensor ◽  
Minimum Energy Consumption

Optimizing and enhancing network lifetime with minimum energy consumption is the major challenge in field of wireless sensor networks. Existing techniques for optimizing network lifetime are based on exploiting node redundancy, adaptive radio transmission power and topology control. Topology control protocols have a significant impact on network lifetime, available energy and connectivity. In this paper we categorize sensor nodes as strong and weak nodes based on their residual energy as well as operational lifetime and propose a Maximizing Network lifetime Operator (MLTO) that defines cluster based topology control mechanism to enhance network lifetime while guarantying the minimum energy consumption and minimum delay. Extensive simulations in Java-Simulator (J-Sim) show that our proposed operator outperforms the existing protocols in terms of various performance metrics life network lifetime, average delay and minimizes energy utilization.

scholarly journals Reinforcement Learning-Based Data Forwarding in Underwater Wireless Sensor Networks with Passive Mobility

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 256 ◽  
Author(s):  
Haotian Chang ◽  
Jing Feng ◽  
Chaofan Duan
Keyword(s):  
Wireless Sensor Networks ◽  
Reinforcement Learning ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Mobility Model ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Underwater Wireless Sensor Networks ◽  
Data Forwarding ◽  
Energy Constrained

Data forwarding for underwater wireless sensor networks has drawn large attention in the past decade. Due to the harsh underwater environments for communication, a major challenge of Underwater Wireless Sensor Networks (UWSNs) is the timeliness. Furthermore, underwater sensor nodes are energy constrained, so network lifetime is another obstruction. Additionally, the passive mobility of underwater sensors causes dynamical topology change of underwater networks. It is significant to consider the timeliness and energy consumption of data forwarding in UWSNs, along with the passive mobility of sensor nodes. In this paper, we first formulate the problem of data forwarding, by jointly considering timeliness and energy consumption under a passive mobility model for underwater wireless sensor networks. We then propose a reinforcement learning-based method for the problem. We finally evaluate the performance of the proposed method through simulations. Simulation results demonstrate the validity of the proposed method. Our method outperforms the benchmark protocols in both timeliness and energy efficiency. More specifically, our method gains 83.35% more value of information and saves up to 75.21% energy compared with a classic lifetime-extended routing protocol (QELAR).

scholarly journals Game Theory Based Construction Efficient Topology in Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-12
Author(s):  
M. J. Abbasi ◽  
Muhammad Shafie Bin Abd Latiff ◽  
Hassan Chizari ◽  
N. Fisal
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Topology Control ◽  
Spanning Tree ◽  
Minimum Spanning Tree ◽  
Wireless Sensor ◽  
Noncooperative Game ◽  
Power Cost ◽  
Minimum Power

Topology control is one of the most important techniques used in wireless sensor networks; to some extent it can reduce energy consumption in which each node is capable of minimizing its transmission power level while preserving network connectivity. Reducing energy consumption has been addressed through different aspects till now. In this paper, we present a minimum spanning tree- (MST-) based algorithm, called noncooperative minimum spanning tree (NMST), for topology control in wireless multihop networks. In this algorithm, each node constructs its minimum power-cost spanning tree which is a tree and can connect the node with one hop away from its neighbor node in constructed topology. In addition we address the power-cost allocation problem when node acts selfishly. A class of strategies is proposed which construct minimum power-cost spanning tree such that the sum of the power-cost (as proxy of weight), at the same time, is a strong Nash equilibrium for a noncooperative game associated with the problem of efficient topology construction. Simulation results show that NMST can maximize the sensor network lifetimes.

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