scholarly journals Calculation and Simulation of Transmission Reliability in Wireless Sensor Network Based on Network Coding

2017 ◽  
Vol 13 (12) ◽  
pp. 150 ◽  
Author(s):  
Zhifu Luan
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Network Coding ◽  
Sensor Network ◽  
Data Transmission ◽  
Average Energy ◽  
Wireless Sensor ◽  
Finite Domain ◽  
Transmission Reliability ◽  
Average Energy Consumption

<span style="font-family: 'Times New Roman',serif; font-size: 10pt; mso-fareast-font-family: 'Times New Roman'; mso-ansi-language: EN-US; mso-fareast-language: DE; mso-bidi-language: AR-SA;">The wireless sensor network (WSN) has penetrated into every corner in our lives, ranging from national defense, biological medicine, environmental monitoring, to traffic management. It is of great significance to study the reliability of data transmission, a key determinant of the results of monitoring events. The network reliability lies in fault tolerance: when some nodes or links in the network fail, the data can be recovered at the sink node by selecting the appropriate finite domain space. In this paper, network coding is used to improve the reliability of WSN. Firstly, the author calculated the data transmission reliability and average energy consumption of network coding in single-path and multi-path scenarios. Then, the average energy consumption of network coding was compared with that of the traditional method. Finally, the reliabilities of the two different methods were simulated on MATLAB at different channel loss rates. The experimental results show that the reliability of the network coding technique is better than the traditional one at the expense of a small amount of energy.</span>

scholarly journals A mobility aware duty cycling and preambling solution for wireless sensor network with mobile sink node

2021 ◽  
Author(s):  
Craig Thomson ◽  
Isam Wadhaj ◽  
Zhiyuan Tan ◽  
Ahmed Al-Dubai
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Average Energy ◽  
Mobile Sink ◽  
Maximum Energy ◽  
Wireless Sensor ◽  
Sink Node ◽  
Duty Cycling ◽  
Average Energy Consumption

AbstractUtilising the mobilisation of a sink node in a wireless sensor network to combat the energy hole, or hotspot issue, is well referenced. However, another issue, that of energy spikes may remain. With the mobile sink node potentially communicating with some nodes more than others. In this study we propose the Mobility Aware Duty Cycling and Dynamic Preambling Algorithm (MADCaDPAL). This algorithm utilises an existing solution where a communication threshold is built between a mobile sink node using predictable mobility and static nodes on its path. MADCaDPAL bases decisions relating to node sleep function, moving to clear channel assessment and the subsequent sending of preambles on the relation between the threshold built by the static node and the position of the mobile sink node. MADCaDPAL achieves a reduction in average energy consumption of up to 80%, this when used in conjunction with a lightweight carrier-sense multiple access based MAC implementation. Maximum energy consumption amongst individual nodes is also brought closer to the average, reducing energy spikes and subsequently improving network lifetime. Additionally, frame delivery to the sink is improved overall.

scholarly journals A New Energy-Efficient Data Transmission Scheme Based on DSC and Virtual MIMO for Wireless Sensor Network

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Na Li ◽  
Liwen Zhang ◽  
Bing Li
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Data Transmission ◽  
Source Coding ◽  
Distributed Source Coding ◽  
Wireless Sensor ◽  
Transmission Scheme ◽  
Distributed Source

Energy efficiency in wireless sensor network (WSN) is one of the primary performance parameters. For improving the energy efficiency of WSN, we introduce distributed source coding (DSC) and virtual multiple-input multiple-output (MIMO) into wireless sensor network and then propose a new data transmission scheme called DSC-MIMO. DSC-MIMO compresses the source data using distributed source coding before transmitting, which is different from the existing communication schemes. Data compression can reduce the length of the data and improve the energy efficiency. In addition, DSC-MIMO does not require the cluster heads to collect the data of the source nodes, which reduces the frequencies of data transmission and saves energy. In the simulation, we analyze the energy consumption of DSC-MIMO. The results indicate that DSC-MIMO can effectively reduce the energy consumption and improve the energy efficiency of the whole wireless sensor network.

Reliable data transmission method based on 6LoWPAN for building energy systems

2019 ◽  
Vol 41 (5) ◽  
pp. 623-633
Author(s):  
Cui-Min Li ◽  
Chun-Ying Li ◽  
Lei Wang
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Data Transmission ◽  
Building Energy ◽  
Reliable Data ◽  
Wireless Sensor ◽  
Building Energy Consumption ◽  
Transmission Method ◽  
Energy Monitoring ◽  
Transmission Reliability

The building energy internet of things is based on radio frequency technology and a wireless sensor network that can collect building energy consumption data in real time. However, with the increasing complexity of wireless sensor network topology, there is a problem of insufficient IP address space relying on IPv4 protocol. In this paper, a design scheme of a building energy system based on 6LoWPAN network is proposed. IPv4/IPv6 address conversion is used to realise the access of IP addresses to each other, so as to monitor building energy consumption information anytime and anywhere. In view of the shortcomings of existing wireless network data transmission methods in low energy consumption and high reliability in building energy monitoring applications, a reliable data transmission method based on multipath routing coding algorithm is proposed. This strategy improves the transmission reliability of the network by increasing the number of redundant packets, and reduces the energy consumption of the network by reducing the number of transmission paths. The simulation results show that the proposed method can effectively improve the success rate of data packet transmission, reduce the standard energy consumption of sensor networks, and provide an effective method for the application of wireless sensor networks in building energy monitoring systems. Practical application: This paper studies how to improve transmission reliability and energy efficiency in cluster-based WSN and proposes a multi-path transmission strategy for selective coding of intermediate cluster head nodes. The strategy improves the transmission reliability of the network by increasing the number of transmissions of redundant packets and reduces the network energy consumption by reducing the number of transmission paths. It has good use value for the actual development and application of the building energy consumption monitoring system.

STBCP: An Energy Efficient Sub-threshold Bee Colony-based Protocol for Wireless Sensor Networks

2019 ◽  
Vol 9 (4) ◽  
pp. 443-453
Author(s):  
Ghazaleh Kia ◽  
Alireza Hassanzadeh
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Energy Efficient ◽  
Average Energy ◽  
Wireless Sensor ◽  
Battery Lifetime ◽  
Bee Colony

Background & Objective: In this paper, a new energy efficient LEACH-based protocol for wireless sensor network is presented. One of the main issues in Wireless Sensor Networks (WSNs) is the battery consumption. In fact, changing batteries is a time consuming task and expensive. It is even impossible in many remote WSNs. Methods: The main goal of the presented protocol is to decrease the energy consumption of each node and increase the network lifetime. Lower power consumption results in longer battery lifetime. This protocol takes the advantage of sub-threshold technique and bee colony algorithm in order to optimize the energy consumption of a WSN. Simulation results show that the energy consumption of the wireless sensor network reduces by 25 percent using STBCP in comparison with recent LEACHbased protocols. It has been shown that the average energy of the network remains balanced and the distribution of residual energy in each round is equitable. Conclusion: In addition, the lifetime of a network using STBCP protocol has been increased by 23 percent regarding recently presented routing protocols.

Enhancement of network coding in wireless sensor network using improved lion algorithm: intention toward maximizing network throughput and lifetime

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Prashant R. Dike ◽  
T.S. Vishwanath ◽  
Vandana Rohakale
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Objective Function ◽  
Network Coding ◽  
Sensor Network ◽  
Network Throughput ◽  
Wireless Sensor ◽  
Content Type ◽  
Lion Algorithm ◽  
Better Than

PurposeSince communication usually accounts as the foremost problem for power consumption, there are some approaches, such as topology control and network coding (NC), for diminishing the activity of sensors’ transceivers. If such approaches are employed simultaneously, then the overall performance does raise as expected. In a wireless sensor network (WSN), the linear NC has been shown to enhance the performance of network throughput and reduce delay. However, the NC condition of existing NC-aware routings may experience the issue of false-coding effect in some scenarios and usually neglect node energy, which highly affects the energy efficiency performance. The purpose of this paper is to propose a new NC scheduling in a WSN with the intention of maximizing the throughput and minimizing the energy consumption of the network.Design/methodology/approachThe improved meta-heuristic algorithm called the improved mutation-based lion algorithm (IM-LA) is used to solve the problem of NC scheduling in a WSN. The main intention of implementing improved optimization is to maximize the throughput and minimize the energy consumption of the network during the transmission from the source to the destination node. The parameters like topology and time slots are taken for optimizing in order to obtain the concerned objective function. While solving the current optimization problem, it has considered a few constraints like timeshare constraint, data-flow constraint and domain constraint. Thus, the network performance is proved to be enhanced by the proposed model when compared to the conventional model.FindingsWhen 20 nodes are fixed for the convergence analysis, performed in terms of multi-objective function, it is noted that during the 400th iteration, the proposed IM-LA was 10.34, 13.91 and 50% better than gray wolf algorithm (GWO), firefly algorithm (FF) and particle swarm optimization (PSO), respectively, and same as LA. Therefore, it is concluded that the proposed IM-LA performs extremely better than other conventional methods in minimizing the cost function, and hence, the optimal scheduling of nodes in a WSN in terms of the multi-objective function, i.e. minimizing energy consumption and maximizing throughput using NC has been successfully done.Originality/valueThis paper adopts the latest optimization algorithm called IM-LA, which is used to solve the problem of network coding scheduling in a WSN. This is the first work that utilizes IM-LA for optimal network coding in a WSN.

Reliable Data Transmission Scheme Based on Network Coding in Wireless Sensor Network

2014 ◽  
Vol 1046 ◽  
pp. 339-342
Author(s):  
Tao Niu ◽  
Yi Zhuang
Keyword(s):  
Wireless Sensor Network ◽  
Network Coding ◽  
Sensor Network ◽  
Data Transmission ◽  
Base Station ◽  
Reliable Data ◽  
Wireless Sensor ◽  
Transmission Scheme ◽  
Linear Network ◽  
Linear Network Coding

In order to achieve reliable data transmission in clustering structure based data acquisition systems of wireless sensor network, in this paper, we propose a reliable data transmission scheme based on network coding for clustering wireless sensor network. We use random linear network coding to solve reliable multicast data transmission from base station to other nodes, and then combine random linear network coding with multipath routing for transmitting acquired data to the base station, so as to improve the success rate for sending acquired data to the base station. Simulation results show that the proposed algorithm can achieve reliable data transmission with lower energy, and significantly improve the transmission reliability compared to data transmission without using network coding.

scholarly journals Pollination Inspired Clustering Model for Wireless Sensor Network Optimization

2021 ◽  
Vol 3 (3) ◽  
pp. 196-207
Author(s):  
Subarna Shakya
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Fault Tolerance ◽  
Sensor Network ◽  
Network Lifetime ◽  
Data Transmission ◽  
Management Strategy ◽  
Wireless Sensor ◽  
Clustering Model ◽  
Proposed Model

Remote and dangerous fields that are expensive, complex, and unreachable to reach human insights are examined with ease using the Wireless Sensor Network (WSN) applications. Due to the use of non-renewable sources of energy, challenges with respect to the network lifetime, fault tolerance and energy consumption are faced by the self-managed networks. An efficient fault tolerance technique has been provided in this paper as an effective management strategy. Using the network and communication nodes, revitalization and fault recognition techniques are used for handling diverse levels of faults in this framework. At the network nodes, the fault tolerance capability is increased by the proposed protocol model and management strategy. This enhances the corresponding data transmission in the network. When compared to the conventional techniques, the proposed model increases the network lifetime by five times. It is observed from the validation results that, with a 10% increase in the network lifetime, there is a 2% decrease in the fault tolerance proficiency of the network. The network lifetime and data transmission rate are improved while the network energy consumption is reduced significantly. The MATLAB environment is used for simulation purpose. In terms of energy consumption, network lifetime and fault tolerance, the proposed model offers optimal results.

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