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 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 An Internet of Things Wireless Sensor Network Data Exchange Model Based on Hierarchical Address Automatic Configuration and Header Compression Encoding Strategy

2017 ◽  
Vol 13 (07) ◽  
pp. 140 ◽  
Author(s):  
Yuankun Yang ◽  
Yongqing Ji
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Internet Of Things ◽  
Real Time ◽  
Sensor Network ◽  
Data Exchange ◽  
Wireless Sensor ◽  
The Internet ◽  
Network Data ◽  
Sink Node

<p><span style="font-size: medium;"><span style="font-family: 宋体;">To explore the wireless sensor network data exchange model, an addressing strategy is applied to the Internet of Things, and the real-time communication between the underlying wireless sensor network and the Internet based on the IEEE 802.15.4 protocol is realized. In addition, Hierarchical address auto configuration strategy is adopted. First of all, inside the bottom network, it allows nodes to use link local address derived by 16-bit short address for data packet transmission. Secondly, Sink node in each underlying network accesses to the global routing prefix through the upper IP router, and combined with interface identifier, it forms Sink node global address, and realizes wireless sensor network and Internet data exchange. The research results show that the strategy has certain superiority in network cost, throughput, energy consumption and other performances. In summary, the proposed addressing strategy has the characteristics of effectively integrating heterogeneous networks, reducing system energy consumption, increasing network throughput and ensuring real-time system performance for the future Internet of things.</span></span></p>

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.

scholarly journals Lifetime Optimization of a Multiple Sink Wireless Sensor Network through Energy Balancing

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Tapan Kumar Jain ◽  
Davinder Singh Saini ◽  
Sunil Vidya Bhooshan
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Lifetime ◽  
Maximum Energy ◽  
The Other ◽  
Wireless Sensor ◽  
Energy Balancing ◽  
Multiple Sink ◽  
Lifetime Optimization

The wireless sensor network consists of small limited energy sensors which are connected to one or more sinks. The maximum energy consumption takes place in communicating the data from the nodes to the sink. Multiple sink WSN has an edge over the single sink WSN where very less energy is utilized in sending the data to the sink, as the number of hops is reduced. If the energy consumed by a node is balanced between the other nodes, the lifetime of the network is considerably increased. The network lifetime optimization is achieved by restructuring the network by modifying the neighbor nodes of a sink. Only those nodes are connected to a sink which makes the total energy of the sink less than the threshold. This energy balancing through network restructuring optimizes the network lifetime. This paper depicts this fact through simulations done in MATLAB.

scholarly journals Implementation of FMAC in Healthcare System of Wireless Sensor Network

2020 ◽  
pp. 81-85
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Healthcare System ◽  
Mac Protocol ◽  
Mac Protocols ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sink Node ◽  
Control Packet

Wireless sensor network is the network of sensor nodes. The nodes transmit data to the sink node. Each sensor nodes have its own battery and ability to communicate with sink node. Network of such nodes is called sensor network. The successful operation of WSN largely depends on MAC sublayer which deals with addressing and channel access control. WSN has varied design constraints such as energy consumption, scalability, delay, traffic control, packet delivery throughput and overheads that need an effective MAC protocol to deal with these problems. Energy must be utilized efficiently in order to increase the lifetime of the Wireless Sensor Network. MAC protocols reduce the cost of energy consumption by providing an efficient communication for transmission and hence improves network lifetime. This paper shows the implementation of FMAC Protocol in healthcare system for different reporting rates. The purpose of the study is to identify the best MAC protocol in Healthcare System. Results for implementation of Hybrid MAC for hospital network are presented in the paper. Results for Data transmission between nodes and sink node has been evaluated to identify Good MAC protocol. Paper represents how low energy consumption can be achieved by combining TDMA and CSMA MAC protocols.

scholarly journals Refining Network Lifetime of Wireless Sensor Network Using Energy-Efficient Clustering and DRL-Based Sleep Scheduling

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1540 ◽  
Author(s):  
Ramadhani Sinde ◽  
Feroza Begum ◽  
Karoli Njau ◽  
Shubi Kaijage
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Wireless Sensor ◽  
Second Phase ◽  
Network Delay ◽  
Duty Cycling ◽  
Hybrid Particle Swarm Optimization

Over the recent era, Wireless Sensor Network (WSN) has attracted much attention among industrialists and researchers owing to its contribution to numerous applications including military, environmental monitoring and so on. However, reducing the network delay and improving the network lifetime are always big issues in the domain of WSN. To resolve these downsides, we propose an Energy-Efficient Scheduling using the Deep Reinforcement Learning (DRL) (E2S-DRL) algorithm in WSN. E2S-DRL contributes three phases to prolong network lifetime and to reduce network delay that is: the clustering phase, duty-cycling phase and routing phase. E2S-DRL starts with the clustering phase where we reduce the energy consumption incurred during data aggregation. It is achieved through the Zone-based Clustering (ZbC) scheme. In the ZbC scheme, hybrid Particle Swarm Optimization (PSO) and Affinity Propagation (AP) algorithms are utilized. Duty cycling is adopted in the second phase by executing the DRL algorithm, from which, E2S-DRL reduces the energy consumption of individual sensor nodes effectually. The transmission delay is mitigated in the third (routing) phase using Ant Colony Optimization (ACO) and the Firefly Algorithm (FFA). Our work is modeled in Network Simulator 3.26 (NS3). The results are valuable in provisions of upcoming metrics including network lifetime, energy consumption, throughput and delay. From this evaluation, it is proved that our E2S-DRL reduces energy consumption, reduces delays by up to 40% and enhances throughput and network lifetime up to 35% compared to the existing cTDMA, DRA, LDC and iABC methods.

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