scholarly journals Energy Efficient Interest Forwarding in NDN-Based Wireless Sensor Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Shuai Gao ◽  
Hongke Zhang ◽  
Beichuan Zhang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Real Data ◽  
Wireless Sensor ◽  
Efficient Design ◽  
Total Energy Consumption ◽  
Broadcast Storm ◽  
Flexible Mode

Recently there has been a new emerging trend in integrating Named Data Networking (NDN) and wireless sensor networks (WSNs) together to implement real data-centric Internet of Things (IoT). However, the main solutions in current literature lack energy efficient design to meet the severely limited energy resources in WSNs. In this paper, we propose a dual mode Interest forwarding scheme (called DMIF in short) for NDN-based WSNs. The DMIF consists of two combined forwarding modes, in which several energy efficient mechanisms including flexible mode shift, flooding scope control, broadcast storm avoidance, packet suppression, and energy weight factors are designed to save and balance the energy consumption. We extend the ndnSIM to support wireless multihop communication to validate the proposed scheme. Simulation experiments show that the DMIF outperforms the baseline schemes in terms of total energy consumption, energy equilibrium rate, and network lifetime.

scholarly journals A Collaborative Data Collection Scheme Based on Optimal Clustering for Wireless Sensor Networks

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2487 ◽  
Author(s):  
Guorui Li ◽  
Haobo Chen ◽  
Sancheng Peng ◽  
Xinguang Li ◽  
Cong Wang ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Collection ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Wireless Sensor ◽  
Hilbert Curve ◽  
Total Energy Consumption ◽  
Cluster Data

In recent years, energy-efficient data collection has evolved into the core problem in the resource-constrained Wireless Sensor Networks (WSNs). Different from existing data collection models in WSNs, we propose a collaborative data collection scheme based on optimal clustering to collect the sensed data in an energy-efficient and load-balanced manner. After dividing the data collection process into the intra-cluster data collection step and the inter-cluster data collection step, we model the optimal clustering problem as a separable convex optimization problem and solve it to obtain the analytical solutions of the optimal clustering size and the optimal data transmission radius. Then, we design a Cluster Heads (CHs)-linking algorithm based on the pseudo Hilbert curve to build a CH chain with the goal of collecting the compressed sensed data among CHs in an accumulative way. Furthermore, we also design a distributed cluster-constructing algorithm to construct the clusters around the virtual CHs in a distributed manner. The experimental results show that the proposed method not only reduces the total energy consumption and prolongs the network lifetime, but also effectively balances the distribution of energy consumption among CHs. By comparing it o the existing compression-based and non-compression-based data collection schemes, the average reductions of energy consumption are 17.9% and 67.9%, respectively. Furthermore, the average network lifetime extends no less than 20-times under the same comparison.

scholarly journals Energy-efficient hierarchical routing in wireless sensor networks based on Fog Computing

2020 ◽  
Author(s):  
Ademola Abidoye ◽  
Boniface Kabaso
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Data Transmission ◽  
Energy Efficient ◽  
Fog Computing ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Hierarchical Routing

Abstract Wireless sensor networks (WSNs) have been recognized as one of the most essential technologies of the 21st century. The applications of WSNs are rapidly increasing in almost every sector because they can be deployed in areas where cable and power supply are difficult to use. In the literature, different methods have been proposed to minimize energy consumption of sensor nodes so as to prolong WSNs utilization. In this article, we propose an efficient routing protocol for data transmission in WSNs; it is called Energy-Efficient Hierarchical routing protocol for wireless sensor networks based on Fog Computing (EEHFC). Fog computing is integrated into the proposed scheme due to its capability to optimize the limited power source of WSNs and its ability to scale up to the requirements of the Internet of Things applications. In addition, we propose an improved ant colony optimization (ACO) algorithm that can be used to construct optimal path for efficient data transmission for sensor nodes. The performance of the proposed scheme is evaluated in comparison with P-SEP, EDCF, and RABACO schemes. The results of the simulations show that the proposed approach can minimize sensor nodes’ energy consumption, data packet losses and extends the network lifetime

Nature-Inspired Algorithms in Wireless Sensor Networks

2019 ◽  
pp. 246-275
Author(s):  
Ajay Kaushik ◽  
S. Indu ◽  
Daya Gupta
Keyword(s):  
Wireless Sensor Networks ◽  
Big Data ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Sensor Node ◽  
Optimization Problem ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Nature Inspired Algorithms

Wireless sensor networks (WSNs) are becoming increasingly popular due to their applications in a wide variety of areas. Sensor nodes in a WSN are battery operated which outlines the need of some novel protocols that allows the limited sensor node battery to be used in an efficient way. The authors propose the use of nature-inspired algorithms to achieve energy efficient and long-lasting WSN. Multiple nature-inspired techniques like BBO, EBBO, and PSO are proposed in this chapter to minimize the energy consumption in a WSN. A large amount of data is generated from WSNs in the form of sensed information which encourage the use of big data tools in WSN domain. WSN and big data are closely connected since the large amount of data emerging from sensors can only be handled using big data tools. The authors describe how the big data can be framed as an optimization problem and the optimization problem can be effectively solved using nature-inspired algorithms.

Energy-Efficient Technique for Monitoring of Agricultural Areas with Terrestrial Wireless Sensor Networks

2019 ◽  
Vol 29 (09) ◽  
pp. 2050141 ◽  
Author(s):  
Muhammed Enes Bayrakdar
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Fading Channels ◽  
Energy Efficient ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Efficient Manner

In this paper, a monitoring technique based on the wireless sensor network is investigated. The sensor nodes used for monitoring are developed in a simulation environment. Accordingly, the structure and workflow of wireless sensor network nodes are designed. Time-division multiple access (TDMA) protocol has been chosen as the medium access technique to ensure that the designed technique operates in an energy-efficient manner and packet collisions are not experienced. Fading channels, i.e., no interference, Ricean and Rayleigh, are taken into consideration. Energy consumption is decreased with the help of ad-hoc communication of sensor nodes. Throughput performance for different wireless fading channels and energy consumption are evaluated. The simulation results show that the sensor network can quickly collect medium information and transmit data to the processing center in real time. Besides, the proposed technique suggests the usefulness of wireless sensor networks in the terrestrial areas.

scholarly journals Energy-Efficient and Fast MAC Protocol in UAV-Aided Wireless Sensor Networks for Time-Critical Applications

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2635 ◽  
Author(s):  
Sabitri Poudel ◽  
Sangman Moh
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Multiple Access ◽  
Mac Protocol ◽  
Mac Protocols ◽  
Wireless Sensor ◽  
Sensing Applications ◽  
Time Critical

Unmanned aerial vehicle (UAV)-aided wireless sensor networks (UWSNs) can be effectively used for time-critical sensing applications. UAVs can be used to collect the sensed data from sensors and transfer them to a base station. The real-time transfer of data is highly desired in the time-critical applications. However, the medium access control (MAC) protocols designed for UWSNs so far are primarily focused on the efficient use of UAVs to collect data in the sensing areas. In this paper, we propose an energy-efficient and fast MAC (EF-MAC) protocol in UWSNs for time-critical sensing applications. EF-MAC adopts carrier sense multiple access (CSMA) for the registration of sensor nodes with a UAV and time division multiple access (TDMA) with variable slot time for the transmission of collected data. The UAV is equipped with two transceivers to minimize both energy consumption and delay in air-to-ground communication. The energy consumption and delay are formally analyzed and the performance of EF-MAC is evaluated via extensive simulation. The simulation results show that the proposed EF-MAC outperforms the conventional MAC protocols in terms of energy efficiency and communication delay.

EDMC: An Energy-Efficient Distributed Multi-Hop Clustering Approach for Wireless Sensor Networks

2012 ◽  
Vol 198-199 ◽  
pp. 1668-1671
Author(s):  
Zhu Guo Li ◽  
Bing Wen Wang ◽  
Li Zhu Feng
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Wireless Sensor ◽  
Clustering Method ◽  
The Past ◽  
Decrease Energy Consumption ◽  
Potential Applications ◽  
Clustering Approach

The past few years have witnessed increasing focus on the potential applications of wireless sensor networks. Sensors in these networks are expected to be remotely dispersed in large number and to operate autonomously and unattended. Clustering is a widely used technique that can enhance scalability and decrease energy consumption over sensor networks. We present an energy-efficient distributed multi-hop clustering approach for sensor networks, which combined multi-hop transmission with clustering method, aiming to balance the energy dissipation and prolong the whole network lifetime. Simulations showed that the protocol proposed worked nearly 100% more efficient compared with LEACH and HEED.

scholarly journals Novel Energy-Efficient Data Gathering Scheme Exploiting Spatial-Temporal Correlation for Wireless Sensor Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Ying Zhou ◽  
Lihua Yang ◽  
Longxiang Yang ◽  
Meng Ni
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Data Gathering ◽  
Temporal Correlation ◽  
Wireless Sensor ◽  
Selection Scheme ◽  
Efficient Data ◽  
Transmission Energy Consumption

A novel energy-efficient data gathering scheme that exploits spatial-temporal correlation is proposed for clustered wireless sensor networks in this paper. In the proposed method, dual prediction is used in the intracluster transmission to reduce the temporal redundancy, and hybrid compressed sensing is employed in the intercluster transmission to reduce the spatial redundancy. Moreover, an error threshold selection scheme is presented for the prediction model by optimizing the relationship between the energy consumption and the recovery accuracy, which makes the proposed method well suitable for different application environments. In addition, the transmission energy consumption is derived to verify the efficiency of the proposed method. Simulation results show that the proposed method has higher energy efficiency compared with the existing schemes, and the sink can recover measurements with reasonable accuracy by using the proposed method.

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