scholarly journals Data collection protocols for wireless sensor networks

2021 ◽  
Vol 12 (4) ◽  
pp. 207-214
Author(s):  
Mohamed Labib Borham ◽  
Ghada Khoriba
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Collection ◽  
Wireless Sensor ◽  
Data Delivery ◽  
Energy Aware ◽  
Data Collection Strategy ◽  
Time Required ◽  
Time Systems

Data collection in wireless sensor networks (WSNs) has a significant impact on the network’s performance and lifetime. Recently, several data collection techniques that use mobile elements (MEs) have been recommended, especially techniques that focus on maximising data delivery. However, energy consumption and the time required for data collection are significant for many WSN applications, particularly real-time systems. In this paper, a review of data collection techniques is presented, providing a comparison between the maximum amount shortest path (MASP) and zone-based energy-aware (ZEAL) data collection protocols implemented in the NS-3 simulator. Finally, the study provides a suitable data collection strategy that satisfies the requirements of WSN applications in terms of data delivery, energy consumption, and the time required for data collection.

scholarly journals Energy Consumption Based Low Energy Aware Gateway (LEAG) Protocol in Wireless Sensor Networks

2019 ◽  
Vol 8 (5S3) ◽  
pp. 128-132 ◽  
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Cluster Head ◽  
Base Station ◽  
Low Energy ◽  
Secure Routing ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Aware

Wireless Sensor Networks (WSN) consists of a large amount of nodes connected in a self-directed manner. The most important problems in WSN are Energy, Routing, Security, etc., price of the sensor nodes and renovation of these networks is reasonable. The sensor node tools included a radio transceiver with an antenna and an energy source, usually a battery. WSN compute the environmental conditions such as temperature, sound, pollution levels, etc., WSN built the network with the help of nodes. A sensor community consists of many detection stations known as sensor nodes, every of which is small, light-weight and portable. Nodes are linked separately. Each node is linked into the sensors. In recent years WSN has grow to be an essential function in real world. The data’s are sent from end to end multiple nodes and gateways, the data’s are connected to other networks such as wireless Ethernet. MGEAR is the existing mechanism. It works with the routing and energy consumption. The principal problem of this work is choosing cluster head, and the selection is based on base station, so the manner is consumes energy. In this paper, develop the novel based hybrid protocol Low Energy Aware Gateway (LEAG). We used Zigbee techniques to reduce energy consumption and routing. Gateway is used to minimize the energy consumption and data is send to the base station. Nodes are used to transmit the data into the cluster head, it transmit the data into gateway and gateway compress and aggregate the data then sent to the base station. Simulation result shows our proposed mechanism consumes less energy, increased throughput, packet delivery ration and secure routing when compared to existing mechanism (MGEAR).

scholarly journals An Enhanced Heterogeneous Gateway-Based Energy-Aware Multi-hop Routing Protocol for Wireless Sensor Networks

2022 ◽  
Author(s):  
Fuseini Jibreel ◽  
Emmanuel Tuyishimire ◽  
I M Daabo
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Data Transmission ◽  
Base Station ◽  
Communication Strategy ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Routing Scheme

Wireless Sensor Networks (WSNs) continue to provide essential services for various applications such as surveillance, data gathering, and data transmission from the hazardous environments to safer destinations. This has been enhanced by the energy-efficient routing protocols that are mostly designed for such purposes. Gateway-based Energy-Aware Multi-hop Routing protocol (MGEAR) is one of the homogenous routing schemes that was recently designed to more efficiently reduce the energy consumption of distant nodes. However, it has been found that the protocol has a high energy consumption rate, lower stability period, less data transmission to the Base station (BS). In this paper, an enhanced Heterogeneous Gateway-based Energy-Aware multi-hop routing protocol ( HMGEAR) is proposed. The proposed routing scheme is based on the introduction of heterogeneous nodes in the existing scheme, selection of the head based on the residual energy, introduction of multi-hop communication strategy in all the regions of the network, and implementation of energy hole elimination technique. Results show that the proposed routing scheme outperforms two existing ones.

scholarly journals Enhancement of Data Collection Performance in Wireless Sensor Networks Based on Path-Constrained Mobile Sink

2021 ◽  
Vol 14 (1) ◽  
pp. 400-409
Author(s):  
Mohamed Borham ◽  
◽  
Ghada Khoriba ◽  
Mostafa-Sami Mostafa ◽  
◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Collection ◽  
Routing Protocol ◽  
Maximum Amount ◽  
Wireless Sensor ◽  
Collection Process ◽  
Data Collection Process ◽  
Energy Limitation

Due to the energy limitation in Wireless Sensor Networks (WSNs), most researches related to data collection in WSNs focus on how to collect the maximum amount of data from the network with minimizing the energy consumption as much as possible. Many types of research that are related to data collection are proposed to overcome this issue by using mobility with path constrained as Maximum Amount Shortest Path routing Protocol (MASP) and zone-based algorithms. Recently, Zone-based Energy-Aware Data Collection Protocol (ZEAL) and Enhanced ZEAL have been presented to reduce energy consumption and provide an acceptable data delivery rate. However, the time spent on data collection operations should be taken into account, especially concerning real-time systems, as time is the most critical factor for these systems' performance. In this paper, a routing protocol is proposed to improve the time needed for the data collection process considering less energy consumption. The presented protocol uses a novel path with a communication time-slot assignment algorithm to reduce the count of cycles that are needed for the data collection process with reduction of 50% of the number of cycles needed for other protocols. Therefore, the time and energy needed for data collection are reduced by approximately 25%and 6% respectively, which prolongs the network lifetime. The proposed protocol is called Energy-Time Aware Data Collection Protocol (ETCL).

scholarly journals A Greedy Scanning Data Collection Strategy for Large-Scale Wireless Sensor Networks with a Mobile Sink

Sensors ◽  
2016 ◽  
Vol 16 (9) ◽  
pp. 1432 ◽  
Author(s):  
Chuan Zhu ◽  
Sai Zhang ◽  
Guangjie Han ◽  
Jinfang Jiang ◽  
Joel Rodrigues
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Collection ◽  
Large Scale ◽  
Mobile Sink ◽  
Wireless Sensor ◽  
Data Collection Strategy

An Energy Aware Routing Based on Swarm Intelligence for Wireless Sensor Networks

2013 ◽  
Vol 706-708 ◽  
pp. 635-638
Author(s):  
Yong Lv
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Swarm Intelligence ◽  
Network Lifetime ◽  
Average Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Energy Efficient Routing

Wireless Sensor Networks consisting of nodes with limited power are deployed to collect and distribute useful information from the field to the other sensor nodes. Energy consumption is a key issue in the sensor’s communications since many use battery power, which is limited. In this paper, we describe a novel energy efficient routing approach which combines swarm intelligence, especially the ant colony based meta-heuristic, with a novel variation of reinforcement learning for sensor networks (ARNet). The main goal of our study was to maintain network lifetime at a maximum, while discovering the shortest paths from the source nodes to the sink node using an improved swarm intelligence. ARNet balances the energy consumption of nodes in the network and extends the network lifetime. Simulation results show that compared with the traditional EEABR algorithm can obviously improve adaptability and reduce the average energy consumption effectively.

Two-Level Data Collection for an Energy-Efficient Solution in Wireless Sensor Networks

2016 ◽  
Vol 7 (4) ◽  
pp. 50-67 ◽  
Author(s):  
Besma Benaziz ◽  
Okba Kazar ◽  
Laid Kahloul ◽  
Ilham Kitouni ◽  
Samir Bourekkache
Keyword(s):  
Energy Consumption ◽  
Sensor Networks ◽  
Data Collection ◽  
Timed Automata ◽  
High Energy ◽  
Wireless Sensor ◽  
Data Collection Strategy ◽  
Level Data ◽  
Consumption Data ◽  
The Cost

Density in sensor networks often causes data redundancy, which is often the origin of high energy consumption. Data collection techniques are proposed to avoid retransmission of the same data by several sensors. In this paper, the authors propose a new data collection strategy based on static agents and clustering nodes in wireless sensor network (WSN) for an efficient energy consumption called: Two-Level Data Collection Strategy (TLDC). It consists in two-level hierarchy of nodes grouping. The technique is based on an experience building to perform a reorganization of the groups. Cooperation between agents can be used to reduce the communication cost significantly, by managing the data collection smartly. In order to validate the proposed scheme, the authors use the timed automata (TA) model and UPPAAL engine to validate the proposed strategy; the results after and before reorganization are compared. They establish that the proposed approach reduces the cost of communication in the group and thus minimizes the consumed energy.

scholarly journals Designing Constrained Trajectory Based on Maximizing Energy Reduction in Large-Scale Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Jia Xu ◽  
Chuan Ping Wang ◽  
Hua Dai ◽  
Da Qiang Zhang ◽  
Jing Jie Yu
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Collection ◽  
Large Scale ◽  
Mobile Sink ◽  
Energy Reduction ◽  
Wireless Sensor ◽  
Movement Trajectory ◽  
Computation Efficiency

TheMobile Sinkbased data collection in wireless sensor network can reduce energy consumption efficiently and has been a new data collection paradigm. In this paper, we focus on exploring polynomial algorithm to compute the constrained trajectory of theMobile Sinkfor data collection. We first present a universal system model for designing constrained trajectory in large-scale wireless sensor networks and formulate the problem as theMaximizing Energy Reduction for Constrained Trajectory(MERC) problem. We show that the MERC problem is NP-hard and design an approximation algorithm (CTMER), which follows the greedy approach to design the movement trajectory of theMobile Sinkby maximizing theeffective average energy reduction. Through both rigid theoretical analysis and extensive simulations, we demonstrate that our algorithm achieves high computation efficiency and is superior to otherMobile Sinkbased data collection methods in aspects of energy consumption and network lifetime.

scholarly journals EGCIR: Energy-Aware Graph Clustering and Intelligent Routing Using Supervised System in Wireless Sensor Networks

Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4072
Author(s):  
Tanzila Saba ◽  
Khalid Haseeb ◽  
Ikram Ud Din ◽  
Ahmad Almogren ◽  
Ayman Altameem ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Graph Clustering ◽  
Base Station ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Intelligent Routing

In recent times, the field of wireless sensor networks (WSNs) has attained a growing popularity in observing the environment due to its dynamic factors. Sensor data are gathered and forwarded to the base station (BS) through a wireless transmission medium. The data from the BS is further distributed to end-users using the Internet for their post analysis and operations. However, all sensors except the BS have limited constraints in terms of memory, energy and computational resources that degrade the network performance concerning the network lifetime and trustworthy routing. Therefore, improving energy efficiency with reliable and secure transmissions is a valuable debate among researchers for critical applications based on low-powered sensor nodes. In addition, security plays a significant cause to achieve responsible communications among sensors due to their unfixed and variable infrastructures. Keeping in view the above-mentioned issues, this paper presents an energy-aware graph clustering and intelligent routing (EGCIR) using a supervised system for WSNs to balance the energy consumption and load distribution. Moreover, a secure and efficient key distribution in a hierarchy-based mechanism is adopted by the proposed solution to improve the network efficacy in terms of routes and links integrity. The experimental results demonstrated that the EGCIR protocol enhances the network throughput by an average of 14%, packet drop ratio by an average of 50%, energy consumption by an average of 13%, data latency by an average of 30.2% and data breaches by an average of 37.5% than other state-of-the-art protocols.

Two-Level Data Collection for an Energy-Efficient Solution in Wireless Sensor Networks

2020 ◽  
pp. 194-213
Author(s):  
Besma Benaziz ◽  
Okba Kazar ◽  
Laid Kahloul ◽  
Ilham Kitouni ◽  
Samir Bourekkache
Keyword(s):  
Energy Consumption ◽  
Sensor Networks ◽  
Data Collection ◽  
Timed Automata ◽  
High Energy ◽  
Wireless Sensor ◽  
Data Collection Strategy ◽  
Level Data ◽  
Consumption Data ◽  
The Cost

Density in sensor networks often causes data redundancy, which is often the origin of high energy consumption. Data collection techniques are proposed to avoid retransmission of the same data by several sensors. In this paper, the authors propose a new data collection strategy based on static agents and clustering nodes in wireless sensor network (WSN) for an efficient energy consumption called: Two-Level Data Collection Strategy (TLDC). It consists in two-level hierarchy of nodes grouping. The technique is based on an experience building to perform a reorganization of the groups. Cooperation between agents can be used to reduce the communication cost significantly, by managing the data collection smartly. In order to validate the proposed scheme, the authors use the timed automata (TA) model and UPPAAL engine to validate the proposed strategy; the results after and before reorganization are compared. They establish that the proposed approach reduces the cost of communication in the group and thus minimizes the consumed energy.

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