scholarly journals A Distributed Heuristic Algorithm for Delay Constrained Energy Efficient Routing in Wireless Sensor Networks

2017 ◽  
Author(s):  
Thua Trong Huynh ◽  
Hung Cong Tran ◽  
Vu Duc Anh Dinh
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Computational Complexity ◽  
Heuristic Algorithm ◽  
Energy Efficient ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Efficient Routing ◽  
End To End Delay

Besides energy restriction, wireless sensor networks (WSNs) should be able to provide bounded end-to-end delay when they are used to support real-time applications such as early forest fire alarm systems. In this paper, we investigate the problem of finding the least energy consumption route subject to a delay constraint with low computational complexity in such networks. Based on the distance-vector routing approach, which has less computational complexity and message overhead, we propose a distributed heuristic algorithm called Delay Constrained Energy Efficient Routing (DCEER) in order to minimize the total energy consumption while meeting the end-to-end delay requirement. DCEER only requires a moderate amount of information at each sensor node and does not suffer from the excessive running time. We prove that our proposed algorithm always finishes within a finite time and the computation complexity is only O(n), where n is a divisor of the number of sensor nodes. By mathematical proof and simulation, we verify that DCEER is suitable for large-scale WSNs because the number of messages exchanged between sensor nodes are represented by a polynomial function. Furthermore, we evaluate our proposal to compare its performance with related protocols.

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.

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.

Energy Efficient Multi-Hop Wireless Sensor Networks with CMIMO-SM Scheme

2014 ◽  
Vol 666 ◽  
pp. 322-326
Author(s):  
Yu Yang Peng ◽  
Jae Ho Choi
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Optimal Number ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Improve Energy Efficiency ◽  
Output System

Energy efficiency is one of the important hot issues in wireless sensor networks. In this paper, a multi-hop scheme based on a cooperative multi-input multi-outputspatial modulation technique is proposed in order to improve energy efficiency in WSN. In this scheme, the sensor nodes are grouped into clusters in order to achieve a multi-input multi-output system; and a simple forwarding transmission scenario is considered so that the intermediate clusters only forward packets originated from the source cluster down to the sink cluster. In order to verify the performance of the proposed system, the bit energy consumption formula is derived and the optimal number of hopsis determined. By qualitative experiments, the obtained results show that the proposed scheme can deliver the data over multiple hops consuming optimal energy consumption per bit.

scholarly journals Hierarchical Energy Efficient Routing in Wireless Sensor Networks and its Challenges

2019 ◽  
Vol 9 (1) ◽  
pp. 4024-4027
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Routing Protocols ◽  
Energy Efficient ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Efficient Routing ◽  
Route Of Transmission

Wireless sensor network consists of various sensor nodes connected through wireless media. Sensor nodes are tiny devices having lesser energy capabilities. Sensor nodes are either ad-hoc or mobile in their environment. Wireless sensor network route of transmission media is discovered by routing protocols and responsible for secure communication between sensor nodes. Energy is a precious resource of sensor nodes, and the entire lifetime of WSNs is depending on the energy capability of the sensor nodes. The fundamental problem is how to organize topology of WSN for deployed sensor nodes with lesser power consumption as possible. Major problems in wireless sensor networks which consume extra energy are interference, control message overhead, packet delay, unnecessary transmission, and bandwidth utilization. Therefore, energy efficient techniques are needed to overcome these problems. Hierarchical routing is the best routing method for finding optimal path between sensor nodes which enhance the lifetime of the network. This paper focuses towards various hierarchical energy efficient routing in wireless sensor networks and analyzes various features of WSN that should consider during designing of routing protocols.

scholarly journals Energy-Efficient Clustering Routing Protocol for Wireless Sensor Networks Based on Yellow Saddle Goatfish Algorithm

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1515 ◽  
Author(s):  
Alma Rodríguez ◽  
Carolina Del-Valle-Soto ◽  
Ramiro Velázquez
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Energy Efficient ◽  
Cluster Structure ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cluster Heads ◽  
Energy Efficient Clustering

The usage of wireless sensor devices in many applications, such as in the Internet of Things and monitoring in dangerous geographical spaces, has increased in recent years. However, sensor nodes have limited power, and battery replacement is not viable in most cases. Thus, energy savings in Wireless Sensor Networks (WSNs) is the primary concern in the design of efficient communication protocols. Therefore, a novel energy-efficient clustering routing protocol for WSNs based on Yellow Saddle Goatfish Algorithm (YSGA) is proposed. The protocol is intended to intensify the network lifetime by reducing energy consumption. The network considers a base station and a set of cluster heads in its cluster structure. The number of cluster heads and the selection of optimal cluster heads is determined by the YSGA algorithm, while sensor nodes are assigned to its nearest cluster head. The cluster structure of the network is reconfigured by YSGA to ensure an optimal distribution of cluster heads and reduce the transmission distance. Experiments show competitive results and demonstrate that the proposed routing protocol minimizes the energy consumption, improves the lifetime, and prolongs the stability period of the network in comparison with the stated of the art clustering routing protocols.

scholarly journals Energy-efficient genetic algorithm variants of PEGASIS for 3D Wireless Sensor Networks

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Aaqil Somauroo ◽  
Vandana Bassoo
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Residual Energy ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Efficient Routing ◽  
Delay Performance

Due to its boundless potential applications, Wireless Sensor Networks have been subject to much research in the last two decades. WSNs are often deployed in remote environments making replacement of batteries not feasible. Low energy consumption being of prime requisite led to the development of energy-efficient routing protocols. The proposed routing algorithms seek to prolong the lifetime of sensor nodes in the relatively unexplored area of 3D WSNs. The schemes use chain-based routing technique PEGASIS as basis and employ genetic algorithm to build the chain instead of the greedy algorithm. Proposed schemes will incorporate an energy and distance aware CH selection technique to improve load balancing. Clustering of the network is also implemented to reduce number of nodes in a chain and hence reduce delay. Simulation of our proposed protocols is carried out for homogeneous networks considering separately cases for a static base-station inside and outside the network. Results indicate considerable improvement in lifetime over PEGASIS of 817% and 420% for base station inside and outside the network respectively. Residual energy and delay performance are also considered.

Secured Energy-Efficient Routing in Wireless Sensor Networks Using Machine Learning Algorithm

2020 ◽  
pp. 23-41
Author(s):  
Ahona Ghosh ◽  
Chiung Ching Ho ◽  
Robert Bestak
Keyword(s):  
Machine Learning ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Learning Algorithm ◽  
Low Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Efficient Routing

Wireless sensor networks consist of unattended small sensor nodes having low energy and low range of communication. It has been observed that if there is any system to periodically start and stop the sensors sensing activities, then it saves some energy, and thus, the network lifetime gets extended. According to the current literature, security and energy efficiency are the two main concerns to improve the quality of service during transmission of data in wireless sensor networks. Machine learning has proved its efficiency in developing efficient processes to handle complex problems in various network aspects. Routing in wireless sensor network is the process of finding the route for transmitting data among different sensor nodes according to the requirement. Machine learning has been used in a broad way for designing energy efficient routing protocols, and this chapter reviews the existing works in the said domain, which can be the guide to someone who wants to explore the area further.

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