Construction of Efficient Wireless Sensor Networks for Energy Minimization using a Modified ACO Algorithm.

Author(s):  
Monojit Dey ◽  
Arnab Das ◽  
Avishek Banerjee ◽  
Ujjwal Kumar Kamila ◽  
Samiran Chattopadhyay

In this paper, we have proposed different deployment strategies and have applied area-wise clustering along with modified Ant Colony Optimization to minimize energy consumption. Background: Previously some deployment strategies were used to enhance the lifetime of WSN. In our research, we have applied some novel deployment strategies like random, spiral, and S-pattern along with a novel area-wise clustering process to get better results than the existing literature as shown in Table 4. Objective: The main objective of the research article is to enhance the lifetime of Wireless Sensor Network with the help of different deployment strategies like random, spiral, and S-pattern). A novel clustering process (i.e., area-wise clustering), and a Meta-heuristic algorithm (modified ACO) are applied. Method: We have applied different methods for deployment strategies (random, spiral, and S-pattern). A novel clustering process (i.e., area-wise clustering), and a Meta-heuristic algorithm (modified ACO) are applied to get the desired results. Results: Random Deployment: 11.15 days to 15.09 days. Spiral Deployment: 11.25 days to 15.23 days. S-Pattern Deployment: 11.33 days to 15.33 days. Conclusion: In this paper, efficient Wireless Sensor Networks have been configured considering energy minimization as the prime concern. To minimize the energy consumption a modified ACO algorithm has been proposed. In our work, the minimization of energy consumption leads to an increment of the lifetime of WSN to a significant margin theoretically. The obtained result has been compared with the existing literature and it has been found that the proposed algorithm produced a better result than the existing literature.

2019 ◽  
Vol 29 (09) ◽  
pp. 2050141 ◽  
Author(s):  
Muhammed Enes Bayrakdar

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.


2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xueli Wang

As one of the three pillars of information technology, wireless sensor networks (WSNs) have been widely used in environmental detection, healthcare, military surveillance, industrial data sampling, and many other fields due to their unparalleled advantages in deployment cost, network power consumption, and versatility. The advent of the 5G standard and the era of Industry 4.0 have brought new opportunities for the development of wireless sensor networks. However, due to the limited power capacity of the sensor nodes themselves, the harsh deployment environment will bring a great difficulty to the energy replenishment of the sensor nodes, so the energy limitation problem has become a major factor limiting its further development; how to improve the energy utilization efficiency of WSNs has become an urgent problem in the scientific and industrial communities. Based on this, this paper researches the routing technology of wireless sensor networks, from the perspective of improving network security, and reducing network energy consumption, based on the study of ant colony optimization algorithm, further studies the node trust evaluation mechanism, and carries out the following research work: (1) study the energy consumption model of wireless sensor networks; (2) basic ant colony algorithm improvement; (3) multiobjective ant colony algorithm based on wireless sensor routing algorithm optimization. In this study, the NS2 network simulator is used as a simulation tool to verify the performance of the research algorithm. Compared with existing routing algorithms, the simulation results show that the multiobjective ant colony optimization algorithm has better performance in evaluation indexes such as life cycle, node energy consumption, node survival time, and stability compared with the traditional algorithm and the dual cluster head ant colony optimization algorithm.


2020 ◽  
Vol 16 (8) ◽  
pp. 155014772093902
Author(s):  
Hang Wan ◽  
Michael David ◽  
William Derigent

Wireless Sensor Networks are very convenient to monitor structures or even materials, as in McBIM project (Materials communicating with the Building Information Modeling). This project aims to develop the concept of “communicating concretes,” which are concrete elements embedding wireless sensor networks, for applications dedicated to Structure Health Monitoring in the construction industry. Due to applicative constraints, the topology of the wireless sensor network follows a chain-based structure. Node batteries cannot be replaced or easily recharged, it is crucial to evaluate the energy consumed by each node during the monitoring process. This area has been extensively studied leading to different energy models to evaluate energy consumption for chain-based structures. However, no simple, practical, and analytical network energy models have yet been proposed. Energy evaluation models of periodic data collection for chain-based structures are proposed. These models are compared and evaluated with an Arduino XBee–based platform. Experimental results show the mean prediction error of our models is 5%. Realizing aggregation at nodes significantly reduces energy consumption and avoids hot-spot problem with homogeneous consumptions along the chain. Models give an approximate lifetime of the wireless sensor network and communicating concretes services. They can also be used online by nodes for a self-assessment of their energy consumptions.


Author(s):  
Mohammad Sedighimanesh ◽  
Hesam Zandhesami ◽  
Ali Sedighimanesh

Background: Wireless sensor networks are considered as one of the 21st century's most important technologies. Sensors in wireless sensor networks usually have limited and sometimes non-rechargeable batteries, which they are supposed to be preserved for months or even years. That's why the energy consumption in these networks is of a great importance. Objective: One way to improve energy consumption in a wireless sensor network is to use clustering. In clustered networks, one node is known as the cluster head and other nodes as normal members, which normal nodes send the collected data to the cluster head, and the cluster head sends the information to the base station either by a single step or by multiple steps. Method: Using clustering simplifies resource management and increases scalability, reliability, and the network lifetime. Although the cluster formation involves a time- overhead and how to choose the cluster head is another problem, but its advantages are more than its disadvantages. : The primary aim of this study is to offer a solution to reduce energy consumption in the sensor network. In this study, during the selection of cluster heads, Honeybee Algorithm is used and also for routing, Harmonic Search Algorithm is used. In this paper, the simulation is performed by using MATLAB software and the proposed method is compared with the Low Energy Adaptive Clustering Hierarchy (LEACH) and the multi-objective fuzzy clustering algorithm (MOFCA). Result and Conclusion: By simulations of this study, we conclude that this research has remarkably increased the network lifetime with respect to EECS, LEACH, and MOFCA algorithms. In view of the energy constraints of the wireless sensor network and the non-rechargeable batteries in most cases, providing such solutions and using metaheuristic algorithms can result in a significant reduction in energy consumption and, consequently, increase in the network lifetime.


Author(s):  
Ghazaleh Kia ◽  
Alireza Hassanzadeh

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.


Author(s):  
Padmapriya N. ◽  
N. Kumaratharan ◽  
Aswini R.

A wireless sensor network (WSN) is a gathering of sensor hubs that powerfully self-sort themselves into a wireless system without the use of any previous framework. One of the serious issues in WSNs is the energy consumption, whereby the system lifetime is subject to this factor. Energy-efficient routing is viewed as the most testing errand. Sensor organizes for the most part work in perplexing and dynamic situations and directing winds up repetitive assignment to keep up as the system measure increments. This chapter portrays the structure of wireless sensor network the analysis and study of different research works identified with energy-efficient routing in wireless sensor networks. Along these lines, to beat all the routing issues, the pattern has moved to biological-based algorithms like swarm intelligence-based strategies. Ant colony optimization-based routing protocols have shown outstanding outcomes as far as execution when connected to WSN routing.


2020 ◽  
Vol 17 (5) ◽  
pp. 2415-2420
Author(s):  
Shibin David ◽  
J. Andrew ◽  
Basil Xavier ◽  
Isaac Joel Raj ◽  
R. Jennifer Eunice

Wireless sensor network comprises of scattered sensors to sense, monitor and aggregate the sensed information. The major issue in a wireless sensor network is to balance network load and to maintain less energy consumption where multi parent crossover method is considered. Multiparent cross over method will generate offspring from parent and aims at managing the load. In this paper a comparative study of different algorithms is done where the load balancing and energy consumption issue has been resolved.


2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Chaoqun Li ◽  
Jing Xiao ◽  
Yang Liu ◽  
Guohong Qi ◽  
Hu Qin ◽  
...  

Industrial wireless sensor networks (IWSNs) are usually fixedly deployed in industrial environments, and various sensor nodes cooperate with each other to complete industrial production tasks. The efficient work of each sensor node of IWSNs will improve the efficiency of the entire network. Automated robots need to perform timely inspection and maintenance of IWSNs in an industrial environment. Excessive inspection distance will increase inspection costs and increase energy consumption. Therefore, shortening the inspection distance can reduce production energy consumption, which is very important for the efficient operation of the entire system. However, the optimal detection path planning of IWSNs is an N-P problem, which can usually only be solved by heuristic mathematical methods. This paper proposes a new adaptive immune ant colony optimization (AIACO) for optimizing automated inspection path planning. Moreover, novel adaptive operator and immune operator are designed to prevent the algorithm from falling into the local optimum and increase the optimization ability. In order to verify the performance of the algorithm, the algorithm is compared with genetic algorithm (GA) and immune clone algorithm (ICA). The simulation results show that the inspection distance of IWSNs using AIACO is lower than that of GA and ICA. In addition, the convergence speed of AIACO is faster than that of GA and ICA. Therefore, the AIACO proposed in this paper can effectively reduce the inspection energy consumption of the entire IWSN system.


2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Abbas Varmaghani ◽  
Ali Matin Nazar ◽  
Mohsen Ahmadi ◽  
Abbas Sharifi ◽  
Saeid Jafarzadeh Ghoushchi ◽  
...  

Advances in wireless technologies and small computing devices, wireless sensor networks can be superior technology in many applications. Energy supply constraints are one of the most critical measures because they limit the operation of the sensor network; therefore, the optimal use of node energy has always been one of the biggest challenges in wireless sensor networks. Moreover, due to the limited lifespan of nodes in WSN and energy management, increasing network life is one of the most critical challenges in WSN. In this investigation, two computational distributions are presented for a dynamic wireless sensor network; in this fog-based system, computing load was distributed using the optimistic and blind method between fog networks. The presented method with the main four steps is called Distribution-Map-Transfer-Combination (DMTC) method. Also, Fuzzy Multiple Attribute Decision-Making (Fuzzy MADM) is used for clustering and routing network based on the presented distribution methods. Results show that the optimistic method outperformed the blind one and reduced energy consumption, especially in extensive networks; however, in small WSNs, the blind scheme resulted in an energy efficiency network. Furthermore, network growth leads optimistic WSN to save higher energy in comparison with blinded ones. Based on the results of complexity analysis, the presented optimal and blind methods are improved by 28% and 48%, respectively.


2020 ◽  
Vol 12 (1) ◽  
pp. 205-224
Author(s):  
Anshu Kumar Dwivedi DUBEY

Purpose ”“ In the recent scenario, there are various issues related to wireless sensor networks such as clustering, routing, packet loss, network strength. The core functionality of primarily wireless sensor networks is sensor nodes that are randomly scattered over a specific area. The sensor senses the data and sends it to the base station. Energy consumption is an important issue in wireless sensor networks. Clustering and cluster head selection is an important method used to extend the lifetime of wireless sensor networks. The main goal of this research article is to reduce energy consumption using a clustering process such as CH determination, cluster formation, and data dissemination.   Methodology/approach/design ”“ The simulation in this paper was finished utilizing MATLAB programming methodology and the proposed technique is contrasted with the LEACH and MOD-LEACH protocols.   Findings ”“ The simulation results of this research show that the energy consumption and dead node ratio are improved of wireless sensor networks as compared to the LEACH and MOD-LEACH algorithms.   Originality/value ”“ In the wireless sensor network there are various constraints energy is one of them. In order to solve this problem use CH selection algorithms to reduce energy consumption and consequently increase network lifetime.


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