scholarly journals Lecr: Less Energy Consumption Routing in Internet of Things

2020 ◽  
Vol 8 (5) ◽  
pp. 855-859 ◽  
Keyword(s):  
Energy Consumption ◽  
Internet Of Things ◽  
Traffic Management ◽  
Routing Algorithm ◽  
High Energy ◽  
Base Station ◽  
Experimental Result ◽  
Battery Lifetime ◽  
Iot Devices ◽  
Information Collecting

Internet of Things (IoT) constitutes a network of various devices has an equipment with the mandatory facility of communication and optional facilities of sensing, information collecting, storage and processing. IoT network has been used for research and development purpose in many application areas such as military environment, traffic management, and e-healthcare system. IoT network was enormous in scale and complexity, mainly in terms of energy efficiency because battery lifetime is limited. The previous routing protocols for IoT are difficult and require a huge memory use and high energy consumption which are insufficient for IoT network processing. For that reason, an efficient routing algorithm needed to decrease energy consumption while communication. To tackle this problem, this paper proposes Less Energy Consumption Routing (LECR) algorithm. This algorithm reduces energy consumption using 4 ways in IoT, (1) Sleep and Wake up Scheduling, (2) Route Discovery in IoT Base Station (3) Less Power Consumption Route for Communication (4) Reduce Overhead while Routing. The experimental result proves the LECR algorithm reduces IoT devices battery drain and increases lifetime of the IoT network efficiently

scholarly journals Efficient Energy Utilization with Device Placement and Scheduling in the Internet of Things

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Yanli Zhu ◽  
Xiaoping Yang ◽  
Yi Hong ◽  
Youfang Leng ◽  
Chuanwen Luo
Keyword(s):  
Energy Consumption ◽  
Internet Of Things ◽  
Approximation Algorithm ◽  
Minimum Energy ◽  
Base Station ◽  
Area Coverage ◽  
The Internet ◽  
Minimum Energy Consumption ◽  
Iot Devices ◽  
The Internet Of Things

The low-power wide-area network (LPWAN) technologies, such as LoRa, Sigfox, and NB-IoT, bring new renovation to the wireless communication between end devices in the Internet of things (IoT), which can provide larger coverage and support a large number of IoT devices to connect to the Internet with few gateways. Based on these technologies, we can directly deploy IoT devices on the candidate locations to cover targets or the detection area without considering multihop data transmission to the base station like the traditional wireless sensor networks. In this paper, we investigate the problems of the minimum energy consumption of IoT devices for target coverage through placement and scheduling (MTPS) and minimum energy consumption of IoT devices for area coverage through placement and scheduling (MAPS). In the problems, we consider both the placement and scheduling of IoT devices to monitor all targets (or the whole detection area) such that all targets (or the whole area) are (or is) continuously observed for a certain period of time. The objectives of the problems are to minimize the total energy consumption of the IoT devices. We first, respectively, propose the mathematical models for the MTPS and MAPS problems and prove that they are NP-hard. Then, we study two subproblems of the MTPS problem, minimum location coverage (MLC), and minimum energy consumption scheduling deployment (MESD) and propose an approximation algorithm for each of them. Based on these two subproblems, we propose an approximation algorithm for the MTPS problem. After that, we investigate the minimum location area coverage (MLAC) problem and propose an algorithm for it. Based on the MLAC and MESD problems, we propose an approximation algorithm to solve the MAPS problem. Finally, extensive simulation results are given to further verify the performance of the proposed algorithms.

scholarly journals An improved cluster formation process in wireless sensor network to decrease energy consumption

2020 ◽  
Author(s):  
Hamid Reza Farahzadi ◽  
Mostafa Langarizadeh ◽  
Mohammad Mirhosseini ◽  
Seyed Ali Fatemi Aghda
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Information Transfer ◽  
Cluster Head ◽  
High Energy ◽  
Residual Energy ◽  
Base Station ◽  
Wireless Sensor ◽  
Death Time

AbstractWireless sensor network has special features and many applications, which have attracted attention of many scientists. High energy consumption of these networks, as a drawback, can be reduced by a hierarchical routing algorithm. The proposed algorithm is based on the Low Energy Adaptive Clustering Hierarchy (LEACH) and Quadrant Cluster based LEACH (Q-LEACH) protocols. To reduce energy consumption and provide a more appropriate coverage, the network was divided into several regions and clusters were formed within each region. In selecting the cluster head (CH) in each round, the amount of residual energy and the distance from the center of each node were calculated by the base station (including the location and residual energy of each node) for all living nodes in each region. In this regard, the node with the largest value had the highest priority to be selected as the CH in each network region. The base station calculates the CH due to the lack of energy constraints and is also responsible for informing it throughout the network, which reduces the load consumption and tasks of nodes in the network. The information transfer steps in this protocol are similar to the LEACH protocol stages. To better evaluate the results, the proposed method was implemented with LEACH LEACH-SWDN, and Q-LEACH protocols using MATLAB software. The results showed better performance of the proposed method in network lifetime, first node death time, and the last node death time.

scholarly journals Energy Efficient Multipath Routing Algorithm for Wireless Multimedia Sensor Network

Sensors ◽  
2019 ◽  
Vol 19 (17) ◽  
pp. 3642 ◽  
Author(s):  
Genta ◽  
K.Lobiyal ◽  
Abawajy
Keyword(s):  
Energy Consumption ◽  
Performance Analysis ◽  
Routing Protocols ◽  
Traffic Accidents ◽  
Routing Algorithm ◽  
Multipath Routing ◽  
Cluster Head ◽  
Data Communication ◽  
High Energy ◽  
Wireless Multimedia

Wireless multimedia sensor networks (WMSNs) are capable of collecting multimedia events, such as traffic accidents and wildlife tracking, as well as scalar data. As a result, WMSNs are receiving a great deal of attention both from industry and academic communities. However, multimedia applications tend to generate high volume network traffic, which results in very high energy consumption. As energy is a prime resource in WMSN, an efficient routing algorithm that effectively deals with the dynamic topology of WMSN but also prolongs the lifetime of WMSN is required. To this end, we propose a routing algorithm that combines dynamic cluster formation, cluster head selection, and multipath routing formation for data communication to reduce energy consumption as well as routing overheads. The proposed algorithm uses a genetic algorithm (GA)-based meta-heuristic optimization to dynamically select the best path based on the cost function with the minimum distance and the least energy dissipation. We carried out an extensive performance analysis of the proposed algorithm and compared it with three other routing protocols. The results of the performance analysis showed that the proposed algorithm outperformed the three other routing protocols.

Energy Aware Cluster Head Selection for Maximizing Lifetime Improvement in Internet of Things

2017 ◽  
Vol 9 (4) ◽  
pp. 71-91 ◽  
Author(s):  
Praveen Kumar Reddy Maddikunta ◽  
Rajasekhara Babu Madda
Keyword(s):  
Energy Efficiency ◽  
Internet Of Things ◽  
Hybrid Algorithm ◽  
Artificial Bee Colony ◽  
Cluster Head ◽  
High Energy ◽  
Superior Performance ◽  
Cluster Head Selection ◽  
Bee Colony ◽  
Iot Devices

Energy efficiency is a major concern in Internet of Things (IoT) networks as the IoT devices are battery operated devices. One of the traditional approaches to improve the energy efficiency is through clustering. The authors propose a hybrid method of Gravitational Search Algorithm (GSA) and Artificial Bee Colony (ABC) algorithm to accomplish the efficient cluster head selection. The performance of the hybrid algorithm is evaluated using energy, delay, load, distance, and temperature of the IoT devices. Performance of the proposed method is analyzed by comparing with the conventional methods like Artificial Bee Colony (ABC), Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and GSO algorithms. The performance of the hybrid algorithm is evaluated using of number of alive nodes, convergence estimation, normalized energy, load and temperature. The proposed algorithm exhibits high energy efficiency that improves the life time of IoT nodes. Analysis of the authors' implementation reveals the superior performance of the proposed method.

A Location Based Energy Proficient Path Routing for Internet of Things and Its Applications

2020 ◽  
pp. 6-10
Author(s):  
Arulanantham D ◽  
Pradeepkumar G ◽  
Palanisamy C ◽  
Dineshkumar Ponnusamy
Keyword(s):  
Energy Consumption ◽  
Internet Of Things ◽  
Routing Protocols ◽  
Energy Efficient ◽  
Network Architecture ◽  
Base Station ◽  
Consumer Electronics ◽  
The Internet ◽  
Energy Efficient Routing ◽  
The Internet Of Things

The Internet of Things (IoT) is an establishment with sensors, base station, gateway, and network servers. IoT is an efficient and intellectual system that minimizes human exertion as well as right to use to real devices. This method also has an autonomous control property by which any device can control without any human collaboration. IoT-based automation has become very reasonable and it has been applied in several sectors such as manufacturing, transport, health care, consumer electronics, etc. In WSN’s smaller energy consumption sensors are expected to run independently for long phases. So much ongoing researches on implementing routing protocols for IoTbased WSNs.Energy consciousness is an essential part of IoT based WSN design issue. Minimalizing Energy consumption is well-thought-out as one of the key principles in the Expansion of routing protocols for the Internet of things. In this paper, we propose a Location based Energy efficient path routing for Internet of things and its applications its sensor position and clustering based finding the shortest path and real time implementation of Arduino based wireless sensor network architecture with the ESP8266 module. Finally, analyze the principles of Location-based energy-efficient routing and performance of QoS parameters, and then implemented automatic gas leakage detection and managing system.

scholarly journals A Cross Unequal Clustering Routing Algorithm for Sensor Network

2013 ◽  
Vol 13 (4) ◽  
pp. 200-205 ◽  
Author(s):  
Wang Tong ◽  
Wu Jiyi ◽  
Xu He ◽  
Zhu Jinghua ◽  
Charles Munyabugingo
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Energy Loss ◽  
Sensor Network ◽  
Routing Algorithm ◽  
High Energy ◽  
Wireless Sensor ◽  
Unequal Clustering ◽  
Long Distance ◽  
Cluster Heads

In the routing protocol for wireless sensor network, the cluster size is generally fixed in clustering routing algorithm for wireless sensor network, which can easily lead to the “hot spot” problem. Furthermore, the majority of routing algorithms barely consider the problem of long distance communication between adjacent cluster heads that brings high energy consumption. Therefore, this paper proposes a new cross unequal clustering routing algorithm based on the EEUC algorithm. In order to solve the defects of EEUC algorithm, this algorithm calculating of competition radius takes the node’s position and node’s remaining energy into account to make the load of cluster heads more balanced. At the same time, cluster adjacent node is applied to transport data and reduce the energy-loss of cluster heads. Simulation experiments show that, compared with LEACH and EEUC, the proposed algorithm can effectively reduce the energy-loss of cluster heads and balance the energy consumption among all nodes in the network and improve the network lifetime

scholarly journals Evaluating energy efficiency of Internet of Things software architecture based on reusable software components

2017 ◽  
Vol 13 (1) ◽  
pp. 155014771668273 ◽  
Author(s):  
Doohwan Kim ◽  
Jae-Young Choi ◽  
Jang-Eui Hong
Keyword(s):  
Energy Consumption ◽  
Internet Of Things ◽  
Software Architecture ◽  
Personal Information ◽  
High Energy ◽  
The Internet ◽  
Quality Factors ◽  
Reusable Components ◽  
Energy Evaluation ◽  
Internet Of Things Technology

Nowadays, Internet of Things technology has garnered a great amount of interest because it can make our life much easier, convenient, and even safer. Internet of Things devices can be connected to the Internet or to each other whenever and wherever in order to collect, process, and share information to support various services. In order to provide useful support, important issues related to security, performance, and energy consumption have to be considered. For example, important personal information can be easily exposed to others because Internet of Things can be easily hacked; low performance and high energy consumption can limit the effectiveness of devices. These issues can be considered as quality factors that need to be met in order to develop software applications in the Internet of Things domain. Energy consumption is critical to provide sustained service within mobile and wireless environments. To this end, this article focuses on how to develop Internet of Things software that takes low energy consumption into account. In particular, we propose energy evaluation techniques that are based on a software architecture that is designed to use reusable components. By performing an experiment, we could verify that our proposing method shows maximum 6.83% of error rate against code-based energy simulation. Our technique can help software engineers to judge whether or not software is developed to satisfy the particular requirements related with energy consumption.

scholarly journals Energy Efficient Cross Layer Based Multi-Hop Clustered Routing Protocol For Wireless Sensor Networks

2019 ◽  
Vol 8 (4) ◽  
pp. 11996-12003
Keyword(s):  
Energy Consumption ◽  
Network Lifetime ◽  
Routing Protocols ◽  
Cluster Head ◽  
High Energy ◽  
Residual Energy ◽  
Base Station ◽  
Wireless Sensor ◽  
Cross Layer ◽  
User Friendly

Wireless Sensor network becomes an essential part of Internet of things paradigm due their scalability, ease of deployment and user-friendly interface. However, certain issues like high energy consumption, low network lifetime and optimum quality of service requirement force researchers to develop new routing protocols. In WSNs, the routing protocols are utilized to obtain paths having high quality links and high residual energy nodes for forwarding data towards the sink. Clustering provide the better solution to the WSN challenges by creating access points in the form of cluster head (CH). However, CH must tolerate additional burden for coordinating network activities. After considering these issues, the proposed work designs a moth flame optimization (MFO) based Cross Layer Clustering Optimal (MFO-CLCO) algorithm to consequently optimize the network energy, network lifetime, network delay and network throughput. Multi-hop wireless communication between cluster heads (CHs) and base station (BS) is employed along with MFO to attain optimum path cost. The simulation results demonstrate that the proposed scheme outperforms existing schemes in terms of energy consumption, network lifetime, delay and throughput.

scholarly journals An Election Energy Threshold Based Multi-Hop Routing Protocol in a Grid-Clustered Wireless Sensor Network

2018 ◽  
pp. 327-336 ◽  
Author(s):  
Funom Samuel Dadah ◽  
Ajayi Ore-Ofe ◽  
Aliyu D Usman ◽  
Y A Mshelia ◽  
M O Babatunde
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Routing Protocol ◽  
Energy Efficient ◽  
Routing Algorithm ◽  
Base Station ◽  
Energy Threshold ◽  
Wireless Sensor ◽  
Data Packets

Owing to the limited energy of sensor nodes (SNs) in a wireless sensor network (WSN), it is important to reduce and balance the energy consumption of the SNs in order to extend the WSN lifetime. Clustering mechanism is a highly efficient and effective mechanism for minimizing the amount of energy that SNs consume during the transmission of data packets. In this paper, an election energy threshold based multi-hop routing protocol (mEEMRP) is presented. In order to minimize energy consumption, this routing protocol uses grid clustering, where the network field is divided into grid clusters. SNs in each grid cluster select a cluster head (CH) based on a weight factor that takes the node location, node’s residual energy (RE) as well as the node’s distance from the base station into consideration. An energy efficient multi-hop routing algorithm is adopted during the transmission of data packets from the cluster heads (CHs) to the base station (BS). This multi-hop routing algorithm uses an election energy threshold value, T­nhCH that takes into consideration the RE of CHs as well as the distance between CHs. Simulation results show a 1.77% and 10.65% improvement in terms of network lifetime for two network field scenarios over Energy Efficient Multi-hop Routing Protocol (EEMRP).

scholarly journals Machine Learning based Energy Management at Internet of Things Network Nodes

2020 ◽  
Vol 2 (3) ◽  
pp. 127-133
Author(s):  
Dr. Joy Iong Zong Chen ◽  
Kong-Long Lai
Keyword(s):  
Machine Learning ◽  
Energy Consumption ◽  
Internet Of Things ◽  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
High Energy ◽  
Ant Colony ◽  
Wireless Sensor ◽  
Ant Colony Optimization Algorithm ◽  
Network Nodes

The Internet of Things networks comprising wireless sensors and controllers or IoT gateways offers extremely high functionalities. However, not much attention is paid towards energy optimization of these nodes and enabling lossless networks. The wireless sensor networks and its applications has industrialized and scaled up gradually with the development of artificial intelligence and popularization of machine learning. The uneven network node energy consumption and local optimum is reached by the algorithm protocol due to the high energy consumption issues relating to the routing strategy. The smart ant colony optimization algorithm is used for obtaining an energy balanced routing at required regions. A neighbor selection strategy is proposed by combining the wireless sensor network nodes and the energy factors based on the smart ant colony optimization algorithm. The termination conditions for the algorithm as well as adaptive perturbation strategy are established for improving the convergence speed as well as ant searchability. This enables obtaining the find the global optimal solution. The performance, network life cycle, energy distribution, node equilibrium, network delay and network energy consumption are improved using the proposed routing planning methodology. There has been around 10% energy saving compared to the existing state-of-the-art algorithms.

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