scholarly journals E2-MACH: Energy efficient multi-attribute based clustering scheme for energy harvesting wireless sensor networks

2020 ◽  
Vol 16 (10) ◽  
pp. 155014772096804
Author(s):  
Inam Ul Haq ◽  
Qaisar Javaid ◽  
Zahid Ullah ◽  
Zafar Zaheer ◽  
Mohsin Raza ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Harvesting ◽  
Internet Of Things ◽  
Packet Loss ◽  
Energy Efficient ◽  
Cluster Head ◽  
Wireless Sensor

Internet of things have emerged enough due to its applications in a wide range of fields such as governance, industry, healthcare, and smart environments (home, smart, cities, and so on). Internet of things–based networks connect smart devices ubiquitously. In such scenario, the role of wireless sensor networks becomes vital in order to enhance the ubiquity of the Internet of things devices with lower cost and easy deployment. The sensor nodes are limited in terms of energy storage, processing, and data storage capabilities, while their radio frequencies are very sensitive to noise and interference. These factors consequently threaten the energy consumption, lifetime, and throughput of network. One way to cope with energy consumption issue is energy harvesting techniques used in wireless sensor network–based Internet of things. However, some recent studies addressed the problems of clustering and routing in energy harvesting wireless sensor networks which either concentrate on energy efficiency or quality of service. There is a need of an adequate approach that can perform efficiently in terms of energy utilization as well as to ensure the quality of service. In this article, a novel protocol named energy-efficient multi-attribute-based clustering scheme (E2-MACH) is proposed which addresses the energy efficiency and communication reliability. It uses selection criteria of reliable cluster head based on a weighted function defined by multiple attributes such as link statistics, neighborhood density, current residual energy, and the rate of energy harvesting of nodes. The consideration of such parameters in cluster head selection helps to preserve the node’s energy and reduce its consumption by sending data over links possessing better signal-to-noise ratio and hence ensure minimum packet loss. The minimized packet loss ratio contributes toward enhanced network throughput, energy consumption, and lifetime with better service availability for Internet of things applications. A set of experiments using network simulator 2 revealed that our proposed approach outperforms the state-of-the-art low-energy adaptive clustering hierarchy and other recent protocols in terms of first-node death, overall energy consumption, and network throughput.

Distance Based Clustering Algorithm for Energy Efficiency in Wireless Sensor Networks

2014 ◽  
Vol 626 ◽  
pp. 20-25
Author(s):  
K. Kalaiselvi ◽  
G.R. Suresh
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Base Station ◽  
Wireless Sensor ◽  
Cluster Head Selection ◽  
Energy Efficient Routing

In wireless sensor networks Energy-efficient routing is an important issue due to the limited battery power within the network, Energy consumption is one of the important performance factors. Specifically for the election of cluster head selection and distance between the cluster head node and base station. The main objective of this proposed system is to reduce the energy consumption and prolong the network lifetime. This paper introduces a new clustering algorithm for energy efficient routing based on a cluster head selection

scholarly journals Energy-efficient selection of cluster headers in wireless sensor networks

2018 ◽  
Vol 14 (3) ◽  
pp. 155014771876464 ◽  
Author(s):  
Adem Fanos Jemal ◽  
Redwan Hassen Hussen ◽  
Do-Yun Kim ◽  
Zhetao Li ◽  
Tingrui Pei ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Packet Loss ◽  
Energy Efficient ◽  
Low Energy ◽  
Wireless Sensor ◽  
Adaptive Clustering ◽  
End To End Delay ◽  
End To End

Clustering is vital for lengthening the lives of resource-constrained wireless sensor nodes. In this work, we propose a cluster-based energy-efficient router placement scheme for wireless sensor networks, where the K-means algorithm is used to select the initial cluster headers and then a cluster header with sufficient battery energy is selected within each cluster. The performance of the proposed scheme was evaluated in terms of the energy consumption, end-to-end delay, and packet loss. Our simulation results using the OPNET simulator revealed that the energy consumption of our proposed scheme was better than that of the low-energy adaptive clustering hierarchy, which is known to be an energy-efficient clustering mechanism. Furthermore, our scheme outperformed low-energy adaptive clustering hierarchy in terms of the end-to-end delay, throughput, and packet loss rate.

scholarly journals Load Balanced Energy Efficient Cluster-chain Based Hybrid Protocol for Wireless Sensor Networks

2019 ◽  
Vol 8 (3) ◽  
pp. 3561-3570
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Load Balancing ◽  
Network Lifetime ◽  
Outer Layer ◽  
Energy Efficient ◽  
Cluster Head ◽  
Wireless Sensor ◽  
Load Balanced

In this paper a novel geographical multilayer protocol named Cluster-chain Based Hybrid (CCBH) Protocol is proposed for proper load balancing across the network that enhance the network lifespan and eliminate the energy holes problem. The CCBH protocol divides the network into the multilayer square structure around the sink. Each layer is divided into to the zones in such a way that the zones near to the sink are smaller in size and size of zones increases as the separation from the sink increases. In inner two layers, each zone has a cluster head (CH) and to reduce the load of CH a leader node (LN) is assigned in every zone. LN collects and aggregates the data received from neighboring nodes and sends it to the associated CH. Outer layer zones are larger in size. To reduce the clustering overhead chain strategy is introduced in outer layer zones that ensure lesser energy consumption as compared to clustering. Multi hop communiqué is used, where data is transferred from upper zone’s CH to immediate lower zone’s CH until it reaches to the sink. Simulated tests demonstrate that proposed CCBH protocol shows evident improvement in terms of the network lifetime as compare to LBCN, LEACH, TCAC, and DSBCA protocols

scholarly journals TLFW: A Three-Layer Framework in Wireless Rechargeable Sensor Network with a Mobile Base Station

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Anwen Wang ◽  
Xianjia Meng ◽  
Lvju Wang ◽  
Xiang Ji ◽  
Hao Chen ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Internet Of Things ◽  
Sensor Network ◽  
Cluster Head ◽  
Mobile Station ◽  
Base Station ◽  
Wireless Sensor ◽  
Total Energy Consumption

Wireless sensor networks as the base support for the Internet of things have been a large number of popularity and application. Such as intelligent agriculture, we have to use the sensor network to obtain the growing environment data of crops and others. However, the difficulty of power supply of wireless nodes has seriously hindered the application and development of Internet of things. In order to solve this problem, people use low-power sleep scheduling and other energy-saving methods on the nodes. Although these methods can prolong the working time of nodes, they will eventually become invalid because of the exhaustion of energy. The use of solar energy, wind energy, and wireless signals in the environment to obtain energy is another way to solve the energy problem of nodes. However, these methods are affected by weather, environment, and other factors, and they are unstable. Thus, the discontinuity work of the node is caused. In recent years, the development of wireless power transfer (WPT) has brought another solution to this problem. In this paper, a three-layer framework is proposed for mobile station data collection in rechargeable wireless sensor networks to keep the node running forever, named TLFW which includes the sensor layer, cluster head layer, and mobile station layer. And the framework can minimize the total energy consumption of the system. The simulation results show that the scheme can reduce the energy consumption of the entire system, compared with a Mobile Station in a Rechargeable Sensor Network (MSiRSN).

scholarly journals An energy-efficient unequal clustering routing protocol for wireless sensor networks

2019 ◽  
Vol 15 (9) ◽  
pp. 155014771987938 ◽  
Author(s):  
Fang Zhu ◽  
Junfang Wei
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Routing Protocol ◽  
Energy Efficient ◽  
Cluster Head ◽  
Wireless Sensor ◽  
Unequal Clustering ◽  
Rotation Strategy

Wireless sensor networks have drawn tremendous attentions from all fields because of their wide application. Maximizing network lifetime is one of the main problems in wireless sensor networks. This article proposes an energy-efficient routing protocol which adopts unequal clustering technology to solve the hot spots problem and proposes double cluster head strategy to reduce the energy consumption of head nodes in the clusters. In addition, to balance the energy consumption between cluster heads and cluster members, a hybrid cluster head rotation strategy based on time-driven and energy-driven is proposed, which can make the timing of rotation more reasonable and the energy consumption more efficient. Finally, we compare the proposed protocol with LEACH, DEBUC, and UCNPD by simulation experiments. The simulation results prove that our proposed protocol can effectively improve the performance in terms of network lifetime, energy consumption, energy balance, stability, and throughput.

scholarly journals An Energy-Efficient Cluster Head Selection Scheme for Energy-Harvesting Wireless Sensor Networks

Sensors ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 187 ◽  
Author(s):  
Qian Ren ◽  
Guangshun Yao
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Energy Harvesting ◽  
Energy Efficient ◽  
Cluster Head ◽  
Wireless Sensor ◽  
Cluster Head Selection ◽  
Selection Scheme ◽  
Selection Stage ◽  
Ch Selection

Concerning the large amount of energy consumption during the cluster head selection stage and the unequal harvested energy among nodes in energy-harvesting wireless sensor networks (EH-WSNs), an energy- efficient cluster head selection scheme called EECHS is proposed in this paper. The scheme divides all nodes from one cluster into three types: cluster head (CH), cluster member (CM), and scheduling node (SN). The SN is designed to monitor and store real-time information about the residual energy of all nodes, including CMs and the CH, in the same cluster. In the CH selection stage, the SN specifies a corresponding CM as the new CH according to the monitored results, thereby reducing the energy consumption caused by CH selection. In this way, the task of CH selection is migrated from CHs to SNs and, thus, the CHs can preserve more energy for data forwarding. Moreover, the EECHS adjusts the transmission radius of some nodes dynamically to prevent these nodes from discarding the harvested energy if their batteries are fully charged. A series of experiments were conducted to verify the effectiveness of the proposed EECHS, and the results demonstrate that EECHS can provide an efficient CH selection scheme for EH-WSNs and is able to use the harvested energy more efficiently than corresponding competitors.

Energy Efficient Recursive Clustering and Gathering in Big Data for Wireless Sensor Networks

2019 ◽  
Vol 17 (9) ◽  
pp. 680-687
Author(s):  
S. Subaselvi ◽  
T. Manimekalai ◽  
K. Gunaseelan
Keyword(s):  
Wireless Sensor Networks ◽  
Big Data ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Cluster Head ◽  
Maximum Energy ◽  
Base Station ◽  
Wireless Sensor ◽  
Long Distance

Big data is one of the emerging technology in Wireless Sensor Networks (WSN). Gathering of data is the biggest challenge for implementing big data in WSN. In WSN, the frequent information communications between the nodes are inevitable. Moreover, the long distance communication between the nodes in the network lead to reduction in the lifetime of the nodes. In order to reduce communication distance between the nodes and to efficiently gather large amount of data. Energy Efficient Recursive Clustering and Gathering for big data in WSN is proposed. In proposed algorithm, the grid area will be divided into zones. The zones are divided by finding the minimum and maximum X and Y from the nodes location and distribution of nodes in the network. In each zone, clusters are formed in recursive manner. After the clusters are formed in recursive manner, for every cluster, the Cluster Administrator are elected based on the maximum energy among the nodes in the cluster. Once the Cluster Administrators are elected, the Cluster Administrator which has the maximum energy in the Zone, will be elected as a Cluster Head. The Cluster Head only send the information for a particular zone. Energy consumption will be reduced as the cluster head only sends the information to the base station, instead of every nodes in the zone. The localization algorithm based on Received Signal Strength Indicator (RSSI) and multi hop routing is performed to reduce end-to-end delay in the network. The simulated results show that the proposed algorithm gathers large amount of data with low energy consumption than the existing algorithm.

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