scholarly journals Nonuniform Grid-Based Coordinated Routing in Wireless Sensor Networks

2009 ◽  
Vol 2009 ◽  
pp. 1-11 ◽  
Author(s):  
Robert Akl ◽  
Priyanka Kadiyala ◽  
Mohamad Haidar
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Path Loss ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Nonuniform Grid ◽  
Uniform Grids ◽  
Grid Based

A nonuniform grid-based coordinated routing design in wireless sensor networks is presented. The conditions leading to network partition and analysis of energy consumption that prolongs the network lifetime are studied. We focus on implementing routing in densely populated sensor networks. By maintaining constant values for parameters such as path loss exponent, receiver sensitivity and transmit power, and varying between uniform and non-uniform grids, we observe energy consumption patterns for each of the grid structures and infer from the network lifetime the better suited grids for uniformly and randomly deployed sensor nodes.

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.

scholarly journals Increasing network lifetime using data compression in wireless sensor networks with energy harvesting

2017 ◽  
Vol 13 (1) ◽  
pp. 155014771668968 ◽  
Author(s):  
Sunyong Kim ◽  
Chiwoo Cho ◽  
Kyung-Joon Park ◽  
Hyuk Lim
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Harvesting ◽  
Data Compression ◽  
Network Lifetime ◽  
Average Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Entire Network

In wireless sensor networks powered by battery-limited energy harvesting, sensor nodes that have relatively more energy can help other sensor nodes reduce their energy consumption by compressing the sensing data packets in order to consequently extend the network lifetime. In this article, we consider a data compression technique that can shorten the data packet itself to reduce the energies consumed for packet transmission and reception and to eventually increase the entire network lifetime. First, we present an energy consumption model, in which the energy consumption at each sensor node is derived. We then propose a data compression algorithm that determines the compression level at each sensor node to decrease the total energy consumption depending on the average energy level of neighboring sensor nodes while maximizing the lifetime of multihop wireless sensor networks with energy harvesting. Numerical simulations show that the proposed algorithm achieves a reduced average energy consumption while extending the entire network lifetime.

scholarly journals Hesitant Fuzzy Entropy-Based Opportunistic Clustering and Data Fusion Algorithm for Heterogeneous Wireless Sensor Networks

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 913
Author(s):  
Junaid Anees ◽  
Hao-Chun Zhang ◽  
Sobia Baig ◽  
Bachirou Guene Lougou ◽  
Thomas Gasim Robert Bona
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Fusion ◽  
Network Lifetime ◽  
Cluster Formation ◽  
Fuzzy Entropy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Heterogeneous Clustering

Limited energy resources of sensor nodes in Wireless Sensor Networks (WSNs) make energy consumption the most significant problem in practice. This paper proposes a novel, dynamic, self-organizing Hesitant Fuzzy Entropy-based Opportunistic Clustering and data fusion Scheme (HFECS) in order to overcome the energy consumption and network lifetime bottlenecks. The asynchronous working-sleeping cycle of sensor nodes could be exploited to make an opportunistic connection between sensor nodes in heterogeneous clustering. HFECS incorporates two levels of hierarchy in the network and energy heterogeneity is characterized using three levels of energy in sensor nodes. HFECS gathers local sensory data from sensor nodes and utilizes multi-attribute decision modeling and the entropy weight coefficient method for cluster formation and the cluster head election procedure. After cluster formation, HFECS uses the same techniques for performing data fusion at the first hierarchical level to reduce the redundant information flow from the first-second hierarchical levels, which can lead to an improvement in energy consumption, better utilization of bandwidth and extension of network lifetime. Our simulation results reveal that HFECS outperforms the existing benchmark schemes of heterogeneous clustering for larger network sizes in terms of half-life period, stability period, average residual energy, network lifetime, and packet delivery ratio.

scholarly journals Efficient organization of nodes in wireless sensor networks (clustering location-based LEACH)

2022 ◽  
Vol 12 (1) ◽  
pp. 1011
Author(s):  
Mohammed Réda El Ouadi ◽  
Abderrahim Hasbi
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Rapid Development ◽  
Cluster Head ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Main Element

The rapid development of connected devices and wireless communication has enabled several researchers to study wireless sensor networks and propose methods and algorithms to improve their performance. Wireless sensor networks (WSN) are composed of several sensor nodes deployed to collect and transfer data to base station (BS). Sensor node is considered as the main element in this field, characterized by minimal capacities of storage, energy, and computing. In consequence of the important impact of the energy on network lifetime, several researches are interested to propose different mechanisms to minimize energy consumption. In this work, we propose a new enhancement of low-energy adaptive clustering hierarchy (LEACH) protocol, named clustering location-based LEACH (CLOC-LEACH), which represents a continuity of our previous published work location-based LEACH (LOC-LEACH). The proposed protocol organizes sensor nodes into four regions, using clustering mechanism. In addition, an efficient concept is adopted to choose cluster head. CLOC-LEACH considers the energy as the principal metric to choose cluster heads and uses a gateway node to ensure the inter-cluster communication. The simulation with MATLAB shows that our contribution offers better performance than LEACH and LOC-LEACH, in terms of stability, energy consumption and network lifetime.

Mixed Communication Method on the Grid-Based for Wireless Sensor Networks

2014 ◽  
Vol 686 ◽  
pp. 417-422
Author(s):  
Zhu Yan ◽  
Xi Ne You ◽  
Ran Yan
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Wireless Sensor ◽  
Cluster Radius ◽  
Communication Method ◽  
Balancing Energy ◽  
Grid Based ◽  
Optimal Cluster

When senors transmit their data to the sink via multi-hop communication, the sensors closer to the sink are burdened with heavy relay traffic and tend to die early. On the contrary, if all sensors transmit datas to the sink via single-hop communication, the sensors further from the sink will die much more quickly than those closer to the sink. In this paper, we first develop an analytical model to derive the optimal cluster radius. Then we propose a mixed communication method on grid-based where the sensors can transmit data to the sink in either single-hop or multi-hop. Finally, we conduct extensive experiments and show that our method outperforms LEACH and HEED in terms of network lifetime by balancing energy consumption.

scholarly journals Grid-Based Hybrid Network Deployment Approach for Energy Efficient Wireless Sensor Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Haleem Farman ◽  
Huma Javed ◽  
Jamil Ahmad ◽  
Bilal Jan ◽  
Muhammad Zeeshan
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Load Balancing ◽  
Network Lifetime ◽  
Sensor Nodes ◽  
Hybrid Network ◽  
Wireless Sensor ◽  
Total Energy Consumption ◽  
Grid Based ◽  
Efficient Consumption

Wireless sensor networks (WSN) empower applications for critical decision-making through collaborative computing, communications, and distributed sensing. However, they face several challenges due to their peculiar use in a wide variety of applications. One of the inherent challenges with any battery operated sensor is the efficient consumption of energy and its effect on network lifetime. In this paper, we introduce a novel grid-based hybrid network deployment (GHND) framework which ensures energy efficiency and load balancing in wireless sensor networks. This research is particularly focused on the merge and split technique to achieve even distribution of sensor nodes across the grid. Low density neighboring zones are merged together whereas high density zones are strategically split to achieve optimum balance. Extensive simulations reveal that the proposed method outperforms state-of-the-art techniques in terms of load balancing, network lifetime, and total energy consumption.

Mixed Communication Method on the Grid-Based for Wireless Sensor Networks

2014 ◽  
Vol 1049-1050 ◽  
pp. 1797-1802
Author(s):  
Jing Guo Dai ◽  
Hui Yong Yuan
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Wireless Sensor ◽  
Cluster Radius ◽  
Communication Method ◽  
Balancing Energy ◽  
Grid Based ◽  
Optimal Cluster

When senors transmit their data to the sink via multi-hop communication, the sensors closer to the sink are burdened with heavy relay traffic and tend to die early. On the contrary, if all sensors transmit datas to the sink via single-hop communication, the sensors further from the sink will die much more quickly than those closer to the sink. In this paper, we first develop an analytical model to derive the optimal cluster radius. Then we propose a mixed communication method on grid-based where the sensors can transmit data to the sink in either single-hop or multi-hop. Finally, we conduct extensive experiments and show that our method outperforms LEACH and HEED in terms of network lifetime by balancing energy consumption.

Energy Consumption with Fountain Codes and Clustering in Wireless Sensor Networks: Survey & Analysis‎

2017 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Fatma Belabed ◽  
Ridha Bouallegue
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Erasure Codes ◽  
Fountain Codes ◽  
Crucial Issue ◽  
Energy Consumption Model

<div><p><em>Energy is the most important and crucial issue in the wireless sensor networks since the entire sensor nodes are battery powered devices. As a result, energy efficiency and prolonging network lifetime are a challenge. In order to increase the lifetime of the battery-based sensing nodes, it is essential to minimize the consumed energy in the sensing process</em>. <em>With this objective, specific erasure codes called fountain codes are introduced. Fountain codes' performances can be further improved if they are merged with the strategy of grouping sensor nodes into clusters. In order to reach the energy minimization and network lifetime prolonging, the first step, is to completely know the sources of energy consumption. In this paper, sources of energy consumption with various techniques used have been studied and investigated. Furthermore, a survey has been provided for the energy consumption model by using these two techniques. </em></p></div>

scholarly journals Energy Efficient Clustering for Wireless Sensor Networks using EASSR

2015 ◽  
Vol 15 (3) ◽  
pp. 554
Author(s):  
Y. Chalapathi Rao ◽  
Ch. Santhi Rani
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Average Energy ◽  
Rechargeable Batteries ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Efficient Clustering

<p>Wireless Sensor Networks (WSNs) consist of a large quantity of small and low cost sensor nodes powered by small non rechargeable batteries and furnish with various sensing devices. The cluster-based technique is one of the good perspectives to reduce energy consumption in WSNs. The lifetime of WSNs is maximized by using the uniform cluster location and balancing the network loading between the clusters. We have reviewed various energy efficient schemes apply in WSNs of which we concerted on clustering approach. So, in this paper we have discussed about few existing energy efficient clustering techniques and proposed an Energy Aware Sleep Scheduling Routing (EASSR) scheme for WSN in which some nodes are usually put to sleep to conserve energy, and this helps to prolong the network lifetime. EASSR selects a node as a cluster head if its residual energy is more than system average energy and have low energy consumption rate in existing round. The efforts of this scheme are, increase of network stability period, and minimize loss of sensed data. Performance analysis and compared statistic results show that EASSR has significant improvement over existing methods in terms of energy consumption, network lifetime and data units gathered at BS.</p>

scholarly journals CAF: Cluster Algorithm and A-Star with Fuzzy Approach for Lifetime Enhancement in Wireless Sensor Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-17 ◽  
Author(s):  
Yali Yuan ◽  
Caihong Li ◽  
Yi Yang ◽  
Xiangliang Zhang ◽  
Lian Li
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Clustering Algorithm ◽  
Fuzzy Inference ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Fuzzy Approach

Energy is a major factor in designing wireless sensor networks (WSNs). In particular, in the real world, battery energy is limited; thus the effective improvement of the energy becomes the key of the routing protocols. Besides, the sensor nodes are always deployed far away from the base station and the transmission energy consumption is index times increasing with the increase of distance as well. This paper proposes a new routing method for WSNs to extend the network lifetime using a combination of a clustering algorithm, a fuzzy approach, and an A-star method. The proposal is divided into two steps. Firstly, WSNs are separated into clusters using the Stable Election Protocol (SEP) method. Secondly, the combined methods of fuzzy inference and A-star algorithm are adopted, taking into account the factors such as the remaining power, the minimum hops, and the traffic numbers of nodes. Simulation results demonstrate that the proposed method has significant effectiveness in terms of balancing energy consumption as well as maximizing the network lifetime by comparing the performance of the A-star and fuzzy (AF) approach, cluster and fuzzy (CF)method, cluster and A-star (CA)method, A-star method, and SEP algorithm under the same routing criteria.

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