scholarly journals Energy-efficient routing in the proximity of a complicated hole in wireless sensor networks

2021 ◽  
Author(s):  
Khanh-Van Nguyen ◽  
Chi-Hieu Nguyen ◽  
Phi Le Nguyen ◽  
Tien Van Do ◽  
Imrich Chlamtac

AbstractA quest for geographic routing schemes of wireless sensor networks when sensor nodes are deployed in areas with obstacles has resulted in numerous ingenious proposals and techniques. However, there is a lack of solutions for complicated cases wherein the source or the sink nodes are located close to a specific hole, especially in cavern-like regions of large complex-shaped holes. In this paper, we propose a geographic routing scheme to deal with the existence of complicated-shape holes in an effective manner. Our proposed routing scheme achieves routes around holes with the (1+$$\epsilon$$ ϵ )-stretch. Experimental results show that our routing scheme yields the highest load balancing and the most extended network lifetime compared to other well-known routing algorithms as well.

2013 ◽  
Vol 479-480 ◽  
pp. 783-787
Author(s):  
Yih Chuan Lin ◽  
Jia Hong Zhong

This paper addresses the problem of how to make efficient energy consumption on routing communications among the set of wireless sensor nodes deployed randomly in a large-scale manner. Tree-based routing topology is considered in the study with regarding to its simplicity of routing process. To minimize the energy dissipation of tree-routing, centralized coordination schemes are usually used to construct an optimal tree routing topology. In this paper, a distributed-based tree routing protocol is proposed not only to improve the scalability of the centralized tree routing schemes but also handle the balance consumption among the sensor nodes. With computer simulation, the effectiveness of the proposed routing scheme is verified and shown to be useful in large-scale wireless sensor networks.


2013 ◽  
Vol 4 (2) ◽  
pp. 261-266 ◽  
Author(s):  
Jahangeer Ali ◽  
Gulshan Kumar ◽  
Dr. Mritunjay Kumar Rai

Sensing the environment without human intervention is carried out with Wireless Sensor Networks. Thus WSNs have gained impetus in every field as applicable to various sensing applications. As the sensor nodes are very minute with limited power, memory and controlling mechanism. Thus it is necessary to implement energy efficient routing in sensor nodes such that network lifetime is enhanced. In this paper, we have discussed various existing energy efficient routing schemes and made comparison on various parameters in literature survey. Finally came to conclusion that there is a need of an energy efficient routing protocol which can further extend network lifetime. We propose an idea in which existing; Enhanced Energy Efficient Protocol with Static Clustering (EEEPSC) is modified by placing a fraction of nodes having more energy than normal nodes in the locations where Base Station is far away. And BS is placed within the area of deployed nodes.


Electronics ◽  
2021 ◽  
Vol 10 (13) ◽  
pp. 1539
Author(s):  
Qianao Ding ◽  
Rongbo Zhu ◽  
Hao Liu ◽  
Maode Ma

Machine learning (ML) technology has shown its unique advantages in many fields and has excellent performance in many applications, such as image recognition, speech recognition, recommendation systems, and natural language processing. Recently, the applicability of ML in wireless sensor networks (WSNs) has attracted much attention. As resources are limited in WSNs, identifying how to improve resource utilization and achieve power-efficient load balancing is becoming a critical issue in WSNs. Traditional green routing algorithms aim to achieve this by reducing energy consumption and prolonging network lifetime through optimized routing schemes in WSNs. However, there are usually problems such as poor flexibility, a single consideration factor, and a reliance on accurate mathematical models. ML techniques can quickly adapt to environmental changes and integrate multiple factors for routing decisions, which provides new ideas for intelligent energy-efficient routing algorithms in WSNs. In this paper, we survey and propose a theoretical hypothetic model formulation of ML as an effective method for creating a power-efficient green routing model that can overcome the limitations of traditional green routing methods. In addition, the study also provides an overview of past, present, and future progress in green routing schemes in WSNs. The contents of this paper will appeal to a wide range of audiences interested in ML-based WSNs.


2021 ◽  
Author(s):  
Ramin Danehchin

Abstract Data collection on Wireless Sensor Networks (WSNs) is a significant challenge to satisfy the requirements of various applications. Providing an energy-efficient routing technique is the primary step in data collection over WSNs. The existing data collection techniques in the WSNs field struggle with the imbalance load distribution and the short lifetime of the network. This paper proposes a novel mechanism to select cluster-heads, cluster the wireless sensor nodes, and determine the optimal route from source nodes to the sink. We employ the genetic algorithm to solve the routing problem considering the hop-count of the cluster-heads to the sink, the number of each cluster member, residual energy of cluster-heads, and the number of cluster-heads connected to the sink as the fitness criteria. Our proposed mechanism uses a greedy approach to calculate the hop-count of each cluster-head to the sink for integrating the clustering and routing process on WSNs. The simulation results demonstrate that our proposed mechanism improves the energy consumption, the number of live nodes, and the lifetime of the network compared to other data collection approaches on WSNs.


Author(s):  
Habib M. Ammari ◽  
Amer Ahmed

A wireless sensor network is a collection of sensor nodes that have the ability to sense phenomena in a given environment and collect data, perform computation on the gathered data, and transmit (or forward) it to their destination. Unfortunately, these sensor nodes have limited power, computational, and storage capabilities. These factors have an influence on the design of wireless sensor networks and make it more challenging. In order to overcome these limitations, various power management techniques and energy-efficient protocols have been designed. Among such techniques and protocols, geographic routing is one of the most efficient ways to solve some of the design issues. Geographic routing in wireless sensor networks uses location information of the sensor nodes to define a path from source to destination without having to build a network topology. In this paper, we present a survey of the existing geographic routing techniques both in two-dimensional (2D) and three-dimensional (3D) spaces. Furthermore, we will study the advantages of each routing technique and provide a discussion based on their practical possibility of deployment.


2013 ◽  
Vol 706-708 ◽  
pp. 635-638
Author(s):  
Yong Lv

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.


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.


2015 ◽  
Vol 764-765 ◽  
pp. 838-842
Author(s):  
Young Long Chen ◽  
Yung Chi Chang ◽  
Yu Ling Zeng

Wireless sensor networks (WSNs) are a group of wireless sensor nodes, those sensor nodes with sensing and monitoring of environmental information. Energy consumption is an important topic; the node's power is limited. Therefore, we proposed an Opportunistic Large Array Concentric Geographic Routing Algorithm (OLACGRA) to reduce the node’s energy consumption and analysis the characteristic of energy model. The sink position of our proposed OLACGRA is at the center of concentric topology architecture. The source node wants to transmit data that it needs to calculate the distance between source node and sink node. If this distance bigger than threshold value, we use the multi-hop manner. Otherwise, source node transmits data to sink node directly. Simulation results show that our proposed algorithm can effectively reduce the node’s energy consumption.


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