Energy-Efficient Routing Techniques for Wireless Sensors Networks

2020 ◽  
pp. 917-944
Author(s):  
Asmaa Osamaa ◽  
Shaimaa Ahmed El-Said ◽  
Aboul Ella Hassanien
Keyword(s):  
Wireless Sensors ◽  
Signal Strength ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Awareness ◽  
Energy Efficient Routing ◽  
Routing Techniques ◽  
Physical Phenomena ◽  
And Storage ◽  
Innovative Techniques

Wireless sensor networks (WSNs), which normally consist of hundreds or thousands of sensor nodes each capable of sensing, processing, and transmitting environmental information, are deployed to monitor certain physical phenomena or to detect and track certain objects in an area of interests. The sensor nodes in WSN transmit data depending on local information and parameters such as signal strength, power consumption, location of data collection and accretion. Only reachable nodes are able to communicate with each other directly to collect and transmit data. The motes have limited energy resources along with constraints on its computational and storage capabilities. Thus, innovative techniques that eliminate energy inefficiencies that would shorten the lifetime of the network are highly required. Such constraints combined with a typical deployment of large number of sensor nodes pose many challenges to the design and management of WSNs and necessitate energy-awareness at all layers of the networking protocol stack. In this chapter, we present a survey of the state-of-the-art routing techniques in WSNs that take into consideration the energy issue.

Energy-Efficient Routing Techniques for Wireless Sensors Networks

2016 ◽  
pp. 37-62 ◽  
Author(s):  
Asmaa Osamaa ◽  
Shaimaa Ahmed El-Said ◽  
Aboul Ella Hassanien
Keyword(s):  
Wireless Sensors ◽  
Signal Strength ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Awareness ◽  
Energy Efficient Routing ◽  
Routing Techniques ◽  
Physical Phenomena ◽  
And Storage ◽  
Innovative Techniques

Wireless sensor networks (WSNs), which normally consist of hundreds or thousands of sensor nodes each capable of sensing, processing, and transmitting environmental information, are deployed to monitor certain physical phenomena or to detect and track certain objects in an area of interests. The sensor nodes in WSN transmit data depending on local information and parameters such as signal strength, power consumption, location of data collection and accretion. Only reachable nodes are able to communicate with each other directly to collect and transmit data. The motes have limited energy resources along with constraints on its computational and storage capabilities. Thus, innovative techniques that eliminate energy inefficiencies that would shorten the lifetime of the network are highly required. Such constraints combined with a typical deployment of large number of sensor nodes pose many challenges to the design and management of WSNs and necessitate energy-awareness at all layers of the networking protocol stack. In this chapter, we present a survey of the state-of-the-art routing techniques in WSNs that take into consideration the energy issue.

Wireless Sensor Networks

2018 ◽  
pp. 1-18
Author(s):  
Sonam ◽  
Manju Khari
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Wireless Communication ◽  
Sensor Node ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Awareness ◽  
Wired Communication ◽  
And Storage

This chapter describes how as world is switching from wired communication to wireless communication, the need of a wireless sensor network (WSN) is increasing. WSNs became very popular due to its wide applications. A WSN is a network of small-in-size sensor nodes which are densely deployed for monitoring a chosen environment. In WSNs, each sensor node detects data and sends it to the base station. These sensor nodes have four basic duties, consisting of sensing, computation, transmission and power. Due to the small size, these sensor nodes are more constrained in terms of computational energy and storage resources. Energy awareness is also an essential design issue for routing protocols in WSNs. The focus of this chapter is to provide an overview of WSNs. In addition, this chapter describes the components of WSNs, its challenges and the classifications of WSNs. This chapter compares the results of LEACH, SEP and TEEN protocols.

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
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Geographic Routing ◽  
Routing Algorithms ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Efficient Routing ◽  
Routing Schemes ◽  
Routing Scheme ◽  
Effective Manner

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.

scholarly journals An Integrated Routing Mechanism on Homogenous Wireless Sensor Networks using Genetic Algorithm

2021 ◽  
Author(s):  
Ramin Danehchin
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Collection ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Efficient Routing ◽  
Hop Count ◽  
Routing Problem ◽  
Cluster Heads

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.

scholarly journals Comprehensive Survey of Routing Techniques in Wireless Sensor Network

2013 ◽  
Vol 5 (2) ◽  
pp. 563-575
Author(s):  
Nidhi Sharma ◽  
Shikha Sharma
Keyword(s):  
Power Management ◽  
Routing Protocols ◽  
Data Dissemination ◽  
Wireless Sensor ◽  
Communication Overhead ◽  
Energy Awareness ◽  
Comprehensive Survey ◽  
Routing Techniques ◽  
Design Tradeoffs ◽  
And Performance

Wireless Sensor Netw orks ( WSNs) c onsist of small nodes with sensing, computation, and wireless communications capabilities. Many routing, power management, and data dissemination protocols have been specifically designed for WSNs where energy awareness is an essential design issue. The focus , however, has been given to the routing protocols which might differ depending on the application and netw ork architecture. In this paper, we present a survey of the state-of-the-art routing techniques in WSNs. We first outline the designchallenges for routing protocols in WSNs followed by a comprehensive survey of different routing techniques . Overall, the routing techniques are classified into three categories based on the underlying netw ork structure: flat, hierarchical, and location-based routing. Furthermore, these protocols can be classified into multipath-based,query-based, negotiation-based, QoS-based, and coherent-based depending on the protocol operation. We study the design tradeoffs b e twe e n ener gy and communication overhead savings in every routing paradigm. We also highlight the adv antages and performance issues of each routing technique.

Wireless Sensor Network

2012 ◽  
pp. 339-347
Author(s):  
Noor Zaman ◽  
Azween Abdullah ◽  
Khalid Ragab
Keyword(s):  
Wireless Sensor Networks ◽  
Resource Constraints ◽  
Data Transfer ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Future Directions ◽  
Maximum Benefit ◽  
Routing Techniques ◽  
Different Levels

Wireless Sensor Networks (WSNs) are becoming common in use, with a vast diversity of applications. Due to its resource constraints, it is hard to maintain Quality of Service (QoS) with WSNs. Though they contain a vast variety of applications, at the same time they are also required to provide different levels of QoS, for various types of applications. A number of different issues and challenges still persist ahead to maintain the QoS of WSN, especially in critical applications where the accuracy of timely, guaranteed data transfer is required, such as chemical, defense, and healthcare. Hence, QoS is required to ensure the best use of sensor nodes at any time. Researchers are trying to focus on QoS issues and challenges to get maximum benefit from their applications. With this chapter, the authors focus on operational and architectural challenges of handling QoS, requirements of QoS in WSNs, and they discuss a selected survey of QoS aware routing techniques by comparing them in WSNs. Finally, the authors highlight a few open issues and future directions of research for providing QoS in WSNs.

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.

Localization in Wireless Sensor Networks Using Soft Computing Approach

2017 ◽  
Vol 11 (3) ◽  
pp. 42-53 ◽  
Author(s):  
Sunil Kumar Singh ◽  
Prabhat Kumar ◽  
Jyoti Prakash Singh
Keyword(s):  
Ad Hoc ◽  
Low Cost ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Scheme ◽  
Anchor Nodes ◽  
Received Signal Strength Indication ◽  
Logic System

Wireless sensor network (WSN) is formed by a large number of low-cost sensors. In order to exchange information, sensor nodes communicate in an ad hoc manner. The acquired information is useful only when the location of sensors is known. To use GPS-aided devices in each sensor makes sensors more costly and energy hungry. Hence, finding the location of nodes in WSNs becomes a major issue. In this paper, the authors propose a combination of range based and range-free localization scheme. In their scheme, for finding the distance, they use received signal strength indication (RSSI), which is a range based center of gravity technique. For finding the location of non-anchor nodes, the authors assign weights to anchor and non-anchor nodes based on received signal strength. The weight, which is assigned to anchor and non-anchor nodes, are designed by fuzzy logic system (FLS).

Maximizing the Lifetime of Sliding Wireless Sensors in Barrier Coverage

2012 ◽  
Vol 157-158 ◽  
pp. 503-506 ◽  
Author(s):  
Tao Yang ◽  
Pan Guo Fan ◽  
De Jun Mu
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Lifetime ◽  
Wireless Sensors ◽  
Specific Area ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Barrier Coverage ◽  
Coverage Ratio ◽  
Simulation Results

Wireless sensor network is always deployed in specific area for intrusion detection and environmental monitoring. The sensor nodes suffer mostly from their limited battery capacity.Maximizing the lifetime of the entire networks is mainly necessary considered in the design. Sliding the sensors in different barriers under the optimal barrier construction is a good solution for both maximizing network lifetime and providing predetermined coverage ratio. The simulation results demonstrate that the scheme can effectively reduce the energy consumption of the wireless sensor network and increase the network lifetime.

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