A Review on energy management schemes in energy harvesting wireless sensor networks

Babayo, Aliyu Aliyu; Anisi, Mohammad Hossein; Ali, Ihsan

doi:10.1016/j.rser.2017.03.124

Cited by 156 publications

(68 citation statements)

References 36 publications

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“…Energy conservation is the sparing use of energy in sensor nodes to allow sensor networks to be able to function as required [3]. It usually involves minimizing the communication cost in nodes [3,15] since the radio is known to be the greatest consumer of the available energy [12,23,24]. It may also be achieved by developing energy efficient routing protocols, clustering approaches, sleep/wakeup optimization (duty cycling), and in some cases mobility [15,25,26].…”

Section: Energy Harvesting Energy Sourcementioning

confidence: 99%

“…Energy management schemes are the techniques designed for the efficient use of energy in a network [23] and in some instances for efficient use of harvested energy [15]. Although some of the proposed energy management techniques assume that data acquisition through sensing consumes less energy than data transmission [3,23], this may not be so for all applications [27,28] especially in the case of energy hungry sensors, e.g., gas sensors. Most of these techniques are used to prolong the lifetime of sensor nodes by either reducing energy consumption or replenishing the consumed energy in battery powered nodes or low-powered capacitors.…”

Section: Energy Harvesting Energy Sourcementioning

confidence: 99%

“…Balancing schemes proposed in recent research discussed means of distributing and managing the energy in a sensor node [23]. Clustering schemes have been used to balance energy in the network, and they were processes where nodes are grouped together with a coordinator, usually known as the cluster head, that perform specialized functions such as data fusion and aggregation, and communicate this data from its clusters to the base station.…”

Section: Energy Balancingmentioning

confidence: 99%

See 2 more Smart Citations

Prolonging the Lifetime of Wireless Sensor Networks: A Review of Current Techniques

Engmann

Katsriku

Abdulai

et al. 2018

Wireless Communications and Mobile Computing

158

105

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There has been an increase in research interest in wireless sensor networks (WSNs) as a result of the potential for their widespread use in many different areas like home automation, security, environmental monitoring, and many more. Despite the successes gained, the widespread adoption of WSNs particularly in remote and inaccessible places where their use is most beneficial is hampered by the major challenge of limited energy, being in most instances battery powered. To prolong the lifetime for these energy hungry sensor nodes, energy management schemes have been proposed in the literature to keep the sensor nodes alive making the network more operational and efficient. Currently, emphasis has been placed on energy harvesting, energy transfer, and energy conservation methods as the primary means of maintaining the network lifetime. These energy management techniques are designed to balance the energy in the overall network. The current review presents the state of the art in the energy management schemes, the remaining challenges, and the open issues for future research work.

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Section: Energy Harvesting Energy Sourcementioning

confidence: 99%

Section: Energy Harvesting Energy Sourcementioning

confidence: 99%

Section: Energy Balancingmentioning

confidence: 99%

See 1 more Smart Citation

Prolonging the Lifetime of Wireless Sensor Networks: A Review of Current Techniques

Engmann

Katsriku

Abdulai

et al. 2018

Wireless Communications and Mobile Computing

158

105

View full text Add to dashboard Cite

show abstract

“…For this reason, a clustering network protocol that operates with heterogeneity is more significant than a homogeneous network method [20]. Energy consumption of a sensor node involves models that consume energy so that it can perform specific functions such as sensing, processing and wireless communication of collected data [25][26][27]. These models have become functional by making energy consumption calculations.…”

Section: Deec Modelmentioning

confidence: 99%

Threshold Balanced Sampled DEEC Model for Heterogeneous Wireless Sensor Networks

Vançin

Erdem

2018

Wireless Communications and Mobile Computing

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Due to the restricted hardware resources of the sensor nodes, modelling and designing energy efficient routing methods to increase the overall network lifetime have become one of the most significant strategies in wireless sensor networks (WSNs). Cluster-based heterogeneous routing protocols, a popular part of routing technology, have proven effective in management of topology, energy consumption, data collection or fusion, reliability, or stability in a distributed sensor network. In this article, an energy efficient three-level heterogeneous clustering method (DEEC) based distributed energy efficient clustering protocol named TBSDEEC (Threshold balanced sampled DEEC) is proposed. Contrary to most other studies, this study considers the effect of the threshold balanced sampled in the energy consumption model. Our model is compared with the DEEC, EDEEC (Enhanced Distributed Energy Efficient Clustering Protocol), and EDDEEC (Enhanced Developed Distributed Energy Efficient Clustering Protocol) using MATLAB as two different scenarios based on quality metrics, including living nodes on the network, network efficiency, energy consumption, number of packets received by base station (BS), and average latency. After, our new method is compared with artificial bee colony optimization (ABCO) algorithm and energy harvesting WSN (EH-WSN) clustering method. Simulation results demonstrate that the proposed model is more efficient than the other protocols and significantly increases the sensor network lifetime.

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“…Routing protocols in WSNs can be divided according to network structure into 3 categories: location based, data centric, and hierarchical protocols . Location‐based protocol: location information for all nodes is a major cornerstone during data communication.…”

Section: Introductionmentioning

confidence: 99%

A new algorithm for cluster head selection in LEACH protocol for wireless sensor networks

Al-Baz

El‐Sayed

2017

Int J Communication

156

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SummaryIn wireless sensor network, a large number of sensor nodes are distributed to cover a certain area. Sensor node is little in size with restricted processing power, memory, and limited battery life. Because of restricted battery power, wireless sensor network needs to broaden the system lifetime by reducing the energy consumption. A clustering-based protocols adapt the use of energy by giving a balance to all nodes to become a cluster head. In this paper, we concentrate on a recent hierarchical routing protocols, which are depending on LEACH protocol to enhance its performance and increase the lifetime of wireless sensor network. So our enhanced protocol called Node Ranked-LEACH is proposed. Our proposed protocol improves the total network lifetime based on node rank algorithm. Node rank algorithm depends on both path cost and number of links between nodes to select the cluster head of each cluster. This enhancement reflects the real weight of specific node to success and can be represented as a cluster head. The proposed algorithm overcomes the random process selection, which leads to unexpected fail for some cluster heads in other LEACH versions, and it gives a good performance in the network lifetime and energy consumption comparing with previous version of LEACH protocols. KEYWORDScluster head selection, clustering-based protocols, LEACH protocols, wireless sensor networks | INTRODUCTIONWireless sensor networks (WSNs) consider a base station (BS) that communicates with countless of wireless sensor nodes by means of a radio channel. Data transmission and reception process are the major operations that consume power in WSN. Elimination of redundant data is important issue in WSN, because multiple nodes may sense the same overlapped area. This action will reduce the overall power consumption and use the bandwidth usage.Routing protocols in WSNs can be divided according to network structure into 3 categories: location based, data centric, and hierarchical protocols. 1,2 Location-based protocol: location information for all nodes is a major cornerstone during data communication. Energy consumption during data transmission depends on the target position distance. Data are sent not only to the target area but also to whole sensors network, which is known as flooding. Residual energy is not considered for each node, so many nodes will run out of energy, which leads at the end to an accumulative data transmission failure. [3][4][5] Data-centric protocol 6 : data transmission from sensor node to the BS through intermediate nodes. The intermediate node may not have interest in the data it receives-it is known as relay node in this case. This process reduces the number of packet sent from source to the sink, which leads to reduce the power consumption.

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A Review on energy management schemes in energy harvesting wireless sensor networks

Cited by 156 publications

References 36 publications

Prolonging the Lifetime of Wireless Sensor Networks: A Review of Current Techniques

Prolonging the Lifetime of Wireless Sensor Networks: A Review of Current Techniques

Threshold Balanced Sampled DEEC Model for Heterogeneous Wireless Sensor Networks

A new algorithm for cluster head selection in LEACH protocol for wireless sensor networks

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