Towards Immortal Wireless Sensor Networks by Optimal Energy Beamforming and Data Routing

Du, Rong; Özçelikkale, Ayça; Fischione, Carlo; Xiao, Ming

doi:10.1109/twc.2018.2842192

Cited by 18 publications

(13 citation statements)

References 30 publications

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“…In Du et al, 30 the nodes are charged with wireless energy transfer (WET) and an efficient data routing is designed to realize immortal WSNs. However, the beam is not optimized in the literatures, 29,30 which results in higher communication interference in the network and weakens the communication quality. In wireless power transmission (WPT), beam collection efficiency is considered to improve the performance of the power beam.…”

Section: Related Workmentioning

confidence: 99%

Energy-efficient collaborative transmission algorithm based on potential game theory for beamforming

Zhang

Feng

2019

International Journal of Distributed Sensor Networks

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A group of collaborative nodes can efficiently complete spatial long-distance transmission tasks using beamforming technology. However, a high sidelobe level interferes with communication quality, and uneven energy consumption of nodes affects network lifetime. This paper proposes an energy-efficient collaborative transmission algorithm based on potential game theory for beamforming. First, the minimum number of cooperative nodes is determined in accordance with the energy consumption and spacing limitation condition. A group of nodes satisfying the node spacing condition is selected as cooperative nodes based on the ring array to minimize communication interference among nodes. Second, a potential game model is proposed as a joint method for optimizing the collaborative parameters of the cooperative nodes and their energy consumption balancing features. Finally, the game process is continuously executed until the Nash equilibrium is reached. According to simulation results, the sidelobe level caused by the cooperative nodes is reduced and the transmission conflicts are lessened. Thus, the quality of communication links in between nodes in the network is improved. Energy efficiency is also promoted because a balancing of energy consumption is involved in the proposed potential game model, and network lifetime is effectively prolonged accordingly.

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Section: Related Workmentioning

confidence: 99%

Energy-efficient collaborative transmission algorithm based on potential game theory for beamforming

Zhang

Feng

2019

International Journal of Distributed Sensor Networks

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“…Even the energy beamforming is optimized; if the nodes consume energy inefficiently, the power would be wasted and the network lifecycle performance will be degraded. To maximize the network lifecycle and achieve the immortality of the WSNs, the authors propose to reduce the energy consumption of sensors by optimizing the data routing among the sensors and to improve the WPT efficiency by optimizing the energy beamforming of the chargers [31].…”

Section: Wireless Power Transfermentioning

confidence: 99%

Joint Balanced Routing and Energy Harvesting Strategy for Maximizing Network Lifetime in WSNs

Tala't

Chiu

et al. 2019

Energies

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Nowadays, wireless sensor networks (WSNs) are becoming increasingly popular due to the wide variety of applications. The network can be utilized to collect and transmit numerous types of messages to a data sink in a many-to-one fashion. The WSNs usually contain sensors with low communication ability and limited battery power, and the battery replacement is difficult in WSNs for large amount embedded nodes, which indicates a balanced routing strategy is essential to be developed for an extensive operation lifecycle. To realize the goal, the research challenges require not only to minimize the energy consumption in each node but also to balance the whole WSNs traffic load. In this article, a Shortest Path Tree with Energy Balance Routing strategy (SPT-EBR) based on a forward awareness factor is proposed. In SPT-EBR, Two methods are presented including the power consumption and the energy harvesting schemes to select the forwarding node according to the awareness factors of link weight. First, the packet forwarding rate factor is considered in the power consumption scheme to update the link weight for the sensors with higher power consumption and mitigate the traffic load of hotspot nodes to achieve the energy balance network. With the assistance of the power consumption scheme, hotspot nodes can be transferred from the irregular location to the same intra-layer from the sink. Based on this feature, the energy harvesting scheme combines both the packet forwarding rate and the power charging rate factors together to update the link weight with a new battery charging rate factor for hotspot nodes. Finally, simulation results validate that both power consumption and energy harvesting schemes in SPT-EBR achieve better energy balance performance and save more charging power than the conventional shortest path algorithm and thus improve the overall network lifecycle.

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“…Zhe Wang, Lingjie Duan, Rui Zhang [27] proposes adaptive directional wireless power transfer (AD-WPT) method using power beacons (PBS) to perform energy beamforming and power can be supplied using electromagnetic waves to improve NL. Rong Du, Ayça Özçelikkale [28] propose energy beam forming scheme whose performance is better than other beam forming schemes even for optimized routing and maximization of minimum sampling rate is done with low energy consumption of node. The data cannot be relayed by sensors when they have critical battery levels and collaborative beamforming is used to group closely situated sensor motes to ease the stream of traffic capacity.…”

Section: Beam Formingmentioning

confidence: 99%

An Ephemeral Analysis on Network Lifetime Improvement Techniques for Wireless Sensor Networks

Rekha¹,

Siddaraju²

2019

IJITEE

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Wireless Sensor Network is used in an extensive assortment of applications like enemy vehicle motion detection, surveillance of the environment. For the network to be operational and for longer maintenance of WSN low-cost sensor nodes are the need of the hour. There are many constraints in the WSN network like deployment constraints, energy constraints and hardware constraints which must be handled in a careful manner in order to improve network lifetime. To improve the network lifetime there are techniques which come under beam forming, connectivity factor, coverage and harvesting factors. In this paper, the survey is done on the innumerable delineations of network lifetime and the methods which can help in improving the network lifetime. Battery Level management during the routing process as well as approaches to identify and reduce the number of dead nodes will also improve lifetime.

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Towards Immortal Wireless Sensor Networks by Optimal Energy Beamforming and Data Routing

Abstract: This is the accepted version of a paper published in IEEE Transactions on Wireless Communications. This paper has been peer-reviewed but does not include the final publisher proof-corrections or journal pagination.

Cited by 18 publications

References 30 publications

Energy-efficient collaborative transmission algorithm based on potential game theory for beamforming

Energy-efficient collaborative transmission algorithm based on potential game theory for beamforming

Joint Balanced Routing and Energy Harvesting Strategy for Maximizing Network Lifetime in WSNs

An Ephemeral Analysis on Network Lifetime Improvement Techniques for Wireless Sensor Networks

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