Energy-Efficient Deployment in Static and Mobile Heterogeneous Multi-Hop Wireless Sensor Networks

Karimi-Bidhendi, Saeed; Guo, Jun; Jafarkhani, Hamid

doi:10.1109/twc.2021.3135385

Cited by 25 publications

(10 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several approaches do not rely on a tree structure to disseminate data in wireless ad hoc networks but still attempt to minimize total energy consumption by, for example, proposing an energy-efficient sensor placement algorithm [20] or by letting a controller decide which nodes should transmit the data [21,22]. Other approaches involve the formulation of a linear programming problem that finds the most energy-efficient unicast path to reach all nodes [23], the proposal of a data-forwarding scheme that utilizes nodes' contextual information [24], or the use of a k-coverage algorithm to distribute data energy-efficiently in wireless underwater sensor networks [25].…”

Section: Related Workmentioning

confidence: 99%

Energy-Efficient Decentralized Broadcasting in Wireless Multi-Hop Networks

Sterz,

Klose,

Sommer

et al. 2023

Sensors

View full text Add to dashboard Cite

Several areas of wireless networking, such as wireless sensor networks or the Internet of Things, require application data to be distributed to multiple receivers in an area beyond the transmission range of a single node. This can be achieved by using the wireless medium’s broadcast property when retransmitting data. Due to the energy constraints of typical wireless devices, a broadcasting scheme that consumes as little energy as possible is highly desirable. In this article, we present a novel multi-hop data dissemination protocol called BTP. It uses a game-theoretical model to construct a spanning tree in a decentralized manner to minimize the total energy consumption of a network by minimizing the transmission power of each node. Although BTP is based on a game-theoretical model, it neither requires information exchange between distant nodes nor time synchronization during its operation, and it inhibits graph cycles effectively. The protocol is evaluated in Matlab and NS-3 simulations and through real-world implementation on a testbed of 75 Raspberry Pis. The evaluation conducted shows that our proposed protocol can achieve a total energy reduction of up to 90% compared to a simple broadcast protocol in real-world experiments.

show abstract

Section: Related Workmentioning

confidence: 99%

Energy-Efficient Decentralized Broadcasting in Wireless Multi-Hop Networks

Sterz,

Klose,

Sommer

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…According to statistics, the demand for low-power IoT devices is expected to grow exponentially to 2.97 billion by the end of 2022 [27,29,36]. The corresponding technologies have also come into being with the actual demand for IoT equipments, such as the wireless sensor network [31], radio frequency identiication [53], and interoperability between devices [52]. Most IoT facilities, particularly the wearable and mobile-edge IoT devices, generally utilize the battery as the primary power source.…”

Section: Introductionmentioning

confidence: 99%

Experimental Demonstration of STT-MRAM-based Nonvolatile Instantly On/Off System for IoT Applications: Case Studies

Wang

Zhou

et al. 2023

ACM Trans. Embed. Comput. Syst.

View full text Add to dashboard Cite

Energy consumption has been a big challenge for electronic devices, particularly, for the battery-powered Internet of Things (IoT) equipment. To address such a challenge, on one hand, low-power electronic design methodologies and novel power management techniques have been proposed, such as nonvolatile memories and instantly on/off systems; on the other hand, the energy harvesting technology by collecting signals from human activity or the environment has attracted widespread attention in the IoT area. However, the system with self-powered energy harvesting may suffer frequent energy failures or fluctuating energy conditions, which degrade system reliability and user experience. Therefore, how to make the system under unreliable power inputs operate correctly and efficiently is one of the most critical issues for the energy harvesting technology. In this paper, we built an instantly on/off system based on nonvolatile STT-MRAM for IoT applications, which can instantly power on/off under different conditions of the harvested energy. The system powers on and operates normally when the harvested energy is enough (over the preset threshold); otherwise, the system powers off and stores the operational data back to the nonvolatile STT-MRAM. We described implementations of the hardware/software co-designed architecture (with image acquisition as an example) based on the commercialized 32MB STT-MRAM, and experimentally demonstrated the system functionality and efficiency under five typical energy harvesting scenarios, including radio-frequency (RF), thermal, solar, piezoelectric and WIFI. Our experimental results show that the power consumption and data restore time were reduced by 15.1 \(\% \) and 714 times respectively in comparison with the DRAM-based counterpart.

show abstract

“…Consequently, by incorporating a static leader with adequate parameters, the sensor nodes in the network can be brought into alignment with those parameters, thus achieving convergence. Sensor nodes in a network can also be heterogeneous meaning leaders or any other sensor nodes in the network have different characteristics [ 24 ].…”

Section: Introductionmentioning

confidence: 99%

Nearest Neighbour Node Deployment Algorithm for Mobile Sensor Networks

Ghahroudi,

Shahrabi,

Boutaleb

2023

Sensors

View full text Add to dashboard Cite

Many animal aggregations display remarkable collective coordinated movements on a large scale, which emerge as a result of distributed local decision-making by individuals. The recent advances in modelling the collective motion of animals through the utilisation of Nearest Neighbour rules, without the need for centralised coordination, resulted in the development of self-deployment algorithms in Mobile Sensor Networks (MSNs) to achieve various types of coverage essential for different applications. However, the energy consumption associated with sensor movement to achieve the desired coverage remains a significant concern for the majority of algorithms reported in the literature. In this paper, the Nearest Neighbour Node Deployment (NNND) algorithm is proposed to efficiently provide blanket coverage across a given area while minimising energy consumption and enhancing fault tolerance. In contrast to other algorithms that sequentially move sensors, NNND leverages the power of parallelism by employing multiple streams of sensor motions, each directed towards a distinct section of the area. The cohesion of each stream is maintained by adaptively choosing a leader for each stream while collision avoidance is also ensured. These properties contribute to minimising the travel distance within each stream, resulting in decreased energy consumption. Additionally, the utilisation of multiple leaders in NNND eliminates the presence of a single point of failure, hence enhancing the fault tolerance of the area coverage. The results of our extensive simulation study demonstrate that NNND not only achieves lower energy consumption but also a higher percentage of k-coverage.

show abstract

Energy-Efficient Deployment in Static and Mobile Heterogeneous Multi-Hop Wireless Sensor Networks

Cited by 25 publications

References 44 publications

Energy-Efficient Decentralized Broadcasting in Wireless Multi-Hop Networks

Energy-Efficient Decentralized Broadcasting in Wireless Multi-Hop Networks

Experimental Demonstration of STT-MRAM-based Nonvolatile Instantly On/Off System for IoT Applications: Case Studies

Nearest Neighbour Node Deployment Algorithm for Mobile Sensor Networks

Contact Info

Product

Resources

About