Noise-Aware DVFS for Efficient Transitions on Battery-Powered IoT Devices

Zhuo, Cheng; Luo, Shaoheng; Gan, Hu; Hu, Jiang; Shi, Zhiguo

doi:10.1109/tcad.2019.2917844

Cited by 71 publications

(15 citation statements)

References 33 publications

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“…This article divides the studies into two categories according to the targets of defending security attacks in data collection. One is the security strategies for specific attack behaviors [36,37,41,43]. The other is the trustbased security data collection strategies [5,6,11,14,30,34,36].…”

Section: Related Workmentioning

confidence: 99%

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An active and verifiable trust evaluation approach for edge computing

Wang

Zhang

et al. 2020

J Cloud Comp

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Billions of Internet of Thing (IoT) devices are deployed in edge network. They are used to monitor specific event, process and to collect huge data to control center with smart decision based on the collected data. However, some malicious IoT devices may interrupt and interfere with normal nodes in data collection, causing damage to edge network. Due to the open character of the edge network, how to identify the credibility of these nodes, thereby identifying malicious IoT devices, and ensure reliable data collection in the edge network is a great challenge. In this paper, an Active and Verifiable Trust Evaluation (AVTE) approach is proposed to identify the credibility of IoT devices, so to ensure reliable data collection for Edge Computing with low cost. The main innovations of the AVTE approach compared with the existing work are as follows: (1) In AVTE approach, the trust of the device is obtained by an actively initiated trusted detection routing method. It is fast, accurate and targeted. (2) The acquisition of trust in the AVTE approach is based on a verifiable method and it ensures that the trust degree has higher reliability. (3) The trust acquisition method proposed in this paper is low-cost. An encoding returned verification method is applied to obtain verification messages at a very low cost. This paper proposes an encoding returned verification method, which can obtain verification messages at a very low cost. In addition, the strategy of this paper adopts initiation and verification of adaptive active trust detection according to the different energy consumption of IoT devices, so as to reliably obtain the trust of device under the premise of ensuring network lifetime. Theoretical analysis shows that AVTE approach can improve the data collection rate by 0.5 ~ 23.16% while ensuring long network lifetime compared with the existing scheme.

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Section: Related Workmentioning

confidence: 99%

“…However, an important issue is the security of data collection [36][37][38][39]. Because of the network openness, many IoT devices can be added to the network autonomously [40,41]. Thus, the malicious IoT devices will maliciously prevent the normal data collection.…”

Section: Introductionmentioning

confidence: 99%

An active and verifiable trust evaluation approach for edge computing

Wang

Zhang

et al. 2020

J Cloud Comp

View full text Add to dashboard Cite

show abstract

“…With the development of the Internet of Things (IoT) [15], more and more sensor devices are deployed in various applications, such as vehicles network [18,42], traffic monitoring, healthcare [43], security monitoring [44][45][46], and industrial networks [47][48][49]). Numerous sensor devices are used to sense and collect data, providing rich data for various applications [50].…”

Section: Related Workmentioning

confidence: 99%

Energy-aware MAC protocol for data differentiated services in sensor-cloud computing

et al. 2020

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The energy-aware MAC protocol is the basic communication protocol for device-to-device communication in sensor-cloud computing and facilitates data sensing, computing, and sharing for applications. Transmitting highpriority data to control centers quickly to manage emergencies is essential for sensor-cloud applications. In this paper, a Dynamic Wait time-based MAC (DWT-MAC) protocol is proposed for data differentiated services of a sensor-cloud system (SCS). The DWT-MAC protocol is novel in that it changes the receiver wait time, which has been fixed in previous MAC protocols, and it reduces the delay in data transmission by dynamically adjusting the wait time. In the DWT-MAC protocol, the wait time changes according to the number of senders, which can ensure that it always approaches the optimal value. A dynamic time adjustment algorithm, which causes the wait time to always trail the optimal value, is proposed to reduce delays. While the DWT-MAC protocol cannot ensure wait times of the optimal value, it can ensure that it quickly comes close to the optimal value, which is suitable for dynamically changing networks. Extensive experiments show that the DWT-MAC protocol reduces the average delay in the transmission of data of the highest priority by 49.3%.

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“…Software define networks allow IoT devices to perform system updates or upgrades, thus invoking new functions. Due to the number of IoT devices is large [41], [42], [52]- [53], redeployment is expensive, some devices are difficult to update, and other production activities need to be stopped when updating, which is costly. In the software define network, only by updating software codes, IoT devices can gain new life [54], and the application range of sensor nodes can be expanded, thus having good development prospects [41], [42].…”

Section: Introductionmentioning

confidence: 99%