The IoT Energy Challenge: A Software Perspective

Georgiou, Kyriakos; Xavier‐de‐Souza, Samuel; Eder, Kerstin

doi:10.1109/les.2017.2741419

Cited by 76 publications

(35 citation statements)

References 16 publications

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“…Instead, it shows that the race toward single-core performance under the influence of Amdahl's Law has perhaps obfuscated a more efficient way to match processor and memory frequencies for parallel applications. That is undoubtedly true if the focus is energy efficiency; as such models could be applied, for example, to devise better Dynamic Voltage and Frequency Scaling (DVFS) schemes for the Internet of Things [GXdSE17], data centers [PPZ + 16], and high-performance computing [SFG + 18].…”

Section: Discussionmentioning

confidence: 99%

When Parallel Speedups Hit the Memory Wall

Furtunato¹,

Georgiou

Eder

et al. 2020

IEEE Access

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After Amdahl's trailblazing work, many other authors proposed analytical speedup models but none have considered the limiting effect of the memory wall. These models exploited aspects such as problem-size variation, memory size, communication overhead, and synchronization overhead, but data-access delays are assumed to be constant. Nevertheless, such delays can vary, for example, according to the number of cores used and the ratio between processor and memory frequencies. Given the large number of possible configurations of operating frequency and number of cores that current architectures can offer, suitable speedup models to describe such variations among these configurations are quite desirable for off-line or on-line scheduling decisions. This work proposes new parallel speedup models that account for variations of the average data-access delay to describe the limiting effect of the memory wall on parallel speedups. Analytical results indicate that the proposed modeling can capture the desired behavior while experimental hardware results validate the former. Additionally, we show that when accounting for parameters that reflect the intrinsic characteristics of the applications, such as degree of parallelism and susceptibility to the memory wall, our proposal has significant advantages over machine-learningbased modeling. Moreover, besides being black-box modeling, our experiments show that conventional machine-learning modeling needs about one order of magnitude more measurements to reach the same level of accuracy achieved in our modeling.

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Section: Discussionmentioning

confidence: 99%

When Parallel Speedups Hit the Memory Wall

Furtunato¹,

Georgiou

Eder

et al. 2020

IEEE Access

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“…However, carrying power cord and looking for power supply cause inconvenience for people. The contradiction between battery endurance of IoT devices and the power supply is increasingly prominent [5][6][7][8]. Therefore, wireless power transfer (WPT) draws much attention to provide mobile power supply anywhere and anytime for IoT devices.…”

Section: Introductionmentioning

confidence: 99%

Wireless Energy Transmission Channel Modeling in Resonant Beam Charging for IoT Devices

Wang

Zhang

Lin

et al. 2019

IEEE Internet Things J.

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Power supply for Internet of Things (IoT) devices is one of the bottlenecks in IoT development. To provide perpetual power supply to IoT devices, resonant beam charging (RBC) is a promising safe, long-range and high-power wireless power transfer solution. How long distance can RBC reach and how much power can RBC transfer? In this paper, we analyze the RBC's consistent and steady operational conditions, which determine the maximum power transmission distance. Moreover, we study the power transmission efficiency within the operational distance, which determines the deliverable power through the RBC energy transmission channel. Based on this energy transmission channel modeling, we numerically evaluate its impacts on the RBC system performance in terms of the transmission distance, the transmission efficiency, and the output electrical power. The analysis leads to the guidelines for the RBC system design and implementation, which can deliver multi-Watt power over multi-meter distance wirelessly for IoT devices.

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“…W IRELESS power transfer (WPT) becomes an important and urgent need for mobile devices, such as smartphones [1] and Internet of things (IoT) devices [2,3]. Recently, Qihui Wu and Guoru Ding have made the primary contributions to cognitive Internet of things (CIoT) and its applications, which provide valuable references for this work [4,5].…”

Section: Introductionmentioning

confidence: 99%

TDMA in Adaptive Resonant Beam Charging for IoT Devices

Xiong

Liu

Zhang

et al. 2019

IEEE Internet Things J.

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Resonant beam charging (RBC) can realize wireless power transfer (WPT) from a transmitter to multiple Internet of things (IoT) devices via resonant beams. The adaptive RBC (ARBC) can effectively improve its energy utilization. In order to support multi-user WPT in the ARBC system, we propose the time-division multiple access (TDMA) method and design the TDMA-based WPT scheduling algorithm. Our TDMA WPT method has the features of concurrently charging, continuous charging current, individual user power control, constant driving power and flexible driving power control. The simulation shows that the TDMA scheduling algorithm has high efficiency, as the total charging time is roughly half (46.9% when charging 50 receivers) of that of the alternative scheduling algorithm. Furthermore, the TDMA for WPT inspires the ideas of enhancing the ARBC system, such as flow control and quality of service (QoS).

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The IoT Energy Challenge: A Software Perspective

Cited by 76 publications

References 16 publications

When Parallel Speedups Hit the Memory Wall

When Parallel Speedups Hit the Memory Wall

Wireless Energy Transmission Channel Modeling in Resonant Beam Charging for IoT Devices

TDMA in Adaptive Resonant Beam Charging for IoT Devices

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