Circuit and System Design Guidelines for Ultra-low Power Sensor Nodes

Lee, Yoonmyung; Yoon, David; Kim, Yejoong; Blaauw, David; Sylvester, Dennis

doi:10.2197/ipsjtsldm.6.17

Cited by 8 publications

(2 citation statements)

References 31 publications

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“…Sensors are usually positioned randomly in a large zone; if one of the sensors depletes its energy, replacing the power supply becomes difficult, especially in hostile inaccessible environments, and energy holes emerge [10]. Furthermore, the power of a sensor node decreases during the transmission of data [11,12].…”

Section: Introductionmentioning

confidence: 99%

Variants of the Low-Energy Adaptive Clustering Hierarchy Protocol: Survey, Issues and Challenges

et al. 2018

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Abstract:A wireless sensor network (WSN) is a modern technology in radio communication. A WSN comprises a number of sensors that are randomly spread in a specific area for sensing and monitoring physical attributes that are difficult to monitor by humans, such as temperature, humidity, and pressure. Many problems, including data routing, power consumption, clustering, and selecting cluster heads (CHs), may occur due to the nature of WSNs. Various protocols have been conducted to resolve these issues. One of the important hierarchical protocols that are used to reduce power consumption in WSNs is low-energy adaptive clustering hierarchy (LEACH). This paper presents a comprehensive study of clustering protocols for WSNs that are relevant to LEACH. This paper is the first to emphasis on cluster formation and CHs selection methods and their strengths and weaknesses. A new taxonomy is presented to discuss LEACH variants on the basis of different classes, and the current survey is compared with other existing surveys. A complete comparison of the location, energy, complexity, reliability, multi-hop path, and load balancing characteristics of LEACH variants is conducted. Future research guidelines for CHs selection and cluster formation in WSNs are also discussed.

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Section: Introductionmentioning

confidence: 99%

Variants of the Low-Energy Adaptive Clustering Hierarchy Protocol: Survey, Issues and Challenges

et al. 2018

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“…Fig.2shows the direction of cell leakage and bit line leakage[20].The 1T1C DRAM dissipates leakage current (mostly I sub ) form access transistor and dielectric current (I d ) from the storage capacitor. This is shown in Fig.3[21].Sub-threshold leakage current is the primary source of power dissipation in the idle SRAM and DRAM cells, it is characterized by the following expressions[22]:…”

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confidence: 99%

Power and thermal management in SRAM and DRAM using adaptive body biasing technique

HamaAli

Sulaiman

İbrahim

2019

IEICE Electron. Express

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Low power and thermal design techniques are more advantageous for high-performance memory cells. Body bias is an adaptive technique used for power and thermal management in memory systems. It offers an efficient solution for the memory's power and thermal problems. In this study, a thermal management controller is presented as a complete hardware tuning loop. The controller is applied on both Static Random Access Memory (SRAM) and Dynamic Random Access Memory (DRAM) units that actively monitors and controls the temperature via the power dissipation control in both memory types. The proposed combined circuits within the tuning loop are able to reduce the high power and temperatures, and dragging it around safe limits to avoid chip hardware damages. Results confirm that, the power dissipation of 6T SRAM cell is reduced by 9.77%, while the power of 1T1C DRAM cell is reduced by 8.50%. Thermal reduction was in the range of (5°C-10°C) per each body bias step voltage.

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