Performance evaluation metrics for ring-oscillator-based temperature sensors on FPGAs: A quality factor

Due to technology advances and complexity of designs, thermal issue is a bottleneck in electronics designs. Various dynamic thermal management techniques have been proposed to address this issue. To effectively apply thermal management techniques, providing an accurate thermal map of chips is highly required. For this goal, a network of temperature sensors ought to be provided. There are various implementations for temperature sensors and network of sensors on Field Programmable Gate Arrays (FPGAs). This work defines and formulates four metrics and criteria, in terms of area, thermal, and power overheads and thermal map accuracy for exploring and evaluating efficiency of different implementations of Ring Oscillator-based Temperature Sensor (ROTS) networks on FPGAs and reports the comparison results for 12 networks with various sensor configurations. According to our metrics and experiments, the sensor that it is composed of NOT gates with open latches and RNS ring counter has lower thermal and power overheads compared to other configurations. Moreover, in this work, a new ROTS is presented that occupies 25% less resources than the most compact temperature sensor. Also, it provides 1.72 times higher sensitivity than the best sensitive ROTS design.

This paper presents a thermal sensing and VLSI thermal management scheme using an array of on-chip all-digital delay-line based temperature sensors. A fully digital self-calibration method that removes the temperature sensors' sensitivities to supply voltage and process variations is proposed. The proposed calibration method assigns a unique correction factor, N C to each sensor, making all the sensors' calibrated outputs to be the same at start-up. The correction factor is updated when supply voltage variations are detected. Only one calibration block is required to calibrate multiple delay-line based temperature sensors sequentially. For each additional sensor, only additional registers for storing N C are required. The proposed self-calibrated temperature sensors are demonstrated on an Altera Cyclone IV FPGA based VLSI thermal management system. Runtime thermal profiles for four cores mapped on the Cyclone IV FPGA chip using a hybrid dynamic thermal management (DTM) method are obtained. The percentage of time that each core spent in a particular temperature range is plotted in a histogram. A comparison of different DTM techniques demonstrates that the proposed hybrid DTM reduces the amount of time that the MPSoC spent at higher temperatures and larger thermal gradients, by 10% and 21%, respectively. In addition, the proposed hybrid DTM offers a 10% improvement in the average processing rate (instructions per second) when compared with the conventional global DFS approach.

Wireless sensor networks (WSNs) are densely deployed for monitoring of environments and physical conditions in an extensive range of applications. Network lifetime and energy consumption are the primary performance evaluation metrics for WSNs. In this paper, an adaptive soft thresholding-based energy efficient sensor network (ASTEEN) protocol is proposed to increase the network lifetime by reducing the number of transmissions of non-critical data. It consequently reduces the consumption of communication energy. The performance of the proposed protocol is investigated with correlated and uncorrelated sensed data, and it is compared with the other related and conventional protocols. Simulation results show that the performance of the proposed ASTEEN routing protocol in terms of network lifetime and energy consumption significantly outperforms those of the other protocols, especially with correlated sensed values.

Automatic image segmentation and quantification are critical steps in medical image analysis. The main challenges in medical image segmentation are due to the imbalance in data distribution and spatial variations of ROI. The ideal segmentation should extract all kinds of segments irrespective of size, shape and position. Commonly used metrics such as accuracy, IOU, Dice similarity coefficient consider all the detected pixels in a similar way. However, the detection of smaller segments is critical in medical analysis since it helps in early treatment of the disease and are also easier to miss. Hence, segmentation evaluation must accord larger weighting to pixels in smaller segments compared to the bigger ones. We propose a novel evaluation metric for segmentation performance, emphasizing smaller segments, by assigning a higher weightage to those pixels. Weighted false positives are also considered in deriving the new metric named, “SSEGEP” (Smatt SEGment Emphasized Performance evaluation metric), (range: 0 (Bad) to 1 (Good)). The proposed approach has been applied to two different publicly available real medical data sets of CT modality consisting of scans of the liver and pancreas of 131 and 107 subjects respectively and the results have been compared with existing evaluation metrics. Statistical significance testing is performed to quantity the relevance of the proposed approach. In comparison to Dice similarity coefficient, SSEGEP resulted in a promising p-value of the order 10-18 for hepatic tumor. The proposed metric is found to perform better for the images having multiple segments for a single label and where the regions of interest are not localized.

Increasing on-chip temperature in SoC designs has reinforced the need for Dynamic Thermal Management (DTM). The conventional DTM techniques adopted in microprocessors based on DVFS are not suitable in the context of SoCs as they tend to have multiple voltage and frequency domains. In this paper we propose a reactive and a predictive DTM technique using bus arbitration. Based on the thermal profile the bus grants and hence the bus transactions are controlled. This regulates the data flow which reduces the activity in the functional units. The results show that the on-chip temperature can be maintained 3–5°C below the chip temperature threshold with a worst case performance penalty of 5% and a fast response time of at most 5 clock cycles. The hardware cost of implementing the proposed scheme is 3619.7μm2 in 45nm technology, which is less than 0.06% of the chip area. Apart from its simplicity, lower cost and effectiveness, the solution is non-intrusive on the design and scalable to many cores.

Fabrication and linearisation of conformable POMANI-Mn3O4 nanocomposite based thermistor for temperature monitoring applications in prosthetic gloves

With increasing popularity of wireless local area network (WLAN) and emerging real-time applications, seamless mobility has become one of the primary concerns. Hence, the choice of a proper handover algorithm is of utmost importance. Various performance evaluation metrics for handover algorithms have been proposed in this regard. We argue that in a multiple access point (AP) scenario, the load on each of the APs, the requested data rate of the mobile terminal, and the soft handover have significant impact on these metrics. In this paper, we present an analytical framework to measure various handover performance evaluation metrics under both load condition and soft handover for a specific data rate request. Our approach is based on finding the circular region centered around an AP within which the requested data rate can be satisfied. We have considered WLAN usage efficiency, handover failure probability, and unnecessary handover probability as evaluation metrics. We have analyzed the impact of load and soft handover on these metrics. The impact of velocity on these metrics has also been analyzed. We also have derived lower bounds on both handover failure probability and unnecessary handover probability by formulating the problem into three circle intersection problem. The circular coverage assumption used in the framework is also validated through simulation.

Food production has the major objective to achieve a high and uniform level of quality for raw materials. Temperature and humidity are the critical parameters to verify in many fields of food industry processes, from assurance of quality during production up to storage and transport to final users. In this regard, we focus in this paper on the design of temperature and humidity sensors for an electronic nose used to detect the rotten food in anticipation phase. Those parameters (temperature and humidity of food) have an important role in the array sensor of our nose.

Wireless sensor network (WSN) plays a significant role in various commercial, industrial and agriculture sector in wide ranges of applications. Routing is necessary to maintain the reliable communication between different nodes, cluster heads, and base station; however, performance of routing mechanism is challenging due to network lifetime, dynamic nodes, higher packet drop, scalability issue, limited adaptability and environmental conditions. This paper presents various routing techniques used in WSN that covers the brief overview of flat routing, hierarchical routing, location-based routing and bio-inspired routing techniques such as Ant Colony Optimization (ACO) and Artificial Bee Colony Optimization (ABC) algorithms. It focuses on the routing mechanism, routing scenario, mobility, scalability, energy consumption, data aggregation, performance evaluation metrics, challenges and constraints of the routing in WSN. This comprehensive survey provides the future direction for the improvement in routing mechanisms in WSN.KeywordsBio-inspired routingClusteringFlat routingHierarchical routingRoutingWireless sensor network

This paper presents the design, fabrication and characterization of quartz tuning fork temperature sensor which is based on new ZY-cut-quartz crystal bulk acoustic wave resonator vibrating in a flexural mode. Design and performance analysis of the quartz tuning fork temperature sensor has been conducted and the thermal sensing characteristics were examined by measuring the resonance frequency shift of this sensor cause by an external temperature. The sensor prototype was successfully fabricated and calibrated from operating from 0°C to 100°C with sensitivity of 70ppm/°C. Experimental results show the sensor has high thermal sensitivity, good stability and well reproducibility. This work represents high precision and low power temperature sensor using the comprehensive thermal characterization of ZY-cut-quartz tuning fork resonator.

Today's microprocessors and Systems-on-Chip are thermally limited. Many, therefore, employ dynamic thermal management (DTM) to maximize performance under a reliability constraint. Accurate thermal monitoring is critical as temperature underestimation can hurt reliability by excessively aging devices and overestimation can hurt performance by unnecessarily throttling computing components. Placing temperature sensors close to potential hotspots can help accuracy, but it is non-trivial as hotspots often form inside digital blocks consisting of densely placed digital cells. Large sensors can disrupt cell placement thereby increasing wire lengths and circuit delays. Furthermore, the sensor needs to operate from the same digital power grid as the circuit, one that can be scaled down to near-threshold regime via dynamic voltage scaling. Absent this ability, a separate power grid and dedicated supply voltage for the sensors further increases area overhead. In this paper, we present a sensor circuit that is compact and deeply voltage-scalable and can be embedded among digital cells with little disruption. Simulation results show that it achieves a comparable accuracy to other compact sensor circuits for DTM.

Design and Simulation of the Comb MWCNT Temperature Sensor for Textronics

Integrated monolithic temperature sensors for acquisition and regulation

In order to optimize the design of quartz tuning fork temperature sensor, finite element method (FEM) is applied to model optimum tuning fork geometry, tine tip and tine surface electrode shape and thickness with a resonance frequency close to 32 kHz and a series resistance value of 40 kΩ as design targets. This type of sensor designed with a new ZYtw-cut is proved that working at flexural vibration mode was better than at the others modes. Precise temperature versus frequency analyses of resonators have been carried out and Least Mean Squared (LMS) curve fit algorithm is applied to compute the temperature values quantitatively. The results obtained from the experimental investigations show the method which synthesizes many factors to design quartz tuning-fork temperature sensor. Using ZYtw-cut can bring the temperature coefficient up to 70ppm/(degree C) and make power consumption lower. The temperature sensor based on quartz tuning-fork thermo-sensitive resonator is mounted in a standard holder for use from −30 degree C to 160 degree C with an accuracy of 0.05 degree C and a high resolution of 0.001 degree C. It is proved that it is possible to construct a miniature quartz tuning-fork temperature sensor with high sensitivity and small non-linearity.

Non-invasive core body temperature (CBT) measurements using temperature and heat-flux have become popular in health, sports, work safety, and general well-being applications. This research aimed to evaluate two commonly used sensor designs: those that combine heat flux and temperature sensors, and those with four temperature sensors. We used analytical methods, particularly uncertainty analysis calculus and Monte Carlo simulations, to analyse measurement accuracy, which depends on the accuracy of the temperature and flux sensors, mechanical construction parameters (such as heat transfer coefficient), ambient air temperature, and CBT values. The results show the relationship between the accuracy of each measurement method variant and various sensor parameters, indicating their suitability for different scenarios. All measurement variants showed unstable behaviour around the point where ambient temperature equals CBT. The ratio of the heat transfer coefficients of the dual-heat flux (DHF) sensor's channels impacts the CBT estimation uncertainty. An analysis of the individual components of uncertainty in CBT estimates reveals that the accuracy of temperature sensors significantly impacts the overall uncertainty of the CBT measurement. We also calculated the theoretical limits of measurement uncertainty, which varied depending on the method variant and could be as low as 0.05 °C.