Buffer Delay Research Articles

A 8.1-nW, 4.22-kHz, −40–85 °C relaxation oscillator with subthreshold leakage current compensation and forward body bias buffer for low power IoT applications

This paper presents a relaxation oscillator (RxO) utilizing subthreshold transistor leakage current compensation (SLC) technology to expand the operating range from 70 °C to 85 °C at high temperatures. The compensated RxO outperforms the uncompensated counterpart by 25 times for temperature coefficient (TC). Additionally, forward body bias (FBB) technology optimizes the digital buffer delay with temperature drift at low supply voltage, extending the oscillator’s low-temperature range from −20 °C to −40 °C. Fabricated in a 65 nm CMOS process, the oscillator consumes a mere 8.1 nW at a 0.4 V supply voltage. At room temperature, it operates at 4.22 kHz with an energy efficiency of 1.92 nW/kHz. The oscillator demonstrates a temperature coefficient (TC) of 114.01 ppm/°C within the range of −40 °C to 85 °C, rendering it a prospective choice for low-power Internet of Things (IoT) applications.

Periodic Transmissions in Random Access Networks: Stressed Period and Delay

Most IoT systems use random access protocols for wireless communication. This paper considers an IoT node that generates periodic traffic to be delivered to a destination over a random access network; each packet of the node is expected to be delivered before its deadline. We say that the node is in a stressed period if, within a time interval, its successive packets miss their deadlines. In many systems, the worst-case performance is significantly affected by stressed periods. Characterizing the stochastic properties of stressed periods is thus of fundamental importance. In this paper, we use a fluid flow model to approximate the evolution of the buffer occupancy (i.e., backlog) at the transmitting node. We derive a relationship between buffer occupancy and delay and formally define a stressed period via a time interval in which the buffer occupancy exceeds a certain threshold. With this model, we analyze the dynamics of the buffer occupancy evolution and obtain the probability distributions of stressed period duration and delay. Real network experiments show that our model can well approximate the distributions of stressed period duration and delay in practical WiFi networks. The theoretical results of this paper can be used to analyze the robustness and worst-case performance of IoT monitoring and control systems built on random access networks.

A Low-Cost Measurement Methodology for LiDAR Receiver Integrated Circuits

This paper presents a test methodology to facilitate the measuring processes of LiDAR receiver ICs by avoiding the inherent walk error issue. In a typical LiDAR system, a costly laser diode driver emits narrow light pulses with fast rising edges, and the reflected pulses from targets enter an optical detector followed by an analog front-end (AFE) circuit. Then, the received signals pass through the cascaded amplifiers down to the time-to-digital converter (TDC) that can estimate the detection range. However, this relatively long signal journey leads to the significant decline of rising-edge slopes and the output pulse spreading, thus producing inherent walk errors in LiDAR receiver ICs. Compensation methods requiring complex algorithms and extra chip area have frequently been exploited to lessen the walk errors. In this paper, however, a simpler and lower-cost methodology is proposed to test LiDAR receiver ICs by employing a high-speed buffer and variable delay cells right before the TDC. With these circuits, both START and STOP pulses show very similar pulse shapes, thus effectively avoiding the walk error issue. Additionally, the time interval between two pulses is easily determined by varying the number of the delay cells. Test chips of the proposed receiver IC implemented in a 180-nm CMOS process successfully demonstrate easier and more accurate measurement results.

Optimized Visual Internet of Things for Video Streaming Enhancement in 5G Sensor Network Devices.

The global expansion of the Visual Internet of Things (VIoT)'s deployment with multiple devices and sensor interconnections has been widespread. Frame collusion and buffering delays are the primary artifacts in the broad area of VIoT networking applications due to significant packet loss and network congestion. Numerous studies have been carried out on the impact of packet loss on Quality of Experience (QoE) for a wide range of applications. In this paper, a lossy video transmission framework for the VIoT considering the KNN classifier merged with the H.265 protocols. The performance of the proposed framework was assessed while considering the congestion of encrypted static images transmitted to the wireless sensor networks. The performance analysis of the proposed KNN-H.265 protocol is compared with the existing traditional H.265 and H.264 protocols. The analysis suggests that the traditional H.264 and H.265 protocols cause video conversation packet drops. The performance of the proposed protocol is estimated with the parameters of frame number, delay, throughput, packet loss ratio, and Peak Signal to Noise Ratio (PSNR) on MATLAB 2018a simulation software. The proposed model gives 4% and 6% better PSNR values than the existing two methods and better throughput.

A 5.4 ps resolution TDC design with anti-PVT-variation mechanism using 90-nm CMOS process

ABSTRACT The resolution of time-to-digital converters (TDC) is one parameter that will define its efficiency. This research demonstrates a 5.4 ps TDC with anti-PVT-variation implemented in 90-nm CMOS technology. The proposed converter uses a two-step architecture. The first stage is a Buffer Delay Line (BDL) to acquire a wide dynamic range characteristic. The second stage that will provide a higher resolution is Vernier delay line which receives the start and stop signals from the edge detector. A PVT (process, voltage, temperature) corner detector is equipped in the proposed TDC to resist the PVT variation. The proposed TDC’s post-layout simulation results achieve a delay variation of 2 ps and a resolution of 5.4 ps, and an acceptable dynamic range of 890 ps. The INL and DNL attained a value of 0.8 and −1 LSB from the simulations. The proposed TDC attains the best FOM based on post-layout simulations with a value of 0.177, which makes it superior to all prior designs.

A Single-TSV and Single-DCDL Approach for Skew Compensation of Multi-Dies Clock Synchronization in 3-D-ICs

Existing methods used for the clock distribution of multiple dies employ a balanced tree structure to minimize the impact of the within-die process and loading variations. No topology for die-to-die clock skew compensation of more than two dies has been presented yet. This article presents a novel die-to-die clock skew compensation topology to address these limitations. Unlike existing designs, the proposed topology does not need a phase detector (hence, no dead zone); it only requires one through-silicon via (TSV) to connect a pair of dies and one digitally controlled delay line (DCDL) in each die; thus, there is no skew from extra TSVs and DCDLs. Accordingly, the system has a small chip area and low lock time. The postsynthesis of this work was accomplished in a 65-nm CMOS process. The performance of our design was evaluated theoretically and practically in terms of mismatch/finite resolution of delay lines, buffer mismatch, and TSV delay. Under identical conditions, the residual skew of the proposed design was as low as 13 ps at 1 GHz. This study is the first to obtain the solution for die-to-die clock synchronization of multiple dies (more than two dies) in a three-dimensional (3-D) integrated circuit, while other systems can only support two dies.

Delay-Oriented Resource Allocation for OFDMA Real-Time Mobile Broadband Services

Radio Resource Management (RRM) is the key component that influences the Quality of Service (QoS) in emerging mobile systems. The harsh requirements of recent multimedia applications press on the behavior of the resource allocation model at the Medium Access Control (MAC). This, under certain conditions, deteriorates awareness of the scheduler in satisfying QoS characteristics for the diverse attending traffic flows. The trade-off between QoS metrics may be a viable remedy to this problem. However, if the tradeoff is not meticulously addressed, it definitely increases the delay beyond the allowed threshold and plummets the data rates of the involved flows. In this article, a Delay-oriented Resource Allocation (DoRA) scheduler is proposed for the downlink channel to transmit multimedia applications. The main aim of DoRA is to schedule flows of different volumes with guaranteed low delay values and acceptable throughput under harsh network conditions (i.e., high traffic load and mobility). An efficient priority weight function is formulated based on a delay-oriented rule considering the buffer delay of the diverse flows. Eventually, a greedy algorithm assigns channel resources to the prioritized flows with high weights. DoRA is compared to reference schedulers using system-level simulation over two scenarios. The performance results indicate that DoRA maintains a low end-to-end delay with robust throughput and efficient spectrum efficiency for different flow volumes over congested network states.

Improved random early detection congestion control algorithm for internet routers

In the internet, router plays a strategic role in the transmission of data packets. Active queue management (AQM) aimed at managing congestion by keeping a reduced average buffer occupancy and hence a minimal delay. The novel random early detection (RED) algorithm suffers from large average buffer occupancy and delay shortcomings. This problem is due in part to the existence of a distinctive linear packet drop function it deploys. In this paper, we present a new version of RED, called improved RED (IMRED). An important strategy of IM-RED is to deploy two dropping functions: i) nonlinear (i.e. quadratic) to deal with both light-and moderatenetwork traffic load conditions, and ii) linear to deal with heavy traffic load condition. Simulation experiments conducted using open-source ns-3 software to evaluate and compare the functionality of the proposed IM-RED with other two previous AQM algorithms confirmed that IM-RED reduces the average buffer occupancy and obtained an improved delay performance especially at heavy network traffic load scenario. Very fortunately, since RED algorithm is known to appear as a built-in model in ns-3 and even Linux kernel, its implementation can therefore be leveraged to obtain IMRED while only adjusting the packet dropping probability profile and holding on to its other attributes.

A Low-Delay Hybrid Half/Full-Duplex Link Selection Scheme for Cooperative Relaying Networks

In this paper, we propose a hybrid half-duplex (HD)/full-duplex (FD) link selection scheme for cooperative buffer-aided (BA) relaying networks with small buffers. FD BA relaying offers high spectral efficiency but it does not change the buffer states, while HD relaying offers the ability to change the buffer states, which can be exploited to minimize the outage probability and the average delay by controlling the queue length of the relays. Unlike the existing hybrid BA relaying schemes and opportunistic relying schemes, the proposed scheme considers the average buffering delay and uses probabilistic relay selection (RS) instead of using a fixed RS policy. It probabilistically prioritizes the selection of one of the FD and HD modes over the other. Markov chain (MC) theory is used to model the considered system and derive the throughput, average delay and outage probability as functions of the prioritizing probabilities. Based on the buffer and average channel states, the prioritizing probabilities are determined such that the overall average delay is minimized using the accelerated proximal gradient method. As compared to the existing HD, opportunistic, and hybrid BA relaying schemes, simulation results show that the proposed scheme offers higher throughput and lower average delay.

Video caching and scheduling with edge cooperation

In this paper, we explore a distributed collaborative caching and computing model to support the distribution of adaptive bit rate video streaming. The aim is to reduce the average initial buffer delay and improve the quality of user experience. Considering the difference between global and local video popularities and the time-varying characteristics of video popularity, a two-stage caching scheme is proposed to push popular videos closer to users and minimize the average initial buffer delay. Based on both long-term content popularity and short-term content popularity, the proposed caching solution is decouple into the proactive cache stage and the cache update stage. In the proactive cache stage, we develop a proactive cache placement algorithm that can be executed in an off-peak period. In the cache update stage, we propose a reactive cache update algorithm to update the existing cache policy to minimize the buffer delay. Simulation results verify that the proposed caching algorithms can reduce the initial buffer delay efficiently.

Effects of composite materials and revegetation on soil nutrients, chemical and microbial properties in rare earth tailings

The mining of ionic rare earth elements in Ganzhou left large area of barren tailings with severe vegetation destruction in pressing needs of remediation. However, the remediating effects of soil additives combined with revegetation on the preservation of nutrients in the tailings and microbial communities were rarely studied. For this purpose, pilot experiments were implemented in a field, with the control group (CK) only cultivating plants without adding materials, and three treatments including peanut straw biochar composite (T1), phosphorus‑magnesium composite (T2) and modified zeolite composite (T3) along with the cultivation of Medicago sativa L., Paspalum vaginatum Sw. and Lolium perenne L. Soil pH and organic matter in CK significantly decreased from 4.90 to 4.17 and from 6.62 g/kg to 3.87 g/kg after six months, respectively (p ≤ 0.05), while all the treatments could effectively buffer soil acidification (over 5.74) and delay the loss of soil organic matter. Soil cation exchange capacity was still below the detection limit in all the groups except T2. The results of rainfall runoff monitoring indicated that compared with CK, only T2 could significantly reduce the runoff loss of soil NO3− and SO42− by 45.61 %–75.78 % and 64.03 %–76.12 %, respectively (p ≤ 0.05). Compared with CK, the bacterial diversity in T2 and T3 significantly increased 21.18 % and 28.15 %, respectively (p ≤ 0.05), while T1 didn't change the bacterial or fungal diversity (p > 0.05). Co-occurrence network analysis showed that compared with CK, the whole microbial communities interacted more closely in the three treatments. Functional prediction of the microbial communities revealed all the treatments were dominated by carbon transforming bacteria and saprotrophic fungi except T2. This study demonstrated that the composite materials combined with revegetation couldn't retain soil nitrogen compounds and sulfate in rare earth tailings in the long term.

Deep learning based optimised data transmission over 5G networks with Lagrangian encoder

Video data transmission without buffering is ubiquitous for all contemporary appliances. The increased consumption of video content has created the demand for more efficient video compression algorithms for high-resolution videos. In this study, a video compression technique is presented that uses a Lagrangian encoder (LE) with H.265 protocol. This architecture provides compression with less bandwidth compared to contemporary encoders, and it is compatible with 5 G network transmission speed and latency. Adding LE in the H.265 protocol architecture reduced the buffering delay and increased the efficiency. Along with these parameters, this study focused on the quality of video streaming, which was measured by metrics such as peak signal to noise ratio (PSNR), structural similarity index (SSIM), and video multi-method assessment fusion (VMAF). A comparison of the values of compression ratio and latency with and without H.264 architecture showed improved performance in the architecture. Thus, deep learning-based optimised data transmission can improve accuracy and reduce computational complexity.

Throughput Maximization for Wireless Powered Buffer-Aided Successive Relaying Networks

In this paper, we consider a wireless powered cooperative network, where two energy-constrained buffer-aided relays harvest energy from the source to assist the information delivery to the destination. To improve the spectral efficiency, a wireless powered successive relaying (WPSR) protocol is proposed to allow both relays to receive the information from the source and forward the buffered data to the destination, taking into consideration of the inter-relay-interference (IRI). We first reveal the impact of data buffers and energy storages at the relays by the achievable throughput comparison of the WPSR scheduling schemes with and without considering data buffers and energy storages. Our analysis validates the great potential of the buffer-and-forward data transmission and the harvest-store-use energy management strategies. Then, the network throughput is maximized via adaptive time and power allocation subject to the stability constraints of data buffers and energy buffers, and an adaptive wireless powered buffer-aided successive relaying (WPBSR) scheduling scheme is proposed. The proposed scheme approaches the optimal throughput of the wireless powered successive relaying network with bounded delay and finite length of data and energy buffers. Numerical results validate the analysis and noticeable spectral efficiency gain.

Proportional–integral–derivative-based intra rate controller for low-delay applications of high efficiency video coding screen content coding

Most screen content (SC) video applications are real time, and a low-delay transmission is needed. An effective low-delay transmission requires a precise video rate controller to fit the video bit rate to the capacity of the transmission channel. The rate controller has to support the unique standard coding tools of SC video. We propose a unique intra rate controller based on a unique content-based rate-distortion model for low delay applications of high efficiency video coding SC coding. The proposed model supports the unique SC coding tools and different modes and sizes of coding tree units. The proportional–integral–derivative control concept is used for frame-level bit allocation and rate control. The rate controller utilizes a small size virtual buffer to provide low-delay buffering constraints for the bit stream. Experimental results show that the proposed rate controller can control the bit rate of test sequences with a low buffering delay (about 20 ms) while the rate-distortion performance is maintained.

NOMA-Based Multi-User Mobile Edge Computation Offloading via Cooperative Multi-Agent Deep Reinforcement Learning

Mobile edge computing (MEC) is a promising solution to enable resource-limited mobile devices to offload computation-intensive tasks to nearby edge servers. In this paper, dynamic computation offloading in a non-orthogonal multiple access (NOMA) based multi-user network is investigated by considering stochastic task arrivals and wireless channels. Specifically, a cooperative multi-agent deep reinforcement learning (CMADRL) based framework is proposed to learn decentralized offloading policies to allocate task offloading and local execution powers at each user, which minimizes long-term average network computation cost in terms of power consumption and buffering delay. By leveraging a centralized training and distributed execution strategy, the proposed framework can not only learn efficient decentralized policies, but also relieves users’ computational pressure and works well in coordinating the interference of NOMA-based networks. To reduce the training complexity, it is further improved to train one parameter shared policy network that can be exploited by all users with slightly sacrificed performance. Numerical simulations demonstrate that the proposed CMADRL based framework can learn efficient dynamic offloading policies at each user, which significantly outperforms the conventional independent Q-learning based framework as well as some greedy strategies with lower network computation cost.

A Clock Distribution Scheme Insensitive to Supply Voltage Drift With Self-Adjustment of Clock Buffer Delay

A Clock Distribution Scheme Insensitive to Supply Voltage Drift With Self-Adjustment of Clock Buffer Delay

Adaptive Clocking Using Supply Tracking Clock Modulator With Background-Calibrated Supply Sensitivity

Adaptive clocking (AC) has shown promising results for digital systems when there is a supply droop. However, coping with clock buffer delay and coarsely quantized clock frequency still remains a challenge. To solve these issues, we propose a supply tracking clock modulator placed after the clock buffer, which continuously changes the clock frequency to the supply. A prototype fabricated in 28-nm CMOS allows 36% higher system clock frequency and 25% higher power efficiency in a 15% supply droop, than a normal system without AC.

A 0.6 V 4 GS/s −56.4 dB THD Voltage-to-Time Converter in 28 nm CMOS

A 0.6 V low-voltage voltage-to-time converter (VTC) has been presented in this work for the emerging energy-efficient time-domain circuits and systems. The proposed VTC supports a rail-to-rail input by leveraging shrink sampling with two cascaded voltage sampling and charge sharing switches, breaking the tradeoff between linearity and input range of the traditional VTC and enabling low voltage operation. The charging current source is adjustable to calibrate the VTC gain variation. In addition, a 4-bit tunable delay buffer is inserted at the output stage to calibrate the VTC time offset, enhancing the PVT performance. By resizing the push-pull inverters’ PMOS/NMOS size ratio in the output buffer chain, the jitter contribution from buffers has been reduced. It also recovers the signal’s pulse width consumed during the voltage-time conversion, facilitating the time signal processing following VTC. Designed and fabricated in 28 nm CMOS, the prototype VTC occupies a 0.0012 mm² active area. Measurement results show that the VTC can run up to 4 GHz at a 0.6 V power supply, achieving -56.4 dB total harmonic distortion (THD) with Nyquist input and consuming 2.1 mW.

Research on Mobile English Learning System Based on iOS

In order to improve the use experience of mobile learning and reduce the response delay caused by the slow positioning of system resources, research on mobile English learning systems based on iOS is proposed. Firstly, the value of realizing mobile learning is objectively analyzed, and the practical significance of the research is clarified from the perspectives of social development and learning conditions. On this basis, taking the intelligent client equipped with an iOS operating system as the hardware condition of the system, the system architecture, including data access layer, business logic layer, and presentation layer, is constructed by MVC. In the model module, it is divided into ten difficulty levels by using the frequency of vocabulary, the length of words, and the number of syllables of a single word. The learning resources of the reading class are uniformly represented by the vector space model, and the improved TF-IDF is used to calculate the weight of eigenvalues in the resources. According to the calculation results, the resources are also divided into ten difficulty levels, and the divided resources correspond to their respective databases and use regular expressions to find the learning resources that match the access request. Finally, with the support of the iOS protocol, the feedback mechanism between each module is constructed by Express.js. By analyzing the access requests sent and received by the view, the timely call to the target database resources is realized to improve the response rate of the system. The test results show that the function of the designed system can be realized stably, and the module response delay time is stable within 1s; under the ideal network environment, the buffer delay is in the range of 0.4–0.6 s, and the loading delay is no more than 1.8 s when the network speed is 3 Mpbs, which has a good user experience.

An optimal algorithm for 2-bounded delay buffer management with lookahead

The bounded delay buffer management problem, which was proposed by Kesselman et al. (STOC 2001 and SIAM Journal on Computing 33(3), 2004), is an online problem focusing on buffer management of a switch supporting Quality of Service (QoS). The problem definition is as follows: Packets arrive to a buffer over time and each packet is specified by the release time, deadline and value. An algorithm can transmit at most one packet from the buffer at each integer time and can gain its value as the profit if transmitting the packet by its deadline after its release time. The objective of this problem is to maximize the gained profit. We say that an instance of the problem is s-bounded if for any packet, an algorithm has at most s chances to transmit it. For any s≥2, Hajek (CISS 2001) showed that the competitive ratio of any deterministic algorithm is at least (1+5)/2≥1.618. Recently, Veselý et al. (SODA 2019) designed an online algorithm matching the lower bound.Böhm et al. (ISAAC 2016 and Theoretical Computer Science, 2019) introduced the lookahead ability to an online algorithm. At a time t, the algorithm obtains information about packets arriving at time t+1, and showed that for s=2, there is an algorithm which achieves the competitive ratio of (−1+13)/2≤1.303. Also, they showed that the competitive ratio of any deterministic algorithm is at least (1+17)/4≥1.280. In this paper, for the 2-bounded model with lookahead, we design an algorithm with a matching competitive ratio of (1+17)/4.