Inter-module Interfacing techniques for SoCs with multiple clock domains to address challenges in modern deep sub-micron technologies

Miniaturization of integrated circuits (ICs) due to the improvement in lithographic techniques in modem deep sub-micron (DSM) technologies allows several complex processing elements to coexist in one IC, which are called System-on-Chip. As a first contribution, this thesis quantitatively analyzes the severity of timing constraints associated with Clock Distribution Network (CDN) in modem DSM technologies and shows that different processing elements may work in different dock domains to alleviate these constraints. Such systems are known as Globally Asynchronous Locally Synchronous (GALS) systems. It is imperative that different processing elements of a GALS system need to communicate with each other through some interfacing technique, and these interfaces can be asynchronous or synchronous. Conventionally, the asynchronous interfaces are described at the Register Transfer Logic (RTL) or system level. Such designs are susceptible to certain design constraints that cannot be addressed at higher abstraction levels; crosstalk glitch is one such constraint. This thesis initially identifies, using an analytical model, the possibility of asynchronous interface malfunction due to crosstalk glitch propagation. Next, we characterize crosstalk glitch propagation under normal operating conditions for two different classes of asynchronous protocols, namely bundled data protocol based and delay insensitive asynchronous designs. Subsequently, we propose a logic abstraction level modeling technique, which provides a framework to the designer to verify the asynchronous protocols against crosstalk glitches. The utility of this modeling technique is demonstrated experimentally on a Xilinx Virtex-II Pro FPGA. Furthermore, a novel methodology is proposed to quench such crosstalk glitch propagation through gating the asynchronous interface from sending the signal during potential glitch vulnerable instances. This methodology is termed as crosstalk glitch gating. This technique is successfully applied to obtain crosstalk glitch quenching in the representative interfaces. This thesis also addresses the dock skew challenges faced by high-performance synchronous interfacing methodologies in modem DSM technologies. The proposed methodology allows communicating modules to run at a frequency that is independent of the dock skew. Leveraging a novel clock-scheduling algorithm, our technique permits a faster module to communicate safely with a slower module without slowing down. Safe data communications for mesochronous schemes and for the cases when communicating modules have dock frequency ratios of integer or coprime numbers are theoretically explained and experimentally demonstrated. A clock-scheduling technique to dynamically accommodate phase variations is also proposed. These methods are implemented to the Xilinx Virtex II Pro technology. Experiments prove that the proposed interfacing scheme allows modules to communicate data safely, for mesochronous schemes, at 350 MHz, which is the limit of the technology used, under a dock skew of more than twice the time period (i.e. a dock skew of 12 ns

Anomaly Detection In IoT Devices Using Data Mining Techniques

Internet of Things (IoT) devices are used to transmit data over a network. IoT device usage has grown and has been adopted in healthcare, smart homes, smart grids, connected cars and so on. However, IoT devices have security vulnerabilities and cannot provide a 100% guarantee of data privacy. They are prone to hacks and hardware Trojans that can lead to data theft. Hence there is a need to find ways to help solve the challenges of IoT devices. This paper proposes an approach that investigates how fraud, data theft, or fault, can be detected through the power profile of IoT devices in different operation modes using data mining techniques. Different cases will be made based on the behavior of the IoT device in terms of power consumption. These cases will be dependent on the mode of data transfer. Data mining techniques will be used to develop a model capable of detecting malicious behaviors and any form of the anomaly in power profiles of IoT devices

Global injury morbidity and mortality from 1990 to 2017 : results from the Global Burden of Disease Study 2017

Correction:Background Past research in population health trends has shown that injuries form a substantial burden of population health loss. Regular updates to injury burden assessments are critical. We report Global Burden of Disease (GBD) 2017 Study estimates on morbidity and mortality for all injuries. Methods We reviewed results for injuries from the GBD 2017 study. GBD 2017 measured injury-specific mortality and years of life lost (YLLs) using the Cause of Death Ensemble model. To measure non-fatal injuries, GBD 2017 modelled injury-specific incidence and converted this to prevalence and years lived with disability (YLDs). YLLs and YLDs were summed to calculate disability-adjusted life years (DALYs). Findings In 1990, there were 4 260 493 (4 085 700 to 4 396 138) injury deaths, which increased to 4 484 722 (4 332 010 to 4 585 554) deaths in 2017, while age-standardised mortality decreased from 1079 (1073 to 1086) to 738 (730 to 745) per 100 000. In 1990, there were 354 064 302 (95% uncertainty interval: 338 174 876 to 371 610 802) new cases of injury globally, which increased to 520 710 288 (493 430 247 to 547 988 635) new cases in 2017. During this time, age-standardised incidence decreased non-significantly from 6824 (6534 to 7147) to 6763 (6412 to 7118) per 100 000. Between 1990 and 2017, age-standardised DALYs decreased from 4947 (4655 to 5233) per 100 000 to 3267 (3058 to 3505). Interpretation Injuries are an important cause of health loss globally, though mortality has declined between 1990 and 2017. Future research in injury burden should focus on prevention in high-burden populations, improving data collection and ensuring access to medical care.Peer reviewe

Burden of injury along the development spectrum : associations between the Socio-demographic Index and disability-adjusted life year estimates from the Global Burden of Disease Study 2017

Background The epidemiological transition of non-communicable diseases replacing infectious diseases as the main contributors to disease burden has been well documented in global health literature. Less focus, however, has been given to the relationship between sociodemographic changes and injury. The aim of this study was to examine the association between disability-adjusted life years (DALYs) from injury for 195 countries and territories at different levels along the development spectrum between 1990 and 2017 based on the Global Burden of Disease (GBD) 2017 estimates. Methods Injury mortality was estimated using the GBD mortality database, corrections for garbage coding and CODEm-the cause of death ensemble modelling tool. Morbidity estimation was based on surveys and inpatient and outpatient data sets for 30 cause-of-injury with 47 nature-of-injury categories each. The Socio-demographic Index (SDI) is a composite indicator that includes lagged income per capita, average educational attainment over age 15 years and total fertility rate. Results For many causes of injury, age-standardised DALY rates declined with increasing SDI, although road injury, interpersonal violence and self-harm did not follow this pattern. Particularly for self-harm opposing patterns were observed in regions with similar SDI levels. For road injuries, this effect was less pronounced. Conclusions The overall global pattern is that of declining injury burden with increasing SDI. However, not all injuries follow this pattern, which suggests multiple underlying mechanisms influencing injury DALYs. There is a need for a detailed understanding of these patterns to help to inform national and global efforts to address injury-related health outcomes across the development spectrum.Peer reviewe