As “deep neural networks” (DNNs) achieve increasing accuracy, they are getting employed in increasingly diverse applications, including security-critical applications such as medical and defense. This immense use of DNNs has motivated the researchers to scrutinizingly study their security vulnerability and propose countermeasures, especially in the context of hardware security. In this paper, we present

“Unmanned aerial vehicles” (UAVs) are now being used for a wide range of surveillance applications. Specifically, the detection of on-ground vehicles from UAV images has attracted significant attention due to its potential in applications such as traffic management, parking lot management, and facilitating rescue operations in disaster zones and rugged terrains. This paper presents a survey of deep

Weakly-hard real-time scheduling enables to tolerate certain execution timeouts of tasks, and has been widely exploited in those intelligent embedded systems over the past two decades. In general, the current weakly-hard real-time scheduling algorithms try to rapidly raise the priorities of jobs (instances) of those tasks that have missed deadlines to guarantee their individual weakly-hard constraints

Applications run in embedded systems should usually be completed within the constrained time to reduce energy consumption. Therefore, the memory of embedded system should satisfy time-efficient and energy-efficient. Domain Wall Memory (DWM) achieves high energy efficiency, high density, non-volatile and low cost advantages. However, the data access on DWM always requires shift operations to align the

The existing privacy-preserving authentication models for Vehicular Ad-hoc Networks (VANETs) primarily preserve multiple pseudonyms for one vehicle, while overlooking the consideration of confidential identity requirements. These authentication models cause pseudonyms management complex and revocation inconvenient. Blockchain seems to be suitable for storing the pseudonym certificates as transactions

Liquid state machine(LSM) is an attractive spiking neural network (SNN) for Network-on-Chip(NoC)-based neuromorphic platforms due to their biological characteristics and hardware efficiency. But the randomly connected topology of the liquid in LSM and lots of communication spike bring different dataflow and communication congestion on the NoC-based platform. Aiming to design an accurate and communication

With the wide use of multiprocessor architecture, parallel tasks have been receiving growing attention in both industry and academia. In real-time systems, the scheduling and synchronization that ensure predictable task execution and resource access are of utmost importance. Although the scheduling of (independent) parallel tasks is widely studied in recent years, few works have been done for the synchronization

Side-channel attacks are one of the security threats to the chip-level devices of the communication systems. To strengthen chip-level cryptographic devices against side-channel attacks, a current equalizer that weakens the current difference is proposed, which barely changes the original design flow and is resistant to physical teardown. This method overlays (metal-insulator-metal) MIM capacitors on

The past decade has seen a rapidly growing interest in IoT-connected devices. But as is usually the case with computer systems and networks, malicious individuals soon realized that these objects could be exploited for criminal purposes. The problem is particularly salient since the firmware used in many Internet connected devices was developed without taking into consideration the expertise and best

Virtualized data centers usually consist of heterogeneous servers which have different specifications (performance). Though there usually exist unused heterogeneous servers in such data centers, conventional DVFS (Dynamic Voltage and Frequency Scaling)-based DTM (Dynamic Thermal Management) techniques do not exploit the unused servers to cool down hot servers. In this paper, we propose a novel DTM

The functionality advancements and novel customer features that are currently found in modern automotive systems require high-bandwidth and low-latency in-vehicle communications, which become even more compelling for autonomous vehicles. In a recent effort to meet these requirements, the IEEE Time-Sensitive Networking (TSN) task group has developed a set of standards that introduce novel features in

Time sensitive networks (TSNs) enable deterministic real-time communication over Ethernet networks. According to IEEE 802.1Qbv standards, TSN switches use gates between queues and their corresponding egress ports to facilitate timing-deterministic communications. Management of switch resources, such as queues, has a significant impact on the schedulability of real-time flows. In this paper, we look

There is a need for reliable and efficient methods for monitoring the activity and social behaviour in cows, in order to optimise management in modern dairy farms. This research presents an embedded system that could track individual cows using Ultra-wideband technology. At the same time, social interactions between individuals around the feeding area are analysed with a computer vision module. Detections

To allow more accurate and efficient browsing performance, existing works showed that visual landmarks (e.g.3D pins) can facilitate spatial learning and recalling of browsing performance in Virtual Reality (VR). Compared with visual cues, the additional auditory cue is well known to provide benefits of navigational performance in virtual environments. However, less is known about the effects of such

The emergence of mobile edge computing provides an efficient and stable computing platform for intelligent applications of autonomous vehicles, and deep neural network (DNN) based tasks collaborative inference through joint device-edge is considered an effective way to reduce latency. However, the computing resources allocated to the vehicle are dynamic as the number of requesters changes due to the

Mixed-criticality embedded systems, as the next-generation of safety-critical systems, are increasingly employed in the industry due to consolidating functionalities with varying criticality levels onto the same computing platform. Technology scaling, battery-supplied design, and heavy computation in mixed-criticality systems necessitate employing energy management techniques. Due to the degrading

Motion estimation (ME) is a high efficiency video coding (HEVC) process for determining motion vectors that describe the blocks transformation direction from one adjacent frame to a future frame in a video sequence. ME is a memory and computation consuming process which accounts for more than 50% of the total running time of HEVC. To conquer the memory and computation challenges, this paper presents

Mixed-criticality system is an emerging design paradigm to improve the resource-efficiency for real-time embedded system. However, the traditional mixed-criticality system is commonly designed under pessimistic constraints on overrun handling and slack utilization. These solutions cannot provide efficient resource utilization when considering the dynamic behaviors of MC system. In this paper, we present

Recently, Virtual Prototypes (VPs) were introduced for the emerging RISC-V Instruction Set Architecture (ISA) and become an important part of the growing RISC-V ecosystem. A central component of the VP is the Instruction Set Simulator (ISS). VPs should provide a high simulation performance and at the same time yield accurate results, which are two conflicting requirements. To tackle this problem, we

Recently, federated learning has attracted great attention due to its advantage of enabling model training in a distributed manner. Instead of uploading data for centralized training, it allows devices to keep local data private and only send parameters to server. Then the server aggregates local models to derive a global model. In this paper, we study the aggregation problem in federated learning

Convolutional neural networks (CNNs) have shown appealing performance on stereo matching tasks in recent years. However, existing deep neural networks (DNNs) based matching algorithms use semi-global matching (SGM) to aggregate the matching costs, which limit the processing speed. In this study, we present a novel binarized CNN stereo matching hardware acceleration using local methods on an FPGA, which

Internet of Things (IoT) is a network convergence of multiple intelligent devices and advanced technologies aiming at connecting and exchanging data over the Internet. IoT is extensively applied in consumer, commercial, industrial, infrastructure and military spaces. With the prevalence of IoT applications, security issues such as identity authenticity and data privacy are increasingly become critical

With the development of industrial Internet of things (IIoT), Cloud Manufacturing has been increasingly popular to the manufacturing industry. It can provide resource-sharing and on-demand manufacturing services as well as automatic collaborative manufacturing with the help of edge Programmable Logic Controllers (edge-PLCs). In such a system, there is a high risk of exposing user privacy and trading

The rapid increase in the implementation of Internet of Things (IoT) solutions in diverse healthcare sectors raises the IoT in the healthcare market. The real-time health monitoring to manage the chronic diseases is likely to drive the demand of IoT in healthcare. Moreover, the enhancement in communication technologies like real-time data transmission has improved the patients’ confidence in managing

Cyber-Physical-Social Systems are frequently prescribed for providing valuable information on personalized services. The foundation of these services is big data which must be trustily collected and efficiently processed. Though High Performance Computing and Communication technique makes great contributions to addressing the issue of data processing, its effectiveness still relies on the veracity

Despite of a controversial practice, having the key components of a product undergo accelerated aging has been a very effective approach for planned obsolescence. All previous studies on planned obsolescence merely focused on the aging process itself; however, if a malfunctioned product due to aging is still under its warranty, the manufacturer suffers from financial losses in the form of customer

As the number of users in remote server environments is more prevalent (i.e., in e-payment, e-healthcare), a secure authentication scheme becomes increasingly important for this paradigm. In general, single-factor authentication in remote-systems suffers from several security issues, whereas multi-factor authentication can be considered as an alternative solution where additional factors increase the

As the core layer of the Internet of Things (IoT), middleware bridges the gap between applications and devices to resolve many common IoT issues and enhancing application development. Consequently, developing suitable middleware is the main challenge that covers functionality and required quality to combine heterogeneous hardware and software as the integrated system in the IoT. This survey discusses

Embedded devices are common carriers for deploying inference networks, which leverage the customized accelerator to achieve the promised performance with strict resource constraints. In the inference of Deep Neural Network(DNN), the sparsity existing in the activations and weights of every layer contributes massive non-effective memory accesses and computing operations. The data compression is adopted

With the rapid development of blockchain technology, the cross-blockchain asset transfer has been in great demand. However, most existing cross-blockchain solutions encounter low efficiency problems due to the centralized features, unfriendly development environment, and difficulty in cooperation. This paper proposes an interaction protocol for secure and efficient cross-blockchain transfer process

Traffic forecasting is a critical challenge for Intelligent Transportation Systems (ITS), increasingly enabled by the deepening interconnectedness of intelligent vehicles and traffic infrastructures. In this study, we propose a hybrid short-term forecasting architecture based on the careful consideration and analysis of reservation-based behavior cooperation and the characteristics of Cooperative ITS

Autonomous vehicles, such as drones, are gaining great popularity due to their usability and versatility. Nowadays, a significant number of them operate using open source software, such as Robot Operating System (ROS) and the de facto standard MAVLink communication protocol, as they are free and many of them are reusable enough that they can be deployed in various different vehicles. Although these

This paper proposes a systematic three-stage methodology for migrating complex real-time industrial software systems from single-core to multi-core computing platforms. Single-core platforms have limited computational capabilities that prevent integration of computationally demanding applications such as image processing within the existing system. Modern multi-core processors offer a promising solution

The existence of security threats in software designs can significantly impact the safe and reliable operation of systems. Threats need to be precisely specified before a tool can manipulate them, and though several approaches for threat specification have been proposed, they do not provide the scalability and flexibility required in practice. We take this problem towards an integrated approach for

To achieve low latency transmission of time-sensitive flows in Ethernet networks, the IEEE introduced the IEEE 802.1Qbu Standard, which specifies a 1-level preemption scheme for IEEE 802.1 networks. The specification allows the suspension of a preemptable frame prior to its completion for the speedy transmission of an express frame; but any other preemptable frame cannot be transmitted before the completion

Computing systems continue to evolve, resulting in increased performance when processing workloads in large data centers due to the virtualization benefits. This technology is the key factor that allows multiple applications to share resources, thereby enhancing the overall hardware utilization of cloud computing environments. However, multiple cloud-services contending for shared resources are susceptible

Hardware for energy-efficient AI has received significant attention over the last years with both start-ups and large corporations creating products that compete at different levels of performance and power consumption. The main objective of this hardware is to offer levels of efficiency and performance that cannot be obtained with general-purpose processors or graphics processing units. In parallel

The notion of Public-key Encryption with Keyword Search (PEKS) was first proposed by Boneh et al. in 2004. However, almost all PEKS schemes cannot resist offline Keyword Guessing Attacks (KGA). To address this issue, Huang and Li introduced the notion of Public-key Authenticated Encryption with Keyword Search (PAEKS) in 2017. Recently, Qin et al. put forward a new security model named Multi-Ciphertext

Traditional GPU resource allocation approaches, widely adopted in today’s data centers as the rise of cloud gaming, only focus on server-side functions while ignoring the client-side, which wastes hardware resources. To solve this problem, cloud-edge integrated architectures are put forward, leaving some workloads to the client-side. However, many cloud-edge integrated frameworks suffer from one big

Combination of sustainable resources and expanded developments in vitality utilization have made new challenges for the traditional grid system. To confront these challenges, the Internet of Things (IoT) have changed the traditional grid system into a modernized electrical system which is called smart grid. In smart grid networking, security and privacy are the major concerns. Recently, various authentication

To evaluate the impact of soft errors on convolutional neural networks (CNNs) deployed in edged computation systems, we propose a data-driven assessment strategy to characterize the propagation flow across hardware and software abstraction layers of the system in an interpretable way. Single-bit-flip injections in underlying hardware architecture are performed on virtual embedded system with a CNN-based

Wireless Rechargeable Sensor Network (WRSN) is largely used in monitoring of environment and traffic, video surveillance and medical care, etc., and helps to improve the quality of urban life. However, it is challenging to provide the sustainable energy for sensors deployed in buildings, soil or other places, where it is hard to harvest the energy from environment. To address this issue, we design

Blockchain-based decentralized infrastructure has been adapted in various industries to handle the sensitive data in a privacy-preserving manner without trusting third parties. However, integrating state-of-the-art blockchain platforms with the scalable, enterprise-level applications result in several challenges. Current blockchain platforms do not support high transaction throughput, lack high scalability

Authentication schemes based on homomorphic message authentication codes (HMACs) with or without a homomorphic cryptographic signature (HCS) have always played a vital role in network coding (NC). A newly developing trend with respect to research in this area takes authentication in NC-compatible networks beyond error detection. Current HMAC-based authentication schemes for networks that support NC

Functional-style iterators are present in many popular languages as a way of processing data in several connected steps, in a safe and readable manner. By contrast, Ada started providing general iterators only with its 2012 revision, in a way not directly intended for sequential composition. This paper presents a functional iterators library design inspired by the standard Rust iterators and the RxAda

Virtual machine (VM) placement is a key technique for energy optimization in cloud data centers. Previous work generally focus on how to place the VMs efficiently in servers to optimize the physical resources used (e.g., memory, bandwidth, CPU, etc.), network resources used or cooling energy consumption. These work can optimize the energy consumption of cloud data centers according to one or two aspects

Multipath data transmission techniques have been proposed to aggregate the resource of multiple heterogeneous access networks to enhance the robustness and throughput of multi-homed mobile devices. The Multipath TCP (MPTCP) protocol has been standardized by the IETF as an extension of conventional TCP, which enables establishing several subflows over multiple interfaces for simultaneous data transmission

Uses of Internet of things (IoT) devices and sensors have increased to a great extent in recent years. In order to facilitate computational and storage needs of low powered end devices for time-sensitive applications such as data analytic, which use IoT devices and sensors to get their work done, a new programming paradigm “Fog computing” has come into existence. Storage and processing capabilities

In recent years, big data and data analytics based on Cyber–Physical–Social Systems (CPSS) have become increasingly popular in providing valued services to humans. For many applications of CPSS, adequate computing infrastructure, which can be realized using powerful data centers (DCs), is needed. These DCs can then provide CPSS application developers with flexible and efficient High-Performance-Co

3D convolution neural networks (CNNs) have shown excellent predictive performance on tasks such as action recognition from videos. Since 3D CNNs have unique characteristics and extremely high compute/memory-overheads, executing them on accelerators designed for 2D CNNs provides sub-optimal performance. To overcome these challenges, researchers have recently proposed architectures for 3D CNNs. In this

Several industrial domains are currently developing innovative safety-related autonomous systems characterized by increasing software complexity and high-performance requirements. Due to these features, different research initiatives aim to pave the way towards the usage of Linux for the development of such complex safety-related systems. However, the high execution path variability of the Linux kernel

With the tremendous growth of smart mobile devices, the Content-Based Image Retrieval (CBIR) becomes popular and has great market potentials. Secure image retrieval has attracted considerable interests recently due to the outsourcing of CBIR onto the cloud. In this paper, we propose and implement a secure CBIR framework that performs image retrieval on the cloud without the user’s interaction. A pre-trained

Heterogeneous cluster-based multi/many-core platforms are on the edge, delivering high computing and energy-efficient embedded systems. These platforms support Dynamic Voltage/Frequency Scaling (DVFS), allowing to change the voltage/frequency levels for each cluster independently. Mapping dynamic applications on such platforms at run-time is a tedious task. This article presents a 0–1 Integer Linear

Model-based design methodologies based on the synchrony assumption are widely used in many safety-critical application domains. The synchrony assumption asserts that actions (such as the execution of code) occur instantaneously; however, physical platforms obviously do not possess this property. This paper considers a scheduling problem that arises when one seeks to implement programs that are written

Network-on-Chip (NoC) has been considered as an efficient communication infrastructure to support Multi-Processor System-on-Chip (MPSoC) design requirements for future generation computing. With the increased application requirements and rapid scale down in VLSI technology, the probability of forming thermal hotspots in the processing elements is relatively high which may lead to system failure. Therefore

The Snowden’s Prism incident warned people great threats from internal adversaries. Cryptographic Reverse Firewalls (CRFs), one mean to resolve the problem, are increasingly popular on account of its simplicity and convenience. The current related CRFs solutions are applied to encryption or key agreement. However, CRFs have extremely high requirements for re-randomization. Due to the irreversible hash

As convolutional neural networks (CNNs) improve in accuracy, their model size and computational overheads have also increased. These overheads make it challenging to deploy the CNNs on resource-constrained devices. Pruning is a promising technique to mitigate these overheads. In this paper, we propose a novel pruning technique called CURATING that looks at the pruning of CNNs as a multi-objective optimization

This paper identifies a limitation in the frame preemption model in the TSN standard (IEEE 802.1Q-2018), due to which high priority frames can experience significantly long blocking delays, thereby exacerbating their worst-case response times. This limitation can have a considerable impact on the design, analysis and performance of TSN-based systems. To address this limitation, the paper presents a

In recent years, Network-on-Chip (NoC) based multicore systems have become popular for executing real-time applications. Mapping and scheduling of these applications are critical for system performance. The complexity of the problem increases for dynamic scenarios with real-time applications where new applications unknown at design-time, are submitted by users at runtime. Most of the existing works