In this letter, we analyze the identity-based signature with conditional privacy-preserving authentication scheme (short for IBS-CPPA, published in Journal of Systems Architecture, doi: 10.1016/j.sysarc.2019.101692) and demonstrate that it cannot provide secure authentication between vehicles. Specifically, in IBS-CPPA, two types of adversaries can launch different attacks to forge a valid signature

Mobile edge computing (MEC) is envisioned to integrate cloud-like capabilities into the edge of networks for improving quality of service (QoS). This makes it possible for users with resource-limited devices to execute computation-intensive tasks by offloading them to MEC nodes. Extensive works have been done for MEC. However, few of them involve user mobility. Whether to migrate task dynamically can’t

For satellite communication with bi-directional channels, we investigate the application of Low-Density Parity-Check (LDPC) coding by incorporating channel state information (CSI) to enhance its security performance. Specifically, the scheme includes two main steps: CSI measurement and the design of LDPC security coding. Based on its reciprocity and uniqueness, CSI is first obtained by estimating bidirectional

Domain Wall Memory (DWM) as an ideal candidate for replacing traditional memories especially in parallel systems, has many desirable characteristics such as low leakage power, high density and low access latency. However, due to the tape-like architecture of DWM, shift operations have vital impact on performance. Considering data-intensive applications with massive loops and arrays, increasing parallelism

Recently, Wireless Sensor Network (WSN) is often viewed with an oversized range of sensors that are structured and collaborate to gather and transmit information around the targets. As sensors may be positioned in harsh surroundings, it is critical for secure data transmission. Therefore, a dynamic routing path should be essential for WSN applications. In this paper, a Jellyfish Dynamic Routing Protocol

“Recurrent neural networks” (RNNs) are powerful artificial intelligence models that have shown remarkable effectiveness in several tasks such as music generation, speech recognition and machine translation. RNN computations involve both intra-timestep and inter-timestep dependencies. Due to these features, hardware acceleration of RNNs is more challenging than that of CNNs. Recently, several researchers

Over the past decade, deep convolutional neural networks (CNN) have been widely embraced in various visual recognition applications owing to their extraordinary accuracy. However, their high computational complexity and excessive data storage present two challenges when designing CNN hardware. In this paper, we propose an energy-aware bit-serial streaming deep CNN accelerator to tackle these challenges

Autonomous mobile robots share social spaces with humans, usually working together for domestic or professional tasks. Cyber security breaches in such robots undermine the trust between humans and robots. In this paper, we investigate how to apprehend and inflict security threats at the design and implementation stage of an autonomous mobile robot. To this end, we leverage the idea of directed fuzzing

Highly scalable resource supply capacity of cloud computing has greatly improved the execution speed of workflow applications, however, traditional workflow scheduling algorithms which focus on the optimization of makespan (execution time) of workflows, become inappropriate for the design of large-scale workflow systems. Workflow scheduling in cloud computing is particularly a multiobjective optimization

Formal methods use abstraction and rigorously verified refinement to manage the design of complex systems, ensuring that they satisfy important invariant properties. However, formal verification is not sufficient: models must also be tested to ensure that they behave according to the informal requirements and validated by domain experts who may not be expert in formal modelling. This can be satisfied

Internet of things technology and edge computing have been applied increasingly in the field of medical treatment to solve the problem of imbalanced medical resources. To better diagnose Attention Deficit Hyperactivity Disorder (ADHD), we propose a new short-time diagnosis technology that can quickly analyze the functional magnetic resonance imaging (fMRI) of patients and assist doctors in remote diagnosis

Real-time servers have been widely explored in the scheduling literature to predictably execute aperiodic activities, as well as to allow hierarchical scheduling settings. As they facilitate timing isolation between different software components, there is a renewed interest for the adoption of fixed priority real-time servers in the automotive domain, as a way to implement more efficient reservation

Traffic light detection is a key module in the autonomous driving system to enhance the interactions between drivers and unmanned vehicles. In recent studies, deep neural networks are widely used for traffic light detection and resource/power consumption is a major concern for model deployment in vehicular edge devices. This paper proposes a novel light-weight deep CNN model that integrates the multi-backbone

Simultaneous localization and mapping (SLAM) becomes a solved problem in terms of the algorithms. In order to use them in autonomous mobile robots, researches are focusing on reducing computation complexity and developing embedded systems with appropriate software and hardware architecture. In this work, we aim to perform a fully embedded implementation of a SLAM on an FPGA based SoC combining an embedded

Minimizing latency and power are key goals in the design of NoC routers. Different proposals combine lookahead routing and router bypass to skip the arbitration and buffering, reducing router delay. However, the conditions to use them requires completely empty buffers in the intermediate routers. This restricts the amount of flits that use the bypass pipeline especially at medium and high loads, increasing

Global Health sometimes faces pandemics as are currently facing COVID-19 disease. The spreading and infection factors of this disease are very high. A huge number of people from most of the countries are infected within four months from its first report of appearance and it keeps spreading. The required systems are not ready up to some stages for any pandemic; therefore, mitigation with existing capacity

This work proposes a novel approach to provide comprehensive security to IoT devices. Our approach is based on a reconfigurable hardware-based isolation and protection mechanism (IPM) that operates as a dynamic separation unit between devices and network, far from potential software manipulation. The IPM analyses communications for malicious activities and prevents damage to the IoT device. The IPM

As the most popular digital currency, Bitcoin has a high economic value, and its security has been paid more and more attention. Anomaly detection of Bitcoin has become a problem that must be solved. The existing Bitcoin anomaly detection methods only use static network models, and only the simple structural features such as node attributes and in/out-degree are considered to measure the similarities

While the NAND flash based solid state drive (SSD) has been widely adopted by both custom electronics and enterprise storages, the isolation of the file system and the information of the real status of the physical storage space will inevitably degrade the overall efficiency as well as the reliability of the storage and could become the bottleneck of the high-performance test systems. Open Channel

An important application for discrete wavelet transform (DWT) is the image compression such as the JPEG2000 Standard, and GPU is a good choice for the implementation of the DWT. For the application of image compression in the space environment, this paper has discussed the fault tolerance for the forward DWT (FDWT) implemented on GPUs, to deal with the silent data corruption (SDC) errors caused by

Prefetching has been widely used in general purpose computers, especially in high performance CPUs, but has been much less used in DSPs and embedded processors. The goal of this paper is to investigate adding a perceptron, a single layer neural network [1], to straight-forward hardware prefetching techniques for embedded DSPs, and assess their performance improvement. By using industry standard benchmarks

In the IoT-Fog-Cloud landscape, IoT devices are connected to numerous software applications in order to fully operate. Some applications are deployed on the Fog layer, providing low-latency access to resource, whilst others are deployed on the Cloud to provide important resource capabilities and process heavy computation. In this distributed landscape, the deployment infrastructure has to adapt to

The challenges of deploying robots and autonomous vehicles call for further efforts to bridge the gap between the robotics, the real-time systems and the formal methods communities. Indeed, with robots being more and more involved in costly missions and contact with humans, a rigorous formal verification of their behavior in the presence of various real-time constraints is crucial. In order to increase

In-memory data processing frameworks (e.g., Spark) make big data analysis greatly simpler and efficient. However, stragglers that take much longer to finish than other tasks significantly degrade performance. There exist multiple factors that cause stragglers, either from the hardware resource layer or application layer, e.g. hardware heterogeneity, interference, data locality and data skew. While

This work considers exact schedulability analysis of a set of aperiodic non-preemptive tasks on a given set of computational resources, and the problem is known to be NP-Complete. We propose four different SAT-based encoding schemes to address the exact schedulability problem. Each approach requires a different number of variables and generates a distinct number of clauses. We present extensive comparative

In the current chip-multiprocessor era, 3D-stacked DRAM became an attractive alternative to mitigate the DRAM bandwidth wall problem. In a chip-multiprocessor, the 3D-stacked DRAM is architect either (a) to cache both local and remote data or (b) to cache only the local data. Caching only local data into the 3D-stacked DRAM enforces the chip-multiprocessors to suffer inter-node latency overhead while

For deep learning cloud computing platforms, file system is a fundamental and critical component. Hadoop distributed file system (HDFS) is widely used in large scale clusters due to its high performance and high availability. However, in deep learning datasets, the number of files is huge but the file size is small, making HDFS suffer a severe performance penalty. Although there have been many optimizing

This paper introduces a smart cyber physical multi-source energy system for electric vehicle applications. This system is realized in order to increase the autonomy of the vehicle as well as a good self-dispatch energy system. In this paper, three energy sources have modeled and integrated in the energy conversion chain of the vehicle. Moreover, the design of cyber energy dispatching system is proposed

Unspent Transaction Output (UTXO) set is the foundational model used in many blockchain systems to represent assets. The benefits of UTXO representation include parallel processing, privacy, etc. However, the increasing size of UTXO set is degrading the access performance and severely brings down the validation speed of blockchain further, especially in resource-constrained scenerios, such as IoT.

An AUTOSAR-based embedded software consists of a set of inter-connected Software Components (SWCs). Each SWC contains a set of runnables which are small code-fragments that should be mapped to Operating System (OS) tasks. This process of mapping runnables to tasks may affect both the system real-time schedulability and performance. This paper proposes fast and efficient algorithms for mapping runnables

Edge computing enables users to offload certain computation loads in complex applications to a nearby network consisting of multiple mobile devices such that the mobile devices’ resources can be integrated to afford these complex applications. Due to the social relationships among the owners of mobile devices, networks in edge computing are always complex and consist of multiple sub-networks intersecting

In this paper, we are interested in the energy optimization of hybrid Scratchpad Memory (SPM) which consists of SRAM and Non-Volatile Memory (NVM). We approach the energy optimization by data allocation with the consideration of the impact of program structure like branches. Our method is composed of two stages, i.e., program analysis stage and data allocation stage. In program analysis stage, we design

Wireless network on chip (WiNoC) has been proposed as a promising solution for on-chip interconnection network due to high scalability, high bandwidth, and low latency. However, the variations of traffic pattern distribution and data flow in WiNoCs have made wireless interfaces-equipped routers (WRs) prone to congestion. Congestion is one of the most significant challenges in WiNoCs that reduces network

Indoor localization is an emerging application domain that promises to enhance the way we navigate in various indoor environments, as well as track equipment and people. Wireless signal-based fingerprinting is one of the leading approaches for indoor localization. Using ubiquitous Wi-Fi access points and Wi-Fi transceivers in smartphones has enabled the possibility of fingerprinting-based localization

Traditional centralized virtual memory system design encounters severe scalability problems, which impede the multithreaded applications’ performance increment on many-core systems. In this paper, we propose a decentralized system model to scale the VM systems for many-cores. Our model improves system parallelism by avoiding resource sharing and minimizing state coordination. By applying the model

Graphics processing units (GPUs) can process massive amounts of data efficiently, but the complex computational demands of smart technologies have caused GPUs to consume increasing amounts of power. Moreover, current task scheduling strategies do not consider the loss of energy consumption due to task migration. To reduce GPU power usage, we proposed a dynamic GPU task balance scheduling called coefficient

Power consumption in electronic systems is an essential feature for the management of energy autonomy, performance analysis, and the aging monitoring of components. Thus, several research studies have been devoted to the development of power models and profilers for embedded systems. Each of these models is designed to fit a specific usage context. This paper is a part of a series of works dedicated

Wireless sensor networks (WSNs) with energy harvesting have fascinated the prospectus attention of researchers due to their wide deployment and omnipresent nature in the emerging areas of the Internet of Things (IoT's) and home automation. However, there are a lot of key challenges that affect the performance of WSNs due to their own characteristics. Still, energy constraints remain one of the major

The uncertainties of IoT-edges system and environment make challenges to applications in reliability, stability, and total latency, etc. With edge devices increasingly able to connect to cloud servers from anywhere, applications can potentially perform deployment changing at runtime to improve performance. In this paper, we propose a dynamic-programming based algorithm, named E-ODD, for the on-demand

Due to its attractive characteristics, phase change memory (PCM) has emerged as a promising candidate to be used in main memory of embedded systems in the future. However, the write endurance problem has restricted its application in practical. Discussions regarding on hybrid memory page replacement mechanism have dominated research in recent years. Most existing schemes lack the detection for the

The Information Technology sector has undergone tremendous changes arising due to the emergence and prevalence of Cloud Computing. Microservice Architectures have also been attracting attention from several industries and researchers. Due to the suitability of microservices for the Cloud environments, an increasing number of Cloud applications are now provided as microservices. However, this transition

Currently, GPGPU-Sim has become an important vehicle for academic architecture research. It is a cycle-accurate simulator that models the contemporary graphics processing unit. Machine learning has now been widely used in various applications such as self-driving car, mobile devices, and medication. With the popularity of mobile devices, mobile vendors are interested on porting machine learning or

In automotive/avionic/robot systems, consolidating multiple domains on a powerful SoC is an important trend. From the perspectives of safety and security, each of these domains must execute independently with a self-governed Operating System (OS). Such systems are termed as hybrid multi-OS systems. Generally, in a commonly used hybrid dual-OS system, a real-time OS (RTOS) and a general-purpose OS (GPOS)

Access control technologies are fundamental for addressing the security and privacy requirements of the Internet of Things (IoT). This paper proposes an access control solution for Constrained Application Protocol (CoAP)-based IoT services. The proposed solution considers a network of a single provider that interconnects various IoT endpoints. It leverages the Software-Defined Networking (SDN) paradigm

Cyber Physical Systems (CPS) have increasingly started using Learning Enabled Components (LECs) for performing perception-based control tasks. The simple design approach, and their capability to continuously learn has led to their widespread use in different autonomous applications. Despite their simplicity and impressive capabilities, these components are difficult to assure, which makes their use

Authenticated key agreement (AKA) enables communicating parties to mutually establish a session key, in a way that each entity is assured of the authentication of its peer. Certificateless AKA (CLAKA) protocols are widely designed since they avoid the key escrow problem found in identity-based systems and overcome certificateless management overheads in Public Key Infrastructure (PKI). Furthermore

This paper investigates a mobile edge computing environment for video analysis tasks where edge nodes provide their computation capacities to process the computation intensive tasks submitted by end users. First, we introduce a Cloudlet Assisted Cooperative Task Assignment (CACTA) system that organizes edge nodes that are geographically close to an end user into a cluster to collaboratively work on

Neural networks are increasingly applied into real-time and embedded Artificial Intelligent (AI) systems like autonomous driving system. Such resource-constrained systems cannot support the execution of neural network based tasks due to their high execution overheads on general processors. Hence, we are approaching to design real-time AI applications on embedded systems with CPU and FPGA (Field Programmable

The current ISO/IEC standard of the Ada programming language does not support non-blocking synchronization. The restriction to locks conflicts with Ada’s design goals for program safety and efficiency, because (1) task failure inside a critical section may incur deadlock, and (2) locks stand in the way of scaling parallel programs on multicore architectures. Increased autonomy of software systems and

Recent advances in machine learning, especially techniques such as deep neural networks, are enabling a range of emerging applications. One such example is autonomous driving, which often relies on deep learning for perception. However, deep learning-based perception has been shown to be vulnerable to a host of subtle adversarial manipulations of images. Nevertheless, the vast majority of such demonstrations

Development of critical systems nowadays is hardly achievable without reuse of previous knowledge. Design patterns have an important role in the design of such systems as they define and document common solutions to recurring design problems. However, critical systems such as those that are safety or security related, often require specific assurances that the system is adequate to operate in a given