Aiming at the problem of low overall service quality caused by the disordered collaboration of heterogeneous workflows and discontinuous task execution in cloud computing scenarios, this paper proposes a collaborative scheduling method for heterogeneous workflows in cloud computing based on deep reinforcement learning. The method optimizes workflow makespan, cost, fairness and continuity in cloud computing

Digital signatures are essential techniques used in the real world, especially for validating the authenticity of a given message. The security of the digital signatures based on the traditional security definition, however, may be vulnerable to the side-channel attacks. Currently, although several leakage-resilient signature (LR-Sig) schemes have been proposed to model the side-channel attacks, the

We study a power control strategy for a Massive MIMO enabled IoT system to increase total throughput and to provide better differentiated levels of service to different classes of IoT devices. We use a closed-form signal-to-interference plus noise ratio (SINR) of Massive MIMO and apply the Lagrange multiplier procedure to find the optimum power control coefficients. We investigate several scenarios

Cloud computing, as a large-scale distributed computing system dynamically providing elastic services, is designed to meet the requirement of delivering computing services to users as subscription-oriented services. In general, the problems of resource scheduling in Cloud computing like minimizing makespan are usually NP-Hard problems. Various common algorithms including heuristic, meta-heuristic and

Density Peaks Clustering (DPC) is a recently proposed clustering algorithm that has distinct advantages over existing clustering algorithms, which has already been used in a wide range of applications. However, DPC requires computing the distance between every pair of input points, therefore incurring quadratic computation overhead, which is prohibitive for large data sets. To address this efficiency

This article investigates the bumpless transfer (BT) control problem of switched systems with unmeasured states. Note that the control input signal of the switched system jumps when switching occurs, which may adversely affect the performance of switched systems. By introducing a modified state observer and an auxiliary continuous control signal, a novel description of the BT performance for the system

This article investigates a nonlinear disturbance observer (NDO)-based fault-tolerant sliding-mode control (SMC) for 2-D plane vehicular platoon systems subjected to actuator faults with unknown time-varying fault direction (UTVFD), asymmetric nonlinear actuator saturation (ANAS), nonlinear unmodeled dynamics, and unknown external disturbance. The Nussbaum-type function approach is adopted to solve

The security issue is of the fundamental importance for cyber-physical systems (CPSs) due to the vulnerability to cyber attacks. In this article, an active interdiction defence scheme is proposed as an extra safeguard against the strategic false data-injection (FDI) attacker. To tackle the coupling between the decision-making processes of the FDI attacker and the active interdiction defence scheme

This article is concerned with the global fast finite-time adaptive stabilization for a class of high-order uncertain nonlinear systems in the presence of serious nonlinearities and constraint communications. By renovating the technique of continuous feedback domination to the construction of a serial of integral functions with nested sign functions, this article first proposes a new event-triggered

Convolutional neural networks (CNNs) have attracted much research attention and achieved great improvements in single-image dehazing. However, previous learning-based dehazing methods are mainly trained on synthetic data, which greatly degrades their generalization capability on natural hazy images. To address this issue, this article proposes a semi-supervised learning approach for single-image dehazing

Surrogate-assisted evolutionary algorithms (EAs) have been proposed in recent years to solve data-driven optimization problems. Most existing surrogate-assisted EAs are for centralized optimization and do not take into account the challenges brought by the distribution of data at the edge of networks in the era of the Internet of Things. To this end, we propose edge-cloud co-EAs (ECCoEAs) to solve

Remote sensing image captioning (RSIC), which describes a remote sensing image with a semantically related sentence, has been a cross-modal challenge between computer vision and natural language processing. For visual features extracted from remote sensing images, global features provide the complete and comprehensive visual relevance of all the words of a sentence simultaneously, while local features

When humans interact with each other, eye gaze movements have to support motor control as well as communication. On the one hand, we need to fixate the task goal to retrieve visual information required for safe and precise action-execution. On the other hand, gaze movements fulfil the purpose of communication, both for reading the intention of our interaction partners, as well as to signal our action

In Mobile Edge Computing (MEC), offloading tasks from mobile devices to edge servers may accelerate the processing speed and save the energy of the devices, hence improving device users’ quality of experience. Recently, reinforcement learning (RL) is increasingly used for offload decision making. RL seeks long-term cumulative benefits and is proved useful for a sequence of decisions, thus is well suited

The forestry industry is one of the most hazardous industries in New Zealand, and the physical and cognitive fatigue of forestry workers has been shown to contribute to this. Physical and cognitive fatigue can be exacerbated by prolonged physical and cognitive workload. As such, we propose that the identification and mitigation of fatigue factors could reduce the risk of incident and injury in hazardous

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The skyline is an optimization operator widely used for multi-criteria decision making. It allows minimizing an n-dimensional dataset into its smallest subset. In this work we present SkyFlow, the first heterogeneous CPU+GPU graph-based engine for skyline computation on a stream of data queries. Two data flow approaches, Coarse-grained and Fine-grained, have been proposed for different streaming scenarios

Energy Neutrality is the need of the hour for future Cyber-physical infrastructure. Many past research works suggest low duty cycle networking for energy-efficient wireless sensor network; however, research problem still persist as these proposals have some practical deployment bottlenecks like sleep-latency and may trade-off with data-fidelity and Quality-of-Service (QoS) parameters. The research

As two promising paradigms in emerging 6G wireless systems, service function chaining (SFC) and mobile edge computing (MEC) have attracted insensitive attentions from both industry and academia, and would bring more close-proximity services to 6G users with communication, computing and caching (3C) resources, yet also faced with challenges arising in time-varying channel conditions and resource dynamics

Monitoring infrastructures is a key cornerstone for both security and resilience mechanisms, as well as, infrastructure management helping to ensure availability and reliability. Its importance is increasing in the light of Internet-of-Things (IoT) infrastructures growing both in size and complexity, hence, widening the attack surface and decreasing the possibilities of manual management. There is

If a control input signal constructed by backstepping is used to generate an event-triggered control signal, then not only the real control input is discontinuous, but all the virtual control signals that make up the control signal are also discontinuous and have the same triggering instants with the control input. This fact makes the control design and stability analysis more difficult and complex

Nonsmooth nonlinear systems can model many practical processes with discontinuous property and are difficult to be stabilized by classical control methods like smooth nonlinear systems. This article considers the output-feedback adaptive neural network (NN) control problem for nonsmooth nonlinear systems with input deadzone and saturation. First, the nonsmooth input deadzone and saturation is converted

Modeling sequential behaviors is the core of sequential recommendation. As users visit items in chronological order, existing methods typically capture a user's present interests from his/her past-to-present behaviors, i.e. making recommendations with only the unidirectional past information. This article argues that future information is another critical factor for the sequential recommendation. However

The event-triggered model predictive control (MPC) problem is addressed for polytopic uncertain systems. A new dynamic event-triggered mechanism (DETM) with a bounded dynamic variable and a time-varying threshold is proposed to manage measurement data packet releases. The dynamic output-feedback MPC issue is detailed as a "min-max" optimization problem (OP) with an objective function over an infinite

Facial kinship verification refers to automatically determining whether two people have a kin relation from their faces. It has become a popular research topic due to potential practical applications. Over the past decade, many efforts have been devoted to improving the verification performance from human faces only while lacking other biometric information, for example, speaking voice. In this article

In the field of qualitative decision making with hesitant fuzzy linguistic term sets (HFLTSs), distance measure (DM) is a significant concept that reflects the degree of difference between HFLTSs. Various DMs among HFLTSs have been proposed, which enhance the applicability of HFLTSs in multicriteria decision making (MCDM) under qualitative hesitation information. However, existing strategies not only

In this article, a novel hybrid reinforcement Q -learning control method is proposed to solve the adaptive fuzzy H∞ control problem of discrete-time nonlinear Markov jump systems based on the Takagi-Sugeno fuzzy model. First, the core problem of adaptive fuzzy H∞ control is converted to solving fuzzy game coupled algebraic Riccati equation, which can hardly be solved by mathematical methods directly

Container-based virtualization has become increasingly popular as a lightweight alternative to hypervisor-based virtualization in cloud computing. Isolation is a fundamental property for consistent and reliable performance for cloud environment. However, the isolation between containers is much weaker than virtual machines as containers on the same host share one underlying host kernel. Existing works

Edge computing as a complementary paradigm of cloud computing has gained more attention by providing mobile users with diversified services at the network edge. However, the increasingly complex mobile applications put a heavier load on edge networks. It is challenging to provide concurrency requests with high-quality service processing, especially when the edge networks are dynamically changing. To

Attribute-based access control, which can provide fine-grained and flexible privacy protection, is widely used in practice. Traditional attribute-based access control schemes require the intervention of a trusted third party, which will cause single point of failure. Due to its decentralized nature, blockchain is now considered as a promising way to solve the above issue. The basic idea of existing

Phishing email attack is a dominant cyber-criminal strategy for decades. Despite its longevity, it has evolved during the COVID-19 pandemic, indicating that adversaries exploit critical situations to lure victims. Plenty of detectors have been proposed over the years, which mainly focus on the contents or the textual information of emails; however, to cope with the evolution of phishing emails more

Ultra-Dense Networks (UDNs) have been proposed to meet the ultra-high system capacity and ultra-high user experience rate requirements of sixth generation (6G) mobile networks. However, ultra-dense base stations (BSs) deployment poses challenges for cell-edge users such as BS selection, severe interference, resource allocation, and inter-cell handover. To tackle these obstacles, this paper formulates

Software-defined networking (SDN) has increased the need for security due to the participation of illegitimate packets resulting from poor processing times and inadequate resource utilizations. In recent days, wireless 5G users, e.g., Internet of Things (IoT) users, have accessed networks from great distances due to their mobility, which requires multiple handovers between communication technologies

Falling weight deflectometer backcalculation is a structural health monitoring approach for estimating the dynamic modulus of flexible pavements. It consists of two key aspects: a computational pavement model and an optimization routine. When using gradient-based methods, the optimization problem is commonly ill-posed, whereby a unique solution does not necessarily exist. In this paper, a new tandem

In this paper, the finite element discretization of non-classical continuum models with micro-inertia is analysed. The focus is on micro-inertia extensions of the one-dimensional rod model, the beam bending theories of Euler–Bernoulli and Rayleigh, and the two-dimensional membrane model. The performance of a variety of mass matrices is assessed by comparing the natural frequencies and their modes with

In this paper, we present a new method for designing piezoelectric transducers with connected two-phase electrode. The electrode design problem is formulated as an optimization problem, and the most significant contribution is modeling of connectivity constraints by using results from graph theory. Several examples are shown to corroborate that optimized electrode configurations lead to devices of

In this article, we study the problem of Nash equilibrium (NE) seeking of N -player games with high-order integrator agents over jointly strongly connected networks. The same problem was studied recently over static, undirected, and connected networks. Since a jointly strongly connected network can be directed and disconnected at every time instant, our result strictly includes the existing results

In this work we present a novel Quasi-Newton technique for the black-box partitioned coupling of interface coupled problems. The new RandomiZed Multi-Vector Quasi-Newton method stems from the combination of the original Multi-Vector Quasi-Newton technique with the randomized Singular Value Decomposition algorithm, avoiding thus any dense DOFs-sized square matrix operation. This results in a reduction

Spatial-spectral classification (SSC) has become a trend for hyperspectral image (HSI) classification. However, most SSC methods mainly consider local information, so that some correlations may not be effectively discovered when they appear in regions that are not contiguous. Although many SSC methods can acquire spatial-contextual characteristics via spatial filtering, they lack the ability to consider

The problem of the model-free adaptive resilient control (MFARC) for nonlinear cyber-physical systems (CPSs) suffered from aperiodic jamming attacks is investigated in this article. First, the MFARC framework subject to aperiodic jamming attacks is established, and an intermediate variable method is introduced to avoid using the unavailable time-varying parameter and further eliminate an extra assumption

The ever-increasing number of online services and tremendous data volume make the data center networks expand rapidly. The data center network must be flexible in scalability and cost-effective in order to respond quickly to the ever changing service requirements. However, the costs of switch-centric topologies are high, while the scalabilities of server-centric topologies are not good. How to build

Blockchain-based covert communication has opened up a new research direction for the covert communication field. In blockchain-based storage covert communication, reliability can be guaranteed because of the inherent immutable property of blockchain. Besides, enhanced undetectability is also achieved because the sender and the receiver do not need to establish a direct connection or be online simultaneously