Cloud computing optimizes service quality and resource efficiency via centralized hardware and computational resources. However, the predominantly centralized deployment and operation of cloud data centers increase the physical distance to end-users, leading to degraded service quality. Edge computing addresses this by offloading data processing and analysis tasks directly to devices at the network edge, reducing reliance on backhaul transmission and thus offering a more responsive solution for latency-sensitive applications. Nevertheless, ensuring that applications meet predefined Service Level Agreement (SLA) in resource-constrained edge environments remains challenging. To tackle these issues, this paper investigates elastic scaling strategies in cloud-edge collaborative settings. We propose an attention-enhanced bidirectional LSTM model (A-Bi-LSTM) for microservice workload prediction, and design an adaptive elastic scaling system named XScale. This system incorporates a fall-back scaling mechanism when predictions are unreliable and introduces a proactive load forwarding strategy to enhance overall edge node performance. Experimental results show that, compared to existing elastic scaling methods, XScale reduces SLA violations by 82.3%, increases average resource utilization by 17.4%, decreases average response time by 21.1%, and improves overall edge node performance by 36.3%.

This paper investigates the style transfer of Chinese Traditional Patterns based on diffusion models. Chinese Traditional Patterns boast a rich history and unique artistic style, yet their application and dissemination face challenges. We collected and organized images of Chinese Traditional Patterns, constructing a high-quality Chinese Traditional Dermatoglyphic Pattern Dataset(CTDPD), and proposed the Wide Diffusion Model(WDM) with the Wide AutoEncoder to provide comprehensive receptive field information. The results from the experiment demonstrate that the Wide Diffusion Model achieves outstanding performance on the CTDPD dataset. Our designed WDM achieves the current SOTA performance compared to other cutting-edge methods on CTDPD dataset with Frechet Inception Distance of 5.45 and Inception Score of 207.5. This work thus offers significant backing to the heritability and creation of the Chinese Traditional Patterns.

This paper investigates the optimal channel exploration in multiple spectrum band covert communication. Different from most existing covert communication works that only consider the static wardens, we also take the reactive wardens that release real-time suppression tracking jamming based on their receiving power into consideration. In channel exploration period, the covert transmitter Alice aims to find a channel with high channel gain while guaranteeing its transmission covertness. However, obtaining channel gains on different bands before transmission takes Alice time and Alice has to choose the right time to stop exploring for throughput maximization. Firstly, to address the threats of the inactive and reactive wardens, the strategies of channel inversion power control and feedback based anti-jamming are respectively adopted. Then, we formulate the channel exploration problem with optimal stopping theory after analyzing Alice’s transmission covertness performance. Furthermore, since the conventional approach to this problem requires intensively computation, the one stage look ahead (1-SLA) rule is adopted to reduce the computation complexity. In particular, we mathematically prove that this rule is optimal in maximizing Alice’s expected throughput. At last, the simulation results are provided to validate the analytical results and the superiority of the proposed scheme compared with the benchmarks.

The environmental shelters such as public links can enable covert communication by covering covert transmission. To further exploit shelters, this paper focuses on a two-hop system where multiple pairs of public users and one pair of covert users communicate through a multi-antenna relay. We aim to improve covertness performance while satisfying the covertness constraints of two hops and quality of service (QoS) requirements of public users. The covert throughput maximization problem is formulated via jointly optimizing transmit power and beamformer, which is challenging to solve. We introduce successive convex approximation (SCA) and semidefinite relaxation (SDR) techniques to convert the problem into convex, where the joint optimization algorithm is developed. Considering the computational complexity, we further design a block diagonalization (BD) beamformer at the relay, which translates the beamformer optimization into a power allocation problem and derives the optimal solution in a closed form. We analytically show that the covert throughput first increases and then decreases as the number of public pairs increases in BD-based design, which has been verified numerically and can be generalized in other designs. Numerical results also evaluate the superiority of the joint optimization algorithm and the effectiveness of the BD-based efficient design. In particular, the BD-based design is very close to the joint optimization under small maximum transmit power of users or large maximum transmit power of relay.

In this paper, we consider a novel covert communication scenario where the warden does not have prior knowledge of the transmitter’s power. In this scenario, the current widely adopted likelihood ratio test (LRT)-based detector is not optimal anymore. To address this, we formulate a detection framework based on the generalized likelihood ratio test (GLRT), which replaces the unknown parameter with maximum likelihood estimation (MLE) and is proven optimal in the scenario. Based on the GLRT-based framework, two different detection models are proposed, where one only utilizes observations of the current time and the other can exploit observations of past time slots. We analyze the estimation and fisher information of the transmit power, and even the detection and covert performance under two different detection models, respectively. Based on the analytical results, we further derive the maximum number of tolerable slots under which the transmitter can remain the same transmit power while the detection error probability of the warden is still larger than the regulated threshold. Moreover, the transmit power and the number of tolerable slots are jointly optimized to maximize the transmission throughput subjecting to covertness constraint. The numerical results demonstrate the correctness of the theoretical analysis. We show how the covert rate is influenced by the number of transmitting slots and the transmit power, which can guide the design of the covert transmission strategy.