Online Container Scheduling for Low-Latency IoT Services in Edge Cluster Upgrade: A Reinforcement Learning Approach

In Mobile Edge Computing (MEC), Internet of Things (IoT) devices offload computationally-intensive tasks to edge nodes, where they are executed within containers, reducing the reliance on centralized cloud infrastructure. Frequent upgrades are essential to maintain the efficient and secure operation of edge clusters. However, traditional cloud cluster upgrade strategies are ill-suited for edge clusters due to their geographically distributed nature and resource limitations. Therefore, it is crucial to properly schedule containers and upgrade edge clusters to minimize the impact on running tasks. In this paper, we propose a low-latency container scheduling algorithm for edge cluster upgrades. Specifically: 1) We formulate the online container scheduling problem for edge cluster upgrade to minimize the total task latency. 2) We propose a policy gradient-based reinforcement learning algorithm to address this problem, considering the unique characteristics of MEC. 3) Experimental results demonstrate that our algorithm reduces total task latency by approximately 27\% compared to baseline algorithms

Look Closer to Your Enemy: Learning to Attack via Teacher-Student Mimicking

Deep neural networks have significantly advanced person re-identification (ReID) applications in the realm of the industrial internet, yet they remain vulnerable. Thus, it is crucial to study the robustness of ReID systems, as there are risks of adversaries using these vulnerabilities to compromise industrial surveillance systems. Current adversarial methods focus on generating attack samples using misclassification feedback from victim models (VMs), neglecting VM's cognitive processes. We seek to address this by producing authentic ReID attack instances through VM cognition decryption. This approach boasts advantages like better transferability to open-set ReID tests, easier VM misdirection, and enhanced creation of realistic and undetectable assault images. However, the task of deciphering the cognitive mechanism in VM is widely considered to be a formidable challenge. In this paper, we propose a novel inconspicuous and controllable ReID attack baseline, LCYE (Look Closer to Your Enemy), to generate adversarial query images. Specifically, LCYE first distills VM's knowledge via teacher-student memory mimicking the proxy task. This knowledge prior serves as an unambiguous cryptographic token, encapsulating elements deemed indispensable and plausible by the VM, with the intent of facilitating precise adversarial misdirection. Further, benefiting from the multiple opposing task framework of LCYE, we investigate the interpretability and generalization of ReID models from the view of the adversarial attack, including cross-domain adaption, cross-model consensus, and online learning process. Extensive experiments on four ReID benchmarks show that our method outperforms other state-of-the-art attackers with a large margin in white-box, black-box, and target attacks. The source code can be found at https://github.com/MingjieWang0606/LCYE-attack_reid

Efficient Serverless Function Scheduling at the Network Edge

Serverless computing is a promising approach for edge computing since its inherent features, e.g., lightweight virtualization, rapid scalability, and economic efficiency. However, previous studies have not studied well the issues of significant cold start latency and highly dynamic workloads in serverless function scheduling, which are exacerbated at the resource-limited network edge. In this paper, we formulate the Serverless Function Scheduling (SFS) problem for resource-limited edge computing, aiming to minimize the average response time. To efficiently solve this intractable scheduling problem, we first consider a simplified offline form of the problem and design a polynomial-time optimal scheduling algorithm based on each function's weight. Furthermore, we propose an Enhanced Shortest Function First (ESFF) algorithm, in which the function weight represents the scheduling urgency. To avoid frequent cold starts, ESFF selectively decides the initialization of new function instances when receiving requests. To deal with dynamic workloads, ESFF judiciously replaces serverless functions based on the function weight at the completion time of requests. Extensive simulations based on real-world serverless request traces are conducted, and the results show that ESFF consistently and substantially outperforms existing baselines under different settings

Research on model fitting and strength characteristics of critical state for expansive soil

According to Mengzi expansive soil, consolidated drained tests and undrained tests are carried on under saturated and remoulded conditions. The stress-strain characteristics of saturated soil are researched systematically under different confining pressure, initial dry density, initial water content, shearing rate and drainage condition. The inherent unity of diversity of shearing strength for the same samples measured by different experimental methods is indicated according to the normalization of critical state test results. And the failure lines in p ‘- q - ν space of remoulded saturated expansive soil under consolidated drained and undrained conditions are attained. The hyperbolic curve model can fit well the weak hardening stress-strain curves and the exponential curve model can fit the weak softening stress-strain curves. The test results can provide technical parameters and theoretical help for shearing strength variation of slope during rainfall and strength state of soil structure in normal water level

Physical Layer Security of Intelligent Reflective Surface Aided NOMA Networks

Intelligent reflective surface (IRS) technology is emerging as a promising performance enhancement technique for next-generation wireless networks. Hence, we investigate the physical layer security of the downlink in IRS-aided non-orthogonal multiple access networks in the presence of an eavesdropper, where an IRS is deployed for enhancing the quality by assisting the cell-edge user to communicate with the base station. To characterize the network's performance, the expected value of the new channel statistics is derived for the reflected links in the case of Nakagami-m fading. Furthermore, the performance of the proposed network is evaluated both in terms of the secrecy outage probability~(SOP) and the average secrecy capacity (ASC). The closed-form expressions of the SOP and the ASC are derived. We also study the impact of various network parameters on the overall performance of the network considered. To obtain further insights, the secrecy diversity orders and the high signal-to-noise ratio slopes are obtained. We finally show that: 1) the expectation of the channel gain in the reflected links is determined both by the number of IRSs and by the Nakagami- m fading parameters; 2)~The SOP of both receiver 1 and receiver 2 becomes unity, when the number of IRSs is sufficiently high; 3) The secrecy diversity orders are affected both by the number of IRSs and by the Nakagami-m fading parameters, whereas the high-SNR slopes are not affected by these parameters. Our Monte-Carlo simulations perfectly demonstrate the analytical results

Rapid evolutionary divergence of Gossypium barbadense and G. hirsutum mitochondrial genomes

Background The mitochondrial genome from upland cotton, G. hirsutum, was previously sequenced. To elucidate the evolution of mitochondrial genomic diversity within a single genus, we sequenced the mitochondrial genome from Sea Island cotton (Gossypium barbadense L.). Methods Mitochondrial DNA from week-old etiolated seedlings was extracted from isolated organelles using discontinuous sucrose density gradient method. Mitochondrial genome was sequenced with Solexa using paired-end, 90 bp read. The clean reads were assembled into contigs using ABySS and finished via additional fosmid and BAC sequencing. Finally, the genome was annotated and analyzed using different softwares. Results The G. barbadense (Sea Island cotton) mitochondrial genome was fully sequenced (677,434-bp) and compared to the mitogenome of upland cotton. The G. barbadensemitochondrial DNA contains seven more genes than that of upland cotton, with a total of 40 protein coding genes (excluding possible pseudogenes), 6 rRNA genes, and 29 tRNA genes. Of these 75 genes, atp1, mttB, nad4, nad9, rrn5, rrn18, and trnD(GTC)-cp were each represented by two identical copies. A single 64 kb repeat was largely responsible for the 9 % difference in genome size between the two mtDNAs. Comparison of genome structures between the two mitochondrial genomes revealed 8 rearranged syntenic regions and several large repeats. The largest repeat was missing from the master chromosome in G. hirsutum. Both mitochondrial genomes contain a duplicated copy of rps3 (rps3-2) in conjunction with a duplication of repeated sequences. Phylogenetic and divergence considerations suggest that a 544-bp fragment of rps3 was transferred to the nuclear genome shortly after divergence of the A- and D- genome diploid cottons. Conclusion These results highlight the insights to the evolution of structural variation between Sea Island and upland cotton mitochondrial genomes

Regulatory Effect of High-Protein Diet on Circadian Rhythm of Lipid Metabolism in Obese Mice

This study aimed to investigate the regulatory effect of high-protein diet on circadian rhythm disturbances of lipid metabolism in obese mice induced by high-fat diet. Totally 120 specific pathogen-free (SPF)-grade C57BL/6J mice were randomly divided into normal, high-fat and high-fat/high-protein groups. The metabolic status of mice was monitored at the 4th and 12th week of intervention, and mice were sacrificed at 2, 8, 14, and 20 o’clock after completion of feeding. Lipid levels in blood and liver, the expression of genes related to fat anabolism and catabolism and the expression of circadian rhythm-related genes were measured, and circadian rhythm changes were analyzed. The results showed that high-fat feeding caused an increase in body mass and obesity index and a decrease in voluntary activity and caloric expenditure during the active period. The changes were accompanied by dyslipidemia and an abnormal increase in liver lipid levels, manifested by continuous gene expression of acetyl-CoA carboxylase and fatty acid synthetase, key enzymes involved in fat anabolism in liver, at high levels during the active and resting periods, a slow increase in the gene expression of sensitive lipase and acetyl-CoA oxidase, key enzymes involved in fat catabolism in liver, and changes in the diurnal variation pattern. Compared with high-fat intervention, high-protein intervention significantly increased the amount of voluntary activity and energy expenditure during the active period, restored the expression rhythm of fat synthase that was higher during the active period and lower during the rest period, and resulted in high-level expression of ACOX, a key enzyme gene involved in fat catabolism, after ingestion, showing obvious circadian rhythms. Further analysis showed that the improvement effects of high-protein intervention on circadian rhythm disorders of lipid metabolism caused by high-fat diet were closely related to the regulation of the expression of two clock genes in liver, circadian locomotor output cycle kaput (CLOCK) and brain and muscle-Arnt-like protein 1 (BMAL1). In conclusion, high-protein diets can alleviate biological clock disorders in liver induced by high-fat diets and ameliorate hepatic lipid metabolism disorders in mice by stabilizing circadian rhythms

Activin A and BMP4 Signaling Expands Potency of Mouse Embryonic Stem Cells in Serum-Free Media.

Inhibitors of Mek1/2 and Gsk3β, known as 2i, and, together with leukemia inhibitory factor, enhance the derivation of embryonic stem cells (ESCs) and promote ground-state pluripotency (2i/L-ESCs). However, recent reports show that prolonged Mek1/2 suppression impairs developmental potential of ESCs, and is rescued by serum (S/L-ESCs). Here, we show that culturing ESCs in Activin A and BMP4, and in the absence of MEK1/2 inhibitor (ABC/L medium), establishes advanced stem cells derived from ESCs (esASCs). We demonstrate that esASCs contributed to germline lineages, full-term chimeras and generated esASC-derived mice by tetraploid complementation. We show that, in contrast to 2i/L-ESCs, esASCs display distinct molecular signatures and a stable hypermethylated epigenome, which is reversible and similar to serum-cultured ESCs. Importantly, we also derived novel ASCs (blASCs) from blastocysts in ABC/L medium. Our results provide insights into the derivation of novel ESCs with DNA hypermethylation from blastocysts in chemically defined medium