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Due to the huge capacities of computing and storage resources, wide-area distributed computing environment has become important infrastructures supporting computing power and data interconnection.In wide-area distributed computing environment, matching of tasks and resources is important to improve system performance.However, the diversity of tasks and resources and the geographical dispersion of resources increase the complexity of matching problems.To solve the problems of high response delay and low matching efficiency, a dynamic bidirectional matching method of tasks and resources oriented to wide-area distributed computing environments is proposed.The matching process is simplified and the response delay is mitigated by building a unified task requirement model and resource capability model.Moreover, the task-oriented and resource-oriented matching degrees are defined to express the preference of task-perspective and resource-perspective; the two-side comprehensive matching degree of tasks and resources is defined by the trade-off of the task-oriented and resource-oriented matching degree.The two-side comprehensive matching degrees are dynamically calculated for each task group and the resources to improve the matching quality.The experimental results show that the proposed method can effectively promoting the matching quality and significantly reduce the response delay compared with the existing methods.

Miniaturized fiber-optic magnetic field sensors have attracted considerable interest owing to their superiorities in anti-electromagnetic interference and compactness. However, the intrinsic thermodynamic properties of the material make temperature cross-sensitivity a challenging problem in terms of sensing accuracy and reliability. In this study, an ultracompact multicore fiber (MCF) tip sensor was designed to discriminatively measure the magnetic field and temperature, which was subsequently evaluated experimentally. The novel 3D printed sensing component consists of a bowl-shaped microcantilever and a polymer microfluid-infiltrated microcavity on the end-facet of an MCF, acting as two miniaturized Fabry-Perot interferometers. The magnetic sensitivity of the microcantilever was implemented by incorporating an iron micro ball into the microcantilever, and the microfluid-infiltrated microcavity enhanced the capability of highly sensitive temperature sensing. Using this tiny fiber-facet device in the two channels of an MCF allows discriminative measurements of the magnetic field and temperature by determining the sensitivity coefficient matrix of two parameters. The device exhibited a high magnetic field intensity sensitivity, approximately 1805.6 pm/mT with a fast response time of ~ 213 ms and a high temperature sensitivity of 160.3 pm/℃. Moreover, the sensor had a low condition number of 11.28, indicating high reliability in two-parameter measurements. The proposed 3D printed MCF-tip probes, which detect multiple signals through multiple channels within a single fiber, can provide an ultracompact, sensitive, and reliable scheme for discriminative measurements. The bowl-shaped microcantilever also provides a useful platform for incorporating microstructures with functional materials, extending multi-parameter sensing scenarios and promoting the application of MCFs.

For a multi-user integrated sensing and communication system in the network of vehicles, a robust sensing-assisted communication massive multiple-input multiple-output (MIMO) orthogonal time frequency space (OTFS) transmission scheme was proposed.Due to the limited sensing accuracy of the radar, errors existed in the channel state information (CSI) reconstructed based on sensing parameters.The transmission performance decreased as a result.To address this issue, the CSI in the delay doppler domain was reconstructed based on the sensing parameters by the transmitter firstly.And a robust beam forming scheme was designed considering the CSI error.Secondly, the channel estimation error and inter user interference were perceived by receivers based on sensing parameters.Then the robust receiver was designed by incorporating the perceived interference errors into the signal detector in an analytical way.Finally, numerical simulation results show that the proposed method effectively reduces the system bit error rate and increases the data reception rate of users.The proposed method improves the overall system performance in this situation.

In this article, a mid-infrared all-fiber light-induced thermoelastic spectroscopy (LITES) sensor based on a hollow-core anti-resonant fiber (HC-ARF) was reported for the first time. The HC-ARF was applied as a light transmission medium and gas chamber. The constructed all-fiber structure has merits of low loss, easy optical alignment, good system stability, reduced sensor size and cost. The mid-infrared transmission structure can be utilized to target the strongest gas absorption lines. The reversely-tapered SM1950 fiber and the HC-ARF were spatially butt-coupled with a V-shaped groove between the two fibers to facilitate gas entry. Carbon monoxide (CO) with an absorption line at 4291.50 cm−1 (2.33 µm) was chosen as the target gas to verify the sensing performance. The experimental results showed that the all-fiber LITES sensor based on HC-ARF had an excellent linear response to CO concentration. Allan deviation analysis indicated that the system had excellent long-term stability. A minimum detection limit (MDL) of 3.85 ppm can be obtained when the average time was 100 s

Interest grows in designing silicon-on-insulator slot waveguides to trap optical fields in subwavelength-scale slots and developing their optofluidic devices. However, it is worth noting that the inherent limitations of the waveguide structures may result in high optical losses and short optical paths, which challenge the device’s performance in optofluidics. Incorporating the planar silicon-based slot waveguide concept into a silica-based hollow-core fiber can provide a perfect solution to realize an efficient optofluidic waveguide. Here, we propose a subwavelength-scale liquid-core hybrid fiber (LCHF), where the core is filled with carbon disulfide and surrounded by a silicon ring in a silica background. The waveguide properties and the Stimulated Raman Scattering (SRS) effect in the LCHF are investigated. The fraction of power inside the core of 56.3% allows for improved sensitivity in optical sensing, while the modal Raman gain of 23.60 m−1·W−1 is two times larger than that generated around a nanofiber with the interaction between the evanescent optical field and the surrounding Raman media benzene-methanol, which enables a significant low-threshold SRS effect. Moreover, this in-fiber structure features compactness, robustness, flexibility, ease of implementation in both trace sample consumption and reasonable liquid filling duration, as well as compatibility with optical fiber systems. The detailed analyses of the properties and utilizations of the LCHF suggest a promising in-fiber optofluidic platform, which provides a novel insight into optofluidic devices, optical sensing, nonlinear optics, etc.

We optimized and fabricated an ultra-bend-resistant 4-core simplex cable (SXC) employing 4-core multicore fiber (MCF) suitable for short-reach dense spatial division multiplexing (DSDM) optical transmission in the O-band. The characteristics of transmission loss, macro-bending and cross-talk (XT) between adjacent cores after cabling were firstly clarified. By introducing the trapezoid index and optimizing the cabling process, the maximum values of added XT of 1.17 dB/km due to 10 loops with a bending radius of 6 mm imposed over the 4-core SXC and a macro-bending loss of 0.37 dB/10 turns were, respectively, achieved.P Then, the optical transmission with low bit error rate (BER) was presented using a 100GBASE-LR4 transceiver over the 1.2 km long 4-core SXC. The excellent bending resistance of the 4-core SXC may pave the way for a reduction in space pressure and increase in access density on short-reach optical interconnect (OI) based on DSDM.

Atherosclerosis (AS) is a chronic inflammatory disease, involving a pathological process of endothelial dysfunction, lipid deposition, plaque rupture, and arterial occlusion, and is one of the leading causes of death in the world population. The progression of AS is closely associated with several inflammatory diseases, among which periodontitis has been shown to increase the risk of AS. Porphyromonas gingivalis (P. gingivalis), presenting in large numbers in subgingival plaque biofilms, is the “dominant flora” in periodontitis, and its multiple virulence factors are important in stimulating host immunity. Therefore, it is significant to elucidate the potential mechanism and association between P. gingivalis and AS to prevent and treat AS. By summarizing the existing studies, we found that P. gingivalis promotes the progression of AS through multiple immune pathways. P. gingivalis can escape host immune clearance and, in various forms, circulate with blood and lymph and colonize arterial vessel walls, directly inducing local inflammation in blood vessels. It also induces the production of systemic inflammatory mediators and autoimmune antibodies, disrupts the serum lipid profile, and thus promotes the progression of AS. In this paper, we summarize the recent evidence (including clinical studies and animal studies) on the correlation between P. gingivalis and AS, and describe the specific immune mechanisms by which P. gingivalis promotes AS progression from three aspects (immune escape, blood circulation, and lymphatic circulation), providing new insights into the prevention and treatment of AS by suppressing periodontal pathogenic bacteria.

ObjectiveThe surgical management of lesions involving the lateral area of the suprasellar region, including the lateral aspect of the planum sphenoidale and the tight junction region of the optic canal (OC), anterior clinoid process (ACP), and internal carotid artery (ICA) and its dural rings, is extremely challenging. Here, these regions, namely, the “parasuprasellar” area, are described from the endonasal perspective. Moreover, the authors introduce two novels endoscopic endonasal supraoptic (EESO) and endoscopic endonasal infraoptic (EEIO) approaches to access the parasuprasellar area.MethodsSurgical simulation of the EESO and EEIO approaches to the parasuprasellar area was conducted in 5 silicon-injected specimens. The same techniques were applied in 12 patients with lesions involving the parasuprasellar area.ResultsThe EESO approach provided excellent surgical access to the lateral region of the planum sphenoidale, which corresponds to the orbital gyrus of the frontal lobe. With stepwise bone (OC, optic strut and ACP) removal, dissociation of the ophthalmic artery (OA) and optic nerve (ON), the EEIO approach enables access to the lateral region of the supraclinoidal ICA. These approaches can be used independently or in combination, but are more often employed as a complement to the endoscopic endonasal midline and transcavernous approaches. In clinical application, the EESO and EEIO approaches were successfully performed in 12 patients harboring tumors as well as multiple aneurysms involving the parasuprasellar area. Gross total and subtotal tumor resection were achieved in 9 patients and 1 patient, respectively. For two patients with multiple aneurysms, the lesions were clipped selectively according to location and size. Visual acuity improved in 7 patients, remained stable in 4, and deteriorated in only 1. No postoperative intracranial infection or ICA injury occurred in this series.ConclusionsThe EESO and EEIO approaches offer original treatment options for well-selected lesions involving the parasuprasellar area. They can be combined with the endoscopic endonasal midline and transcavernous approaches to remove extensive pathologies involving the intrasellar, suprasellar, sphenoid, and cavernous sinuses and even the bifurcation of the ICA. This work for the first time pushes the boundary of the endoscopic endonasal approach lateral to the supraclinoidal ICA and ON.

To solve the inter-symbol interference (ISI) and background noise challenges of molecular communication via diffusion (MCvD),four ISI-resistant signal-features were deployed,and a reliable non-coherent signal detection algorithm,which was insensitive to different types of molecular channel impulse response (CIR),was proposed.Also,an adaptive decision threshold and theoretical bound of bit error rate (BER) were deduced.Simulation results demonstrate a lower BER of the proposed non-coherent scheme compared to the state-of-the-art schemes in the same order of computational complexity,therefore suggesting its potential applications for future nano-scale MC.

Abstract In the past decade, artificial intelligence and Internet of things (IoT) technology have been rapid development, gradually began to integrate with each other, especially in coming 5G era. Admittedly, image recognition is the key technology due to a huge number of video cameras integrated in intelligent IoT equipment, such as driverless cars. However, the rapidly growing body of research in adversarial machine learning has demonstrated that the deep learning architectures are vulnerable to adversarial examples. Thus, the raises questions about the security of intelligent Internet of thing (IoT) and trust sensitive areas. This emphasizes the urgent need for practical defense technology that can be deployed to real-time combat attacks at any time. Well-crafted small perturbations lead to the misclassification of legitimate images by neural networks, but not the human visual system. It is worth noting that many attack strategies are designed to disrupt image pixels in a visually imperceptible manner. Therefore, we propose a new defense method and take full advantage of 5G high-speed bandwidth and mobile edge computing (MEC) effectively. We use singular value decomposition (SVD) which is the optimal approximation of matrix in the sense of square loss to eliminate the perturbation. We have conducted extensive and large-scale experiments with German Traffic Sign Recognition Benchmark (GTSRB) datasets and the results show that adversarial attacks, such as Carlini-Wagner’s l 2, Deepfool, and I-FSGM, can be better eliminated by the method and provide lower latency.

The Non-Volatile Memory Express (NVMe) SSD provides high I/O performance for current computer systems, and direct memory access (DMA) is the critical enabling mechanism for direct I/O. However, the lengthy I/O stack becomes a new bottleneck that degrades the potential of NVMe SSD. This paper reveals that existing user-level DMA introduces additional overhead for pinning memory used by DMA from the user space. Moreover, it cannot adapt to I/O requests of different data sizes. This paper proposes an efficient and dynamically adaptive user-level DMA (uDMA) mechanism that can adapt to I/O requests for different data sizes and lighten the I/O software stack by amortizing per-request latency. The critical component of uDMA is the pinned memory pool, which avoids frequently pinning new memory blocks by reusing allocated and pinned memory blocks. In addition, it effectively connects the discrete pinned memory blocks by the scatter/gather lists, improving the utilization of the pinned memory pool. Compared with the latest user-level DMA method, uDMA has an improvement of at least 17% under various data sizes.

An optimized multi-step index (MSI) 2-LP-mode fiber is proposed and fabricated with low propagation loss of 0.179 dB/km, low intermodal crosstalk and excellent bend resistance. We experimentally clarified the characteristics of backward Brillouin scattering (BBS) and forward Brillouin scattering (FBS) induced by radial acoustic modes (R0,m) in the fabricated MSI 2-LP-mode fiber, respectively. Via the use of this two-mode fiber, we demonstrated a novel discriminative measurement method of temperature and acoustic impedance based on BBS and FBS, achieving improved experimental measurement uncertainties of 0.2 °C and 0.019 kg/(s·mm2) for optoacoustic chemical sensing. The low propagation loss of the sensing fiber and the new measurement method based on both BBS and FBS may pave the way for long-distance and high spatial resolution distributed fiber sensors.

Surgery for pituitary adenomas (PAs) with cavernous sinus (CS) invasion in Knosp grade 4 is a great challenge and whether to adopt a conservative or aggressive surgical strategy is controversial. The aim of this study is to provide the outcomes and complications of an aggressive resection strategy for Knosp grade 4 PAs with transsphenoidal endoscopic surgery. Outcomes and complications were retrospectively analyzed in 102 patients with Knosp grade 4 PAs. Among them, primary PAs were seen in 60 patients and recurrent PAs were seen in 42 cases. Gross total resection (GTR) of the entire tumor was achieved in 72 cases (70.6%), subtotal tumor resection (STR) in 18 cases (17.6%), and partial tumor resection (PTR) in 12 cases (11.8%). Additionally, GTR of the tumor within the CS was achieved in 82 patients (80.4%), STR in 17 patients (16.7%), and PTR in 3 patients (2.9%). Statistical analyses showed that both recurrent tumors and firm consistency tumors were adverse factors for complete resection (P

BackgroundIt is well known that the clivus is composed of abundant cancellous bone and is often invaded by pituitary adenoma (PA), but the range of these cancellous bone corridors is unknown. In addition, we found that PA with clivus invasion is sometimes accompanied by petrous apex invasion, so we speculated that the petrous apex tumor originated from the clivus cancellous bone corridor. The aim of this study was to test this hypothesis by investigating the bony anatomy associated with PA with clival invasion and its clinical significance.MethodsTwenty-two cadaveric heads were used in the anatomical study to research the bony architecture of the clivus and petrous apex, including six injected specimens for microsurgical dissection and sixteen cadavers for epoxy sheet plastination. The surgical videos and outcomes of PA with clival invasion in our single center were also retrospectively reviewed.ResultsThe hypoglossal canal and internal acoustic meatus are composed of bone canals surrounded by cortical bone. The cancellous corridor within clivus starts from the sellar or sphenoid sinus floor and extends downward, bypassing the hypoglossal canal and finally reaching the occipital condyle and the medial edge of the jugular foramen. Interestingly, we found that the cancellous bone of the clivus was connected with that of the petrous apex through petroclival fissure extending to the medial margin of the internal acoustic meatus instead of a separating cortical bone between them as it should be. It is satisfactory that the anatomical outcomes of the cancellous corridor and the path of PA with clival invasion observed intraoperatively are completely consistent. In the retrospective cohort of 49 PA patients, the clival component was completely resected in 44 (89.8%), and only five (10.2%) patients in the early-stage had partial residual cases in the inferior clivus.ConclusionThe petrous apex invasion of PA is caused by the tumor invading the clivus and crossing the petroclival fissure along the cancellous bone corridor. PA invade the clivus along the cancellous bone corridor and can also cross the hypoglossal canal to the occipital condyle. This clival invasion pattern presented here deepens our understanding of the invasive characteristics of PA.

After the local outlier factor was first proposed, there is a large family of local outlier detection approaches derived from it. Since the existing approaches only focus on the extent of overall separation between an object and its neighbors, and ignore the degree of dispersion between them, the precision of these approaches will be affected by various degrees in the scattered datasets. In addition, the outlier data occupy a relatively small amount in the dataset, but the existing approaches need to perform local outlier factor calculation on all data during the outlier detection, which greatly reduces the efficiency of the algorithms. In this paper, we redefine a local outlier factor called local deviation coefficient (LDC) by taking full advantage of the distribution of the object and its neighbors. And then, we propose a safe non-outlier objects elimination approach named as rough clustering based on multi-level queries (RCMLQ) to preprocess the datasets to eliminate the non-outlier objects to the utmost. Finally, an efficient local outlier detection approach named as efficient density-based local outlier detection for scattered data (E2DLOS) is proposed based on the LDC and RCMLQ. The RCMLQ greatly reduces the amount of data that needs to be quantified for local outlier factor and the LDC is more sensitive to the degree of anomaly of the scattered datasets, and so the E2DLOS improves the existing local outlier detection approaches in time efficiency and detection accuracy. Experiments show that the LDC can better reflect the true abnormal situations of the data for the scattered datasets. And the RCMLQ can be used in parallel with the traditional methods of improving the efficiency of the nearest neighbor search, which can further improve the efficiency of the E2DLOS algorithm by about 16%.

The polarity conversion sequence directly determines polarity conversion efficiency and then affects polarity optimization efficiency. However, few studies have focused on the polarity conversion sequence problem of Reed-Muller (RM) circuits. In this paper, we propose a continuous Hopfield neural network (CHNN)-based polarity conversion algorithm (CHNNPCA) for Mixed Polarity RM (MPRM) circuits, which uses the CHNN to solve the best polarity conversion sequence of polarity set waiting for evaluation before converting the polarity set. Moreover, based on the CHNNPCA, a polarity optimization algorithm (POA) is proposed to improve the polarity optimization efficiency of MPRM circuits. The experimental results on MCNC benchmark circuits show that for the large-scale polarity set, the CHNNPCA is superior to the mixed polarity conversion algorithm based on the tabular technique in terms of polarity conversion efficiency. Furthermore, compared to the traditional polarity optimization algorithm neglecting polarity conversion sequence, the POA has a considerable advantage in improving polarity optimization efficiency, especially for large-scale circuits. The POA can be extended to improve the polarity optimization efficiency of fixed polarity RM circuits.

Logic minimization has recently attracted significant attention because in many applications it is important to have a compact representation as possible. In this paper, we propose a fast minimization algorithm (FMA) of fixed polarity Reed-Muller expressions (FPRMs). The main idea behind the FMA is to search the minimum FPRM with the fewest products by using the proposed binary differential evolution algorithm (BDE). The BDE can efficiently maintain population diversity and achieve a better tradeoff between the exploration and exploitation capabilities by use of proposed binary random mutation operator and improved selection operator. The experimental results on 24 MCNC benchmark circuits demonstrate that the FMA outperforms the genetic algorithm-based and simulated annealing genetic algorithm-based FPRMs minimization algorithms in terms of accuracy of solutions and solving efficiency. To the best of our knowledge, we are the first to use differential evolution algorithm to minimize FPRMs. The FMA can be extended to derive a minimum mixed polarity Reed-Muller expression.

Coupling losses for all-fiber integration of subwavelength core hybrid optical fibers have been first analyzed and optimized in detail. We have taken into account the effects of mode size, mode shape, effective refractive index, tapering beat length, interface, and endface reflections on the coupling loss. By optimizing parameters such as the subwave-length core diameter, single mode condition, and transition length, the coupling losses can be reduced. In addition, the influence of the core fabrication and misalignment tolerances have been explored. The results will benefit the all-fiber integration of hybrid optical fibers and their nanoengineering realization.

The integrity measurement method is used to detect whether the files are tampered with and to build a trusted environment. It can improve the security of virtual machines using base and increment image. Currently, the traditional integrity measurement methods (MDA-IMM) are based on the message digest algorithm with high computational complexity and heavy data. As a result, the MDA-IMM consumes a lot of I/O resources and spends too much time. To address those issues, we propose a novel method (COW-IMM) based on copy-on-write for the files in base image, the precondition is that, there is oneto-one correspondence between the cluster of image and the logic block of file system, and both of them have the same size. The COW-IMM gets the information of files for integrity measurement from base image and measures the integrity of files in increment image. We implement a prototype based on KVM, Qcow2 image, and Ext4. The algorithm analysis shows that, the volume of data used by COW-IMM is 512 times smaller than that used by MDA-IMM at least, if the file size is the same. The experimental evaluations show that, the speed of COW-IMM is faster and faster than that of MDA-IMM with the increment of file size. For example, when the file size is 0.1M, the speed of COW-IMM is about 10 times faster than that of MDA-IMM; when the file size is 90M, the speed of COW-IMM is about 592 times faster than that of MDA-IMM.

Based on the high-performance computing global virtual data space system, a wide-area collaborative scheduling system for big data processing applications was designed and implemented.This system can address the issue of how big data processing applications unified use wide-area storage and computing resources.And it can collaborative schedule of application data and computing tasks based on the computing characteristics of the application and data layout through collaborative scheduling, load balancing scheduling, data locality scheduling strategies.By unified scheduling of application data and computing tasks in the wide-area environment, it can coordinate the utilization of wide-area computing and storage resources, and effectively improve the running performance of big data processing applications.The actual test results in the national high-performance computing environment show that the scheduling method proposed can support big data processing applications effectively, and the running efficiency of typical applications such as wide-area target collaborative recognition and molecular docking can be increased by 3~4 times.

Aiming at the problem of a large amount of network bandwidth wasted by data redundancy transmission when the edge client accesses and shares remote data in the GVDS, the caching technology in the wide-area virtual data space system was studied and an edge caching mechanism to optimize the data access path was proposed.The data is cached at a file granularity close to the edge client, thereby improving the performance of upper-level applications to access and share data.The experimental results show that the edge cache system proposed can improve the performance of wide-area data sharing as a supplement to the GVDS.

Device-to-device (D2D) communication has become a key technology in the fifth-generation cellular networks. Resource allocation is critical to ensure satisfactory performance. However, most existing resource allocation policies focus on delay-unaware performance metrics, such as throughput and power consumption, thus being effective only in delay-insensitive scenarios. To overcome this problem, in this paper, we consider an orthogonal frequency division multiple access-based cellular network, where multiple cellular users and D2D pairs along with delay quality-of-service (QoS) requirements coexist to share multiple sub-channels. We propose an effective resource allocation and source adaptation policy to maximize the system throughput while satisfying each user's delay QoS requirement. Specifically, we formulate a constraint optimization problem and solve it using the Lagrangian approach. In the dual domain, the key problem is solving for the dual function under given dual variable. This is a mixed integer non-linear programming problem with non-concave function and is non-linearly coupled over layers, thus being very difficult to solve. In response, we propose effective algorithms based on an alternating optimization method, successive convex approximation method, and outer approximation method. Analysis on the convergence and optimality of the proposed algorithms is given. Simulation results show that our proposed policy can improve the QoS-guaranteed system throughput significantly compared with the baselines.

High-performance computing (HPC) environment is the core information infrastructure supporting national scientific and technological innovation, economic development and national defense construction.High-performance computing powers around the world have been building wide-area HPC environments based on multi-supercomputing center resources.However, in the high-performance computing environment, there are many kinds of resources and wide geographical distribution, which cannot effectively exert the aggregation effect of resources, and it is difficult to meet the requirements of large-scale applications for unified management and efficient access to wide-area distributed data.To this end, a complete set of technologies were proposed, which could be used to build wide-area global virtual data space, including virtual data space model, cross-domain virtual data space constructing, efficiently migrating data in a wide-area environment, co-scheduling of storage resources and computing job and cross-domain high concurrency data aggregation processing, etc.Based on the above, a virtual data space system has been developed for the national high-performance computing environment (NHPCE), which can effectively support the unified and efficient access to the wide area distributed heterogeneous storage resources, and the distributed data in the wide-area environment can be shared and cooperative processed in a cross-domain manner.At present, the system was experimental deployed in NHPCE and three typical large-scale applications, such as molecular docking, genome-wide association study and weather forecasting model, have been verified.The verification results show that the developed technology and software system can effectively aggregate the wide area distributed storage resources and meet the data space requirements of large-scale applications.

The wide-area high-performance computing environment is the core information infrastructure to support technology innovation, economic development, and national defense.However, heterogeneous storage resources are geographically distributed in wide-area high-performance computing environments, resulting in the barriers between applications and data.The requirements of unified data management and efficient data access cannot be met.A method of establishing virtual data space and a data access optimization method was presented, and a global virtual data space (GVDS) for wide-area high-performance computing environments to satisfy the requirements was implemented.GVDS aggregates geographically distributed and heterogeneous storage resources, creating a unified virtual data space to provide unified and efficient data access.Sharing and collaborative processing of geographically distributed data were achieved in widearea environments.The experimental results indicate that compared with the state-of-the-art wide-area storage system in the field of high-performance computing, such as OneData and GFFS, GVDS has similar functions and improves the read bandwidth significantly.

Fiber gas sensing techniques have been applied for a wide range of industrial applications. In this paper, the basic fiber gas sensing principles and the development of different fibers have been introduced. In various specialty fibers, hollow-core photonic crystal fibers (HC-PCFs) can overcome the fundamental limits of solid fibers and have attracted intense interest recently. Here, we focus on the review of HC-PCF gas sensing, including the light-guiding mechanisms of HC-PCFs, various sensing configurations, microfabrication approaches, and recent research advances including the mid-infrared gas sensors via hollow core anti-resonant fibers. This review gives a detailed and deep understanding of HC-PCF gas sensors and will promote more practical applications of HC-PCFs in the near future.

To effectively improve the throughput performance of secondary user in cognitive networks, a dual threshold based opportunistic spectrum access policy was proposed, which could be implemented under the condition that secondary user had non-ideal spectrum sensing capability. The proposed policy can take both channel quality information of secondary user and the inaccurate channel occupation information into account, to make secondary user access the channel in sensed idle and busy states with different channel quality thresholds. Based on this, the throughput performance of secondary user can be improved significantly by utilizing the transmission opportunities with good channel quality. With this policy, an optimization problem maximizing the effective throughput of secondary user with interference constraint for protecting primary user was formulated, and the optimal channel quality thresholds were derived under non-ideal spectrum sensing. Simulation results demonstrate the effective throughput performance of secondary user with non-ideal spectrum sensing capability can be improved significantly by implementing the proposed dual threshold based opportunistic spectrum access policy.

Second-order vector modes, possessing doughnut-shaped intensity distribution with unique polarization, are widely utilized in material micromachining, optical tweezers, and high-resolution microscopy. Since the hollow-core fiber can act as a flexible and robust optical waveguide for ultra-short pulse delivery and manipulation, high-order vector modes guided in hollow-core fibers will have huge potential in many advanced applications. We firstly reveal that a second-order vector mode can be well guided in a hollow-core antiresonant fiber with the suppression of the fundamental mode and other second-order vector modes at the red side of transmission band. We interpret our observation through a phase-matched coupling mechanism between core modes and coupled cladding modes. A single second-order vector mode such as TE01, TM01, or HE21 can be guided with low confinement loss at specific wavelengths with appropriate structure parameters. Our proposed hollow-core fibers have a modal engineering function which will open up a new avenue toward the single second-order vector mode propagation and its fiberized applications.

Botnet emulation,a new technology to investigate Botnet characteristics,gains increasing focus.The practical virtualization based Botnet emulation platform is few and lacks support of rapid deployment,multiple virtualization,specific features of the Botnet like Botnets' circadian random shutdown and starting,and high scalability which will greatly influence the Botnet propagation emulation effect.A Botnet emulation system and its scalability improvement technologies were introduced.Experiments show that the memory performance optimization and CPU performance optimization reduce more than 77% of host memory per virtual machine,the maximum virtual machines one physical machine can starts up increase from 15 to 43; the host CPU utility is deduced from 100% to 20% when the vCPU's performance is restricted to 100 000.

The I/O performance of big data storage system is one of the key factors that affect the overall performance of big data applications.The I/O performance optimization of big data storage system in storage system architecture,metadata I/O performance and data I/O performance was summarized,and some research directions of I/O performance optimization for big data storage systems in future were pointed out.

With the increasing scale of the melody database, the query-by-humming system faces the trade-offs between response speed and retrieval accuracy. Melody accurate matching is the key factor to restrict the response speed. In this paper, we present a GPU acceleration method for melody accurate matching, in order to improve the response speed without reducing retrieval accuracy. The method develops two parallel strategies (intra-task parallelism and inter-task parallelism) to obtain accelerated effects. The efficiency of our method is validated through extensive experiments. Evaluation results show that our single GPU implementation achieves 20x to 40x speedup ratio, when compared to a typical general purpose CPU’s execution time.

This paper presents results for delay and Doppler spread characterization in high-speed railway (HSR) hilly scenario. To investigate the propagation characteristics in this specific terrain, a measurement campaign is conducted along the “Guangzhou-Shenzhen” HSR in China. A wideband channel sounder with 40 MHz bandwidth is used to collect raw data at 2.4 GHz band. The delay spread and Doppler frequency features are analyzed based on measured data. It is found that there are abundant multipath components (MPCs) in this scenario. We present the relationship between the delay spreads and the transceiver distances. The measured route can be divided into four areas with different delay and Doppler characteristics. Finally, a tapped delay line (TDL) model is proposed to parameterize the channel responses in the HSR hilly environment, which is supposed to provide criterions for evaluations of the radio interface and development of wireless communication system.

Distributed MIMO (D-MIMO) system is one of the candidates for future wireless access networks. In this study, the spatial correlation and capacity in indoor D-MIMO system are presented. All results are from the actual channel measurements in typical indoor scenarios, including office and corridor. Based on measured data, spatial correlation coefficients between distributed transmitting antennas are analyzed. Although the literature about D-MIMO system assumes the small scale fading between distributed antennas is independent, we find that spatial correlation may still exist in specific propagation scenario. This correlation can also degrade the performance of D-MIMO system. To mitigate the impact of spatial correlation, one efficient method is to use transmitting antenna selection technique.

This paper focuses on the fading characteristics of wireless channel on High-Speed Railway (HSR) in hilly terrain scenario. Due to the rapid speed, the fading characteristics of HSR channel are highly correlated with time or Transmit-Receive distance and have their own special property. To investigate the fading characteristics, the measurement is conducted on the Guangzhou-Shenzhen passenger-dedicated line in China with the speed of 295 km/h in the data-collection area at 2.4 GHz. From the measured data, the amplitude of each path is estimated by using the Subspace-Alternating Generalized Expectation-Maximization (SAGE) algorithm along with other parameters of channel impulse responses. Then the fading parameters, including path loss, shadow fading, and K-factor, are analysed. With the numerical results in the measurement and analysis, the fading characteristics have been revealed and modelled. It is supposed that this work has a promotion for HSR communication system design and improvement.

Aircraft seems to be the last isolated island where the wireless access is still not available. In this paper, we consider the distributed multiple-input multiple-output (D-MIMO) system application based on measurements in aircraft cabin. The channel response matrices of in-cabin D-MIMO system are collected by using a wideband channel sounder. Channel capacities with optimum transmit antenna selections (TASs) are calculated from the measured data at different receiver positions. Then the optimum capacity results are compared to those without selection in different transmit SNR. It is shown that the TAS can lead obvious capacity gain, especially in the front and back of cabin. The capacity gain represents a decreasing trend with the transmit SNR increasing. The optimal transmit antenna subset is closely related to the transmit SNR. With the SNR increasing, more transmit antennas will be chosen for higher performance. The subset of those transmit antennas near the receiver is a reasonable choice in practical application of D-MIMO system.

We investigate the uplink of a power-controlled multi-user distributed antenna system (DAS) with antennas deployed on a circle. Applying results from random matrix theory, we prove that for such a DAS, the per-user sum rate and the total transmit power both converge as user number and antenna number go to infinity with a constant ratio. The relationship between the asymptotic per-user sum rate and the asymptotic total transmit power is revealed for all possible values of the radius of the circle on which antennas are placed. We then use this rate-power relationship to find the optimal radius. With this optimal radius, the circular layout DAS (CL-DAS) is proved to offer a significant gain compared with a traditional colocated antenna system (CAS). Simulation results are provided, which demonstrate the validity of our analysis.