Miracle-dz/UniFAR-FTUs huggingface dataset:
S3R5: A Snapshot Storage System Based on ROW with Rapid Rollback, Recovery and Read-Write

As an essential aspect of distributed storage system, reliability plays a very important role. Open-source storage systems are becoming more and more popular in both academia and industry, while their data protection capabilities are rather limited. This paper focuses on the research of S3R5, a snapshot storage system based on ROW with rapid rollback, recovery and read-write. We present a rapid rollback method, which redirects writing and updating to a new allocated storage area and provides high performance of rollback operation. We also present a rapid recovery method, called reverse data recovery, which could rebuilt hot data and index in DRAM. What's more, we present a rapid read-write method, called multi-level unsorted index, which provides high performance of read-write operation. The evaluations show that that compared with Ceph, our work can provide better performance in rollback operation up to 44.40%, recovery operation up to 59.29% and read-write operation up to 34.19%.
Enhanced TL-LEACH routing protocol for large-scale WSN applications

Routing sensor data from sensor node to base station is a challenging task in a wireless sensor network (WSN) application. The sensor nodes have a number of constraints such as limited energy, low memory, processing capabilities, etc. It is important to consider these constraints while designing a routing protocol so that the overall network lifetime and the data robustness may be efficiently maintained. This research focuses on improving the Two-Level Hierarchy for Low Energy Adaptive Clustering Hierarchy (TL-LEACH) protocol to provide energy efficiency; in terms of communication overhead and making the communication among the end-nodes, cluster-heads and base station as robust as possible. Two major drawbacks of the TL-LEACH protocol have been focused in this research that are mainly related to using the protocol for large-scale WSN and making the communication among the nodes robust. A novel cluster-head selection mechanism has been introduced to improve the energy-efficiency of the TL-LEACH and the new version has been named as Extended TL-LEACH (ETL-LEACH). The simulation results show that the ETL-LEACH performs better in terms of energy consumption, node lifetime and the communication delay has been decreased to a significant amount.
$ezswap$ : Enhanced Compressed Swap Scheme for Mobile Devices

The limited memory capacity of mobile devices leads to the popular use of compressed swap schemes, which reduce the I/O operations involving the swapping in and out of infrequently accessed pages. However, most of the current compressed swap schemes indiscriminately compress and store all swap-out pages. Considering that both energy and computing power are scarce resources in mobile devices, and modern applications frequently deal with already-compressed multimedia data, this blind approach may cause adverse impacts. In addition, they focus only on anonymous pages and not on file-mapped pages, because the latter are backed by on-disk files. However, our observations revealed that, in mobile devices, file-mapped pages consume significantly more memory than anonymous pages. Last but not least, most of the current compressed swap schemes blindly follow the least-recently-used (LRU) discipline when choosing the victim pages for replacement, not considering the compression ratio or data density of the cached pages. To overcome the aforementioned problems and maximize the memory efficiency, we propose a compressed swap scheme, called enhanced zswap (ezswap), for mobile devices. ezswap accommodates not only anonymous pages, but also clean file-mapped pages. It estimates the compression ratio of incoming pages with their information entropy, and selectively compresses and caches the pages only with beneficial compression ratios. In addition, its admission control and cache replacement algorithms are based on a cost-benefit model that considers not only the access recency of cached pages but also their information density and expected eviction cost. The proposed scheme was implemented in the Linux kernel for Android. Our evaluation with a series of commercial applications demonstrated that it reduced the amount of flash memory read by up to 55%, thereby improving the application launch time by up to 22% in comparison to the original zswap.
Finite-Time and Fixed-Time Consensus of Nonlinear Stochastic Multi-Agent Systems With ROUs and RONs via Impulsive Control

This paper discusses the finite-time and the fixed-time consensus of nonlinear stochastic multi-agent systems (NSMSs) with randomly occurring uncertainties (ROUs) and randomly occurring nonlinearities (RONs) in a leader-following framework. Nonlinear control and impulsive pinning control protocols are designed to guarantee that follower agents realize consensus with the leader agent in finite time(fixed time). Based on the finite-time and fixed-time consensus theory, stochastic analysis technique, comparison system theory and algebra graph theory, some sufficient conditions are proposed to guarantee the finite-time and fixed-time consensus of systems. Then, the setting times of finite-time consensus and fixed-time consensus are estimated. Finally, two simulation examples are presented to illustrate the correctness of our conclusions.
Direct power control of 12/8 Switched Reluctance Generator connected to single-phase electrical grid using the self-tuning FUZZY PI Controller

This paper presents the direct power control of the 12/8 switching reluctance generator (SRG) using the Fuzzy self-tuning PI controller. Initially were studied the operational principles of the machine and power electronics converter topology. Using the Matlab/Simulink simulation software, the authors implemented the model of switched reluctance machine using the current and its torque characteristic curves. To control the generated power by the machine and use its dynamic mathematical model, the authors implemented the Fuzzy self-tuning PI controller. Thus, it was designed a PI controller for DC-link’s control, as well as the P+resonant controller, in order to improve the generator response to the steady state injected power to the electrical grid. For this purpose, the authors used a single-phase two-level converter. The simulation results show the good performance of the proposed system.
Stackelberg Differential Game based Resource Allocation in Wireless Networks with Fog Computing

Fog computing is a kind of new calculation mode using numerous and mutually collaborative terminal devices or edge devices to provide services such as storage, computing etc. Fog computing extends the cloud computing to the edge of the network, solves the problems of cloud computing being limited to the aspects such as location awareness, weak mobility application adaptability, high service delay etc. In this paper, we investigate the resource allocation problem between the fog server and the end terminals in a fog computing based wireless networks, where resources transactions exist between the fog server and the terminals. The Stackelberg game is used to formulate the transaction relationships, the fog server acts as the leader, which control the price for the resource transactions. The terminals act as the followers, and control their available resources. Meanwhile, the energy state of the networks is formulated based on the differential game. Then the resource allocation problem can be considered as a Stackelberg differential game. We use the feedback Nash equilibriums solution to the proposed game as the optimal solutions. We also give some numerical simulations and results for how to allocate the resources based on the proposed algorithms.
Dynamic Model of Soil Moisture for Smart Irrigation Systems

In geographical areas subject to an arid climate, one of the most precious resources is water, which often get wasted due to inefficient irrigation systems. Automated irrigation systems which relies on closed loop control and feedback from sensors can help to closely match the water supply to the crop demand and avoid waste. In recent years, predictive control strategies were proposed for high tech watering systems which rely heavily on complex models incorporating variables such as crop water demand, soil evapotranspiration, weather conditions etc. Through these models it is possible to anticipate the water demand of the crop, and give optimal irrigation scheduling with a significant reduction in water consumption. In this paper we developed a model of the soil moisture dynamics based on climatological data of the Kingdom of Bahrain. The model, which is based on the hydraulic balance approach, was validated by comparing its estimated output with real measurements.
Joint Computing and Radio Resource Allocation in C-RAN Systems Under Imperfect CSI

Cloud radio access network (C-RAN) is a promising solution for future wireless network due to easy cooperation among remote radio heads (RRHs) and concentrated management in baseband unit (BBU) pool. Virtual machine(VM) in the BBU pool provides computation ability to different users(UE). However, the advantages of centralized scheduling needs to accurately understand the channel state information(CSI) of the served users, which is hard to get due to quantization error, estimation error, etc. In this paper, we focus on the joint radio and computing resource allocation under imperfect CSI, which is more practical. By jointly optimizing beamforming vector, RRH selection and VM-UE computation resource mapping under the constraint of limited fronthaul and imperfect CSI, we aim to minimize the network power consumption (NPC) in both RRHs and BBU pool. Due to the existence of unknown channel error, the number of SINR constraint is uncertain. We propose a simple two-stage iterative algorithm to solve the problem. Firstly, by fixing RRH selection, we solve the two subproblem: RRH beamforming problem and VM-UE computing resource mapping problem. Then the problem is solved by finding best RRH selection to obtain the minimum NPC. Simulation results suggest that our proposed robust radio and computing resource allocation algorithm can improve the system performance and save energy.
swCPD: Optimizing Canonical Polyadic Decomposition on Sunway Manycore Architecture

Canonical Polyadic Decomposition (CPD) is one of the most popular methods in tensor decomposition and plays an important role in big data analysis. For sparse tensor, the major computation procedure in CPD, known as matricized tensor times Khatri-Rao product (MTTKRP), exhibits discontiguous memory access and becomes the performance bottleneck from achieving high performance on emerging processor architectures. In this paper, we propose swCPD, an efficient CPD implementation on the many-core Sunway architecture. The main idea adopted in swCPD is a hierarchical partitioning mechanism. From the computation perspective, the 64 CPEs are divided into eight groups, each group contains seven workers and one controller. From the data perspective, we partition the sparse tensor into different granularities including blocks, bands and tiles. Moreover, we develop a communication mechanism through register communication for cooperation between CPEs. We evaluate our implementation with both synthesized and real-world datasets, which achieves better performance than two cutting-edge CPD implementations.
Distribution Characteristics of Fragments Size and Optimization of Blasting Parameters Under Blasting Impact Load in Open-Pit Mine

The size distribution characteristics of fragments formed after loose blasting in open-pit mine will directly affect the economic benefits of the mining enterprise. The impact load test of coal samples with pressure ranging from 0.13MPa to 2.0MPa was carried out by using the split Hope Pressure Bar Test System (SHPB). Based on the theory of stress wave attenuation, the relationship between blasting load and coal samples impact test in the laboratory is established. It is concluded that with the increase of impact pressure, the degree of coal samples breakage increases gradually. According to the requirement of blasting quality in open-pit mine, it is concluded that the impact pressure range with good crushing effect is 0.30MPa ≤P ≤0.90 MPa. Based on image recognition method, the fragmentation distribution characteristics of loose deposits of coal seam blasting in open-pit mine are obtained. Combining the impact load test in the laboratory and the fragmentation distribution of coal seam blasting, the influence area of blasting impact fragmentation is divided. According to the research results, two optimization schemes of blasting parameters are put forward and the blasting effect of the two schemes is verified by numerical simulation using ANSYS/LSDYNA. Through field blasting optimization test in open-pit mine, it is concluded that increasing blasting hole spacing and row spacing can effectively control dust pollution and increase massive coal rate.
Cognitive Virtual Network Topology Reconfiguration Method Based on Traffic Prediction and Link Importance

With the increase of network services, how to avoid link congestion and make full use of limited bandwidth resources in network virtualization environment have become the key challenges. In this paper, we introduce the cognitive method into virtual network topology reconfiguration and modify the connectivity to reach the target topology by sensing the traffic. Then, we formulate an optimization problem to maximize the ratio of cumulative saved resources to the square of changed link number (CSR/SCLNR) and determine which virtual link to be added or deleted. Finally, a heuristic algorithm called cognitive virtual network topology reconfiguration method based on traffic prediction and link importance (CVNTRM-TPLI) is proposed to solve this optimization problem. In the CVNTRM-TPLI, the link importance is presented in link deletion as the topological factor to avoid the ping pang effect. Also, a hybrid traffic prediction algorithm based on optimal parameter selection is put forward, where immune optimization is introduced to select the optimal parameters and the virtual network topology can react promptly to the traffic fluctuation without adding or deleting virtual link frequently. Simulation results show that the CVNTRM-TPLI not only has the highest CSR/SCLNR, but also solves the link congestion and makes full use of the limited bandwidth resources.
Towards Using a 2D Magneto-Optical Trap to Improve a Mercury Optical Lattice Clock

We report on the recent improvements of the mercury optical lattice clock based on 199Hg operating at LNESYRTE. In particular we describe how the exploitation of a 2D Magneto Optical Trap (2D-MOT) allowed us to increase significantly the number of useful atoms gathered in a given time. As a consequence we were able to decrease the loading time of the mercury optical lattice clock, so as the cycle time, that is the main factor of the Dick effect.
Training Design and Two Stage Channel Estimation for Correlated Two-Way MIMO Relay Systems under Colored Disturbance

In this paper, we propose a two stage channel estimation scheme and the training signal design in correlated twoway multiple-input-and-multiple-output (MIMO) relay systems under colored disturbance. We propose a novel forward channel estimators and the related training signal, where the estimated backwardchannelsandthestatisticalknowledgeoftheestimation error are taken into the derivation. For training signal design at the second stage, we propose a novel criterion which minimizes the relaxation of the total asymptotic mean square error (MSE) of the forward channel estimators, which is conditioned on the estimated backward channels. Based on the criterion, we propose the novel structure of the training signal. Finally, the numerical results show that the proposed training signal can improve the MSE performance under both high and low spatial correlation channels.
Analysis on the Propulsion of Ionic Wind During Corona Discharge in Various Electrode Configuration with High Voltage Sources

Corona Discharge (CD) in high tension wires is often considered as loss in the form of power loss, insulation failure and audible noise. The present study aims at showing the ability of CD to be used as Ionic Thruster (IT) in an electrode combination. Individual experiments were conducted on each set of electrodes (plate to plate, sphere to sphere, wire to plate & sphere to plate) with three distinct High Voltage (HV) sources (Neon Sign Transformer (NST), Cockcroft Walton Multiplier (CWM) and fly back transformer) to analyze and compare their effect on the ionic wind propulsion. After comparing the developed mathematical models for electric field and mechanical characteristics of 12 combinations of electrodes with HV sources, it highlight that the best geometrical configuration is the wire to plate Dielectric Barrier Discharge (DBD). It allows to induce ionic wind jet with max velocity of 3.75 m/s with potential radius of 176 mm. This article had also fruitful results for future research and development in the field of ionic propulsion, medical treatment of asthma patients and cooling methods for electronic devices.
A Multi-Objective Localization Algorithm with Real Average Distance in WSN

Location information is an essential requirement in wireless sensor networks (WSN), many wireless sensor applications would be limited without location information. Distance vector-hop (DV-Hop), as a typical path-dependence algorithm, utilizes the connectivity and multi-hop transmission for estimated positioning. However, a large positioning error is caused because of its simple and rough estimated method. In this work, we analyze the defects of the existing traditional single-objective and multi-objective model based on DV-Hop algorithm, and provide a multi-objective localization model based on the real average estimated distance of all beacon nodes. Then, we solve it using the multi-objective optimization algorithm (NSGA-II), and named it RAMGA-DV-Hop. Eventually, we tested it with different aspects, and the simulation results confirm our method significantly outperforms the DV-Hop and OCS-LC-DV-Hop. Moreover, compare with existing multi-objective localization algorithms, such as NSGAII-DV-Hop, its overall performance also has advantages.
Stuck-at-OFF Fault Analysis in Memristor-Based Architecture for Synchronization

Nonlinear circuits may be interconnected and organized in networks to couple their dynamics and achieve synchronization, a process that is commonly observed in nature. Recent works have shown that memristors may be used as coupling elements in synchronization applications. However, these devices may suffer from low endurance and thus switching faults. Hence, evaluating redundancy and adaptive properties against possible device failures is important. In this direction, we study the performance of a network of chaotic circuits that are coupled using memristors organized in a crossbar geometry. This topology is analyzed in terms of robustness while assuming the existence of defective coupling devices. Our simulation results, based on a physics-based model of bipolar memristor, demonstrate the adaptive behavior of the crossbar architecture and show evidence of different network topologies whose performance outperforms that of the fully functional crossbar.
Anomaly Detection of Passenger OD on Nanjing Metro Based on Smart Card Big Data

Urban metro alleviates traffic pressure and also faces safety management problems. The metro AFC (Automatic Fare Collection System) records the OD (Origin-Destination) data of passengers’ daily trips. Many researches often neglect the pretreatment of data cleaning based on smart card data. Anomaly OD records also reflect the safety problems. How to use OD to identify anomalous data and passengers’ anomalous behavior is a research hotspot of metro big data. OD data of Nanjing metro were analyzed, and standard data cleaning processes were proposed including inbound records until the day before yesterday, inbound records of next days, negative records and overtime records. Then, using the data after cleaning, we analyze long-time records, short-time records, inbound and outbound records between the same stations, the swiping card records of more times, and carry out analysis. One day is chosen as an example to illustrate the analysis process, and then the OD records of several days are compared to summarize the classification of OD anomalies. Through analysis, OD anomalies can be classified into two categories: system anomalies and passenger behavior anomalies. System anomalies can be eliminated by upgrading. Abnormal passenger behavior reflects some potential safety problems. This research can effectively identify the abnormal behavior of passengers by tracking and comparing the appearing frequency of passenger cards. OD anomaly classification can be further refined, so that it has more practical value, can improve the level of metro safety management.
Interference and Topology-Aware VM Live Migrations in Software-Defined Networks

Live migration of virtual machines (VMs) serves as the key technique that enables the resource management, server maintenance, and load balancing in cloud datacenters, while introducing a sufficient amount of performance degradation to both the source and destination physical machines (PMs) during and after the migration. Existing works generally focus on either minimizing the VM migration time (or downtime) or reducing the performance degradation for an individual VM migration from the host aspect. Jointly optimizing the performance of multiple concurrent VM migrations and the performance interference among VMs from the network aspect, however, receives comparably little attention. Leveraging the benefits of Software-Defined Network (SDN), in this paper, we propose ITEM, an Interference and Topology-awarE VM live Migration strategy to minimize the overall VM migration cost, which jointly optimizes the VM migration time during the migration and the VM performance interference after the migration. Specifically, our ITEM strategy seeks to decide the optimal migration destination PM, the migration path, and the allocated network bandwidth for a single migration (ITEM-S) and a set of concurrent migrations (ITEM-M). Extensive experiments using OpenFlow in the Mininet virtual network environment show that our ITEM strategy can significantly reduce the migration cost and improve the network bandwidth utilization, in comparison to the state-of-the-art VM migration strategies, yet with acceptable runtime overhead.