As cloud computing gains widespread adoption, cloud storage services have become the primary means of data management for users. Authenticated data structures (ADS) are a novel computational model designed to address ...
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As cloud computing gains widespread adoption, cloud storage services have become the primary means of data management for users. Authenticated data structures (ADS) are a novel computational model designed to address data authentication problems in distributed environments. With the growing demand for robust data security, vulnerability detection in storage systems has become a critical area of focus to ensure resilience against potential threats. However, traditional ADS, while ensuring consistency between cloud data and source data, have limitations in handling dynamic data operations on multiple types of files, storage space expansion, and single-point failure issues. To tackle these issues, this paper proposes a blockchain-assisted classifiable data auditing scheme with dynamic operations. First, trapdoor hash functions are used to construct a binary tree. During dynamic data operations, the impact of hash updates is confined to a subset of nodes, ensuring global stability and reducing computational resource consumption. Second, innovative data structures and verification mechanisms are introduced, reducing the risk of single-point failures by decentralizing the dependency on verification paths. Finally, data types are confirmed based on data identifiers, and corresponding path information is recorded, enabling efficient and rapid dynamic operations on specific types of files within multi-source data. Both security analysis and performance assessment demonstrate that BCDAS conducts data auditing for with reliability and efficiency.
Software reuse enables developers to reuse architecture, programs and other software artifacts. Realizing a systematical reuse in software brings a large amount of benefits for stakeholders, including lower maintenanc...
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Restricted by their energy storage mechanism,current energy storage devices have certain drawbacks,such as low power density for batteries and low energy density for ***,the nearest ion capacitors,such as lithium-ion ...
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Restricted by their energy storage mechanism,current energy storage devices have certain drawbacks,such as low power density for batteries and low energy density for ***,the nearest ion capacitors,such as lithium-ion and sodium-ion capacitors containing battery-type and capacitor-type electrodes,may allow achieving both high energy and power *** the inspiration,a new zinc-ion capacitor(ZIC)has been designed and realized by assembling the free-standing manganese dioxide-carbon nanotubes(MnO2-CNTs)battery-type cathode and MXene(Ti3C2Tx)capacitortype anode in an aqueous *** ZIC can avoid the insecurity issues that frequently occurred in lithium-ion and sodium-ion capacitors in organic *** expected,the ZIC in an aqueous liquid electrolyte exhibits excellent electrochemical performance(based on the total weight of cathode and anode),such as a high specific capacitance of 115.1 F g?1(1 mV s?1),high energy density of 98.6 Wh kg?1(77.5 W kg?1),high power density of 2480.6 W kg?1(29.7 Wh kg?1),and high capacitance retention of^83.6%of its initial capacitance(15,000 cycles).Even in an aqueous gel electrolyte,the ZIC also exhibits excellent *** work provides an essential strategy for designing next-generation high-performance energy storage devices.
The cloud computing paradigm is featured by its ability to offer elastic computational resource provisioning patterns and deliver on-demand and versatile services. It's thus getting increasingly popular to build b...
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ISBN:
(数字)9781728187891
ISBN:
(纸本)9781728187907
The cloud computing paradigm is featured by its ability to offer elastic computational resource provisioning patterns and deliver on-demand and versatile services. It's thus getting increasingly popular to build business process and workflow-based applications upon cloud computing platforms. However, it remains a difficulty to guarantee cost-effectiveness and quality of service of cloud-based workflows because real-world cloud services are usually subject to real-time performance variations or fluctuations. Existing researches mainly consider that cloud are with constant performance and formulate the scheduling decision-making as a static optimization problem. In this work, instead, we consider that scientific computing processes to be supported by decentralized cloud infrastructures are with fluctuating QoS and aim at managing the monetary cost of workflows with the completion-time constraint to be satisfied. We address the performance-trend-aware workflow scheduling problem by leveraging a time-series-based prediction model and a Critical-Path-Duration-Estimation-based (CPDE for short) scheduling strategy. The proposed method is capable of exploiting real-time trends of performance changes of cloud infrastructures and generating dynamic workflow scheduling plans. To prove the effectiveness of our proposed method, we build a large-prime-number-generation workflow supported by real-world third-party commercial clouds and show that our method clearly beats existing approaches in terms of cost, workflow completion time, and Service-Level-Agreement (SLA) violation rate.
Given base classes with sufficient labeled samples, the target of few-shot classification is to recognize unlabeled samples of novel classes with only a few labeled samples. Most existing methods only pay attention to...
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GCC compiler is a retargetable compiler program that was developed to increase the efficiency of programs in the GNU system. In recent years, compiler optimization based on data dependency analysis has become an impor...
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An integration of satellites and terrestrial networks is crucial for enhancing performance of next generation communication systems. However, the networks are hindered by the long-distance path loss and security risks...
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Recently published graph neural networks (GNNs) show promising performance at social event detection tasks. However, most studies are oriented toward monolingual data in languages with abundant training samples. This ...
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In this paper, we study a distributed privacy-preserving learning problem in social networks with general topology. The agents can communicate with each other over the network, which may result in privacy disclosure, ...
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Docker has been widely adopted in production environment, but unfortunately deployment and cold-start of container are limited by the low speed of disk. The emerging non-volatile memory (NVM) technology, which has hig...
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