With the challenges brought by the expansion of network scale,as well as the diversity of the equipments and the complexity of network protocols,many self-configurable systems have been proposed combining formal speci...With the challenges brought by the expansion of network scale,as well as the diversity of the equipments and the complexity of network protocols,many self-configurable systems have been proposed combining formal specification and model finding techniques.In this paper,we pay more attention to formal specifications of network information,i.e.,exploring principles and algorithm to map network information(topology,devices and status,etc.) to Alloy specifications.We first model network information in relational form,which is easy to realize because of the structured feature of network information in nature.Then we map the relational data to Alloy specifications according to our novel data mapping principles and algorithm.Based on the transition of relational data,it is possible to automatically map network information to Alloy specifications.We evaluate our data mapping principles and algorithm by applying them to a practical application scenario.The results illustrate that we can find a model for the task within a tolerant time interval,which implies that our novel approach can convert relational data to Alloy specifications correctly and efficiently.展开更多
In the relentless quest for digital sovereignty, organizations face an unprecedented challenge in safeguarding sensitive information, protecting against cyber threats, and maintaining regulatory compliance. This manus...In the relentless quest for digital sovereignty, organizations face an unprecedented challenge in safeguarding sensitive information, protecting against cyber threats, and maintaining regulatory compliance. This manuscript unveils a revolutionary blueprint for cyber resilience, empowering organizations to transcend the limitations of traditional cybersecurity paradigms and forge ahead into uncharted territories of data security excellence and frictionless secrets management experience. Enter a new era of cybersecurity innovation and continued excellence. By seamlessly integrating secrets based on logical environments and applications (assets), dynamic secrets management orchestrates and automates the secrets lifecycle management with other platform cohesive integrations. Enterprises can enhance security, streamline operations, fasten development practices, avoid secrets sprawl, and improve overall compliance and DevSecOps practice. This enables the enterprises to enhance security, streamline operations, fasten development & deployment practices, avoid secrets spawls, and improve overall volume in shipping software with paved-road DevSecOps Practices, and improve developers’ productivity. By seamlessly integrating secrets based on logical environments and applications (assets), dynamic secrets management orchestrates and automates the application secrets lifecycle with other platform cohesive integrations. Organizations can enhance security, streamline operations, fasten development & deployment practices, avoid secrets sprawl, and improve overall volume in shipping software with paved-road DevSecOps practices. Most importantly, increases developer productivity.展开更多
While databases are widely-used in commercial user-facing services that have stringent quality-of-service(QoS)requirement,it is crucial to ensure their good performance and minimize the hardware usage at the same time...While databases are widely-used in commercial user-facing services that have stringent quality-of-service(QoS)requirement,it is crucial to ensure their good performance and minimize the hardware usage at the same time.Our investigation shows that the optimal DBMS(database management system)software configuration varies for different user request patterns(i.e.,workloads)and hardware configurations.It is challenging to identify the optimal software and hardware configurations for a database workload,because DBMSs have hundreds of tunable knobs,the effect of tuning a knob depends on other knobs,and the dependency relationship changes under different hardware configurations.In this paper,we propose SHA,a software and hardware auto-tuning system for DBMSs.SHA is comprised of a scaling-based performance predictor,a reinforcement learning(RL)based software tuner,and a QoS-aware resource reallocator.The performance predictor predicts its optimal performance with different hardware configurations and identifies the minimum amount of resources for satisfying its performance requirement.The software tuner fine-tunes the DBMS software knobs to optimize the performance of the workload.The resource reallocator assigns the saved resources to other applications to improve resource utilization without incurring QoS violation of the database workload.Experimental results show that SHA improves the performance of database workloads by 9.9%on average compared with a state-of-the-art solution when the hardware configuration is fixed,and improves 43.2%of resource utilization while ensuring the QoS.展开更多
基金supported by the National Science Foundation for Distinguished Young Scholars of China under Grant No.61225012 and No.71325002the Specialized Research Fund of the Doctoral Program of Higher Education for the Priority Development Areas under Grant No.20120042130003the Liaoning BaiQianWan Talents Program under Grant No.2013921068
文摘With the challenges brought by the expansion of network scale,as well as the diversity of the equipments and the complexity of network protocols,many self-configurable systems have been proposed combining formal specification and model finding techniques.In this paper,we pay more attention to formal specifications of network information,i.e.,exploring principles and algorithm to map network information(topology,devices and status,etc.) to Alloy specifications.We first model network information in relational form,which is easy to realize because of the structured feature of network information in nature.Then we map the relational data to Alloy specifications according to our novel data mapping principles and algorithm.Based on the transition of relational data,it is possible to automatically map network information to Alloy specifications.We evaluate our data mapping principles and algorithm by applying them to a practical application scenario.The results illustrate that we can find a model for the task within a tolerant time interval,which implies that our novel approach can convert relational data to Alloy specifications correctly and efficiently.
文摘In the relentless quest for digital sovereignty, organizations face an unprecedented challenge in safeguarding sensitive information, protecting against cyber threats, and maintaining regulatory compliance. This manuscript unveils a revolutionary blueprint for cyber resilience, empowering organizations to transcend the limitations of traditional cybersecurity paradigms and forge ahead into uncharted territories of data security excellence and frictionless secrets management experience. Enter a new era of cybersecurity innovation and continued excellence. By seamlessly integrating secrets based on logical environments and applications (assets), dynamic secrets management orchestrates and automates the secrets lifecycle management with other platform cohesive integrations. Enterprises can enhance security, streamline operations, fasten development practices, avoid secrets sprawl, and improve overall compliance and DevSecOps practice. This enables the enterprises to enhance security, streamline operations, fasten development & deployment practices, avoid secrets spawls, and improve overall volume in shipping software with paved-road DevSecOps Practices, and improve developers’ productivity. By seamlessly integrating secrets based on logical environments and applications (assets), dynamic secrets management orchestrates and automates the application secrets lifecycle with other platform cohesive integrations. Organizations can enhance security, streamline operations, fasten development & deployment practices, avoid secrets sprawl, and improve overall volume in shipping software with paved-road DevSecOps practices. Most importantly, increases developer productivity.
基金sponsored by the National Natural Science Foundation of China under Grant Nos.62022057,61832006,61632017,and 61872240.
文摘While databases are widely-used in commercial user-facing services that have stringent quality-of-service(QoS)requirement,it is crucial to ensure their good performance and minimize the hardware usage at the same time.Our investigation shows that the optimal DBMS(database management system)software configuration varies for different user request patterns(i.e.,workloads)and hardware configurations.It is challenging to identify the optimal software and hardware configurations for a database workload,because DBMSs have hundreds of tunable knobs,the effect of tuning a knob depends on other knobs,and the dependency relationship changes under different hardware configurations.In this paper,we propose SHA,a software and hardware auto-tuning system for DBMSs.SHA is comprised of a scaling-based performance predictor,a reinforcement learning(RL)based software tuner,and a QoS-aware resource reallocator.The performance predictor predicts its optimal performance with different hardware configurations and identifies the minimum amount of resources for satisfying its performance requirement.The software tuner fine-tunes the DBMS software knobs to optimize the performance of the workload.The resource reallocator assigns the saved resources to other applications to improve resource utilization without incurring QoS violation of the database workload.Experimental results show that SHA improves the performance of database workloads by 9.9%on average compared with a state-of-the-art solution when the hardware configuration is fixed,and improves 43.2%of resource utilization while ensuring the QoS.
