The document describes the architecture of the CUBRID database system. It consists of a database server, broker, and client modules. The database server processes queries and manages objects. The broker relays communication between the server and clients. Key components of the server and client modules include transaction management, storage management, object management, query processing, and communication between clients and servers. The architecture follows a multi-threaded client-server model to allow concurrent access and processing of requests from multiple clients.
Analysis of a Pool Management Scheme for Cloud Computing Centres by Using Par...IJERA Editor
A monolithic model may suffer from and poor scalability due to large number of parameters. A cloud user may
submit a super task at once. The user request is sent to the global queue and then to the Resource Assigning
Module (RAM). A number of heterogeneous server pools placed in the RAM. First is Hot, in which the servers
will be handling the jobs currently, second is Warm, in which the servers are kept in ideal state, then Finally
Cold, in which the servers are Turned Off state. Initially the request is send to Hot, if those servers are busy the
request is forwarded to warm, then finally if required to Cold if both the hot and warm server pools are busy.
The user submitted supertask may split so that the individual task run on different physical machines, this is
called as partial acceptance policy. So the supertask rejection ratio will be reduced.
Wide area frequency easurement system iitbPanditNitesh
This project report discusses improvements made to a wide area frequency measurement system. It describes receiving streaming frequency data from multiple sensors over UDP, validating the data, and storing it in a MySQL database for online analysis and display. The system threads data reception and constraint checking, calculates a hash value for storage order, and inserts validated data into the database along with error logging. Future work may include interpolation of frequencies, daily triggers, and threading for improved performance.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Kerberos is an authentication protocol that allows nodes communicating over a non-secure network to prove their identity to one another in a secure manner. It is integral to Windows 2000 Active Directory implementations. The document describes the Kerberos authentication process, which involves an initial authentication service exchange, a ticket-granting service exchange, and a client/server exchange between the user and domain controllers. It also discusses key concepts like tickets, ticket-granting tickets, and how Kerberos handles authentication in mixed and multi-domain environments.
HTTP is the protocol that allows sending documents back and forth on the web. It uses a client-server model where clients initiate interactions by sending requests to servers, which then respond. Requests use methods like GET, POST, PUT, and DELETE and include headers and an optional body. Responses include headers, like Content-Type, and a body. REST is an architectural style that uses HTTP to build applications by representing resources with URLs and manipulating them via representations. It applies constraints like using a client-server architecture, stateless communication, caching, and a uniform interface.
Analysis of quality of service in cloud storage systemsijfcstjournal
Data replication is generally used for increasing
accessibility, availability, performance and scalability
of database systems. For implementing data replication mechanisms, we encounter with some consistency
problems.One of the important problems for implementing data replication mechanism is consistency. In this paper,
the performance tradeoffs of consistency models for semi-active data replication protocol in distributed systems
are analyzed.A brief deliberation about consistency models in data replication is shown.Research on how client-centric guarantees relate to data-centric models is discussed.How guaranteeing conditions of data -centric consistency models and client-centric consistency models is provided, is also analyzed.Analysis of the consistency models guarantee in terms of multi-client and single
client for the semi-active data replication protocol without failure and leader death is presented. The experimental results show that semi-active data replication protocol is appropriate for distributed systemsby multi- client replication such as web services.
The document discusses message-driven beans and Java Messaging Service (JMS). It defines synchronous and asynchronous messaging and explains the need for messaging in software design. It describes JMS elements like the messaging server, clients, and destinations. It provides examples of configuring topic and queue destinations. It also provides examples of message-driven beans that can consume from topics and queues, and JMS client code that acts as producers to topics and queues.
A New Security Model For Distributed SystemSanoj Kumar
The document proposes a new collaborative trust and enhanced security model for distributed systems. It introduces components like a SuperHost, Key Distribution Center (KDC), agents, clients, and servers. The SuperHost acts as a central controller and authenticates clients. An agent system balances server loads and provides client references. Clients are authenticated through the KDC before requesting services from load-balanced servers. The proposed model enhances security and performance in distributed systems through collaborative authentication and load balancing.
Analysis of a Pool Management Scheme for Cloud Computing Centres by Using Par...IJERA Editor
A monolithic model may suffer from and poor scalability due to large number of parameters. A cloud user may
submit a super task at once. The user request is sent to the global queue and then to the Resource Assigning
Module (RAM). A number of heterogeneous server pools placed in the RAM. First is Hot, in which the servers
will be handling the jobs currently, second is Warm, in which the servers are kept in ideal state, then Finally
Cold, in which the servers are Turned Off state. Initially the request is send to Hot, if those servers are busy the
request is forwarded to warm, then finally if required to Cold if both the hot and warm server pools are busy.
The user submitted supertask may split so that the individual task run on different physical machines, this is
called as partial acceptance policy. So the supertask rejection ratio will be reduced.
Wide area frequency easurement system iitbPanditNitesh
This project report discusses improvements made to a wide area frequency measurement system. It describes receiving streaming frequency data from multiple sensors over UDP, validating the data, and storing it in a MySQL database for online analysis and display. The system threads data reception and constraint checking, calculates a hash value for storage order, and inserts validated data into the database along with error logging. Future work may include interpolation of frequencies, daily triggers, and threading for improved performance.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Kerberos is an authentication protocol that allows nodes communicating over a non-secure network to prove their identity to one another in a secure manner. It is integral to Windows 2000 Active Directory implementations. The document describes the Kerberos authentication process, which involves an initial authentication service exchange, a ticket-granting service exchange, and a client/server exchange between the user and domain controllers. It also discusses key concepts like tickets, ticket-granting tickets, and how Kerberos handles authentication in mixed and multi-domain environments.
HTTP is the protocol that allows sending documents back and forth on the web. It uses a client-server model where clients initiate interactions by sending requests to servers, which then respond. Requests use methods like GET, POST, PUT, and DELETE and include headers and an optional body. Responses include headers, like Content-Type, and a body. REST is an architectural style that uses HTTP to build applications by representing resources with URLs and manipulating them via representations. It applies constraints like using a client-server architecture, stateless communication, caching, and a uniform interface.
Analysis of quality of service in cloud storage systemsijfcstjournal
Data replication is generally used for increasing
accessibility, availability, performance and scalability
of database systems. For implementing data replication mechanisms, we encounter with some consistency
problems.One of the important problems for implementing data replication mechanism is consistency. In this paper,
the performance tradeoffs of consistency models for semi-active data replication protocol in distributed systems
are analyzed.A brief deliberation about consistency models in data replication is shown.Research on how client-centric guarantees relate to data-centric models is discussed.How guaranteeing conditions of data -centric consistency models and client-centric consistency models is provided, is also analyzed.Analysis of the consistency models guarantee in terms of multi-client and single
client for the semi-active data replication protocol without failure and leader death is presented. The experimental results show that semi-active data replication protocol is appropriate for distributed systemsby multi- client replication such as web services.
The document discusses message-driven beans and Java Messaging Service (JMS). It defines synchronous and asynchronous messaging and explains the need for messaging in software design. It describes JMS elements like the messaging server, clients, and destinations. It provides examples of configuring topic and queue destinations. It also provides examples of message-driven beans that can consume from topics and queues, and JMS client code that acts as producers to topics and queues.
A New Security Model For Distributed SystemSanoj Kumar
The document proposes a new collaborative trust and enhanced security model for distributed systems. It introduces components like a SuperHost, Key Distribution Center (KDC), agents, clients, and servers. The SuperHost acts as a central controller and authenticates clients. An agent system balances server loads and provides client references. Clients are authenticated through the KDC before requesting services from load-balanced servers. The proposed model enhances security and performance in distributed systems through collaborative authentication and load balancing.
This presentation reveals many important aspects of the CUBRID Database, including its unique features, future roadmap, comparison with other databases, architecture, etc.
CUBRID HA - Guaranteed Way to Never-Die Web Services - OSCON 2011CUBRID
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive function. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms.
This document provides step-by-step instructions for installing CUBRID database server on Windows. It outlines 14 steps for completing the installation, which include downloading the installer, selecting installation options like destination directory and setup type, accepting license agreements, viewing compatibility information, selecting additional options, reviewing the installation summary, and completing the installation process. The document also recommends installing sample databases and provides links for help resources.
Research Inventy : International Journal of Engineering and Scienceresearchinventy
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
Data Dictionary Similarities Discussion.docxstudywriters
1. A data dictionary is a set of read-only tables that provide key information about the database such as definitions of schema objects, space allocation, and integrity constraints.
2. Common data dictionary views are DBA_TABLES, DBA_TAB_COLUMNS, and DBA_ALL_TABLES which describe tables, columns, and both relational and object tables respectively.
3. A client-server architecture contains clients that request services and servers that fulfill requests, with processing traditionally located on mainframe computers and clients using terminals.
The document describes client-server and peer-to-peer architecture styles. Client-server architecture divides an application into two parts - the client and the server. The client makes requests to the server which processes requests and returns results. Common client-server structures include 2-tier with a database server and client, and 3-tier with an additional middle tier. Peer-to-peer architecture has no servers or clients - each node can request and provide services to other nodes on the network.
Review on tls or ssl session sharing based web cluster load balancingeSAT Journals
Abstract Internet users increase the traffic on the servers and server security is the major concern with which the user’s privacy needs to be protect. TLS (Transport Layer Security) is a widely deployed protocol that establishes a secure channel between communicating parties over the internet. But TLS/SSL has huge impact on webserver’s performance by degrading it to a considerable amount. When TLS/SSL session is generated it is broadcasted to all servers in the cluster with which session reuse can be used to save time in negotiation. TLS Handshake and Session resume is occur at the server end so in future if client requests again and its session is not expired then it can again joins that its own session without renegotiating which saves the session initialization time. Ultimately a new load balancing cluster design is proposed that can share TLS sessions in the cluster to effectively improve the performance of TLS web cluster. The web cluster server shares the sessions of users within the cluster. The another technique for improving the latency and throughput of the server SSL/TLS with backend forwarding technique is compare and is analyzed. The traditional method has flaws in the load balancing of the server but with the new implanted technique on the server improves the performance during the high load .The results are reviewed with 16 and 32 node cluster system. With new technique the latency of system has been decreased by the 40 % and throughput of the system is extremely better than classical balancing technique. Keywords: TLS/SSL session sharing, Web cluster, TLS/SSL session reuse
Review on tls or ssl session sharing based web cluster load balancingeSAT Publishing House
This document summarizes a research paper that proposes a new technique for improving load balancing and performance in TLS/SSL web clusters. The technique shares TLS/SSL sessions across servers in the cluster so that if a client reconnects, the session can be reused without renegotiating. This saves time compared to establishing a new session. The document outlines how TLS/SSL works, how traditional load balancing can degrade performance under high loads, and how the proposed technique of sharing sessions within a cluster improves requests per second by 40-60% compared to no session sharing. It also compares the new technique to using SSL with backend forwarding and finds it reduces latency by 40% and improves throughput.
Chapter 3-Process in distributed system.pptAschalewAyele2
1. A process is a program currently being executed on a virtual processor, while threads allow for parallel execution within a process and represent individual flows of control.
2. Virtualization allows processes to run concurrently and be highly portable across hardware by mimicking interfaces. It also helps isolate failures.
3. Process migration can help achieve scalability and dynamically configure clients and servers. Multithreaded servers improve performance by exploiting parallelism across threads.
Kerberos is a network authentication protocol that provides secure authentication for client/server applications. It uses secret-key cryptography and relies on a trusted third party called the Key Distribution Center (KDC) which is aware of all systems on the network. Kerberos introduces tickets that allow a client access to a server after initial authentication with the KDC. The authentication process involves the client receiving a ticket-granting ticket from the KDC and then exchanging messages with the ticket-granting service and target server to gain access.
This document discusses Java networking and the client-server model. It explains that Java socket programming allows sharing of data between devices using protocols like TCP and UDP. Sockets are bound to port numbers to identify applications. The client-server model involves clients sending requests and servers sending responses. Examples of Java code for a simple client and server are also provided.
This document discusses load balancing in cloud computing. It begins with an introduction to cloud computing and discusses how load balancing can improve user satisfaction and resource utilization by evenly distributing tasks across resources. It then describes different types of load balancing algorithms like round robin, equally spread current execution, min-min, and max-min algorithms. It also covers dynamic load balancing approaches like ant colony optimization and honeybee foraging behavior algorithms. The document concludes by comparing various load balancing algorithms based on metrics like throughput, fault tolerance, response time, overhead, and scalability. Load balancing is important for cloud computing to efficiently allocate dynamic workloads across nodes and improve performance.
DYNAMIC ALLOCATION METHOD FOR EFFICIENT LOAD BALANCING IN VIRTUAL MACHINES FO...acijjournal
This paper proposes a Dynamic resource allocation method for Cloud computing. Cloud computing is a model for delivering information technology services in which resources are retrieved from the internet through web-based tools and applications, rather than a direct connection to a server. Users can set up
and boot the required resources and they have to pay only for the required resources. Thus, in the future providing a mechanism for efficient resource management and assignment will be an important objective of Cloud computing. In this project we propose a method, dynamic scheduling and consolidation mechanism that allocate resources based on the load of Virtual Machines (VMs) on Infrastructure as a service (IaaS). This method enables users to dynamically add and/or delete one or more instances on the basis of the load and the conditions specified by the user. Our objective is to develop an effective load balancing algorithm using Virtual Machine Monitoring to
maximize or minimize different performance parameters(throughput for example) for the Clouds of
different sizes (virtual topology de-pending on the application requirement).
A Distributed Control Law for Load Balancing in Content Delivery NetworksSruthi Kamal
1. The document presents a novel load balancing algorithm for content delivery networks that aims to minimize load imbalance and metric movement costs.
2. It proposes estimating system state through probability distributions of node capacities and load to help peers schedule transfers without centralized control.
3. Each peer independently manipulates partial system information and reassigns virtual servers based on the approximated system state.
The document discusses session tracking techniques in servlets. It describes four main techniques: cookies, hidden form fields, URL rewriting, and HTTP sessions. Cookies are the simplest technique and involve assigning a unique session ID to each client as a cookie. Hidden form fields maintain state by storing information in hidden form fields and transmitting it across requests. URL rewriting appends a session ID to the URL. HTTP sessions involve saving client-specific information on the server side in an HTTP session object.
The document proposes a scheme for secure access to outsourced databases in cloud computing environments. It uses a modified row-based encryption technique where each database row is encrypted with a separate key. The scheme also uses client-side memory and selective encryption to increase performance. A modified Diffie-Hellman key exchange algorithm is used to establish secure communication between the cloud service provider and users, inhibiting malicious outsiders. The scheme aims to overcome security challenges like information leakage, key management, revocation handling and user authentication that exist in current solutions for securing outsourced databases.
This presentation reveals many important aspects of the CUBRID Database, including its unique features, future roadmap, comparison with other databases, architecture, etc.
CUBRID HA - Guaranteed Way to Never-Die Web Services - OSCON 2011CUBRID
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive function. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms.
This document provides step-by-step instructions for installing CUBRID database server on Windows. It outlines 14 steps for completing the installation, which include downloading the installer, selecting installation options like destination directory and setup type, accepting license agreements, viewing compatibility information, selecting additional options, reviewing the installation summary, and completing the installation process. The document also recommends installing sample databases and provides links for help resources.
Research Inventy : International Journal of Engineering and Scienceresearchinventy
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
Data Dictionary Similarities Discussion.docxstudywriters
1. A data dictionary is a set of read-only tables that provide key information about the database such as definitions of schema objects, space allocation, and integrity constraints.
2. Common data dictionary views are DBA_TABLES, DBA_TAB_COLUMNS, and DBA_ALL_TABLES which describe tables, columns, and both relational and object tables respectively.
3. A client-server architecture contains clients that request services and servers that fulfill requests, with processing traditionally located on mainframe computers and clients using terminals.
The document describes client-server and peer-to-peer architecture styles. Client-server architecture divides an application into two parts - the client and the server. The client makes requests to the server which processes requests and returns results. Common client-server structures include 2-tier with a database server and client, and 3-tier with an additional middle tier. Peer-to-peer architecture has no servers or clients - each node can request and provide services to other nodes on the network.
Review on tls or ssl session sharing based web cluster load balancingeSAT Journals
Abstract Internet users increase the traffic on the servers and server security is the major concern with which the user’s privacy needs to be protect. TLS (Transport Layer Security) is a widely deployed protocol that establishes a secure channel between communicating parties over the internet. But TLS/SSL has huge impact on webserver’s performance by degrading it to a considerable amount. When TLS/SSL session is generated it is broadcasted to all servers in the cluster with which session reuse can be used to save time in negotiation. TLS Handshake and Session resume is occur at the server end so in future if client requests again and its session is not expired then it can again joins that its own session without renegotiating which saves the session initialization time. Ultimately a new load balancing cluster design is proposed that can share TLS sessions in the cluster to effectively improve the performance of TLS web cluster. The web cluster server shares the sessions of users within the cluster. The another technique for improving the latency and throughput of the server SSL/TLS with backend forwarding technique is compare and is analyzed. The traditional method has flaws in the load balancing of the server but with the new implanted technique on the server improves the performance during the high load .The results are reviewed with 16 and 32 node cluster system. With new technique the latency of system has been decreased by the 40 % and throughput of the system is extremely better than classical balancing technique. Keywords: TLS/SSL session sharing, Web cluster, TLS/SSL session reuse
Review on tls or ssl session sharing based web cluster load balancingeSAT Publishing House
This document summarizes a research paper that proposes a new technique for improving load balancing and performance in TLS/SSL web clusters. The technique shares TLS/SSL sessions across servers in the cluster so that if a client reconnects, the session can be reused without renegotiating. This saves time compared to establishing a new session. The document outlines how TLS/SSL works, how traditional load balancing can degrade performance under high loads, and how the proposed technique of sharing sessions within a cluster improves requests per second by 40-60% compared to no session sharing. It also compares the new technique to using SSL with backend forwarding and finds it reduces latency by 40% and improves throughput.
Chapter 3-Process in distributed system.pptAschalewAyele2
1. A process is a program currently being executed on a virtual processor, while threads allow for parallel execution within a process and represent individual flows of control.
2. Virtualization allows processes to run concurrently and be highly portable across hardware by mimicking interfaces. It also helps isolate failures.
3. Process migration can help achieve scalability and dynamically configure clients and servers. Multithreaded servers improve performance by exploiting parallelism across threads.
Kerberos is a network authentication protocol that provides secure authentication for client/server applications. It uses secret-key cryptography and relies on a trusted third party called the Key Distribution Center (KDC) which is aware of all systems on the network. Kerberos introduces tickets that allow a client access to a server after initial authentication with the KDC. The authentication process involves the client receiving a ticket-granting ticket from the KDC and then exchanging messages with the ticket-granting service and target server to gain access.
This document discusses Java networking and the client-server model. It explains that Java socket programming allows sharing of data between devices using protocols like TCP and UDP. Sockets are bound to port numbers to identify applications. The client-server model involves clients sending requests and servers sending responses. Examples of Java code for a simple client and server are also provided.
This document discusses load balancing in cloud computing. It begins with an introduction to cloud computing and discusses how load balancing can improve user satisfaction and resource utilization by evenly distributing tasks across resources. It then describes different types of load balancing algorithms like round robin, equally spread current execution, min-min, and max-min algorithms. It also covers dynamic load balancing approaches like ant colony optimization and honeybee foraging behavior algorithms. The document concludes by comparing various load balancing algorithms based on metrics like throughput, fault tolerance, response time, overhead, and scalability. Load balancing is important for cloud computing to efficiently allocate dynamic workloads across nodes and improve performance.
DYNAMIC ALLOCATION METHOD FOR EFFICIENT LOAD BALANCING IN VIRTUAL MACHINES FO...acijjournal
This paper proposes a Dynamic resource allocation method for Cloud computing. Cloud computing is a model for delivering information technology services in which resources are retrieved from the internet through web-based tools and applications, rather than a direct connection to a server. Users can set up
and boot the required resources and they have to pay only for the required resources. Thus, in the future providing a mechanism for efficient resource management and assignment will be an important objective of Cloud computing. In this project we propose a method, dynamic scheduling and consolidation mechanism that allocate resources based on the load of Virtual Machines (VMs) on Infrastructure as a service (IaaS). This method enables users to dynamically add and/or delete one or more instances on the basis of the load and the conditions specified by the user. Our objective is to develop an effective load balancing algorithm using Virtual Machine Monitoring to
maximize or minimize different performance parameters(throughput for example) for the Clouds of
different sizes (virtual topology de-pending on the application requirement).
A Distributed Control Law for Load Balancing in Content Delivery NetworksSruthi Kamal
1. The document presents a novel load balancing algorithm for content delivery networks that aims to minimize load imbalance and metric movement costs.
2. It proposes estimating system state through probability distributions of node capacities and load to help peers schedule transfers without centralized control.
3. Each peer independently manipulates partial system information and reassigns virtual servers based on the approximated system state.
The document discusses session tracking techniques in servlets. It describes four main techniques: cookies, hidden form fields, URL rewriting, and HTTP sessions. Cookies are the simplest technique and involve assigning a unique session ID to each client as a cookie. Hidden form fields maintain state by storing information in hidden form fields and transmitting it across requests. URL rewriting appends a session ID to the URL. HTTP sessions involve saving client-specific information on the server side in an HTTP session object.
The document proposes a scheme for secure access to outsourced databases in cloud computing environments. It uses a modified row-based encryption technique where each database row is encrypted with a separate key. The scheme also uses client-side memory and selective encryption to increase performance. A modified Diffie-Hellman key exchange algorithm is used to establish secure communication between the cloud service provider and users, inhibiting malicious outsiders. The scheme aims to overcome security challenges like information leakage, key management, revocation handling and user authentication that exist in current solutions for securing outsourced databases.
This document discusses concepts related to client-server computing and database management systems (DBMS). It covers topics such as DBMS concepts and architecture, centralized and distributed systems, client-server systems, transaction servers, data servers, parallel and distributed databases, and network types. Key points include the definitions of centralized, client-server, and distributed systems. Transaction servers and data servers are described as two types of server system architectures. Issues related to parallelism such as speedup, scaleup, and factors limiting them are also covered.
An in-building multi-server cloud system based on shortest Path algorithm dep...IOSR Journals
This document summarizes a proposed in-building multi-server cloud system based on the shortest path algorithm. The system would allow for mobile client nodes to upload and access data from the closest of multiple upload stations located throughout an office building. It describes using Bluetooth as the wireless transmission medium between nodes and stations. The stations would be interconnected to allow data access from any station. An application would determine the nearest station for each upload and encrypt data during transmission and storage for security.
This document describes a proposed multi-server cloud system within a building based on determining the nearest server using the shortest path algorithm. The system has multiple upload stations that act as servers, and client nodes that can be mobile. When a client tries to upload data, the system intelligently finds the nearest upload station based on the client's location and measured signal strength. Data is encrypted during transmission and storage for security. The design includes a client application that allows users to login, access files and more. Data structures like dictionaries and lists are used to store user and file information in text files on the upload stations.
This document provides an overview of client-server computing. It defines client-server computing as a distributed computing model where client applications request services from server processes that run on different interconnected computers. The document discusses key aspects of client-server systems including the roles of clients and servers, examples, design considerations like thin vs fat clients and stateful vs stateless servers, and how distributed object computing is an extension of the client-server model.
A brief report on Client Server Model and Distributed Computing. Problems and Applications are also discussed and Client Server Model in Distributed Systems is also discussed.
SOFTWARE AS A SERVICE – COMMON SERVICE BUS (SAAS-CSB)IJCSEA Journal
This document summarizes a research paper on a proposed Software as a Service - Common Service Bus (SaaS-CSB) architecture. The proposed system uses multiple CSBs to allow multiple producers to efficiently send data to multiple receivers simultaneously, overcoming delays from single CSB approaches. A SaaS-CSB portal is used to monitor, consume and manage applications running on multiple clouds. Compared to existing single CSB systems, the proposed multi-CSB approach improves performance, scalability, and redundancy while reducing operational costs. Future work may explore enhancing the system in PaaS and IaaS environments with improved security and customer engagement features.
Database Sharding the Right Way: Easy, Reliable, and Open source - HighLoad++...CUBRID
The presentation the CUBRID team presented at Russian HighLoad++ Conference in October, 2012. The presentation covers the topic of Big Data management through Database Sharding. CUBRID open source RDBMS provides native support for Sharding with load balancing, connection pooling, and auto fail-over features.
Installing CUBRID Database and CUBRID Manager on WindowsCUBRID
This document provides commands to control the CUBRID database service - cubrid service start starts the service, cubrid service stop stops it, cubrid service restart restarts the service, and cubrid service status checks the status of the service.
Growing in the Wild. The story by CUBRID Database Developers.CUBRID
The presentation the CUBRID team presented at Russian Internet Technologies Conference in 2012. The presentation covers such questions as *WHY* CUBRID was developed, *WHY* the developers did not fork existing solutions, *WHY* it was necessary to develop a new RDBMS from scratch, and *HOW* CUBRID Database was evolved over the years.
The document describes CUBRID Cluster, a project to enable CUBRID database to scale out across multiple servers. Key points:
- The goal is to provide dynamic scalability, location transparency, and increased volume/performance compared to a single CUBRID database.
- The design includes a global schema, distributed data partitioning across nodes, global transactions, and dynamic scalability through adding/removing nodes.
- Milestones included implementing the global schema, distributed partitioning, performance improvements, and dynamic scalability features.
- Demo and performance testing showed increased throughput from data and query distribution across multiple servers compared to a single CUBRID database.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
OpenID AuthZEN Interop Read Out - AuthorizationDavid Brossard
During Identiverse 2024 and EIC 2024, members of the OpenID AuthZEN WG got together and demoed their authorization endpoints conforming to the AuthZEN API
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
Infrastructure Challenges in Scaling RAG with Custom AI modelsZilliz
Building Retrieval-Augmented Generation (RAG) systems with open-source and custom AI models is a complex task. This talk explores the challenges in productionizing RAG systems, including retrieval performance, response synthesis, and evaluation. We’ll discuss how to leverage open-source models like text embeddings, language models, and custom fine-tuned models to enhance RAG performance. Additionally, we’ll cover how BentoML can help orchestrate and scale these AI components efficiently, ensuring seamless deployment and management of RAG systems in the cloud.
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
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Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
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Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
2. CONTENTS
1. Introduction ____________________________________________________________________ 3
1.1 Overall Architecture of the CUBRID System _______________________________________________5
1.2 Process Architecture ______________________________________________________________________6
1.2.1 CONNECTION CONFIGURATION ______________________________________________________7
2. Broker __________________________________________________________________________ 8
2.1 The cub_broker Process __________________________________________________________________8
2.2 The cub_cas Process _____________________________________________________________________8
3. Client and Server Modules_____________________________________________________ 10
3.1 Module Configuration______________________________________________________________________11
3.1.1 TRANSACTION MANAGEMENT COMPONENT __________________________________________11
3.1.2 SERVER STORAGE MANAGEMENT COMPONENT ______________________________________13
3.1.3 CLIENT STORAGE MANAGEMENT COMPONENT _______________________________________14
3.1.4 OBJECT MANAGEMENT COMPONENT ________________________________________________15
3.1.5 CLIENT-SERVER COMMUNICATIONS__________________________________________________17
3.1.6 THREAD MANAGEMENT COMPONENT ________________________________________________18
3.1.7 QUERY PROCESSING _______________________________________________________________18
3.2 Detailed Description for the Modules ______________________________________________________19
3.2.1 TRANSACTION MANAGEMENT COMPONENT __________________________________________19
3.2.2 OBJECT MANAGEMENT COMPONENT ________________________________________________21
3.2.3 QUERY PROCESSING _______________________________________________________________22
3. CUBRID is an object-relational database management system (DBMS) consisting of the Database Server, the Broker,
and the CUBRID Manager.
As the core component of the CUBRID Database Management System, the Database Server saves and manages
data in a multi-threaded client/server architecture. The Database Server processes the queries entered by users
and manages objects in the database. The CUBRID Database Server provides seamless transactions using locking
and logging methods even when multiple users use the database at the same time. It also supports database
backup and restore for the operation.
The Broker is a CUBRID-specific middleware that relays the communication between the Database Server and
external applications. It provides functions including connection pooling, monitoring, and log tracing and analysis.
The CUBRID Manager is a GUI tool that manages database and broker. It also provides the Query Editor, a tool
that allows users to execute SQL queries on the Database Server.
The basic configuration of CUBRID is shown in Figure 1 below.
1.Introduction
5. 1. Introduction
1.1 Overall Architecture of the CUBRID System
Figure 2. Overall Architecture of the CUBRID System
Figure 2 shows the overall architecture of the CUBRID system.
The CUBRID system follows the client/server model that allows multiple applications to access the same database
simultaneously. The client module (the Broker in Figure 2) and the server module (the Server in Figure 2) on separate
systems (computers) are connected through a network. Even when a broker and a server on the same system are
connected, the same architecture as above is configured because they are connected via socket IPC. A server
performs the requests from multiple clients in a single process/multi-threaded environment, and each server process
manages one database.
The client module analyzes SQL queries on the database from users or applications and executes them to the
optimization level. Then it generates a query plan tree and sends it to the server. And it receives the execution results
from the server by using the cursor navigation and delivers them to the users or applications. The client caches object
instances from the database to its memory to provide fast access to data by using the query execution results or
directly by users/applications. In addition, it caches locks as well as objects from the server for concurrency control.
The execution of triggers or methods specified by users or applications is also performed in the client module.
The server module receives and processes requests from the client module (e.g., object requests or query execution
requests from a query execution tree) and then returns the query execution results. The server can execute the
requests from multiple clients in a single process/multi-threaded environment. To support multiple client modules with
the appropriate number of threads, the server threads are allocated to each broker request, not to each broker. The
server performs input and output operations for database and log volume and provides a file access method to the
database volume in a file or page. In addition, it manages page buffer in a memory and uses a B+-tree index to
6. 1. Introduction
increase retrieval speed. The server also provides concurrency control, deadlock detection, and failover between
multiple transactions.
1.2 Process Architecture
Figure 3. Process Architecture of the CUBRID System
Figure 3 shows the process architecture of the CUBRID system. In the server host, there can be one master process
(cub_master) and more than one database server process (cub_server). Each client process (cub_cas) that exists in
multiple broker hosts connects to each single database server process.
The cub_broker process allocates cub_cas, passes a connection and manages cub_cas for a connect request from an
application. The cub_cas process executes database queries from the application.
7. 1. Introduction
1.2.1 Connection Configuration
The cub_cas process connects to the defined connection port number of the master process. The master process
checks whether the requested database server is running; the connection request is rejected if the server is not
running. If the requested database server is running, the master process passes the connected socket to the requested
server process. Then, the server process communicates with the client process (cub_cas) directly through the socket.
The database server process connects to the master process's port and then registers its server name (database
name) and establishes a UNIX Domain Socket (or Named Pipe) connection to the master process. In this connection,
the master process passes a socket descriptor to the client (cub_cas); the connection is maintained for server
shutdown and other future operations. After the connection between the server and client processes (cub_cas) is
established, the server process allocates threads for each client request and performs tasks.
Master Process (cub_master)
1. Checks whether other master process is running by connecting to cubrid_port_id
2. Switches to the demon process, opens a socket to the port defined as cubrid_port_id, and waits for the connection
between the client and the server.
3. Registers a server name and establishes a UNIX domain socket connection to the server process if the connection
is from the database server process.
4. Passes the connected socket number (socket descriptor) to the database server requested by the client to
establish a socket connection between the client and the server if it is connected from the client process (cub_cas).
Database Server Process (cub_server)
1. Connects to the designated port of the master process. If the connection fails, the connection attempt is aborted,
assuming that the master process is not running.
2. Registers its server name (database name) to the master process if the connection to the master process is
established. At this time, if a server with the same name already exists, the registration is rejected, and the server
is terminated.
3. Creates a UNIX Domain socket (or Named Pipe), sends a connection path (socket file path) to the master process
and terminates the socket connection to the designated port when the master process is connected.
4. Waits for task requests from the connected client. At this time, a connection relay of a new client from the master
process is processed, if any.
5. Accepts requests from the connected client and performs tasks by allocating threads.
Client Process (cub_cas)
1. Connects to the master process that exists on a remote or local server through the port defined as cubrid_port_id.
2. Sends the name of the database to connect when the connection to the master process is established and checks
whether the database server process is registered and running. At this time, the connection is rejected if there is no
corresponding server.
3. Receives response messages directly from the server because the master process passes the socket connection
between the client and the master process to the corresponding server process.
8. The Broker is a middleware that relays the communication between the database server and applications. It consists of
cub_broker and cub_cas.
2.1 The cub_broker Process
The cub_broker process allocates cub_cas, passes a connection and manages cub_cas for a connection request from
an application. cub_broker has a multi-threaded architecture and consists of the following threads:
main
This thread creates other threads and manages the number of cub_cas processes. It increases or decreases the
number of cub_cas processes depending on the number of requests in the job queue.
receiver_thread
As a thread waiting for the accept() system call, this thread puts a connection request from an application into the
job queue.
dispatch_thread
This thread finds cub_cas available to allocate to the connection requests in the job queue and passes the
connection to cub_cas.
cas_monitor_thread
If cub_cas is abnormally terminated, this thread restarts cub_cas.
2.2 The cub_cas Process
The cub_cas process executes database queries from an application and has a single thread architecture. This
process connects to the database server when it receives a “connection” request from an application and calls a
function corresponding to the request from the application. After the connection with the application is terminated, this
process can receive a connection from another application. When disconnecting an application, the connection to the
database server is not terminated. If next application uses the same database as the current one, the existing
database connection is reused.
Depending on the application's connection status, cub_cas has four statuses: IDLE, BUSY, CLIENT WAIT, or CLOSE
WAIT.
- IDLE: No connection is made to an application.
- BUSY: A connection is made to an application, and the request from the application is being processed.
2.Broker
9. 2. Broker
- CLIENT WAIT: A request from an application is waited for, and a transaction is being processed.
- CLOSE WAIT: A request from an application is waited for but a transaction has been terminated. If the
connection between cub_cas and an application is disconnected in this status, the application attempts
reconnection.
The cub_cas process waits for the select() call after a connection to the application is established and processes each
function passed by the application. Main functions that respond to requests from an application are as follows:
fn_end_tran
This function performs commit/rollback. If KEEP_CONNECTION is set to off in the cubrid_broker.conf file, it
terminates the connection the application when a transaction is terminated; establishes a new connection when a
new transaction starts. If KEEP_CONNECTION is set to auto, the status of cub_cas changes to CLOSE_WAIT
when a transaction is terminated. In this case, if the application connected to cub_cas has not sent a new request,
and a new application has sent a "connection" request, the cub_broker process can select the cub_cas whose
status is CLOSE_WAIT to terminate the connection to the previous application and send a request to cub_cas
asking for the connection to a new application.
fn_prepare
This function processes a prepare request from an application. It compiles the queries, creates a handle for the
compiled query and sends it to the application. Then, the application sends an execution request by using the
created handle. After the queries are compiled, if they are the SELECT queries, meta information on columns is
extracted and sent to the application.
fn_execute
This function executes a prepared query statement. If the query statement is SELECT, it sends the query results
as the specified buffer size and sends the query execution results for other query statements. If JDBC RESULT
CACHE is in use and the executed query already exists in JDBC RESULT CACHE, this function determines
whether the stored query results can be reused. If they can be reused, the query results are not sent. Instead,
only a flag indicating reusability is sent to the JDBC.
fn_fetch
This function copies the query results of the SELECT statement as the specified buffer size and sends them to an
application.
10. This chapter describes the components of the entire server (hereinafter, the server) and the native C API & other
modules (hereinafter, the client) in the Client Library of the Broker as shown in Figure 4.
Figure 4. Detailed Architecture of the CUBRID System
3. Client and Server Modules
11. 3. Client and Server Modules
3.1 Module Configuration
The CUBRID client and server modules consist of the following components:
Transaction Management Component
Handles system transactions across the client and server (including system failover).
Server Storage Management Component
Accesses and manages database and log volume on the server (including page buffering).
Client Storage Management Component
Allocates and manages a workspace for the object cache and access on the client.
Object Management Component
Defines a class object, creates and modifies an object, converts the object representation structure between the
disk and the memory.
Client-Server Communications
Manages the network communication between the client and the server.
Thread Management
Manages threads of a server process.
Query Processing
Executes query plans on the server, which are created by translating, analyzing and optimizing SQL statements
on the client.
The module configuration of each component is described in the following section.
3.1.1 Transaction Management Component
The Transaction Management Component consists of the modules in dark blue in Figure 5.
12. 3. Client and Server Modules
Figure 5. Module Configuration of Transaction Management Component
Object Locator
As a module passing object data between a workspace on the clients and the page buffer pool on the server, it
caches an object and acquires a lock to a workspace.
Transaction Manager
As a module performing transaction start, commit, and rollback, it initializes other modules (lock/log/recovery
manager) of Transaction Management Component. This module also supports commit, rollback, and savepoint
including 2PC (2-phase commit).
Lock Manager
As a module performing lock management based on the 2PL (2-phase locking) protocol, it supports a granularity
locking protocols.
Recovery Manager
13. 3. Client and Server Modules
As a module protecting database consistency from the system failure, it employs a failover method that uses
UNDO/REDO logging and the WAL (Write Ahead Logging) protocol. This module supports total rollback, partial
rollback (to savepoint), and nested top operation, and uses LSA (Log Sequence Address) and CLR
(Compensation Log Record), etc.
3.1.2 Server Storage Management Component
The Server Storage Management Component consists of the modules shown in Figure 6.
Figure 6. Module Configuration of Server Storage Management Component
I/O Manager
As a module performing I/O tasks for the disk volume (or volume file), it performs a volume mount/unmount
process and locks a volume. This module performs write synchronization for a log volume.
Page Buffer Management
As a module managing the page buffer in a virtual memory that is used for disk page buffering, it employs the
LRU page replacement algorithm and the FIX/UNFIX protocol to use page buffer. In addition, this module uses a
hash table to quickly retrieve a requested page in the buffer pool.
Disk Manager
It is a module managing the internal structure of the disk volume (or volume file). A volume consists of sectors,
and a sector is a group of continuous pages. Each volume consists of system area and user area. The bit
allocation map is used for page allocation in the volume.
14. 3. Client and Server Modules
File Manager
As a module helping access to a database only in a file and page regardless of internal structure of the volume
(volume, sector and page), it is used in a file structure such as B+-tree, heap, or hash. The File Manager module
keeps and manages information on the sector that is allocated to a file in a file header.
Slotted Page Manager
As a module inserting, deleting and updating records in a file page, it provides slot structure that indicates the
position (offset) of records in a page; it can move records in a page through a slot.
Overflow Page Manager
A module inserting, deleting and updating records with the size of over one page in an overflow page area. With
this module, you can treat a large size data atomically.
Object Heap Manager
It is a module inserting, deleting and, updating an object in a file through the heap structure. The instances
(records) of a class (table) are stored into an object heap file, and a unique OID (object identifier) is allocated to
each record. The OID consists of "Volume ID | + Page ID + Slot ID," and it is not reused except for a special case.
This OID expression is the same as disk addressing in the Disk Manager. That is, the OID indicates the physical
location of a disk where a record is stored.
Extendible Hash Manager
As a module providing the extendible hashing to access data quickly, it is used to retrieve class OIDs with a class
name.
B+-tree Manager
As a module providing an index file structure based on the prefix B+-tree, it inserts, deletes, and retrieves a key
for B+-tree.
Long Data Manager
As a module processing ad-hoc large objects such as multimedia data, it can modify part of the data.
3.1.3 Client Storage Management Component
The Client Storage Management Component consists of the modules shown in Figure 7.
15. 3. Client and Server Modules
Figure 7. Module Configuration of Client Storage Management Component
Workspace Manager
A module managing the database objects cached in the workspace of the client process. Through an object table
implemented as a hash, it converts a disk object identifier OID to a memory object pointer (MOP). The MOP has a
memory pointer that helps access to objects cached in the client memory.
Garbage Collector
A module collecting garbage for the client workspace. This module releases the memory that is allocated to MOPs
and cached objects.
Quick Fit Storage Allocator
A module allocating a memory to the workspace for an object.
3.1.4 Object Management Component
The Object Management Component consists of the modules in Figure 8.
16. 3. Client and Server Modules
Figure 8. Module Configuration of Object Management Component
Representation Manager
This is a module performing conversion between disk expression structure and memory expression structure of
an object. An object data is suitable to query execution in a disk and it has a structure which helps an application
access it in a memory. The Representation Manager does conversion between these two expression formats. It
also performs byte ordering during conversion.
Schema Manager
As a module defining and changing a class, it creates, modifies, or manages the inheritance of a column, method,
or class.
Object Access Manager
As a module creating, deleting, modifying, checking an object or calling a method, it is closely related to the
Schema Manager.
Dynamic Loader
A module providing a dynamic link to an application that is executing methods written in C.
Trigger Manager
A module implementing a trigger feature with a system object. This module is closely related to the Schema
Manager and Object Access Manager.
17. 3. Client and Server Modules
Authorization Manager
A module checking the authority of a database user. This module is implemented on top of the API provided by
the Object Access Manager.
Data Type and Domain
A module manipulating internal data structure (representation format) for data type and domain information. This
module caches the information about the used domain to a connection list and has a domain conversion matrix.
3.1.5 Client-Server Communications
Client-Server Communications consists of the modules in Figure 9.
Figure 9. Module Configuration of Client-Server Communications
Socket Manager
A module managing communications in the client, the server and the master process (cub_master). This module
manages the procedures of connection to the client or server through the master process.
Packet Manager
A module processing a packet that is used to exchange information between the client and the server. The packet
types include request packet, data packet, close packet, out-of-band packet, or error packet. The request packet
and data packet can communicate asynchronously by using a queue in the client and server.
Client-Server Interface
A module providing an interface to use Client-Server Communications in the system. This module processes an
exception that occurs during communications as well as out-of-band such as user interrupt, etc.
18. 3. Client and Server Modules
3.1.6 Thread Management Component
Thread Management Component manages multiple threads in the server process; it is implemented by using pthread.
This component detects a request from the client by using the select() system call and allocates a task to the threads
per each request. Similarly, the worker thread processing a request from the client waits for a task in the Job Queue
and wakes up when a task enters the process. After it processes the task, it waits for another task in the Job Queue.
There are also system threads that process only special system tasks as well as this worker thread.
Deadlock detection thread
This thread checks whether a deadlock occurs at a fixed interval or when there is a lock request, and it solves a
problem when there is a deadlock.
Checkpoint thread
This thread performs a checkpoint feature that flushes the data page, which is already committed at a fixed
interval but not reflected to the disk and cached in the page buffer. Performing a periodic checkpoint reduces the
restore time during failover.
OOB (out-of-band) thread
This thread receives the OOB signal and passes it to thread.
Page-flush thread
This thread periodically flushes the dirty pages in the page buffer to the disk. This improves system performance
by reducing flushing dirty pages to the disk during page replacement.
Log-flush thread
This thread flushes the log page to the log volume. It provides group and asynchronous commit methods by using
the log flush thread.
3.1.7 Query Processing
The Query Processing consists of the following modules.
Scanner/Parser
As a module translating queries (SQL) from users or applications, it creates a parse tree.
Semantic Checker
A module performing node typing, name resolution, semantic checking, or view translation, etc.
XASL Generator/Optimizer
A module creating XASL (eXtended Access Specification Language) tree which is a query execution plan and
performing query optimization by using schema information and database statistics. The XASL tree includes scan
information (heap scan, index scan, list file scan, set scan, and method scan), a value list (values required for
query results) and predicate. The query optimization employs cost-based optimization and rewrite optimization.
Query Manager
A server module executing a given XASL_tree from the client. This module consists of the Query File Manager
that stores the query's XASL plan and its results as well as the Query Evaluator that evaluates queries and
19. 3. Client and Server Modules
creates a result list file. This module interfaces with the Transaction Manager or Recovery Manager to approve or
cancel a transaction.
Cursor Manager
A module fetching data from the list file that is created as the retrieval results.
3.2 Detailed Description for the Modules
3.2.1 Transaction Management Component
A. Object Locator
The Object Locator is a module delivering object data between a workspace on the clients and the page buffer pool on
the server. The Object Locator provides simultaneous access, use, and failover for database objects by using the
Transaction Management Component's locking and restore algorithm.
The Object Locator is divided into Object Locator on the client, Object Locator on the server, and Object Locator on the
client/server. The Client Object Locator executes its tasks by using Workspace Manager, Representation Manager
(Transformation Manager), and Heap File Manager. The Authorization Manager, Schema Manager, Object Access
Manager and Query Parser (Scanner/Parser) use the functions of Client Object Locator. The Server Object Locator
executes tasks by using Object Heap Manager, Representation Manager (Transformation Manager), Lock Manager,
Catalog Manager, and B+-tree Manager. In the Client Object Locator, the functions of Server Object Locator module is
used for object fetch and flush.
The objects that are cached to the workspace of a client by the Object Locator maintains coherency with the objects in
a server by using cache coherency number. If the cache coherency number of an object, that is cached into the
workspace of a client, is not the same as the cache coherency number of an object that exists in the page buffer (or
disk) of a server, the cached object becomes invalid (invalidation). The Server Object Locator increases the cache
coherency number of an object whenever an object is flushed from a server and it is sent to a server.
Validation check for a cached object is performed when the object is first used by transaction. Because lock is also
cached (set up) when an object is cached, the validation of an object is effective while one transaction is being
executed. When a transaction requests an object, the Client Object Locator checks whether the object and its lock are
cached. If both the object and lock are cached, the transaction can use the cached objects in the workspace memory
much faster. If neither the object nor lock is cached, send a request to the Server Object Locator. The Server Object
Locator sets up lock that is requested for an object by using the Lock Manager. When lock is acquired, the cache
coherency number of an object in the workspace and the cache coherency number of an object that exists in the
database (page buffer or disk) of a server are compared. If these two values are different, a new object data from the
server is sent to the client and it replaces the old cached object.
When a transaction is terminated, the cached objects are flushed to a server. When a transaction is rolled back, the
objects are all de-cached. In addition, when a class object is invalidated (e.g., a schema is changed by a transaction of
another client), all the instance objects in the class are flushed/de-cached all together. And all the objects are flushed
to a server together with query execution requests because queries are executed in a server.
To reduce the communication amount between a client and a server, the Object Locator sends flush data together with
object fetch request packet or pre-fetches related class objects or other surrounding objects when caching objects.
20. 3. Client and Server Modules
The Server Object Locator fetches an object from database and updates it to the database upon the request of Client
Object Locator by using the Heap File Manager. In addition, it manages lock setting by using the Lock Manager.
B. Transaction Manager
The Transaction Manager is a module which does transaction start, approval, and rollback, etc. The Transaction
Manager calls the Object Locator to flush an object that is used for transaction, the Lock Manager to release a cached
lock, or the Log Manager (Recovery Manager) for transaction approval/rollback.
The Transaction Manager is divided into a client and a server. When an application requests transaction termination
(approval, rollback), the Client Transaction Manager flushes the objects (among the objects in the workspace) that are
changed during transaction execution to the page buffer of a server. (If it is rollback request, the changed objects are
not flushed to a server. Instead, they are immediately removed from the workspace.) Next, the Client Transaction
Manager requests approval/rollback to the Server Transaction Manager. In case of approval, the Server Transaction
Manager calls the Log Manager (Recovery Manager) executes postpone action to the database in a server and also
loose_end postpone action in a client. After that, it releases all the acquired locks and closes all the open cursors. In
case of rollback, the Log Manager (Recovery Manager) returns the tasks that are executed by transaction by using
UNDO log and releases all the acquired locks. When a transaction is approved or rolled back, the locks that are
cached by the Client Transaction Manager are all released.
It supports 2PC (2-phase commit) protocol for global transaction.
C. Lock Manager
The Lock Manager is a module that manages locks according to the 2PL (2 Phase Locking) protocol and Granularity
Locking protocol. The Lock Manager searches for a transaction identifier, calls the Log Manager (Recovery Manager)
to get the lock waiting time of a transaction, and calls the Server Transaction Manager to roll back a transaction to
handle deadlock. The Server Object Locator uses the Lock Manager to acquire and release a lock for an object and
the Log Manager uses the Lock Manager to release locks all together.
When accessing an instance object, lock setting is necessary for the class objects that define the all attributes of the
instance and also for the upper class objects that are inherited. In case of the schema change for a class object,
eXclusive lock must be set for the class and its lower classes.
In case of query execution, the instance of a class and the instance of its lower classes are all searched. In addition,
because a class object is a domain that defines the corresponding instance, the domain class and its lower classes are
all accessed. Therefore, set up shared lock for the class to search and its lower classes and also the domain class that
defines an instance and its lower classes during query execution.
To detect a deadlock, WFG (Waits-For-Graph) method is used. If WFG detects a deadlock, one of the involved
transactions is forcibly terminated by the system.
The Lock Manager manages Lock Table. The Lock Table is implemented with hash table for OID and access to the
table is set up as critical section to maintain consistency.
D. Recovery Manager
The Recovery Manager reflects the status of all the committed transactions to the database and does not reflect the
effect of transactions that are not committed when any fault to transaction, system, or media occurs. For this, the
Recovery Manager records a log and restores database from diverse faults based on the log. The CUBRID Recovery
Manager uses UNDO/REDO restore protocol and this protocol is based on the following rules:
21. 3. Client and Server Modules
UNDO Rule
Record data value before it is changed. It is assured the last committed value is recorded into a log before it is
overwritten by a value that is not yet committed.
REDO Rule
The values updated by a transaction are surely recorded into a log before the transaction is committed. That is,
the data value before committing is recorded into a log.
A log is a file in which data is appended in an arbitrary length. To implement a log file with infinite length, recent log
data is recorded into an active log and previous log data is archived into an archive log.
The UNDO/REDO logging is designed to achieve the maximum efficiency during general operation, rather than
database system fault restore time. The flush of data page can be avoided as much as possible during commit or
rollback due to the logging protocol. The data page is only written to a disk only when it is replaced by another page.
3.2.2 Object Management Component
The Object Management Component defines a table, creates or modifies an object, and formats an object in a disk or
memory.
A. Representation Manager
This is a module performing conversion between disk expression structure and memory expression structure of an
object. An object data is suitable to query execution in a disk and it has a structure which helps an application access it
in a memory. The Representation Manager does conversion between these two expression formats.
Figure 10. Disk Expression Format of an Object
22. 3. Client and Server Modules
The disk expression format of an object is shown in Figure 10. The class OID and Representation ID of an object
come first, and these are used to judge which format the object has. The following CHN (Cache Coherency Number) is
used to judge the validity of caches object. In the disk expression format, the columns (attributes) are divided into a
fixed length type column where all the values have the same length just like an integer and a variable length column
where all the values have different lengths just like a string. The fixed length columns are saved into a pre-defined
location, and the location of each column is obtained from the information that is managed by the Catalog Manager.
The location of the variable length column is obtained from the variable length column offset table which has location
information of each variable length column. The last entry of offset table indicates the end of an object. The offset table
is not saved for the object of a table which has no variable length column.
When an object is cached into a memory, the MOP indicates a memory block that has the columns of the object. The
fixed length column values are continuously saved into an object block and the values of a variable length column are
saved into a memory block that is separately allocated. The CHN is also included in the memory expression format.
The object locator compares this CHN value and the CHN value that is stored in a disk to judge the validity of an object.
If two CHN values are different, it means the object that is cached to the memory is not valid. Then, the object locator
de-caches the object and caches the content of a new object.
Figure 11. Memory Expression Format of an Object
The Representation Manager uses the Workspace Manager to receive a storage space for the memory expression of
an object and uses the Schema Manager to determine the size and architecture of an object.
When the CUBRID changes schema, it does not change the expression format of the records in the schema. Therefore,
if you find an object that is saved in the old expression format during the conversion process between two expression
formats, convert it to the recent expression format. At this time, use schema information for the recent expression
format and the old expression format. During expression format conversion process, convert the difference of hardware
architecture between the client equipment and the server equipment, e.g., the byte ordering difference.
3.2.3 Query Processing
23. 3. Client and Server Modules
Figure 12. The Procedures of Query Compile in a Client
A. Scanner/Parser
The parser keeps the data structure to create a parse tree during parsing process, the data structure to maintain the
created parse tree, and data structure to manage multiple SQL statements, and information about lexer.
B. Semantic Checker
If a parse tree is configured without an error, it means a query statement with correct syntax is input. Semantic
checking is a feature that checks whether the semantics of an input statement is valid. It performs the following tasks:
1. Name resolution and parse tree node type checking
Checks whether an existing table or column is used and infers the type of a column.
2. Semantic checking
Checks whether an operation that is not supported between types is used.
3. View translation
Converts the definition statement of a view.
24. 3. Client and Server Modules
C. XASL Generator/Optimizer
The query statement input by a user goes through parsing and semantic checking, and then it is converted into the
augmented parse tree where catalog information is listed. When query optimization is performed based on this
augmented parse tree, the XASL tree, i.e. action plan, is created as a result. The XASL tree is a tree where the most
optimized access sequence and method are specified for the tables to access during query execution. It consists of
action plans which has the lowest access path cost among many other possible plans. With a parse tree and catalog
statistics information, one XASL tree can be created as follows:
1. Classifying terms to configure search conditions in table units
A term becomes a search condition for one or more tables. When there is one table to which the term is applied,
the term is scan term (sarg). If there are two, the term is join term (edge). If there are three, the term is other term.
For the terms specified in the where clause of a parse tree, divide them into join terms or scan terms. Classify the
scan terms according to the table to which each term is applied.
2. Determining the most optimized access method to each table
For the scan terms that will be applied to an arbitrary table, calculate the selectivity of each scan term and select a
search method of a term whose selectivity is lowest as a table search method. That is, determine whether to use
sequential scan or index scan for a table. If the index scan is used, determine which index to use.
3. Calculating selectivity for each table
Calculate the selectivity of each table by using the selectivity of each scan term that is calculated in the step 2.
4. Determining access sequence among tables
To determine the access sequence among tables, list various access sequences and calculate access path cost
of each case. Select the execution sequence whose access cost is lowest as the final execution plan.
5. Creating XASL tree for the final execution plan
D. Query Manager
This is a server module that executes a XASL tree from a client. During Query Processing, a client sends a XASL tree
that is created through the XASL Generator/Optimizer module to a server. A query is executed when the server
receives and executes this XASL tree. Actually, it is undesirable, in terms of performance, to go through the XASL
Generator/Optimizer whenever there is a query of the same pattern, the CUBRID saves the XASL tree into the Query
Plan Cache and reuses it. In addition, when the same query is executed repeatedly, it saves the query result into the
Query Cache and returns the result without query execution next time.
25. 3. Client and Server Modules
Figure 13. Query Execution on the Server
The procedure of query processing through these components is shown in Figure 14.
26. 3. Client and Server Modules
Figure 14. Query Execution Steps