WO2004077214A2 - Systeme et procede permettant d'ordonnancer des fonctions de serveur indépendamment des fonctionnalités dudit serveur - Google Patents

Systeme et procede permettant d'ordonnancer des fonctions de serveur indépendamment des fonctionnalités dudit serveur Download PDF

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Publication number
WO2004077214A2
WO2004077214A2 PCT/IN2004/000025 IN2004000025W WO2004077214A2 WO 2004077214 A2 WO2004077214 A2 WO 2004077214A2 IN 2004000025 W IN2004000025 W IN 2004000025W WO 2004077214 A2 WO2004077214 A2 WO 2004077214A2
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instructions
recited
server
resources
computing system
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PCT/IN2004/000025
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WO2004077214A3 (fr
Inventor
Vinayak K. Rao
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Vaman Technologies (R & D) Limited
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Publication of WO2004077214A3 publication Critical patent/WO2004077214A3/fr

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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/48—Program initiating; Program switching, e.g. by interrupt
    • G06F9/4806—Task transfer initiation or dispatching
    • G06F9/4843—Task transfer initiation or dispatching by program, e.g. task dispatcher, supervisor, operating system
    • G06F9/485—Task life-cycle, e.g. stopping, restarting, resuming execution
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/48—Program initiating; Program switching, e.g. by interrupt
    • G06F9/4806—Task transfer initiation or dispatching
    • G06F9/4843—Task transfer initiation or dispatching by program, e.g. task dispatcher, supervisor, operating system
    • G06F9/4881—Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues

Definitions

  • a multi-user technology is one that allows more than one user or client to connect to the server and simultaneously perform tasks with other users sharing the same server resources.
  • One of the earliest known multi-user technologies available for user computing was the Operating System.
  • the multi-user functionality for any server is implemented to carry out centralized control and management, for security and for commonplace of data storage and for sharing excellent server resources across dumb clients.
  • the above is also known as the Client Server Technology in which dumb clients use highly resourceful and intelligent servers to achieve automation.
  • the earlier clients were inexpensive relative to the server, having minimum processing power and were useful just for data accessing purposes like the input and the output.
  • the existence of dumb clients and the need to implement business rules had resulted in server functionalities and features being pushed more to the servers and even the simplest validations were server-driven.
  • the present invention provides a software-implemented process, system, and method for use in a computing environment.
  • the present invention consists of a system and method in which server scheduling functions are decomposed as objects whose features and functionalities, which are currently implemented using standard structural programming could be implemented as a series of events or finite state machines.
  • server scheduling functions are decomposed as objects whose features and functionalities, which are currently implemented using standard structural programming could be implemented as a series of events or finite state machines.
  • each functional server grappled with the same issues of Disk Management, Memory Management, Connection Management and CPU sharing across concurrent client requests.
  • the proposed invention is a resource scheduler, which abstracts and maps patterns of functional usage with patterns of data, its state transition during these functional usage and derives a relationship wherein each resource usage irrespective of any functional server on any operating system and any vendor fall into a finite set of object and state entities for specific server resources and can be reused and applied generic irrespective of derived functionalities.
  • Network Agent just manages receipts and transmissions (functional pattern) of network packets irrespective of protocols (patterns of data) and size of data (i.e. data carrying capacity per
  • Disk Agent manages basic file operations like Open, Close, Read, Write, Seek etc... (functional pattern) irrespective of data patterns (Swap, Rollback Segment, Log, Dbf) and size of data (i.e. static data - fixed size metadata and dynamic data - data in tuples of user defined objects)
  • the scheduler using set of messages, events and action map manages these agents. i.e.
  • Each Server ⁇ Agents (Set of Agents)
  • Each Agent ⁇ Modules + ⁇ States + ⁇ Events (Set of Modules, States, Events)
  • Each Module ⁇ Functions (Set of Functions)
  • Server Object ⁇ Memory + ⁇ Disk + ⁇ CPU + ⁇ Network + ⁇ Timer
  • FIG. 3 depicts the multifunctional server as a composition of set of resource agents and the CPU is decomposed into functional servers such as Database, Web, Mail etc... These derived server are further set of agents required to deliver server specific functionality. Also shown in the figure are common agents such as Dispatcher and Scheduler Agent 305. Hence the GUI representation shown the functional derived of an agent as set of modules executed under a given event under a given state.
  • the entire perception of an object begins from the initiation of a client request, undergoing a series of data transformations as per request options and parameters, linked or synchronized as options specified in request and finally generating resultant response buffer.
  • This is analogous to manufacturing based on order (user input query) wherein the raw materials (CPU, Disk, Network, CPU, Timer) under goes a series of transition under various item (query parameters i.e. options and values) compositions to deliver the final finished good(s) (resultant buffer).
  • query parameters i.e. options and values
  • the design and implementation takes care of recursions and locking of a resource for a prolonged time.
  • the scheduler and object event implementations are divided into functionally small finite states linked and sequenced to deliver object functionality.
  • This implementation design hence requires minimum locking and delivers ' maximum CPU utilization because instead of functions calling functions like in linear programming here functions become tasks/state machine which deliver functionality but simultaneously allows scheduler to dynamically prioritize events.
  • the entire principle enforced in designing agents or functional modules is to enforce preemption by design rather than time based scheduling.
  • the design of the scheduler kernel is based on co-operative multithreading hence concurrency is achieved by a yield based kernel scheduled by priority rather than time driven kernel which has a predefined period of preemption.
  • Agent ⁇ Modules + ⁇ States + ⁇ Events (Set of Modules, States, Events)
  • Agent ⁇ Modules ⁇ + ⁇ Modules 2 + ⁇ Modules 3 + + ⁇ Modules ⁇ 0 o
  • Each Module being a collection of functions will have a MIN to MAX time of execution based on the extreme values of iterative parameters passed i.e.
  • Agent Execution Time ⁇ Modules! + ⁇ Modules 2 + + ⁇ Modules 100 Max Max Max
  • Agent minimum execution time is the summation of best minimum timing and maximum execution time is the summation of best maximum timing.
  • agent wise timing which with an approximation of error percentage could be derived under defined resource restrictions i.e. assuming a 1Ghz CPU, 128Mb RAM, 40Gb Hard disk drive and 100 Mbps network card etc... and gauging agent wise performance which use these resources under varying needs and ratios.
  • This equation or mathematical model representation of a resource agent or functional agent helps manage and optimize best performance of server in concurrent or distributed environment under given resource limitation and helps the scheduler to optimize the best way to service a request query in fastest possible response time. Also because of this unique approach the software implementation and any derived entities based on this principle can be easily fabricated to an application-specific integrated circuit (ASIC) or Very Large Scale Integrated (VLSI) chip unlike other schedulers or functional servers.
  • ASIC application-specific integrated circuit
  • VLSI Very Large Scale Integrated
  • FSM Finite State Machine
  • FIG 1 is a block diagram depicting the functional blocks of the scheduler of the preferred embodiment of the invention.
  • FIG 2 is a flow diagram illustrating the scheduler carrying out the server scheduling functions.
  • FIG 3 is a screenshot illustrating the scheduler agent carrying out the scheduling functions.
  • Fig 1 is a block diagram depicting the functional blocks of the scheduler of the preferred embodiment of the invention.
  • the present invention has separate agents like the Network Agent 100 for network hardware and capable of servicing every network request irrespective of protocols configured on server or hardware supported. This is the primary block through which every request source reaches the Scheduler Agent 102 and response to requests are obtained.
  • the Scheduler Agent 102 upon receiving any request has to locate and isolate source of request (basically protocols) and nature of clients i.e. Browser, email client, ODBC compliant client etc.
  • agents for each resource as a manager to source and sink events and deliver functionality expected from the resource as per command options irrespective of functional servers using the same resource.
  • agents for managing disk, network, memory, timer and CPU functionality which actually delivers various combinational servers is decomposed into server specific functional agents such as DML, Server, HTTP etc.
  • the network agent 100 has events and states defined to receive and transmit packets of request or response data irrespective of protocol or underlying hardware i.e. NIC (network interface card) or DUN (dial up network).
  • NIC network interface card
  • DUN dial up network
  • the Network agent creates protocol specific threads, which are binded and configured to enable functionality expected from desired servers using these protocol as its native communication interface.
  • the Network Module 112 creates the DB Threads 114 such as TCP/IP, IPX SPX, UDP, Named pipes or the Web Threads 116 like FTP or HTTP. For every request the worker threads are created that is one thread per protocol is created. As per the analysis of the incoming data a thread is assigned per protocol. For example each http request is given to a new http thread.
  • the Timer Agent 138 is mainly used to force synchronicity and prevent any asynchronous events to run astray. Some periodic functionality checks for monitoring resource usage by current process and well as by other processes running on the server currently are managed by the timer agent. Also as per number of unflushed committed transactions and size of this uncommitted data a periodic checkpointing is also triggered by the timer agent.
  • the Disk Agent 140 is primarily responsible for archiving data as well as managing intermediate data files like log files (committed transactional data) or rollback segments (uncommitted transactional data) or other configuration files.
  • the uniqueness of this agent is that irrespective of different functional servers, which the Scheduler Agent 102 manages the persistent data generated or used is managed by the disk agent analyzing patterns of data as per functional scope that is irrespective of server data patterns the final persistent data is an ODBC compatible data type or its combination. This makes data exchange seamless and SQL queries, which could never work on web / mail objects can now be accessed as functional extension of database server.
  • the Resource Analyzer 124 is responsible for allocating resources such as the Disk, the Network, the Random Access Memory (RAM), and the Central Processing Unit (CPU). For execution of any of these commands check is any resource is required either RAM or Disk space etc the resource analyzer 124 notifies to the cache manager or disk manager to allocate and manage resource for the request execution calculating requirements based on options specified in the client request. Since the scheduler is configured to be a unified scheduler, working irrespective of the nature of the server, the resource management between concurrently logged clients (Database, Web or Mail) becomes the primary objective of the scheduler. We classify the basic resources disk, network, RAM, timer and CPU as the primary resources, which are used as per the behavioral pattern of the functional server in various combinations as desired.
  • Various constraints are validated during every state entity of object or transaction based on the parameter settings of resource usage set by the user, state of available versus free resources, quantity of the resource and time for which the resource is available. Any translation of resource between primary or secondary is decided by the resource analyzer and the RAM is swapped or retrieved accordingly.
  • transition data states before, during and after being committed are managed in various disk pattern storages like rollback segment, log file and final database file.
  • the kernel Since the scheduler kernel design is primarily asynchronous, yield based priority scheduling of any set of tasks, which requires synchronicity is enforced using the timer agent.
  • the kernel therefore, is designed to be yield based, wherein the method of deciding the priority of the query received and scheduling server resources is based primarily on the yield of the query received which makes it possible to utilize the CPU most efficiently by relinquishing the resource once the query has been processed and executed.
  • the Dispatcher Agent 104 is responsible in case of sending outgoing request and buffering the request as per requirements.
  • the Global Cache 106 is used as virtual memory available to any of the requesting operations.
  • the primary function of this dispatcher agent 104 is to help the resource analyzer 124 synchronize the "RAM" and "Network" for every nature of response. This may vary from a server side cursor created by any database client to a frequently used web page of a web server client.
  • the dispatcher agent 104 optimizes the memory usage across repetitive client requests by synchronizing cached objects and various states of frequently used data.
  • the Parser 108 is responsible for translating, analyzing, evaluating, validating any syntactic or semantic errors and parsing the client request that could either be SQL or XQL or OQL. In other words it manages to analyze and parse requests or commands irrespective of the nature of the clients, which could be either a web client or an ftp client or an ODBC compliant client or a mail client etc.
  • the DAT 110 is a repository for various objects like parser dictionary, message and error strings, and basic metadata definitions.
  • the repository has also some decision matrix data which is a ratio of response time for various data structure operations like search, insert, delete across algorithms and its derivatives like trees, hash tables, linked lists with respect to loads of data v/s resource constraints.
  • decisions taken by scheduler and resource analyzer 124 are based on the anticipated resultant time-ratio as dictated by the values in these DAT 110 structures and stored in Look-Up Tables (LUTs).
  • the License Manager 118 Before execution of any successfully parsed command the License Manager 118 checks constraints for execution of the command as dictated by the purchasing licenses. A license file decides the constraints validated by the license manager. This license file is shipped as per the purchase details like server edition, user licenses, OS etc.
  • the Audit Manager 120 tracks and logs every action and result as per the audit parameter settings for the request. This helps in tracking usage of the object and the operation irrespective of function of server that is Database Server, Web Server, Mail Server etc and enhance security.
  • the Command Analyzer 122 decides upon the flow of execution of the request and passes control to the respective agent as per the scope of work expected and options specified in the command. In the event of local request the command is analyzed by local command Analyzer.
  • the DML Agent analyzes the DML command and the Server Agent analyzes the server command.
  • OOOV Operation, Object, Option and Value
  • the command analyzer 122 decides the flow of execution and messages the appropriate agents to execute the required tasks.
  • the granularity of state machines and its modularity mapping with options of object functionality ensures that only optimum code gets executed as per user query options and effectively utilizes CPU to a minimum.
  • the state machine based scheduler dynamically decides program flow execution rather than the programmer incorporating it in the program code itself.
  • the command analyzer 122 decides this flow in real time based on few heuristics analyzed by the table generated by the virtual statistics 130 and associates a series of functional event patterns to execute for various agents as needed by the query.
  • the Messaging 126 is a way in which one has to communicate between two of the states like either sourcing a request or sinking a request in the case of an event.
  • the Priority Queuing 128 is based on task according to priority that can be scheduled by the kernel.
  • the scheduler can raise the priority so as to get maximum CPU time.
  • a series of client requests, based on the source of request i.e. whether HTTP/ FTP/ SMTP / POP requests) have various protocol timeouts pre-assigned.
  • Database clients also have query and connection timeouts. Hence these timeout constraints force the scheduler to execute and update the clients about their requests on an on-going basis and work on the process for execution.
  • the scheduler must ensure that none of these clients timeout for need of resources or server attention.
  • the criteria's based on which the scheduler arranges queries in the priority queue 128 include source request protocol, nature of query - (DDL / DML etc), complexity of query (joins, conditions etc), state of objects in the query (under transactional lock, dropped etc), resource availability (RAM, Disk etc), Burst or workload of requests within unit time, response timeout, transitional resources required before deriving final result buffer, size of response data and size of cache.
  • a module is a group of atomic functions, which is scheduled by the scheduler.
  • Any functional agent such as DML
  • DML is a set of sequenced modules to deliver DML functionality (such as select / insert / update / delete).
  • the scheduler tracks each query flow across various functional server agents and changes the priorities dynamically due to any unfavorable condition during execution (such as need for lock on an object). This makes queuing unique and optimizes CPU usage. Any change in flow required, to change the state entity of a query being currently executed, can be messaged and monitored across the flow between the various agents or can be aborted to relinquish certain resources.
  • Virtual Statistics 130 run and have to maintain global data about the number of request like number of Insert, Delete etc. Also currently how many Select etc is in memory are maintained in the virtual statistics in a virtual table.
  • the Virtual Statistics 130 is primarily a derivative of various historical and real-time statistical analysis of operations on objects. A lot of heuristics required to predict resource pattern usage is analyzed and updated per operation on any object in the server. This process helps in mapping a pattern of resource flow across various modules of agents required to deliver various server functionalities. The heuristics are calculated based on resource specific functional agents like disk, network, timer etc. and are formulated into a mathematical model to derive functional throughput (i.e. per unit time per unit cost per unit of measurement).
  • the Error Handling & Notification block 132 looks after the error handling, reporting or notification.
  • Display Log and Statistical Log block 134 handles how the display for example an HTML (Hyper Text Markup Language) file in case of a browser are handled and also the Statistical Log is maintained.
  • HTML Hyper Text Markup Language
  • HTTP agent 136 does this translation of query data to html tagged syntaxes.
  • Script agent in conjunction with HTTP agent manages validation and execution of web scripts like ASP/JSP etc. »
  • the Server Agent 142 is mainly involved for DDL / DCL operations.
  • the server agent manages any object creation, alteration or deletion of objects. It also executes any DCL commands for statistical history or for either query or object analysis.
  • the DML Agent 144 executes only DML specific queries. As soon as a syntactically valid client request reaches the agent it validates the needs of the query objects and returns an error incase the object is invalid. It then analyses the requirements as per the response buffer expected and allocates resource required for execution. The cursor type specified by the client request and size of anticipated result after or during query execution typically dictates this. If the queries require some expression to be evaluated or special functions to be executed on operands (i.e. mathematical / logical) the DML Agent organizes the resources and executes.
  • the flow diagram illustrates the preferred embodiment of the present invention explaining the process by which the system carries out the scheduling and integrating various server functionalities and extending this functionalities for seamless data and functionality interchange.
  • the process begins with the Scheduler Agent 102 receiving a Client request 200, such as 'CONNECT'.
  • the Scheduler agent 102 then proceeds to isolate the source and nature of the request 202.
  • the queries received are dynamically ordered in a Priority Queue based on predetermined conditions. As and when new queries are received the Priority Queue evaluates the nature and source of those queries to rearrange the ordering of the queries in the Priority Queue.
  • the Scheduler Agent 102 After completing the isolation of the request, the Scheduler Agent 102 then proceeds to check if the request is a Scheduler command 204. In the event that the request is not a Scheduler Command, the Scheduler generates an error code 206. In case the request is a Scheduler command, it needs to be executed beyond the scope of the scheduler functionality and the Scheduler agent 102 notifies various agents as per the request scope. Hence a web request, ODBC request or mail client request is directed to the respective agent such as database server or a web server or a mail server.
  • the Scheduler Agent 102 proceeds to analyze if it a DML command 210. In the event that it is a DML command it is given 212 to the DML Agent 144. In the event it is a non-DML command as per request parameters and options the request is given 214 either to Server Agent 142 for DDL or DCL requests. On giving the request to the Server Agent, the request is then checked for having any sub DML queries 216. In the event that the request does not have any sub DML queries, it is passed 212 to the DML Agent 144.
  • the Scheduler Agent 102 forks a new thread for sub queries 218 and the sub query is passed 212 to the DML Agent 144.
  • the DML Agent 144 then proceeds to send the request 220 to the Resource analyzer 124, which allocates the resources such as RAM etc.
  • the Resource analyzer 124 then proceeds to check if RAM is required 222. In the event the RAM is required, the request is passed 224 to the Cache Manager 106 for processing. In the event of no RAM required, the Disk Agent 140 directly processes the request 226. After the processing done by the Cache Manager 106 and the Disk Agent 140, the request is executed 228, that is after the successful resource allocation the query is executed and the resultant buffer is prepared.
  • the request is then checked for Response to Transmit 230.
  • the request is passed 232 to the Network Agent 100, which transmits the result.
  • the result is then analyzed to ascertain whether it is a successful command 234.
  • an error handler is generated 236.
  • a response is sent 238.
  • the request is sent 232 to the Network Agent 100.
  • the result is then analyzed to ascertain whether it is a successful command 234.
  • an error handler is generated 236.
  • a response is sent 238.
  • the notification message data varies as per the nature of source request i.e. web clients get a html error page whereas an ODBC client gets an error code as per ODBC standard.
  • the Scheduler agent 102 checks if it is a web- based request 246, meant for a Web Server. If the request is for a Web Server, the Scheduler checks whether it is an http request 248. In case the request is an http request, it is given 250 to the Http Agent 136. Next the Http Agent 136 passes on this request for translation of the OQL to DML or DDL 252. In the event of non-http request, the Scheduler Agent 102 classifies it as an ftp request 254. In the event it is not an ftp request, it is classified as a an unknown client request 258.
  • every ftp command translates and maps to the database maintained virtual file system. After this translation to DDL or DML respectively the process to check for DML command and onwards is carried out.
  • the request On checking if the request if for a Web Server 246, in the event that it is not, it is checked to ascertain if it is a request for the Mail Server 256. If the request if not for a Mail Server, it is classified as an unknown client request 258. The request is classified as a SMTP/POP request 260 and it is then given for translation from OQL to DML or DDL 252.
  • FIG. 3 illustrates a screenshot of an embodiment of the present invention.
  • the Scheduler Agent 305 is is depicted with the functional servers and resources listed in the column on the left.
  • the GUI representation shown the functional derived of an agent as set of modules executed under a given event under a given state.

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Abstract

L'invention concerne en général un système et un procédé permettant de planifier et d'intégrer des fonctionnalités variées de serveur telles que système de gestion de base de données ou serveur Web ou serveur de courrier électronique, etc., et à étendre ces fonctionnalités à des données continues et à des échanges fonctionnels sans affecter les applications existantes d'un client pour les serveurs individuels.
PCT/IN2004/000025 2003-01-30 2004-01-29 Systeme et procede permettant d'ordonnancer des fonctions de serveur indépendamment des fonctionnalités dudit serveur WO2004077214A2 (fr)

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US10222986B2 (en) 2015-05-15 2019-03-05 Cisco Technology, Inc. Tenant-level sharding of disks with tenant-specific storage modules to enable policies per tenant in a distributed storage system
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US9213612B2 (en) 2008-09-29 2015-12-15 Cisco Technology, Inc. Method and system for a storage area network
US10243826B2 (en) 2015-01-10 2019-03-26 Cisco Technology, Inc. Diagnosis and throughput measurement of fibre channel ports in a storage area network environment
US10826829B2 (en) 2015-03-26 2020-11-03 Cisco Technology, Inc. Scalable handling of BGP route information in VXLAN with EVPN control plane
US10222986B2 (en) 2015-05-15 2019-03-05 Cisco Technology, Inc. Tenant-level sharding of disks with tenant-specific storage modules to enable policies per tenant in a distributed storage system
US11354039B2 (en) 2015-05-15 2022-06-07 Cisco Technology, Inc. Tenant-level sharding of disks with tenant-specific storage modules to enable policies per tenant in a distributed storage system
US10671289B2 (en) 2015-05-15 2020-06-02 Cisco Technology, Inc. Tenant-level sharding of disks with tenant-specific storage modules to enable policies per tenant in a distributed storage system
US11588783B2 (en) 2015-06-10 2023-02-21 Cisco Technology, Inc. Techniques for implementing IPV6-based distributed storage space
US10778765B2 (en) 2015-07-15 2020-09-15 Cisco Technology, Inc. Bid/ask protocol in scale-out NVMe storage
US10949370B2 (en) 2015-12-10 2021-03-16 Cisco Technology, Inc. Policy-driven storage in a microserver computing environment
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