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Patent US20040225689 - Autonomic logging support - Google PatentsSearch Images Maps Play YouTube News Gmail Drive More »Sign inPatentsA system, method and article of manufacture for event management in data processing systems and more particularly to managing events occurring in data processing systems in order to provide an effective logging mechanism. One embodiment provides a method of generating log file entries for events occurring...http://www.google.com/patents/US20040225689?utm_source=gb-gplus-sharePatent US20040225689 - Autonomic logging supportAdvanced Patent SearchTry the new Google Patents, with machine-classified Google Scholar results, and Japanese and South Korean patents.Publication numberUS20040225689 A1Publication typeApplicationApplication numberUS 10/431,917Publication dateNov 11, 2004Filing dateMay 8, 2003Priority dateMay 8, 2003Also published asCN1864157A, CN100487690C, EP1620802A2, EP1620802A4, US20080155548, WO2004100639A2, WO2004100639A3Publication number10431917, 431917, US 2004/0225689 A1, US 2004/225689 A1, US 20040225689 A1, US 20040225689A1, US 2004225689 A1, US 2004225689A1, US-A1-20040225689, US-A1-2004225689, US2004/0225689A1, US2004/225689A1, US20040225689 A1, US20040225689A1, US2004225689 A1, US2004225689A1InventorsRichard Dettinger, Frederick Kulack, Richard Stevens, Eric WillOriginal AssigneeInternational Business Machines CorporationExport CitationBiBTeX, EndNote, RefManPatent Citations (4), Referenced by (89), Classifications (13), Legal Events (1) External Links: USPTO, USPTO Assignment, EspacenetAutonomic logging support
US 20040225689 A1Abstract
A system, method and article of manufacture for event management in data processing systems and more particularly to managing events occurring in data processing systems in order to provide an effective logging mechanism. One embodiment provides a method of generating log file entries for events occurring during execution of a process in a data processing system. The method includes determining an importance level for an occurred event on the basis of trend analysis indicating evolution of the process and creating a log file entry for the occurred event if the determined importance level exceeds the predetermined threshold value. Images(6) Claims(32)
What is claimed is: 1. A method of managing logging activity for a process in a data processing system, comprising: monitoring at least one system status parameter for the data processing system; and managing the logging activity for the process on the basis of the at least one system status parameter. 2. The method of claim 1, wherein the process is an executable instance of an application. 3. The method of claim 1, wherein managing the logging activity comprises increasing the logging activity. 4. The method of claim 1, further comprising: monitoring one or more processes running in the data processing system in order to detect events occurring in the one or more processes; and associating an importance level with each occurred event; and wherein managing the logging activity comprises managing the logging activity on the basis of the at least one system status parameter and at least one of the associated importance levels. 5. The method of claim 1, wherein the at least one system status parameter comprises at least one of used memory, attributed processing capacity, relative storage usage of a process and a size of a log file configured for logging information relating to events occurring during execution of the process. 6. A method of generating log file entries for events occurring during execution of a process in a data processing system, the method comprising: determining an importance level for an occurred event on the basis of trend analysis indicating evolution of the process; comparing the determined importance level with a predetermined threshold value; and creating a log file entry for the occurred event only if the determined importance level exceeds the predetermined threshold value. 7. The method of claim 6, wherein the process is an executable instance of an application. 8. The method of claim 6, further comprising, before determining the importance level, creating a log file entry in a corresponding log file for each occurring event; determining at least one system status parameter for the data processing system; and comparing the at least one determined system status parameter with an associated predetermined parameter threshold; and wherein determining the importance level comprises determining the importance level for the occurred event only if the at least one determined system status parameter exceeds the predetermined parameter threshold. 9. The method of claim 8, wherein the at least one system status parameter comprises at least one of used memory, attributed processing capacity, relative storage usage of a process and a size of a log file configured for logging information relating to events occurring during execution of the process. 10. The method of claim 8, wherein determining the at least one system status parameter is performed according to a predetermined time schedule. 11. The method of claim 6, wherein determining the importance level on the basis of the trend analysis comprises determining process performance parameters to perform the trend analysis. 12. The method of claim 6, wherein determining the importance level on the basis of the trend analysis comprises determining system parameters of the data processing system comprising available storage capacity to perform the trend analysis. 13. The method of claim 6, further comprising: determining the predetermined threshold value on the basis of user input. 14. The method of claim 6, further comprising: determining the predetermined threshold value on the basis of predefined process parameters. 15. The method of claim 6, wherein creating the log file entry comprises initiating a running log process to create log file entries for all subsequently occurring events. 16. The method of claim 6, further comprising: determining whether a corresponding log file exists; if the corresponding log file exists, storing the created log file entry in the log file; and if the corresponding log file does not exist, creating the corresponding log file; and storing the created log file entry in the log file. 17. A computer readable medium containing a program which, when executed, performs an operation of generating log file entries for events occurring during execution of a process in a data processing system, the operation comprising: determining an importance level for an occurred event on the basis of trend analysis indicating evolution of the process; comparing the determined importance level with a predetermined threshold value; and only if the determined importance level exceeds the predetermined threshold value, generating a log file entry for the occurred event. 18. The computer readable medium of claim 17, wherein the process is an executable instance of an application. 19. The computer readable medium of claim 17, wherein the operation further comprises, before determining the importance level, generating a log file entry in a corresponding log file for each occurring event; determining at least one system status parameter for the data processing system; and comparing the at least one determined system status parameter with an associated predetermined parameter threshold; and wherein determining the importance level comprises determining the importance level for the occurred event only if the at least one determined system status parameter exceeds the predetermined parameter threshold. 20. The computer readable medium of claim 19, wherein the at least one system status parameter comprises at least one of used memory, attributed processing capacity, relative storage usage of the process and a size of a log file configured for logging information relating to events occurring during execution of the process. 21. The computer readable medium of claim 19, wherein determining the at least one system status parameter is performed according to a predetermined time schedule. 22. The computer readable medium of claim 17, wherein determining the importance level on the basis of the trend analysis comprises determining process performance parameters to perform the trend analysis. 23. The computer readable medium of claim 17, wherein determining the importance level on the basis of the trend analysis comprises determining system parameters of the data processing system comprising available storage capacity to perform the trend analysis. 24. The computer readable medium of claim 17, wherein the operation further comprises: determining the predetermined threshold value on the basis of user input. 25. The computer readable medium of claim 17, wherein the operation further comprises: determining the predetermined threshold value on the basis of predefined process parameters. 26. The computer readable medium of claim 17, wherein generating the log file entry comprises initiating a running log process to create log file entries for all subsequently occurring events. 27. The computer readable medium of claim 17, wherein the operation further comprises: determining whether a corresponding log file exists; if the corresponding log file exists, storing the created log file entry in the log file; and if the corresponding log file does not exist, creating the corresponding log file; and storing the created log file entry in the log file. 28. A computer readable medium comprising: an event manager program for initiating a background thread for each instance of an executing application in a data processing system, the background thread being configured to: monitor at least one system status parameter for the data processing system; monitor one or more processes running in the data processing system in order to detect events occurring in the one or more processes; associate an importance level with each occurred event; and identify a predetermined action to be taken in the data processing system on the basis of at least one of the associated importance levels and the at least one system status parameter. 29. The computer readable medium of claim 28, wherein at least one of the one or more processes is an executable instance of an application. 30. The computer program product of claim 28, wherein the at least one system status parameter comprises at least one of used memory, attributed processing capacity, relative storage usage of the one or more processes and a size of one or more log files configured for logging information relating to events occurring during execution of the one or more processes. 31. The computer program product of claim 28, wherein the predetermined action to be taken comprises at least one of generating a log file entry for a corresponding occurred event, notifying a user of the corresponding occurred event, initiate a running log process to create log file entries for all subsequently occurring events and inhibiting increased storage and processing capacity usage of a corresponding process. 32. A data processing system comprising: an event manager residing in memory for initiating a background thread for each instance of an executing application, the background thread being configured to monitor at least one system status parameter for the data processing system; monitor one or more processes running in the data processing system in order to detect events occurring in the one or more processes; associate an importance level with each occurred event; and identify a predetermined action to be taken in the data processing system on the basis of at least one of the associated importance levels and the at least one system status parameter; and a processor for running the one or more processes and the at least one background thread. Description
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS INTRODUCTION [0024] The present invention is generally directed to a system, method and article of manufacture for event management in data processing systems and more particularly to managing events occurring in data processing systems for providing an effective logging mechanism. Frequently, specific events occurring in data processing systems are precursors of a future application or system failure (in the following referred to as “failure”, for simplicity). In addition, many of the common causes of failures have preceding trends that are recognizable well before the actual failure occurs. In detecting such specific events and recognizing such trends, preventative action can be taken which may be suitable to prevent a failure. If, however, it is not possible to prevent the failure, at least certain actions can be taken to ensure that undesirable effects are minimized. Such actions may include, for example, logging of the proper information related to specific events and trends. Thus, a quick resolution to a problem leading to the failure can be found when the failure occurred. To this end, a reliable determination of the specific events and trends needs to be performed. [0025] Accordingly, in one embodiment an importance level is determined for an event that occurs during execution of a process in a data processing system. The importance level is determined on the basis of trend analysis indicating evolution of the process. The determined importance level is compared with a predetermined threshold value to determine whether the event is a specific event. Only if the determined importance level exceeds the predetermined threshold value, it is assumed that the event is a specific event and a log file entry is created for the occurred event. [0026] Another embodiment employs an analysis of system status parameters indicating system resource usage in order to manage logging activity for a process in the data processing system. Accordingly, at least one system status parameter is monitored for the data processing system. On the basis of the at least one system status parameter the logging activity for the process is managed. PREFERRED EMBODIMENTS [0027] One embodiment of the invention is implemented as a program product for use with a computer system such as, for example, the computer system 110 shown in FIG. 1 and described below. The program(s) of the program product defines functions of the embodiments (including the methods described herein) and can be contained on a variety of signal-bearing media. Illustrative signal-bearing media include, but are not limited to: (i) information permanently stored on non-writable storage media (e.g., read-only memory devices within a computer such as CD-ROM disks readable by a CD-ROM drive); (ii) alterable information stored on writable storage media (e.g., floppy disks within a diskette drive or hard-disk drive); or (iii) information conveyed to a computer by a communications medium, such as through a computer or telephone network, including wireless communications. The latter embodiment specifically includes information downloaded from the Internet and other networks. Such signal-bearing media, when carrying computer-readable instructions that direct the functions of the present invention, represent embodiments of the present invention. [0028] In general, the routines executed to implement the embodiments of the invention, may be part of an operating system or a specific application, component, program, module, object, or sequence of instructions. The software of the present invention typically is comprised of a multitude of instructions that will be translated by the native computer into a machine-readable format and hence executable instructions. Also, programs are comprised of variables and data structures that either reside locally to the program or are found in memory or on storage devices. In addition, various programs described hereinafter may be identified based upon the application for which they are implemented in a specific embodiment of the invention. However, it should be appreciated that any particular nomenclature that follows is used merely for convenience, and thus the invention should not be limited to use solely in any specific application identified and/or implied by such nomenclature. [0029] Referring now to FIG. 1, a computing environment 100 is shown. In general, the distributed environment 100 includes a data processing system 110, interchangeably referred to as a computer system 110, and a plurality of networked devices 146. The computer system 110 may represent any type of computer, computer system or other programmable electronic device, including a client computer, a server computer, a portable computer, an embedded controller, a PC-based server, a minicomputer, a midrange computer, a mainframe computer, and other computers adapted to support the methods, apparatus, and article of manufacture of the invention. In one embodiment, the computer system 110 is an eServer iSeries 400 available from International Business Machines of Armonk, N.Y. [0030] Illustratively, the computer system 110 comprises a networked system. However, the computer system 110 may also comprise a standalone device. In any case, it is understood that FIG. 1 is merely one configuration for a computer system. Embodiments of the invention can apply to any comparable configuration, regardless of whether the computer system 110 is a complicated multi-user apparatus, a single-user workstation, or a network appliance that does not have non-volatile storage of its own. [0031] The embodiments of the present invention may also be practiced in distributed computing environments in which tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote memory storage devices. In this regard, the computer system 110 and/or one or more of the networked devices 146 may be thin clients which perform little or no processing. [0032] The computer system 110 could include a number of operators and peripheral systems as shown, for example, by a mass storage interface 137 operably connected to a direct access storage device 138, by a video interface 140 operably connected to a display 142, and by a network interface 144 operably connected to the plurality of networked devices 146. The display 142 may be any video output device for outputting viewable information. [0033] Computer system 110 is shown comprising at least one processor 112, which obtains instructions and data via a bus 114 from a main memory 116. The processor 112 could be any processor adapted to support the methods of the invention. [0034] The main memory 116 is any memory sufficiently large to hold the necessary programs and data structures. Main memory 116 could be one or a combination of memory devices, including Random Access Memory, nonvolatile or backup memory, (e.g., programmable or Flash memories, read-only memories, etc.). In addition, memory 116 may be considered to include memory physically located elsewhere in the computer system 110 or in the computing environment 100, for example, any storage capacity used as virtual memory or stored on a mass storage device (e.g., direct access storage device 138) or on another computer coupled to the computer system 110 via bus 114. [0035] The memory 116 is shown configured with an operating system 118. The operating system 118 is the software used for managing the operation of the computer system 110. Examples of the operating system 118 include IBM OS/400®, UNIX, Microsoft Windows®, and the like. [0036] The memory 116 further includes one or more application programs 120 and an event manager 130 having a system status parameter monitor 132, an event monitor 134 and an action processing unit 136. The application programs 120 and the event manager 130 are software products comprising a plurality of instructions that are resident at various times in various memory and storage devices in the computing environment 100. When read and executed by one or more processors 112 in the computer system 110, the application programs 120 and the event manager 130 cause the computer system 110 to perform the steps necessary to execute steps or elements embodying the various aspects of the invention. The application programs 120 may interact with a database 139 (shown in storage 138). The database 139 is representative of any collection of data regardless of the particular physical representation of the data. The event manager 130 is shown having a plurality of constituent elements. However, the event manager 130 may alternatively be implemented without providing separate constituent elements, e.g., as a single software product implemented in a procedural approach. The event manager 130 is further described below with reference to FIG. 2. [0037] [0037]FIG. 2 shows an illustrative relational view 200 of the event manager 130 and other components of the invention. The event manager 130 is configured to make a prediction of future failures in the data processing system 110 possible. Further, the event manager 130 provides support for avoiding/resolving problems leading to such failures. In one embodiment the event manager 130 identifies problems by correlating the evolution of one or more processes running on the data processing system 110 with status changes of the data processing system 110. When the correlation results in the identification of a problem which may lead to failure, the event manager identifies a predetermined action to be taken. The predetermined action is either designed to avoid the failure or to identify and collect critical information that permits a quick resolution of the problem. The event manager 130 may identify the critical information by determining events occurring in the one or more processes which are likely to be relevant to the resolution of the identified problem, i.e., for debugging and analysis purposes if the failure occurs. [0038] In one embodiment, the event manager 130 initiates a background thread for each process running on the data processing system 110. A process may be running, for example, for an instance of an executing application. In one embodiment, the background thread is implemented by the constituent functions of the event manager 130, i.e., by the system status parameter monitor 132, the event monitor 134 and the action processing unit 136. These functions and their interaction are now described. [0039] The system status parameter monitor 132 monitors (as indicated by arrow 204) system status parameters 202 for the data processing system 110. The system status parameters 202 may be determined and provided by the operating system 118 using conventional techniques which are well-known in the art. By way of example, system status parameters 202 include used memory, attributed processing capacity, relative storage usage of one or more processes running on the data processing system 110, and the size of one or more log files configured for logging information relating to events occurring during execution of the one or more processes. In one embodiment, the system status parameters 202 may be determined according to a predetermined time schedule. The predetermined time schedule may specify a periodic determination. Or, if a corresponding process is running for an executable instance of an application, the application may indicate time intervals at which time the system status parameters 202 need to be determined. [0040] The event monitor 134 monitors (as indicated by arrow 214) processes 210 running on the data processing system 110 in order to detect events 212 occurring in the processes 210. Furthermore, the event monitor 134 associates an importance level 218 with each occurred event 212 (as indicated by dashed arrow 216). The importance levels for a plurality of possibly occurring events may be application-specific and predefined by an operator. The importance levels may also be autonomously determined by the data processing system 110 on the basis of predefined generic importance patterns. Such generic importance patterns may, for example, indicate that for any application executing in the data processing system 110 events occurring at initialization of the application are more important than events immediately following the initialization. In another embodiment, the importance levels may be autonomously determined by the data processing system 110 on the basis of the system status parameters 202, thereby correlating the occurring events 212 with a current system status. By way of example, any combination of the above-described possibilities is considered. For instance, the importance levels may be autonomously determined by the data processing system 110 on the basis of the system status parameters 202 and additionally be weighted on the basis of the predefined generic importance patterns. Persons skilled in the art will recognize other embodiments for defining or determining the importance levels. [0041] The action processing unit 136 correlates the system status parameters 202 monitored by the system status parameter monitor 132 with the evolution of the processes 210 monitored by the event monitor 134. In addition, the action processing unit 136 analyses the occurred events 212. Thus, the action processing unit 136 determines whether a problem appeared which may be indicative of a possible future failure. If a problem needs to be addressed, the action processing unit 136 identifies a predetermined action to be taken in the data processing system 110. In one embodiment, the predetermined action is identified on the basis of at least one of the associated importance levels 218 and at least one of the system status parameters 202. [0042] The predetermined action to be taken includes managing logging activity of the data processing system 110. If, for instance, the problem is determined on the basis of the system status parameters 202 but cannot be unambiguously attributed to a specific process, the action processing unit 136 may increase logging activity for all processes running on the data processing system 110. If the problem is related to an event in a specific process, a running log process may be initiated to create log file entries 220 for all subsequently occurring events in the specific process. The log file entries 220 are stored in a corresponding log file 222 which is illustratively contained in the database 139. The predetermined action to be taken may further include notification 240 of a user of the occurred event 212 or the appeared problem and acting on allocated processing (CPU) and/or storage capacities 230, e.g., in order to inhibit increased storage and processing capacity usage of the specific process. Acting on allocated CPU and/or storage capacities 230 may additionally include (as indicated by dashed arrow 250) an increase of allocated storage capacity for the log file 222 in the database 139, if logging activity is increased. [0043] It should be noted that the above-described interactions between the constituent functions of the event manager 130 are merely illustrative and not construed for limiting the invention to these described interactions. Those skilled in the art will recognize that only a part of the functions could be used to implement an effective logging activity management mechanism for a process in a data processing system according to the invention. For instance, the system status parameter monitor 132 may monitor at least one system status parameter for the data processing system 110 and the action processing unit 136 may manage the logging activity for the process on the basis of the at least one system status parameter. Thus, implementation of the event monitor 134 may be omitted. Alternatively, the event monitor 134 may detect events occurring during execution of the process and determine an importance level for an occurred event on the basis of trend analysis indicating evolution of the process. The trend analysis illustratively consists of a determination of at least one process performance parameter such as used memory, allocated processing capacity or duration between a process request and result delivery. The action processing unit 136 may then compare the determined importance level with a predetermined threshold value and create a log file entry for the occurred event only if the determined importance level exceeds the predetermined threshold value. Thus, implementation of the system status parameter monitor 132 may be omitted. However, it will be recognized by the skilled person that in both cases the logging activity is managed either on the basis of an absolute or on the basis of a relative importance of corresponding process events or activities. Thus, in both cases an improved and effective logging activity management mechanism is provided. [0044] An embodiment of the operation of an event manager (e.g., event manager 130 of FIGS. 1 and 2) is described below with reference to FIGS. 3-5. For simplicity, in the following explanations reference is only made to the event manager as such without explicitly referring to individual constituent functions thereof. Moreover, by referring only to the event manager as such, an implementation thereof wherein separate constituent functions cannot unambiguously be distinguished is contemplated. [0045] Referring now to FIG. 3, an illustrative method 300 is shown that represents a sequence of operations as performed by the event manager in a data processing system (e.g., data processing system 110 of FIG. 1). Method 300 is entered at step 310. At step 320, the event manager detects an occurring event (e.g., event 212 of FIG. 2). At step 330, the event manager determines one or more system status parameters (e.g., system status parameters 202 of FIG. 2). [0046] The event manager then establishes a relation between the occurred event and the one or more system status parameters. To this end, the event manager determines at step 340 whether the one or more system status parameters exceed associated predetermined parameter thresholds. Specifically, if one of the one or more system status parameters exceeds its associated predetermined parameter threshold, it is assumed that the occurred event influenced the overall performance of the data processing system and caused a system status change. In this case, at step 350, the event manager performs a predetermined action as described above. Selection of the predetermined action to be taken is described below with reference to FIG. 4. [0047] If, to the contrary, none of the system status parameters exceed their associated predetermined parameter threshold, it may be assumed that the data processing system is correctly performing and that the system status did not change. In this case the event manager may create a log file entry (e.g., log file entry 220 of FIG. 2) at step 360 for the occurred event for tracking or reporting purposes. At step 370, the event manager stores the log file entry in a corresponding log file (e.g., log file 222 of FIG. 2). Method 300 then exits at step 380. Alternatively, the event manager may renounce to performance of steps 360 and 370 as it is assumed that the data processing system is correctly performing. Thus, it may be assumed that no log file entry needs to be created so that method 300 may exit at step 380. [0048] Referring now to FIG. 4, an illustrative method 400 for selecting a predetermined action to be taken according to step 350 of FIG. 3 is described. In one embodiment, the selection is performed on the basis of user-specified selection criteria. User-specified criteria refer to settings that are predefined by a user. For instance, a user may define that certain events require a user notification while other events require only an increase of logging activity. Specifically, if correct performance of an application is critical to the business of a user, the user may wish to be notified whenever a problem occurs in order to take desired preventative actions as soon as possible in order to prevent failure. If performance of the application is not particularly important, failure may not be critical for the business of the user so that an increase of logging activity would be sufficient for resolving the problem once failure occurs. [0049] Selection of a predetermined action may also be performed on the basis of application-specific criteria or system-determined criteria. Application-specific criteria refer to criteria which are hard-coded in an application and, thus, predefined by the programmer. System-determined criteria refer to criteria which are hard-coded in the data processing system, e.g., in the operating system 118 of FIG. 1, and thus independent on the user or application. [0050] In any case, the selection of the predetermined action to be taken starts at step 402. At step 402, the event manager determines whether logging activity should be increased. Illustratively, the event manager determines whether a log file entry (e.g., log file entry 220 of FIG. 2) should be created for the occurred event, thereby increasing the logging activity. If it is determined that logging activity should be increased, processing continues at step 404, where the log file entry for the occurred event is processed. Processing of the log file entry is described below with reference to FIG. 5. [0051] If it is determined that logging activity should not to be increased, the selection continues at step 406. At step 406, the event manager determines whether a user notification is required. If it is determined that user notification (e.g., user notification 240 of FIG. 2) is required, the event manager notifies the user at step 408. Notification may be performed by conventional techniques such as displaying a visual indication on a display device (e.g., display 142 of FIG. 1). Processing then exits at step 410. [0052] If it is determined that the user should not be notified, the selection continues at step 412. At step 412, the event manager determines whether action on processing and/or storage capacities (e.g., CPU and/or storage capacities 230 of FIG. 2) is required. If it is determined that such action is required, the event manager identifies a specific action to be performed, e.g., limiting the available storage for a process, and performs the action at step 414. Action on processing and/or storage capacities may also be performed by conventional techniques. Processing then exits at step 416. [0053] If it is determined that such action is not required, processing proceeds from step 412 to step 418. Step 418 is representative of any other type of predetermined action to be taken by the event manager contemplated as embodiments of the present invention. However, it should be understood that embodiments are contemplated in which less then all the available predetermined actions to be taken are implemented. For example, in a particular embodiment only logging activity management is used. In another embodiment, only user notification and action on processing and/or storage capacities are used. Furthermore, more than one predetermined action can be performed. For instance, logging activity may be increased and, additionally, the user may be notified. In this case, instead of exiting method 400 after performance of a predetermined action according to one of steps 404, 408, 414, the method 400 continues subsequently with one of steps 406, 412 and 418, respectively. Such a continuation may be made independent on the respective determinations made in one of steps 402, 406 or 412. [0054] Referring now to FIG. 5, an illustrative method 500 for processing a log file entry (e.g., log file entry 220 of FIG. 2) according to step 404 of FIG. 4 is described. At step 510, the event manager determines and associates an importance level with the occurred event. At step 520, the event manager determines whether the importance level exceeds a predetermined threshold value. The predetermined threshold value may, for instance, be defined on the basis of user input or on the basis of predefined process parameters. Accordingly, a user may provide a plurality of predetermined threshold values for possibly occurring events, which may be based on the user's experience or an analysis of respective training data indicating an absolute or relative importance of occurring events. The predefined process parameters refer, for example, to common performance parameters of the process which may be determined by previous execution(s) of a corresponding process. Accordingly, the predefined process parameters include parameters such as memory used by the process and processing capacity allocated to the process. [0055] Specifically, step 520 represents a determination by the event manager as to whether the occurred event is actually related to a problem which may cause a failure in the future or not. More specifically, according to the determination made at step 340 in FIG. 3 it is assumed at step 520 that the occurred event potentially represents a problem that may lead to failure. However, it is possible that the system status parameters exceed their associated predetermined parameter thresholds only because of a general load peak occurring in the data processing system that usually ceases without resulting in a failure. Thus, in order to ensure that the occurred event actually relates to a problem and that a log file entry needs to be created for the occurred event, an additional verification may be made at step 520. Accordingly, if the importance level exceeds the predetermined threshold value, it is assumed that the occurred event is actually related to a problem which may cause failure of the data processing system in the future. Therefore, the event manager creates a log file entry (e.g., log file entry 220 of FIG. 2) at step 530 for the occurred event for debugging/analysis purposes in order to allow for a quick resolution of the problem if failure occurs. At step 540, the event manager stores the log file entry in a corresponding log file (e.g., log file 222 of FIG. 2). Method 500 then exits at step 550. If, however, the importance level does not exceed the predetermined threshold value, it is assumed that the occurred event is not related to a problem which may cause failure of the data processing system in the future. Accordingly, method 500 exits at step 550. [0056] It should be understood that the foregoing are merely representative embodiments, and that the invention admits of many other embodiments. For example, it is also contemplated that a background thread implementing an event manager can be started when an application comes up as part of a logging component's initialization. The logging component reads a configuration file, collects user customized information on what types of events the logging component should be looking for and what actions the logging component should take if such events occur. There can be multiple specialized background threads created to handle different events for scalability. The logging component can be implemented such that changes can be made to it dynamically. For instance, if the logging component receives a request to log a debug message but a logging level for logging exclusively error messages is set, the debug message is not logged. In this case, the logging component can receive an update command from the background thread requesting the logging component to update itself in order to increase logging activity for logging also debug messages. Accordingly, after the update the logging component will also log debug messages. [0057] In various embodiments, the invention provides numerous advantages over the prior art. For instance, memory leaks representing commonly occurring problems in data processing systems may easily be recognized and prevented according to the invention. Memory leaks refer to unused memory which is allocated to a process or application such that at least one active user reference to this memory continuously exists. The at least one active user reference prevents returning this memory for reuse by another application or process. Accordingly, by increasing the number of memory leaks in a data processing system, the unused memory is increased and, consequently, the available memory shrinks. [0058] Such memory leaks are notoriously hard to find and typically recreate only over very long periods of time, as memory generally leaks slowly until all available memory resources are gone. In the present context “recreate” means “to occur again”. In other words, memory leaks are problems that are generally only recognized after long periods of running because of an occurring failure, e.g., the system crashes. But the memory leak problem typically exists all along running. It just does not cause any obvious outward signs of failure. Even in languages such as Java which has garbage collection support, memory leaks are a problem. A Java Virtual Machine can only cleanup memory if there are no user references to it anymore. If however, for example, a globally scoped hash table is created and new objects are continuously stacked into it, none of them ever becomes unreachable if the reference to the hash table itself is not lost. Eventually, the hash table will even grow to consume the systems resources entirely. In this case simply logging occurring events in the data processing system according to conventional techniques would be very unsatisfactory. In fact, as the memory leaks over a long period of time a corresponding conventional log file can be very voluminous. Thus, analyzing the corresponding log file would be very time-consuming and difficult as it would be hard for an operator to identify the relevant information. According to the invention, the potential for memory leaks and a related subsequent failure may be determined in advance. Thus, an appropriate preventative action may be taken in advance to the failure. In one aspect of the invention such action may, for instance, be taken against a logging component by increasing its activity. [0059] According to another aspect, a process trend analysis is performed by monitoring one or more system status parameters. For example, most applications or processes normally reach a so-called “steady-state” by which they are basically using new memory at the same rate at which they are returning old memory. If an application never reaches the steady-state, it will eventually crash and cause failure because of memory leaks. In other words, if an application that has been running at a given level for a longer period of time begins to consume more and more resources, this indicates that something has changed that could potentially be significant. Accordingly, this determination may prompt logging at an increased level as things could be moving towards failure. Thus, by performing the trend analysis, occurring events are detected and all events which require an increased attention are identified. This identification may be performed by associating an importance level with each occurred event as described above. [0060] In addition to memory leaks, many other types of situations can warrant execution of preventative actions. Such situations include, for instance, threads that have a stack that is not changing (looping) or increasing numbers of blocked threads (deadlocks) in a data processing system. In these cases, the system could be configured so that areas experiencing trouble would be the only areas in which the background thread increases logging information. Furthermore, applications in which response time is a critical feature can warrant execution of preventative actions. In such applications the system could be configured such that the background thread increases logging information immediately once the required response times are not being met consistently to provide immediately relevant debugging information to an operator. Once the required response times are met consistently again, the background thread may decrease the logging information to the previous level. [0061] Another illustrative application of the present invention is with respect to application programming interfaces such as Java Database Connectivity. Java Database Connectivity (JDBC) is an application program interface (API) specification for connecting programs written in Java to the data in popular databases. The application program interface allows users to encode access request statements in Structured Query Language (SQL) that are then passed to the program that manages the database. The database manager returns the results through a similar interface. One commercially available JDBC driver has a statement handle array where it stores all database resources that are in use. If all database handles are in use, the system is considered to be “out of resources” despite the availability of sufficient memory. Therefore, the burden is on users to ensure that any JDBC connections previously opened are eventually closed. Inevitably, however, users fail to properly manage these resources eventually leading to an unacceptably high unreachable number of resources. In one embodiment of the invention, a logging plug-in is built specifically to watch the statement handle structure. During what appears as normal operation, the logging level is low. Upon detecting a threshold condition indicating a resource problem, logging activity is increased. The threshold condition may be, for example, a predetermined number of handles in handle structure, a certain percentage/number of handles that has not been used in a certain amount of time, etc. [0062] In another embodiment, the logging plug-in described above may perform preventative actions in addition to logging. For example, in the case of the growing number of statement handles, there may be a last accessed flag for each statement in the statement handle array. The plug-in may be configured to increase logging, close the connection explicitly and close database resources explicitly. This could result in operations failing, but preserves the overall system and application from failure. [0063] While the foregoing is directed to embodiments of the present invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof, and the scope thereof is determined by the claims that follow. 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destination for evaluation before sending the attachmentUS20100251020 *Jun 11, 2010Sep 30, 2010Hitachi, Ltd.Method and apparatus for data recovery using storage based journalingUS20100274985 *Jul 12, 2010Oct 28, 2010Hitachi, Ltd.Method and apparatus for backup and recovery using storage based journalingUS20110317523 *Jun 25, 2010Dec 29, 2011International Business Machines CorporationMerging calendar entriesUS20120284287 *May 6, 2011Nov 8, 2012Sap AgSystems and Methods for Business Process LoggingUS20120284316 *May 6, 2011Nov 8, 2012Sap Ag, A German CorporationSystems and methods for business process loggingUS20160092295 *Sep 25, 2014Mar 31, 2016Oracle International CorporationAdaptive application loggerCN103645983A *Dec 17, 2013Mar 19, 2014山东中创软件工程股份有限公司Method and device for generating journal file in domestic environmentWO2015009405A1 *Jun 20, 2014Jan 22, 2015Netapp, Inc.Systems and methods for filtering low utility value messages from system logs* Cited by examinerClassifications U.S. Classification1/1, 707/999.2International ClassificationG06F17/30, H04L12/24, H04L12/26Cooperative ClassificationH04L41/0686, G06F11/0715, H04L41/069, G06F11/0781European ClassificationG06F11/07P4E, G06F11/07P1C, H04L41/06F, H04L41/06GLegal EventsDateCodeEventDescriptionMay 8, 2003ASAssignmentOwner name: INTERNATIONAL BUSINESS MACHINES CORPORATION, NEW YFree format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:DETTINGER, RICHARD D.;KULACK, FREDERICK A.;STEVENS, RICHARD J.;AND OTHERS;REEL/FRAME:014063/0175;SIGNING DATES FROM 20030429 TO 20030505RotateOriginal ImageGoogle Home - Sitemap - USPTO Bulk Downloads - Privacy Policy - Terms of Service - About Google Patents - Send FeedbackData provided by IFI CLAIMS Patent Services


text:
Tampa to Providence Flights: Cheap Flights from TPA to PVD $197.6 | Expedia
Cheap Flights from Tampa to Providence $197.6 Flight onlyFlight + Hotel HotelsPlease correct the errors belowDestinationCheck-inCheck-outRooms123456789+Adults (18+)1234567891011121314Children (0-17)0123456Child 1: Age <11234567891011121314151617Child 2: Age <11234567891011121314151617Child 3: Age <11234567891011121314151617Child 4: Age <11234567891011121314151617Child 5: Age <11234567891011121314151617Child 6: Age <11234567891011121314151617Room 1Adults (18+)1234567891011121314Children (0-17)0123456Child 1: Age <11234567891011121314151617Child 2: Age <11234567891011121314151617Child 3: Age <11234567891011121314151617Child 4: Age <11234567891011121314151617Child 5: Age <11234567891011121314151617Child 6: Age <11234567891011121314151617Room 2Adults (18+)1234567891011121314Children (0-17)0123456Child 1: Age <11234567891011121314151617Child 2: Age <11234567891011121314151617Child 3: Age <11234567891011121314151617Child 4: Age <11234567891011121314151617Child 5: Age <11234567891011121314151617Child 6: Age <11234567891011121314151617Room 3Adults (18+)1234567891011121314Children (0-17)0123456Child 1: Age <11234567891011121314151617Child 2: Age <11234567891011121314151617Child 3: Age <11234567891011121314151617Child 4: Age <11234567891011121314151617Child 5: Age <11234567891011121314151617Child 6: Age <11234567891011121314151617Room 4Adults (18+)1234567891011121314Children (0-17)0123456Child 1: Age <11234567891011121314151617Child 2: Age <11234567891011121314151617Child 3: Age <11234567891011121314151617Child 4: Age <11234567891011121314151617Child 5: Age <11234567891011121314151617Child 6: Age <11234567891011121314151617Room 5Adults (18+)1234567891011121314Children (0-17)0123456Child 1: Age <11234567891011121314151617Child 2: Age <11234567891011121314151617Child 3: Age <11234567891011121314151617Child 4: Age <11234567891011121314151617Child 5: Age <11234567891011121314151617Child 6: Age <11234567891011121314151617Room 6Adults (18+)1234567891011121314Children (0-17)0123456Child 1: Age <11234567891011121314151617Child 2: Age <11234567891011121314151617Child 3: Age <11234567891011121314151617Child 4: Age <11234567891011121314151617Child 5: Age <11234567891011121314151617Child 6: Age <11234567891011121314151617Room 7Adults (18+)1234567891011121314Children (0-17)0123456Child 1: Age <11234567891011121314151617Child 2: Age <11234567891011121314151617Child 3: Age <11234567891011121314151617Child 4: Age <11234567891011121314151617Child 5: Age <11234567891011121314151617Child 6: Age <11234567891011121314151617Room 8Adults (18+)1234567891011121314Children (0-17)0123456Child 1: Age <11234567891011121314151617Child 2: Age <11234567891011121314151617Child 3: Age <11234567891011121314151617Child 4: Age <11234567891011121314151617Child 5: Age <11234567891011121314151617Child 6: Age <11234567891011121314151617Adults (18+)9101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899Children (0-17)0123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899Search Search Flights Please correct the errors below.RoundtripOne WayMultiple DestinationsLeaving fromGoing toDepartingReturningAdults (18+) 123456Children (0-17) 0123456Flight 1Flying fromFlying to Departing Flight 2Flying fromFlying toDepartingFlight 3Flying fromFlying toDeparting Flight 4Flying fromFlying toDepartingFlight 5Flying fromFlying toDepartingAdults (18+) 123456Children (0-17) 0123456Child 1Age <1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Child 2Age <1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Child 3Age <1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Child 4Age <1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Child 5Age <1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Child 6Age<1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Children under 2 must either sit in laps or in seats.In lapIn seatAdvanced optionsAdvanced optionsNonstopRefundable flight Preferred airline No preference Tigerair Australia with BagTigerair Singapore with BagTigerair TaiwanAir BurkinaAeroGalMaya Island AirAir Choice OneSilver AirwaysBoutique AirLATAM Airlines ArgentinaInterjetGermanwingsCemairSun Air ExpressEra AlaskaInsel Air InternationalPAN AM World Airways DominicanaInsel Air ArubaMyanmar Airways InternationalPacific Coastal AirlinesCape AirTropic AirAir MoldovaAvior AirlinesJet AirwaysSouthern AirwaysAegeanAmerican AirlinesairberlinAir CanadaAzulAir FranceAir IndiaAeromexicoAerolineas ArgentinasAlaska AirlinesRoyal Air MarocAviancaFinnairAlitaliaLa CompagnieJetBlue AirwaysBritish AirwaysSeaborne AirlinesFlybeRoyal Brunei AirlinesAir BotswanaEVA AirwaysAir BalticCaribbean AirlinesAir ChinaAirlines of Papua 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A.PrecisionAirSurinam AirwaysQantas AirwaysQatar AirwaysLao AirlinesAserca AirlinesNepal AirlinesRoyal JordanianTarom-Romanian Air TransportSATA International-Azores Airlines S.A.South African AirwaysShandong AirlinesXL AirwaysSASBrussels AirlinesSingapore AirlinesCorsairAeroflot-Russian AirlinesSaudi Arabian AirlinesTACA AirlinesJetairflyThai Airways InternationalTradewind AviationTurkish AirlinesAir Tahiti NuiTAP PortugalAir TransateasyJetUral AirlinesUnitedVistaraSriLankan AirlinesTransaero AirlinesUtair AviationAir EuropaVision AirlinesVirgin AustraliaVivaAerobusVietnam AirlinesTACV-Cabo Verde AirlinesVirgin AtlanticAeromar AirlinesVirgin AmericaLC PeruWindward Island Airways InternationalWestJetWOW airOman AirLATAM Airlines EcuadorVolarisGreat Lakes AirlinesPegasus AsiaPreferred class First Class BusinessEconomy Premium EconomySearchSearch Flight + Hotel Please correct the errors below. Leaving from Going to DepartingReturningRooms 1 2 3 Adults (18 +) 123456Children (0 - 17) 0123456Child 1:Age <1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Child 2:Age <1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Child 3:Age <1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Child 4:Age <1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Child 5:Age <1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Child 6:Age <1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Room 2Adults (18 - 64)123456Children (0 - 17)0123456Child 1-?- <1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Child 2-?- <1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Child 3-?- <1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Child 4-?- <1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Child 5-?- <1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Child 6-?- <1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Room 3Adults (18 - 64)123456Children (0 - 17)0123456Child 1Age <1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Child 2Age <1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Child 3Age <1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Child 4Age <1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Child 5Age <1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Child 6Age <1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Children under 2 must either sit in laps or in seats.In lapIn seatI only need a hotel for part of my trip Check-inCheck-outSearch
Cheapest Flights from Tampa to Providence (TPA to PVD)
14 Feb - 14 FebTPATampaPVDProvidence$197.60roundtrip25 Jan - 30 JanTPATampaPVDProvidence$201.70roundtrip14 Jan - 16 JanTPATampaPVDProvidence$203.20roundtrip14 Dec - 14 DecTPATampaPVDProvidence$205.58roundtrip5 Jan - 9 JanTPATampaPVDProvidence$205.70roundtrip5 Jan - 9 JanTPATampaPVDProvidence$207.20roundtrip13 Dec - 13 DecTPATampaPVDProvidence$209.67roundtrip15 Dec - 16 JanTPATampaPVDProvidence$215.10roundtrip13 Dec - 19 DecTPATampaPVDProvidence$220.51roundtrip15 Dec - 16 JanTPATampaPVDProvidence$223.12roundtrip14 Feb - 14 FebTPATampaPVDProvidence$224.60roundtrip15 Dec - 16 JanTPATampaPVDProvidence$225.70roundtrip8 Dec - 13 DecTPATampaPVDProvidence$228.17roundtrip4 Feb - 5 FebTPATampaPVDProvidence$228.70roundtrip14 Dec - 15 DecTPATampaPVDProvidence$231.50roundtrip4 Feb - 5 FebTPATampaPVDProvidence$232.70roundtrip
New BedfordEWB-New Bedford Regional$612.70WorcesterORH-Worcester Regional$424.60
Los Angeles to Providence (LAX - PVD)Orlando to Providence (MCO - PVD)Fort Lauderdale to Providence (FLL - PVD)Washington to Providence (DCA - PVD)Charlotte to Providence (CLT - PVD)Jacksonville to Providence (JAX - PVD)Fort Myers to Providence (RSW - PVD)Washington to Providence (WAS - PVD)Weyers Cave to Providence (SHD - PVD)Atlanta to Providence (ATL - PVD)Raleigh to Providence (RDU - PVD)
Answer : December 15th offers bookings (as of November 28th) that are 41% below the average price for this route. Saving on flight costs means you'll have more cash in hand for the trip.
Question : Which airline is giving the best deals for round-trip flights from Tampa International Airport (TPA) to Theodore Francis Green Memorial State Airport (PVD)?
Question : From Tampa to Providence, which day is going to have the most flight times?
Answer : Wednesday has the most flight times for Tampa to Providence with 31.
Question : What's the expected flight time for TPA to PVD?
Answer : On average, the flight time from Tampa to Providence is 2 hours and 48 minutes.
Question : If you're booking TPA to PVD, how many different options of departure times do you have on a daily basis?

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David Copperfield stooge claims he was left brain-damaged in bungled vanishing trick | Daily Mail Online
London-born chef Gavin Cox, 55, was called on stage by David Copperfield
But he fell backstage after taking part in an illusion with inflatable balls
Mr Cox said he was left permanently brain damaged as a result
Copperfield's lawyers denied Mr Cox's allegations and say the illusion has been safely performed for 15 years involving 100,000 participants
By Caroline Graham And Paul Cahalan
Published: 18:49 EST, 4 June 2016 | Updated: 05:33 EST, 5 June 2016
It should have been the magical highlight of a holiday of a lifetime.
Having flown to Las Vegas with his wife to celebrate his birthday, Gavin Cox was excited to get the hottest ticket in town, to see David Copperfield at the MGM Hotel and Casino.
Mr Cox and his wife Minh were braced for an evening of dazzling entertainment from the world’s most famous magician, whose tricks are a closely guarded secret and have brought him a vast fortune and an enviable A-list lifestyle.
Then the night got even better, as Mr Cox was invited to be one of the volunteers to join Copperfield on stage and take part in his act.
But from that moment followed a series of events that London-born Mr Cox claims have ‘wrecked’ his life and have placed him at legal loggerheads with Copperfield.
The extraordinary case has dragged on for almost three years and led to the magician’s techniques being revealed in unprecedented detail.
Mr Cox, 55, had been picked from the audience to take part in an illusion in which 13 fans ‘vanish’ from inside a suspended cage on stage – only to ‘miraculously’ reappear moments later at the back of the theatre.
Gavin Cox in hospital after his fall. Gavin fell and injured himself seriously at the MGM Grand after volunteering in a David Copperfield show
But according to Mr Cox, a chef who once cooked for the Queen Mother, the stunt went horribly wrong after he slipped and fell in a poorly lit area, leaving him permanently brain-damaged.
It is his sensational court documents in a claim for millions of dollars against the magician and the hotel which shed light on the smoke and mirrors world of a modern-day Houdini.
The claim states: ‘During the trick plaintiff [Mr Cox] was injured when he was hurried with no guidance or interaction through a dark area under construction with cement dust and debris, causing him to slip and fall.’
In an exclusive interview with The Mail on Sunday last night, Mr Cox said: ‘Seeing David Copperfield was the highlight of a dream trip to celebrate my 53rd birthday. Instead it turned into a nightmare. My health has been wrecked, and I’ve lost my business and my life savings.’
Mr Cox and his wife are seeking punitive damages from Copperfield and MGM for alleged negligence. The magician and the hotel vehemently deny the claims, saying the injuries were caused by ‘pre-existing and/or unrelated medical conditions’.
David Copperfield with his wife, designer Chloe Gosselin at an event in New York. Copperfield is one of the biggest names in magic
Today Mr Cox is forced to wear an oxygen ‘lung’ at night because he stops breathing, and he spent three months in a Californian brain trauma centre. The couple claim they have been forced to live in the US for nearly three years as the case drags on.
Their lifestyle could not be more different from Copperfield’s, whose talents have earned him a £550 million fortune, including palatial homes in Nevada and California, and a string of 11 private islands in the Bahamas known as Copperfield Bay.
Meanwhile, home for the Coxes is a rented apartment in a suburb of Las Vegas.
‘We are too broke to go out and Gavin’s injuries prevent us from enjoying a normal life,’ Mrs Cox said. ‘Gavin once cooked for royalty but now he can’t even bake a muffin because he has nerve damage in his hands and no sense of smell.’
Their nightmare began in November 2013 when Copperfield ‘chose’ Gavin to take part in the trick – called 13 – by hurling giant inflatable balls into the audience. Those who caught them were invited to the stage. ‘I was in seventh heaven when I caught a ball,’ Mr Cox said.
It was total pandemonium. You don’t know where you are going. It’s dark. There are hands pushing you on your back. As I went around a corner, my feet slipped from underneath me and I hit the ground
As he walked to the stage, the 6ft 4in chef said he was asked three questions by a Copperfield employee: Could he run? Was he a magician? Was he a member of the Press?
Once on stage, he and 12 others were seated in a suspended cage and given torches to hold. He recalled: ‘A curtain comes down over the box and torch light shines out to give the impression we are still in there.’
But in reality ‘all hell broke lose’ once the curtain came down, according to Mr Cox. He said Copperfield’s assistants hurried him down a secret passage, through a door and outside into the open air. He said: ‘It was like a fire alarm went off. They were saying “Hurry! Run, run, run!”
‘It was total pandemonium. You don’t know where you are going. It’s dark. There are hands pushing you on your back. As I went around a corner, my feet slipped from underneath me and I hit the ground.’ Mr Cox fell as he ran around the side of the theatre. His lawsuit claims Copperfield ‘failed to prevent, inspect, maintain and warn of dangerous conditions’ and claimed the magician and the hotel failed to ‘devise a trick that would be safe for audience participants’.
Copperfield’s lawyers deny this, saying ‘multiple inspections’ were made of the area.
Mr Cox blacked out after his fall but remembers the audience cheering at the end of the trick.
Afterwards Copperfield came to a side room to talk to the 13 and said he trusted they would not to reveal its secrets.
Mr Cox claims the magician was told, ‘This guy is injured. He needs an ambulance’, and that he told Copperfield he finished the trick despite the injuries as ‘I didn’t want to let you down’.
However, documents filed in Copperfield’s defence insist Mr Cox asked for help only after the magician left the room.
An ambulance took Mr Cox to hospital where his right shoulder was found to be dislocated.
Two days later he filled out an accident report at MGM and hired a US personal injury lawyer.
Gavin Cox and wife Minh at their lawyer's office in Las Vegas. Gavin fell and injured himself seriously at the MGM Grand after volunteering in a David Copperfield show
His wife said: ‘We stayed in the US for three weeks because Gavin’s injuries meant he couldn’t fly.’ Once back in Britain, Mr Cox said he began to suffer chronic pain, headaches and confusion. A scan would later show lesions on his brain.
But Mrs Cox said NHS waiting lists were ‘too long and he needed immediate treatment’.
So the couple returned to Vegas in February 2014. Their travel insurer refused to pay for ongoing treatment, but they were seen under a ‘medical lien’ – doctors agreed to treat Mr Cox and receive payment only when the lawsuit is settled.
Mr Cox’s career had once included years as a chef at London’s Buck’s Club, where he cooked for the Queen Mother, Margaret Thatcher and Dracula actor Christopher Lee, and running a guesthouse in Broadstairs, Kent.
But he has been unable to work since the accident.
Having had multiple operations on his back and neck, he has been diagnosed with permanent brain damage and a form of Parkinson’s.
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His wife said: ‘The force of the fall shook up his brain. His shoulder took the brunt. A doctor said if he’d hit his head his neck would have snapped and he’d be dead.’
Their 11-year-old son Harry has remained in the UK, cared for by the couple’s oldest son Oliver, 25. The Coxes were forced to sell their guesthouse for £515,000 at the end of 2014 and having been living off their savings.
A recent date for mediation was pushed back after the magician’s lawyers said they needed to travel to the UK to question Mr Cox’s sons and British doctors under oath.
Copperfield’s legal team claim Mr Cox could have received the care he needed in the UK, saying: ‘The claim that they were forced to seek treatment in Las Vegas and are now trapped here is not true.’
Last night Copperfield’s lawyers said: ‘This illusion has been performed for more than 15 years and with more than 100,000 participants. The history of the show speaks for itself. We deny all allegations. Unfortunately we cannot comment further due to ongoing litigation.’

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Entry Level Jobs, Employment in Everett, WA | Indeed.com
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Municipal ferry, City of New York, [named] Brooklyn skip navigation
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Municipal ferry, City of New York, [named] Brooklyn
Title: Municipal ferry, City of New York, [named] Brooklyn
Reproduction Number: LC-DIG-det-4a16074 (digital file from original)
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"G 6608" on negative.
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value: This website is the research library that officially serves the United States Congress and is the de facto national library of the United States. It is the oldest federal cultural institution in the United States.


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Empirical Studies on Volatility in International Stock Markets book by Eugenie M.J.H. Hol | 2 available editions | Alibris Books
Empirical Studies on Volatility in International Stock Markets describes the existing techniques for the measurement and estimation of volatility in international stock markets with emphasis on the SV model and its empirical application. Eugenie Hol develops various extensions of the SV model, which allow for additional variables in both the mean and the variance equation. In addition, the forecasting performance of SV models is compared not only to that of the well-established GARCH model but also to implied volatility and ... Read More
Empirical Studies on Volatility in International Stock Markets describes the existing techniques for the measurement and estimation of volatility in international stock markets with emphasis on the SV model and its empirical application. Eugenie Hol develops various extensions of the SV model, which allow for additional variables in both the mean and the variance equation. In addition, the forecasting performance of SV models is compared not only to that of the well-established GARCH model but also to implied volatility and so-called realised volatility models which are based on intraday volatility measures. The intended readers are financial professionals who seek to obtain more accurate volatility forecasts and wish to gain insight about state-of-the-art volatility modelling techniques and their empirical value, and academic researchers and students who are interested in financial market volatility and want to obtain an updated overview of the various methods available in this area. Read Less
ISBN-13: 9781441953759
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