Data processing: database and file management or data structures – Database design – Data structure types
Reexamination Certificate
1998-08-18
2001-09-25
Vu, Kim (Department: 2172)
Data processing: database and file management or data structures
Database design
Data structure types
C707S793000, C707S793000, C707S793000, C707S793000, C707S793000, C709S248000, C714S012000, C714S015000, C714S020000
Reexamination Certificate
active
06295541
ABSTRACT:
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BACKGROUND OF THE INVENTION
The present invention relates generally to management of information or datasets stored on electronic devices and, more particularly, to a system implementing methods for maintaining synchronization of datasets among one, two, or more such devices.
With each passing day, there is ever increasing interest in providing synchronization solutions for connected information appliances. Here, the general environment includes “appliances” in the form of electronic devices including, but not limited to, cellular phones, pagers, other hand-held devices (e.g., REX™, PalmPilot™ and Windows™ CE devices), personal computers (PCs) of all types and sizes, and Internet or intranet access devices (e.g., PCs or embedded computers running, for example, Java virtual machines or browsers or Internet Protocol (IP) handlers).
A problem facing such an environment today is that these devices, and the software applications running on these devices, do not communicate well with one another and are typically not designed with data synchronization in mind. In particular, a problem exists as to how one integrates information—such as calendaring, scheduling, and contact information—among disparate devices and software applications. Consider, for instance, a user who has his or her appointments on a desktop PC at work, but also has a notebook computer at home and a battery-powered, hand-held device for use in the field. What the user really wants is for the information (e.g., appointments), in each device to remain synchronized with corresponding information in all devices in a convenient, transparent manner. Still further, some devices (e.g., PCs) are typically connected at least occasionally to a server computer, e.g., an Internet server, which stores information for the user. The user would of course like the information on the server computer to participate in the synchronization, so that the server also remains synchronized.
There have been attempts to solve the problem of synchronizing datasets across different devices or software applications. An early approach to maintaining consistency between datasets was to import or copy one dataset on top of another. This simple “one-way” approach, one which overwrites a target dataset without any attempt at reconciling any differences, is inadequate for all but the simplest of applications. Expectedly, more sophisticated synchronization techniques were developed. In particular, techniques were developed for synchronization of exactly two datasets by attempting to reproduce in each dataset the changes found in the other dataset since a previous synchronization.
The conventional synchronization techniques, which are limited to such pair-wise, or binary, synchronization, may satisfy an information appliance user who wishes to synchronize exactly two datasets. However, these conventional techniques do not adequately satisfy the modem information appliance user, who is accumulating ever more information appliances and software applications and frequently wants to synchronize information from more than just two datasets. To synchronize more than two datasets, such a user is forced by the conventional synchronization techniques to try to achieve the correct synchronization result using successive binary synchronizations. This approach is not only inefficient and generally inconvenient and confusing for the user, but is also fraught with potential for human error, and, further, may produce incorrect results in certain situations.
As an example, consider a user who needs to synchronize information, e.g., scheduling information, from three sources: a PalmPilot organizer device (“Pilot”), a Windows CE device (“CE Device”), and a Microsoft Outlook PIM (Personal Information Manager) software application (“Outlook”) on a PC. The user may first perform a Pilot-and-Outlook synchronization, typically using a first synchronization software program that is designed and sold specifically for the Pilot. Next, the user may perform an Outlook-and-CE-Device synchronization, typically using a second synchronization program that is designed and sold specifically for the CE Device. At this point, the user may think he or she is finished. However, he or she in reality must still perform another Pilot-and-Outlook synchronization to ensure that the Pilot correctly includes the latest information from the CE Device. Unfortunately, conventional synchronization programs do not tell the user of the need for this additional synchronization.
In general, the conventional synchronization programs do not adequately help the user in keeping more than two datasets synchronized. For example, the conventional programs do not provide a single user interface (UI) that allows the user to select more than two datasets to be synchronized with every other selected dataset. The conventional programs also do not automatically perform the synchronization of data in more than two datasets for the user without further user input. At most, a conventional synchronization program may permit the user to select a pair of datasets having data of one type (e.g., contacts data) for synchronization and a possibly different pair of datasets having data of a different type (e.g., calendar data) for synchronization. Although the user selects more than two datasets in total, any actual synchronization involves only two datasets. More particularly, synchronization of similar data involves only two datasets. Put another way, no single data record on a particular dataset will effect changes in more than one other dataset in response to a user's selection of datasets using the conventional program. In short, the conventional synchronization scheme is inconvenient and susceptible to human error, especially by less technically-savvy users, and especially as the number of datasets above two increases for a user.
The conventional synchronization scheme suffers from a further problem in that when more than two datasets are synchronized using multiple binary synchronizations, dataset status information (e.g., data modification times) that may be available during earlier-performed synchronizations may not be available during later-performed synchronizations. The failure to retain these status information may be intentional and also reasonable under an assumption that only two datasets need ever be synchronized. The failure to retain these status information may also be caused in part by the design limitations of particular information devices or software applications. Whatever the cause, the unavailability of status information during later-performed synchronizations can lead to erroneous results when, for example, conflicts are resolved during later synchronizations, as will be described in a later section.
Another characteristic of the modem environment for connected information appliances is that new appliances are introduced with ever increasing frequency. Conventionally, an entirely new synchronization software application is released with each new appliance. Such a synchronization application is dedicated to synchronizing data in a single particular information appliance with data in one or several popular PIM applications on a PC. Consequently, the user must buy and install a separate synchronization application, which typically is multi-megabytes long, for each new information appliance. This approach is undesirable for a variety of reasons, including the reason that such large software applications typically cannot be quickly downloaded from the Internet by telephone modem or low-bandwidth channels. Furthermore, should it become desirable for the synchronization programs to synchronize additional types of data, e.g., ele
Bodnar Eric O.
Dube Bryan
Kirani Shekhar
LaRue Chris
Suresh Sethuraman
Ly Anh
Smart John A.
Starfish Software, Inc.
Vu Kim
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