Abstract: Techniques are described for managing execution of programs, such as for distributed execution of a program on multiple computing nodes. In some situations, the techniques include selecting a cluster of computing nodes to use for executing a program based at least in part on data to be used during the program execution. For example, the computing node selection for a particular program may be performed so as to attempt to identify and use computing nodes that already locally store some or all of the input data that will be used by those computing nodes as part of the executing of that program on those nodes. Such techniques may provide benefits in a variety of situations, including when the size of input datasets to be used by a program are large, and the transferring of data to and/or from computing nodes may impose large delays and/or monetary costs.

Abstract: Techniques are described for managing distributed execution of programs. In at least some situations, the techniques include decomposing or otherwise separating the execution of a program into multiple distinct execution jobs that may each be executed on a distinct computing node, such as in a parallel manner with each execution job using a distinct subset of input data for the program. In addition, the techniques may include temporarily terminating and later resuming execution of at least some execution jobs, such as by persistently storing an intermediate state of the partial execution of an execution job, and later retrieving and using the stored intermediate state to resume execution of the execution job from the intermediate state. Furthermore, the techniques may be used in conjunction with a distributed program execution service that executes multiple programs on behalf of multiple customers or other users of the service.

Abstract: Techniques are described for managing distributed execution of programs. In some situations, the techniques include dynamically monitoring the ongoing distributed execution of a program on a cluster of multiple computing nodes, and may include automatically determining the status of execution of the program on each of the multiple computing nodes and/or automatically determining the aggregate usage of one or more types of computing resources across the cluster of multiple computing nodes by the distributed program execution. The information obtained from the dynamic monitoring may be used in various manners, including to facilitate dynamically modifying the ongoing distributed program execution in various manners, such as to temporarily throttle usage of computing resources by the distributed program execution (e.g., to remove or reduce one or more bottlenecks).

Abstract: Techniques are described for identifying the use of software applications, such as to determine an identity of a user interacting with a Web site or other electronic information service based on information regarding an application copy used by the user. When a communication is received from a software application, the communication is analyzed to attempt to identify a particular software application copy that sent the communication. Various types of information about a client software application copy may be used in the analysis, including information about particular configuration settings for the client software application and for the client computing device on which the client software application is executing. After a matching software application copy is identified for a received communication, possible inappropriate activities related to the received communication may be identified in various ways, including based on previous communications received from the same software application copy.

Abstract: Techniques are described for managing distributed execution of programs. In some situations, the techniques include dynamically modifying the distributed program execution in various manners, such as based on monitored status information. The dynamic modifying of the distributed program execution may include adding and/or removing computing nodes from a cluster that is executing the program, modifying the amount of computing resources that are available for the distributed program execution, terminating or temporarily suspending execution of the program (e.g., if an insufficient quantity of computing nodes of the cluster are available to perform execution), etc.

Abstract: Techniques are described for use in inhibiting attempts to fraudulently obtain access to confidential information about users. In some situations, the techniques involve automatically analyzing at least some requests for information that are received by a Web site or other electronic information service, such as to determine whether they likely reflect fraudulent activities by the request senders or other parties that initiate the requests. For example, if a request is being made to a Web site based on a user's interaction with a third-party information source (e.g., another unaffiliated Web site) that is not authorized to initiate the request, the third-party information source may be a fraudulent phishing site or engaging in other types of fraudulent activity. If fraudulent activity is suspected based on analysis of one or more information requests, one or more actions may be taken to inhibit the fraudulent activity.

Abstract: Techniques are described for use in selectively authorizing proposed transactions under certain circumstances, such as when payments for the transactions are not assured. In some situations, when payments to a merchant from customers are not assured for proposed item acquisition transactions involving those customers, determinations are made to authorize and proceed with at least some of those proposed transactions in an automatic and selective manner without the assurance of receiving the payments for the selected transactions. For example, a selective determination of whether to authorize a proposed transaction may be made based on analyzing information about the proposed transaction (e.g., about the item(s) involved in the transaction, a payment amount of the transaction, the customer(s) involved in the transactions, etc.) and on information regarding other prior transactions.

Abstract: Techniques are described for managing distributed execution of programs. In at least some situations, the techniques include decomposing or otherwise separating the execution of a program into multiple distinct execution jobs that may each be executed on a distinct computing node, such as in a parallel manner with each execution job using a distinct subset of input data for the program. In addition, the techniques may include temporarily terminating and later resuming execution of at least some execution jobs, such as by persistently storing an intermediate state of the partial execution of an execution job, and later retrieving and using the stored intermediate state to resume execution of the execution job from the intermediate state. Furthermore, the techniques may be used in conjunction with a distributed program execution service that executes multiple programs on behalf of multiple customers or other users of the service.

Abstract: Techniques are described for detecting inappropriate activities based on interactions with Web sites and other electronic information services. In some situations, the techniques involve analyzing user interactions with an electronic information service in order to determine whether the user interactions are likely to reflect fraudulent activities by the user. In at least some situations, information about user interactions may be analyzed by applying one or more assessment tests that are each configured to assess one or more aspects of the interactions and to provide indications of whether those interaction aspects reflect inappropriate activities. If an analysis of one or more user interactions determines that a user is suspected of inappropriate activity, various actions may be taken to inhibit the inappropriate activity from continuing or recurring in the future.

Abstract: Disclosed is an architecture for an intelligent agent and for a distributed platform for supporting many of such agents. Also described are scenarios wherein intelligent agents may be used.