Abstract: A system and method in a wireless network for discovering which resources (e.g., other wireless computing devices) are proximate a user's wireless computing device. Wireless signal strengths with respect to various base stations are compared with the signal strengths of other network devices or resources, to determine which devices are experiencing similar signal strengths. Devices with similar signal strengths are deemed proximate. Each participating computing device may send its signal strength reports to a proximity server, which distributes proximity data to network clients. Each client may receive and process the signal strength data for determining which other clients/resources are proximate, or the server can perform proximity computations and return a list of proximate clients. Once computed, the identities of the proximate clients can be used to query for additional data about the clients, such as the names and other details of their owners, or information about the resource.

Abstract: A method and system for execution in a graphical user interface environment are provided to incorporate digital image files in an email message. A template layout gallery is presented that includes a plurality of template layouts for digital image files for possible inclusion in the email message. When an indication is received that at least one digital image file is selected to be included in the email message and that one of the template layouts is to be applied to the at least one selected digital image file, the selected layout is created within the email message body according to the selected template. Prior to sending, the images are compressed.

Abstract: A system and method for automating the web service selection based on reputation information, to help negotiate a contractual web service binding between a client and a server. Reputation information may be schematized into behavioral attributes such as web service responsiveness, web service latency, web service uptime, cost data, business solvency and other trustworthiness and business-related data. Some of the reputation data may be empirically determined, and provided by an independent or other trusted auditor. In one implementation, a client queries a search engine, which returns a ranked list of web services, with the ranking based on reputation scores computed for each web service as collected by an auditor. Clients may provide computational data to weigh the attributes separately. A corporate internet can maintain reputation data for web services to act as an auditor, and a web service server can also execute trusted code to act as an auditor.