In this paper, we consider burst detection within the context of privacy. In our scenario, multiple parties want to detect a burst in aggregated time series data, but none of the parties want to disclose their individual data. Our approach calculates bursts directly from linear transform coefficients using a cumulative sum calculation. In order to reduce the chance of a privacy breech, we present multiple data perturbation strategies and compare the varying degrees of privacy preserved. Our strategies do not share raw time series data and still detect significant bursts. We empirically demonstrate this using both real and synthetic distributed data sets. When evaluating both privacy guarantees and burst detection accuracy, we find that our percentage thresholding heuristic maintains a high degree of privacy while accurately identifying bursts of varying widths

This workshop aims to provide a venue for discussion and exchange of ideas on data and knowledge engineering issues in the dynamic environment of e-business, enterprise computing, and business services and transformation.

Web++ is a prototype system that supports user transparent wide area replication of resources in order to improve the response time and reliability of the HTTP service. Our architecture is based on smart clients, and can be dynamically downloaded as mobile code into a user's application, presents a number of advantages. Clients keep track of the average HTTP latency that they experience from various servers and use that information in order to make to choose the replica of a resource that is expected to deliver the best response time for them. The clients also provide feedback on the observed request latencies to the servers, which allows helps the servers to determine which resources should be replicated and what would be the best locations for the replicas. We describe in this paper a distributed server-initiated approach for resource replication in which all servers can decide autonomously whether to replicate resources and the locations where the replicas should be allocated. In addition to the novel use of smart clients, our algorithm also avoids keeping track of complex network topologies by using the concept of logical segments. We present the results of experiments that show that our algorithm for resource allocation scale well with respect to the number of servers and the number of replicated resources.

Business-to-business (B2B) e-commerce is emerging as a new market with tremendous potential. Organizations are trying to link services across organizational boundaries in order to electronically trade goods and services. Standards such as RosettaNet, CBL, ED1, OB1, and cXML, describe how electronic B2B interactions should be carried on so that dynamic trade partnerships can be established and transactions can be executed across organizations. While the development of standards is a fundamental step towards enabling e-business, the problem of linking B2B interactions with internal business processes is still a challenge. In addition, as the industry standards evolve continuously based on changing needs, organizations have to adopt new standards quickly. In this paper we describe how workflow technology can be extended in order to support B2B interactions and to link them with the internal workflows. The proposed framework can be used to speed up both the development of new business processes that support B2B interaction standards and the enhancement of the existing business processes by the addition of B2B interaction capability.

We developed Web++, a prototype system based on user-transparent geographic replication which aims at improving the response time and the reliability of the HTTP service. Web++ extends the current Web client/server architecture with additional capabilities. The extension is provided via Java servlets at the server side and applets at the client side. The servlets pre-process the requested documents such that each logical URL is replaced by a list of physical URLs corresponding to the list of the resource's replica. An applet is automatically downloaded to the client machines together with the first request of each new user session. For subsequent requests within a user session, the applet chooses the physical URT, that corresponds to a resource held by an available server that is expected to deliver the best response time for the server.