In order for current e-Businesses to mature from hastily assembled systems and applications, formal processes must be put in place for planning and budgeting, pricing and costing, and for establishing quality of service and service--level assurances. There are many challenges that e-Businesses face in formalizing these processes. The most important problem is to bridge the semantic disconnect between business objectives and the information system performance objectives. Next, the characterization of the e-Business infrastructure is extremely complex, given the variety of applications and system configurations at a web site and the traffic it receives. Finally, e-Businesses need to associate and apply traditional economic factors, such as depreciation and usage to applications, operating systems, and databases. In this paper, we propose an approach for defining and quantifying effective e-Business capacity that allows us to translate quality of service objectives into the number of users that a web site can support. This approach is based on inducing online models using machine learning and statistical pattern recognition techniques. As a consequence, the approach is flexible: it adapts to any site configuration and environment. The concept of e-Business capacity allows us to naturally answer planning and operational questions about the information system infrastructure needed to support the e-Business. The questions range from indicating which performance measures in the system are "important" to simulating "if-then" scenarios

Describes SRI International's ERDoS (End-to-end Resource management of Distributed Systems) project. ERDoS is a distributed middleware with comprehensive resource management support, including application scheduling, resource allocation and graceful adaptation. We discuss how we have implemented this resource management as part of the Java Virtual Machine (JVM). We have also provided a resource management application programming interface (API) as a new Java class library. The ERDoS development environment enables nonprogrammers to create complex distributed applications by simply stringing together multiple Java methods. The ERDoS runtime environment utilizes a structuring algorithm to create a distributed Java application dynamically, and then provides allocation, scheduling and content-based, graceful, adaptive QoS support to these applications. We demonstrate the benefits of content-based adaptation and of dynamic structuring of distributed applications, using a set of video applications.

In this paper we describe the implementation of our end-to-end QoS-driven resource management scheme, called ERDoS, within a CORBA-compliant ORB that we call the ERDoS QoS ORB. Unlike other real-time CORBA implementations that focus on real-time support for simple client-server applications, our ERDoS QoS ORB provides end-to-end QoS support (i.e., QoS spanning computer network, and storage resources) to applications, while retaining the benefits of an open distributed object system. Specifically we present three contributions. First, we present a model for describing end-to-end applications as a combination of client-server interactions between CORBA objects. Second, we define a model for relating the user/application level QoS requirements to the corresponding resource demand requirements of these individual CORBA objects. Third, we suggest a framework for performing distributed resource management within the CORBA environment.

The estimation of the motion transformation of a moving object from a sequence of images is of prime interest in computer vision. In this paper, the issues in estimating the motion parameters from a sequence of range images are addressed. The motion estimation task involves: (1) extracting the surfaces and establish the correspondence of the surfaces over the frames in the sequence of range images, and (2) computing the motion transformation using these surface correspondences. A novel procedure based on a hierarchical hypergraph representation of range images is presented for finding surface correspondence. Motion transformation between image frames is computed using the planar and the quadric surface pairings. The authors' solution strategy computes the motion by extracting unique linear features from the quadric surfaces and using them to compute the motion transformation.>

Given a 3D range image of a scene containing multiple arbitrarily shaped objects, the authors segment the scene into homogeneous surface patches. A novel modular framework for the segmentation task is proposed. In the first module, over-segmentation is achieved using zeroth and first order local surface properties. The segmentation is then refined in the second module using high order surface representations dictated by the high level vision tasks. The procedure has been applied successfully to many range images, five of which are presented.>

The authors present a novel approach for segmentation of dense three-dimensional range images. In this approach, four local properties, namely the 3-D coordinate, the surface normal, the Gaussian curvature, and the mean curvature of each data point, are combined in a hierarchical data structure to segment a given 3-D dense range map into surface patches. This algorithm is applicable to planar as well as curved surfaces; several examples of segmentation of such surfaces are presented.>