Engaging patients in the management of their health care can improve the quality of their care and enhance their experience while making more efficient use of care provider resources, especially for chronic diseases. However, health care system complexity and the challenge of consumer health literac

In the absence of end-to-end quality of service (QoS), overlay routing has been used as an alternative to the default best effort Internet routing. Using end-to-end network measurement, the problematic parts of the path can be bypassed, resulting in improving the resiliency and robustness to failures. Studies have shown that overlay paths can give better latency, loss rate, and TCP throughput. Overlay routing also offers flexibility as different routes can be used based on application needs. There have been very few proposals of using bandwidth as the main metric of interest, which is of great concern in media applications. We introduce our scheme BARON (Bandwidth-Aware Routing in Overlay Networks) that utilizes capacity between the end hosts to identify viable overlay paths and measures available bandwidth to select the best route. We propose our path selection approaches, and using the measurements between 174 PlanetLab nodes and over 13,189 paths, we evaluate the usefulness of overlay routes in terms of bandwidth gain. Our results show that among 658,526 overlay paths, 25% have larger bandwidth than their native IP routes, and over 86% of (source, destination) pairs have at least one overlay route with larger bandwidth than the default IP routes. We also present the effectiveness of BARON in preserving the bandwidth requirement over time for a few selected Internet paths.

Abstract — Estimation of network proximity among nodes is an important building block in several applications like service selection and composition, multicast tree formation, and overlay construction. Recently, scalable techniques have been proposed to estimate inter-node latencies, including network coordinate systems like GNP and Vivaldi. However, existing mechanisms for querying such information do not scale well to a very large number of nodes, when one wants to accurately find a set of nodes globally closest to a given node. In this paper we are concerned with distributing the position data among a set of infrastructure nodes, and propose ways of partitioning and querying this data. The trade-offs between accuracy and overhead in this distributed infrastructure are explored. We evaluate our solution through simulations with real and synthetic network measurement data. I.

Abstract — As the academic world moves away from physical journals and proceedings towards online document repositories, the ability to efficiently locate work of interest among the torrent of newly-generated papers will become increasingly important. To aid in this endeavor, we designed SmartSeer, a system that allows users to register personalized continuous queries over the CiteSeer database of technical documents. Users are then alerted whenever papers that match their queries are put online. SmartSeer has two main design requirements. First, to allow effective information retrieval, it should support rich continuous queries (as opposed to simple keyword searches). Second, to make effective use of donated infrastructure, it should be capable of running on a loosely maintained group of unreliable machines spread across multiple organizations (as opposed to assuming a reliable and tightly coupled distributed system). Existing work on distributed continuous query systems fails at least one of these requirements. Our design for SmartSeer is based on Distributed Hash Tables (DHTs), and thereby leverages previous work on DHT-based query systems. A prototype of SmartSeer has been implemented and evaluated on Planetlab. Though we evaluate our design only for the SmartSeer application, we believe it also provides useful insights into other distributed and rich continuous query systems (web alerts, news alerts etc). I.

Abstract Emerging large‐scale utility computing systems such as Grids promise computing and storage to be provided to end users as a utility. System management services deployed in the middleware are a key to enabling this vision. Utility Grids provide a challenge in terms of scale, dynamism and heterogeneity of resources and workloads. In this paper, we present a model‐based architecture for resource allocation services for Utility Grids. The proposed service is built in the context of interactive remote desktop session workloads and takes application performance QoS models into consideration. The key design guidelines are hierarchical request structure, application performance models, remote desktop session performance models, site admission control, multi‐variable resource assignment system and runtime session admission control. We have also built a simulation framework that can handle mixed batch and remote desktop session requests, and have implemented our proposed resource allocation service into the framework. We present some results from experiments using the framework. Our proposed architecture for resource allocation services addresses the needs of emerging utility computing systems and captures the key concepts and guidelines for building such services in these environments. Copyright © 2005 John Wiley & Sons, Ltd.

Efficient resource discovery based on dynamic attributes such as CPU utilization and available bandwidth is a crucial problem in the deployment of computing grids. Existing solutions are either centralized or unable to answer advanced resource queries (e.g., range queries) efficiently. We present the design of NodeWiz, a grid information service (CIS) that allows multi-attribute range queries to be performed efficiently in a distributed manner. This is obtained by aggregating the directory services of individual organizations in a peer-to-peer information service.

Estimation of network proximity among nodes is an important building block in several applications like service selection and composition, multicast tree formation, and overlay construction. Recently, scalable techniques have been proposed to estimate inter-node latencies, including network coordinate systems like GNP and Vivaldi. However, existing mechanisms for querying such information do not scale well to a very large number of nodes, when one wants to accurately find a set of nodes globally closest to a given node. In this paper we are concerned with distributing the position data among a set of infrastructure nodes, and propose ways of partitioning and querying this data. The trade-offs between accuracy and overhead in this distributed infrastructure are explored. We evaluate our solution through simulations with real and synthetic network measurement data.

With the falling price of memory, an increasing number of multimedia servers and proxies are now equipped with a large memory space. Caching media objects in the memory of a proxy helps to reduce the network traffic, the disk I/O bandwidth requirement, and the data delivery latency. The running buffer approach and its alternatives are representative techniques to caching streaming data in the memory. There are two limits in the existing techniques. First, although multiple running buffers for the same media object co-exist in a given processing period, data sharing among multiple buffers is not considered. Second, user access patterns are not insightfully considered in the buffer management. In this paper, we propose two techniques based on shared running buffers in the proxy to address these limits. Considering user access patterns and characteristics of the requested media objects, our techniques adaptively allocate memory buffers to fully utilize the currently buffered data of streaming sessions, with the aim to reduce both the server load and the network traffic. Experimentally comparing with several existing techniques, we show that the proposed techniques achieve significant performance improvement by effectively using the shared running buffers.

Utility Grids implement a virtualization architecture and allow for sharing of infrastructure for improved return on investment (ROI). We consider extending the existing Grid infrastructure to support interactive sessions in an enterprise setting. This would allow users to remotely execute interactive applications in the Grid and view their output using remote display technologies. We propose a resource allocation architecture to support such interactive sessions in utility Grids. End-users submit requests for a remote desktop session. A utility Grid site resource allocation system assigns a compute node for this request considering performance needs of such remote desktop sessions. We also propose a hierarchical admission control system. The system consists of a site admission control system for admission control of remote desktop sessions, and a session admission control system at the compute node for admission check of per-application interactive sessions. We also present discussion on mixed workloads consisting of requests for batch jobs and interactive remote desktop sessions.

With the falling price of the memory, an increasing number of multimedia servers and proxies are now equipped with a large DRAM memory space. Caching media objects in the memory of a proxy helps to reduce network traffic, disk I/O bandwidth requirement, and data delivery latency. The running buffer approach and its alternatives are representative techniques to cache streaming data in the memory. However, there are two limits in the existing techniques. First, although multiple running buffers for the same media object co-exist in a given processing period, data sharing among the multiple buffers is not considered. Second, user access patterns are not insightfully considered in the buffer management. In this paper, we propose two techniques based on shared running buffers (SRB) in the proxy to address these limits. Considering user access patterns and characteristics of the requested media objects, our techniques adoptively allocate memory buffers to fully utilize the currently buffered data of streaming sessions, with the aim to reduce both the server load and the network traffic. Experimentally comparing with several existing techniques, we show that the proposed techniques have achieved significant performance improvement by effectively using the shared running buffers.

Abstract Traditional use of Grid computing systems has been for batch jobs in the scientific and academic computing. We envision the next generation Grid computing systems to support graphical interactive sessions. In this paper, we propose a resource management framework for supporting graphical interactive sessions in a Grid computing system. We describe the high‐level architectural resource management framework distributed among the submission node, central scheduler node, and the execution node. We then describe in detail the resource management framework on the execution node. The description of the resource management framework on the scheduler node is kept at a high level in this paper. The framework on execution nodes consists of Resource Management Agents, an Admission Control system and Application Predictor system. The agents on the execution node are Startup Agents, Sensor Agents, Monitoring Agents, Aggregator Agents, Enforcement Agents and Registration Agents. The Session Admission Control system is responsible for determining if a new application session can be admitted to the execution node. An Application Predictor system is responsible for predicting the resource utilization behavior of applications based on data obtained from the Resource Management Agents. The proposed framework allows for implementation of a scalable and extensible middleware for interactive Grid resource management. It supports fine‐grained performance guarantees specified in service level agreements and brings forth some important and novel contributions to enable graphical interactive sessions on Grids. Copyright © 2004 John Wiley & Sons, Ltd.

With the wide availability of high-speed network access, we are experiencing high quality streaming media delivery over the Internet. The emergence of ubiquitous computing enables mobile users to access the Internet with their laptops, PDAs, or even cell phones. When nomadic users connect to the network via wireless links or phone lines, high quality video transfer can be problematic due to long delay or size mismatch between the application display and the screen. Our proposed solution to this problem is to enable network proxies with the transcoding capability, and hence provide different, appropriate video quality to different network environment. The proxies in our transcoding-enabled caching (TeC) system perform transcoding as well as caching for efficient rich media delivery to heterogeneous network users. This design choice allows us to perform content adaptation at the network edges. We propose three different TeC caching strategies. We describe each algorithm and discuss its merits and shortcomings. We also study how the user access pattern affects the performance of TeC caching algorithms and compare them with other approaches. We evaluate TeC performance by conducting two types of simulation. Our first experiment uses synthesized traces while the other uses real traces derived from an enterprise media server logs. The results indicate that compared with the traditional network caches, with marginal transcoding load, TeC improves the cache effectiveness, decreases the user-perceived latency, and reduces the traffic between the proxy and the content origin server.

Traditional use of grid computing allows a user to submit batch jobs in a grid environment. We believe, next generation grids will extend the application domain to include interactive graphical sessions. We term such grids interactive grids. In this paper, we describe some of the challenges involved in building interactive grids. These include fine grain access control, QoS guarantees, and dynamic account management. In order to architect interactive grids, we propose and describe I-GENV, an environment for enabling interactive grids. I-GENV consists of GISH-'Grid Interactive Shell', Controlled Desktop, SAC-'Session Admission Control' module, GMMA-'Grid Monitoring and Management Agents', System Policies, and Dynamic Account Manager. We also present our testbed implementation of I-GENV using and extending Globus Toolkit 2.0 for the Grid middleware infrastructure, and VNC as the remote display technology.

Scalable shared-memory multiprocessors that are designed as cache-only memory architectures (Coma) allow automatic replication and migration of data in the main memory. This enhances programmability by hopefully eliminating the need for data distribution strategies and page migration schemes. A variant of Coma called Simple Coma has been proposed as a lower-cost alternative to hardware-intensive systems like Flat Coma. However, we find that Simple Coma is quite slower than Flat Coma. The main reason is the high page mapping, unmapping, and transfer overhead caused by memory fragmentation in Simple Coma. We propose a solution to the memory fragmentation problem that we call Multiplexed Simple Coma. The idea is to allow multiple virtual pages to map into the same physical page at the same time, therefore compressing the page working set of the application. Multiplexed Simple Coma requires very little support over Simple Coma and reduces its execution time by about 40%. We find that Multiplexed Simple Coma can be very easily implemented with off-the-shelf processors. In addition, there is no need to be selective when choosing what virtual pages are to share the same physical page. Overall, although Multiplexed Simple Coma is still slower than Flat Coma, since it is cheaper to implement, it represents a good cost-performance design point.