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ItemIQ-Paths: Self-regulating Data Streams across Network Overlays(Georgia Institute of Technology, 2006) Cai, Zhongtang ; Kumar, Vibhore ; Schwan, KarstenOverlay networks have been shown useful for improving the delivery of network and processing resources to applications, in part due to their ability to use alternate or parallel network paths and computational resources. This paper presents IQ-Paths, a set of techniques and their middleware realization that implement self-regulating data streams for data-intensive distributed applications. Self-regulation is based on (1) the dynamic and continuous assessment of the quality of each overlay path, (2) the use of online network monitoring and statistical analyses that provide probabilistic guarantees about available path bandwidth, loss rate, and RTT, and (3) a packet routing and scheduling algorithm that dynamically schedules data packets to different overlay paths in accordance with their available bandwidths. Additional aspects of IQ-Paths are its predictive statistical bandwidth guarantees and the fact that packet scheduling across different overlay paths is governed by application-level specifications of stream utility. An example is to send control data across links that offer strong guarantees for future bandwidth vs. mapping other data across less guaranteed paths. Experimental results presented in this paper use IQ-Paths to better handle the different kinds of data produced by (1) distributed multimedia applications with desired QoS guarantees and (2) data-driven or interactive high performance codes with user-defined utility requirements.
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ItemUtility-Driven Availability-Management in Enterprise-Scale Information Flows(Georgia Institute of Technology, 2006) Cai, Zhongtang ; Kumar, Vibhore ; Cooper, Brian F. ; Eisenhauer, Greg S. ; Schwan, Karsten ; Strom, Robert E.Enterprises rely critically on the timely and sustained delivery of information, supported by middleware that ensures high-availability for such information flows. Our goal is to augment such middleware to create resilient information flows that deliver information while maximizing the utility end user applications derive from such information. Towards this end, this paper presents a `proactive availability-management' technique to offer (1) information flows that dynamically self-determine their availability requirement based on high-level utility specifications, (2) flows that can trade recovery time for performance based on the `perceived' stability and failure predictions (early alarm) for the underlying system, and (3) methods, based on real-world case studies, to deal with both transient and non-transient failures. We have incorporated `proactive availability-management' into information flow middleware, and experiments reported in this paper demonstrate its capability to self-determine availability guarantees, to offer improved performance over a statically configured system, and to be resilient to a wide-range of faults
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ItemAutonomic Information Flows(Georgia Institute of Technology, 2005) Schwan, Karsten ; Cooper, Brian F. ; Eisenhauer, Greg S. ; Gavrilovska, Ada ; Wolf, Matthew ; Abbasi, Hasan ; Agarwala, Sandip ; Cai, Zhongtang ; Kumar, Vibhore ; Lofstead, Jay ; Mansour, Mohamed S. ; Seshasayee, Balasubramanian ; Widener, Patrick M. (Patrick McCall)Today's enterprise systems and applications implement functionality that is critical to the ability of society to function. These complex distributed applications, therefore, must meet dynamic criticality objectives even when running on shared heterogeneous and dynamic computational and communication infrastructures. Focusing on the broad class of applications structured as distributed information flows, the premise of our research is that it is difficult, if not impossible, to meet their dynamic service requirements unless these applications exhibit autonomic or self-adjusting behaviors that are `vertically' integrated with underlying distributed systems and hardware. Namely, their autonomic functionality should extend beyond the dynamic load balancing or request routing explored in current web-based software infrastructures to (1) exploit the ability of middleware or systems to be aware of underlying resource availabilities, (2) dynamically and jointly adjust the behaviors of interacting elements of the software stack being used, and even (3) dynamically extend distributed platforms with enterprise functionality (e.g., network-level business rules for data routing and distribution). The resulting vertically integrated systems can meet stringent criticality or performance requirements, reduce potentially conflicting behaviors across applications, middleware, systems, and resources, and prevent breaches of the `performance firewalls' that isolate critical from non-critical applications. This paper uses representative information flow applications to argue the importance of vertical integration for meeting criticality requirements. This is followed by a description of the AutoFlow middleware, which offers methods that drive the control of application services with runtime knowledge of current resource behavior. Finally, we demonstrate the opportunities derived from the additional ability of AutoFlow to enhance such methods by also dynamically extending and controlling the underlying software stack, first to better understand its behavior and second, to dynamically customize it to better meet current criticality requirements.
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ItemIQ-Services: Network-Aware Middleware for Interactive Large-Data Applications(Georgia Institute of Technology, 2004) Cai, Zhongtang ; Eisenhauer, Greg S. ; He, Qi ; Kumar, Vibhore ; Schwan, Karsten ; Wolf, MatthewIQ-Services are application-specific, resource-aware code modules executed by data transport middleware. They constitute a 'thin' layer between application components and the underlying computational and communication resources that implements the data manipulations necessary to permit wide-area collaborations to proceed smoothly, despite dynamic resource variations. IQ-Services interact with the application and resource layers via dynamic performance attributes, and end-to-end implementations of such attributes also permit clients to interact with data providers. Joint middleware/resource and provider/consumer interactions implement a cooperative approach to data management for the large-data applications targeted by our research. Experimental results in this paper demonstrate substantial performance improvements attained by coordinating network-level with service-level adaptations of the data being transported and by permitting end users to dynamically deploy and use application-specific services for manipulating data in ways suitable for their current needs.