In this paper, we propose a novel autonomic service delivery platform for service-oriented network environments. The platform enables a self-optimizing infrastructure that balances the goals of maximizing the business value derived from processing service requests and the optimal utilization of IT resources. We believe that our proposal is the first of its kind to integrate several well-established theoretical and practical techniques from networking, microeconomics, and service-oriented computing to form a fully distributed service delivery platform. The principal component of the platform is a utility-based cooperative service routing protocol that disseminates congestion-based prices among intermediaries to enable the dynamic routing of service requests from consumers to providers. We provide the motivation for such a platform and formally present our proposed architecture. We discuss the underlying analytical framework for the service routing protocol, as well as key methodologies which together provide a robust framework for our service delivery platform that is applicable to the next-generation of middleware and telecommunications architectures. We discuss issues regarding the fairness of service rate allocations, as well as the use of nonconcave utility functions in the service routing protocol. We also provide numerical results that demonstrate the ability of the platform to provide optimal routing of service requests.

Service providers within an enterprise network are often governed by client service contracts (CSC) that specify, among other constraints, the rate at which a particular service instance may be accessed. The service can be accessed via multiple points (typically middleware appliances) in a proxy tier configuration. The CSC and thus the rate specified have to be collectively respected by all the middleware appliances. The appliances locally shape the service requests to respect the global contract. We investigate the case where the CSC limits the rate to a service to X requests with an enforcement/observation interval of T seconds across all the middleware appliances. In this paper, we extend, implement, and investigate the Credit-based Algorithm for Service Traffic Shaping (CASTS) in a production level enterprise network setting. CASTS is a decentralized algorithm for service traffic shaping in middleware appliances. We show that CASTS respects the CSC and improves the responsiveness of the system to the variations of the input rate and leads to larger service capacity when compared to the traditional static allocation approach.

In this paper, we propose a novel autonomic service delivery platform for service-oriented network environments. The platform enables a self-optimizing infrastructure that balances the goals of maximizing the business value derived from processing service requests and the optimal utilization of IT resources. We believe that our proposal is the first of its kind to integrate several well-established theoretical and practical techniques from networking, microeconomics, and service-oriented computing to form a fully-distributed service delivery platform. The principal component of the platform is a utility-based cooperative service routing protocol that disseminates congestion-based prices amongst intermediaries to enable the dynamic routing of service requests from consumers to providers. We provide the motivation for such a platform and formally present our proposed architecture. We discuss the underlying analytical framework for the service routing protocol, as well as key methodologies which together provide a robust framework for our service delivery platform that is applicable to the next-generation of middleware and telecommunications architectures.

This article focuses on the multireceiver data dissemination problem. Initially, IP multicast formed the basis for efficiently supporting such distribution. More recently, overlay networks have emerged to support point-to-multipoint communication. Both techniques focus on constructing trees rooted at the source to distribute content among all interested receivers. We argue, however, that trees have two fundamental limitations for data dissemination. First, since all data comes from a single parent, participants must often continuously probe in search of a parent with an acceptable level of bandwidth. Second, due to packet losses and failures, available bandwidth is monotonically decreasing down the tree. To address these limitations, we present Bullet, a data dissemination mesh that takes advantage of the computational and storage capabilities of end hosts to create a distribution structure where a node receives data in parallel from multiple peers. For the mesh to deliver improved bandwidth and reliability, we need to solve several key problems: (i) disseminating disjoint data over the mesh, (ii) locating missing content, (iii) finding who to peer with (peering strategy), (iv) retrieving data at the right rate from all peers (flow control), and (v) recovering from failures and adapting to dynamically changing network conditions. Additionally, the system should be self-adjusting and should have few user-adjustable parameter settings. We describe our approach to addressing all of these problems in a working, deployed system across the Internet. Bullet outperforms state-of-the-art systems, including BitTorrent, by 25-70% and exhibits strong performance and reliability in a range of deployment settings. In addition, we find that, relative to tree-based solutions, Bullet reduces the need to perform expensive bandwidth probing.

We believe that application-aware networks will be a core component in the development and deployment of emerging network services. However, previous attempts at enabling application-awareness in the network have failed due to issues with security, resource allocation, and cost of deployment. The emergence of the Extensible Markup Language (XML), an open standard that enables data interoperability, along with advances in hardware, software, and networking technologies, serves as the catalyst for the development of service-oriented networking (SON). SON enables network components to become application-aware, so that they are able to understand data encoded in XML and act upon that data intelligently to make routing decisions, enforce QoS or security policies, or transform the data into an alternate representation. This paper describes the motivation behind service-oriented networking, the potential benefits of introducing application-aware network devices into service-oriented architectures, and discusses research challenges in the development of SON-enabled network appliances.

Increasing application requirements have placed heavy emphasis on building overlay networks to efficiently deliver data to multiple receivers. A key performance challenge is simultaneously achieving adaptivity to changing network conditions and scalability to large numbers of users. In addition, most current algorithms focus on a single performance metric, such as delay or bandwidth, particular to individual application requirements. We introduce a two-fold approach for creating robust, high-performance overlays called adaptive multimetric overlays (AMMO). First, AMMO uses an adaptive, highly-parallel, and metric-independent protocol, TreeMaint, to build and maintain overlay trees. Second, AMMO provides a mechanism for comparing overlay edges along specified application performance goals to guide TreeMaint transformations. We have used AMMO to implement and evaluate a single-metric (bandwidth-optimized) tree similar to Overcast and a two-metric (delay-constrained, cost-optimized) overlay.

In recent years, overlay networks have become an effective alternative to IP multicast for efficient point to multipoint communication across the Internet. Typically, nodes self-organize with the goal of forming an efficient overlay tree, one that meets performance targets without placing undue burden on the underlying network. In this paper, we target high-bandwidth data distribution from a single source to a large number of receivers. Applications include large-file transfers and real-time multimedia streaming. For these applications, we argue that an overlay mesh, rather than a tree, can deliver fundamentally higher bandwidth and reliability relative to typical tree structures. This paper presents Bullet, a scalable and distributed algorithm that enables nodes spread across the Internet to self-organize into a high bandwidth overlay mesh. We construct Bullet around the insight that data should be distributed in a disjoint manner to strategic points in the network. Individual Bullet receivers are then responsible for locating and retrieving the data from multiple points in parallel.Key contributions of this work include: i) an algorithm that sends data to different points in the overlay such that any data object is equally likely to appear at any node, ii) a scalable and decentralized algorithm that allows nodes to locate and recover missing data items, and iii) a complete implementation and evaluation of Bullet running across the Internet and in a large-scale emulation environment reveals up to a factor two bandwidth improvements under a variety of circumstances. In addition, we find that, relative to tree-based solutions, Bullet reduces the need to perform expensive bandwidth probing. In a tree, it is critical that a node's parent delivers a high rate of application data to each child. In Bullet however, nodes simultaneously receive data from multiple sources in parallel, making it less important to locate any single source capable of sustaining a high transmission rate.