Abstract Motivated by ideas from the model theory of metric structures, we introduce a metric set theory, $\mathsf {MSE}$ , which takes bounded quantification as primitive and consists of a natural metric extensionality axiom (the distance between two sets is the Hausdorff distance between their extensions) and an approximate, non-deterministic form of full comprehension (for any real-valued formula $\varphi (x,y)$ , tuple of parameters a , and $r < s$ , there is a set containing the class and contained in the class $\{x:\varphi (x,a) < s\}$ ). We show that $\mathsf {MSE}$ is sufficient to develop classical mathematics after the addition of an appropriate axiom of infinity. We then construct canonical representatives of well-order types and prove that ultrametric models of $\mathsf {MSE}$ always contain externally ill-founded ordinals, conjecturing that this is true of all models. To establish several independence results and, in particular, consistency, we construct a variety of models, including pseudo-finite models and models containing arbitrarily large standard ordinals. Finally, we discuss how to formalize $\mathsf {MSE}$ in either continuous logic or Łukasiewicz logic.

Abstract In this paper we introduce and characterize two ‘analog reducibility’ notions for $[0,1]$-valued oracles on $\omega $ obtained by applying the syntactic characterizations of Turing and enumeration reducibility in terms of (positive) relatively $\varSigma _1$ and $\varPi _1$ formulas to formulas in continuous logic (Ben Yaacov, Berenstein, Henson and Usvyatsov, 2008, Model Theory for Metric Structures, vol. 2 of London Mathematical Society Lecture Note Series, pp. 315–427. Cambridge University Press.). The resulting analog and analog enumeration degree structures, $\mathscr {D}_a$ and $\mathscr {D}_{ae}$, naturally extend $\mathscr {D}_T$ and $\mathscr {D}_e$ in a compatible way. To show that these extensions are proper we prove that a sufficiently generic total $[0,1]$-valued oracle does not ‘analog enumerate’ any non-c.e. discrete set and that a sufficiently generic positive $[0,1]$-valued oracle neither ‘analog enumerates’ a non-c.e. discrete set nor ‘analog computes’ a non-trivial total $[0,1]$-valued oracle. We also provide a characterization of the continuous degrees among $\mathscr {D}_{ae}$ as precisely $\mathscr {D}_e \cap \mathscr {D}_a$. Finally we characterize a generalization of r.i.c.e. relations to metric structures via $\varSigma _1$ formulas in the ‘hereditarily compact superstructure’, which was the original motivation for the concepts in this paper.

One of the main driving forces of the growing adoption of virtualization is its dramatic simplification of the provisioning and dynamic management of IT resources. By decoupling running entities from the underlying physical resources, and by providing easy-to-use controls to allocate, deallocate and migrate virtual machines (VMs) across physical boundaries, virtualization opens up new opportunities for improving overall system resource use and power efficiency. While a range of techniques for dynamic, distributed resource management of virtualized systems have been proposed and have seen their widespread adoption in enterprise systems, similar techniques for dynamic power management have seen limited acceptance. The main barrier to dynamic, power-aware virtualization management stems not from the limitations of virtualization, but rather from the underlying physical systems; and in particular, the high latency and energy cost of power state change actions suited for virtualization power management.

An autonomic manager for enterprise server hardware management, called AMP, is described. AMP is designed to handle multiple aspects of hardware management and to work in conjunction with other management components, in particular application managers, in a way that reduces energy waste, protects server health, and preserves a high degree of autonomy both for itself and for the managers with which it works. AMP interacts with other managers in two ways: (1) exchange of nominal control over individual servers; and (2) provision of a synthetic cost function giving AMP's assessment of relative desirability of using different servers. The high-level architecture of AMP is discussed, with particular focus on the way it effects a natural decomposition of the combined hardware-and-application management problem, and on initial versions of the algorithms it uses to manage server power states and determine the cost function. AMP's viability in practice is demonstrated via prototype implementation in which it operates on real servers in collaboration with a state-of-the-art application manager. The overall system behavior is investigated via simulation.

Systems management techniques that allocate resources to running entities, such as processes and virtual machines (VMs), often require estimates of the resources required by each of these resource consumers. For example, many proposed virtual machine placement algorithms attempt to allocate VMs to physical hosts in such a way as to minimize the number of physical hosts that are occupied, while ensuring that each VM receives the CPU required to do its task adequately. The common practice is to assume that the CPU requirement is equal to the current CPU utilization, or to use a prediction of it over an appropriate time horizon. In this paper, we demonstrate that, when multiple VMs or processes co-reside on a physical host, the measured CPU utilization may provide a poor estimate of the actual requirement. We derive a simple, much more accurate alternative estimate of CPU demand, implement it, and demonstrate its superiority experimentally. Furthermore, we demonstrate that using our demand estimation framework in conjunction with dynamic resource allocation in a virtualized environment greatly improves the effectiveness of dynamic placement, resulting in one-shot convergence to optimal placement and significant improvements in the overall performance of the individual VMs.

With the continued growth of computing power and reduction in physical size of enterprise servers, the need for actively managing electrical power usage in large datacenters is becoming ever more pressing. By far the greatest savings in electrical power can be effected by dynamically consolidating workload onto the minimum number of servers needed at a given time and powering off the remainder. However, simple schemes for achieving this goal fail to cope with the complexities of realistic usage scenarios. In this paper we present a combined power-and performance-management system that builds on a state-of-the-art performance manager to achieve significant power savings without unacceptable loss of performance. In our system, the degree to which performance may be traded off against power is itself adjustable using a small number of easily-understood parameters, permitting administrators in different facilities to select the optimal tradeoff for their needs. We characterize the power saved, the effects of the tradeoff between power and performance, and the changes in behavior as the tradeoff parameters are adjusted, both in simulation and in a sample deployment of the real system.

Deploying a modern software service usually involves installing several software components, and configuring these components properly to realize the complex interdependencies between them. This process, which accounts for a significant portion of information technology (IT) cost, is complex and error-prone. In this paper, we propose delta configuration - an approach that reduces the cost of software deployment by eliminating a large number of choices on parameter values that administrators have to make during deployment. In delta configuration, the complex software stack of a distributed service is first installed and tested in a test environment. The resulting software images are then captured and used for deployment in production environments. To deploy a software service, we only need to copy these pre-configured software images into a production environment and modify them to account for the difference between the test environment and a production environment. We have implemented a prototype system that achieves software deployment using delta configuration of the configuration state captured inside virtual machines. We perform a case study to demonstrate that our scheme leads to substantial reduction in complexity for the customer, over the traditional software deployment method.

The expression of contracts in computer readable form, and the development of automated tests for completeness and well-formedness of contracts, has opened the door to significant advances in automating contract negotiation. To meet the needs of automation, such negotiations must follow explicitly specified message-exchange protocols. But to meet the needs of the negotiating parties, these protocols must be independent of the decision-making processes driving them as well as neutral to the outcome of the negotiations. In this paper we illustrate how both needs may be simultaneously met by a small set of conversation policies employed within a general purpose conversation support architecture.

No abstract available.

Business process integration and automation (BPIA) has emerged as an important aspect of the enterprise computing landscape. Intra-enterprise application integration (EAI) as well as the inter enterprise integration (B2B) are increasingly being performed in the context of business processes. The integration scenarios typically involve distributed systems that are autonomous to some degree. From the BPIA perspective, the autonomy refers to the fact that the systems being integrated have their own process choreography engines and execute internal business processes that are private to them. In the case of B2B integration, the systems being integrated are fully autonomous, while various levels of autonomy exist in systems partaking in EAI. We present a new paradigm for business process integration. Our approach is based on a conversation model that enables autonomous, distributed BPM (Business Process Management) modules to integrate and collaborate. Our conversation model supports the exchange of multiple correlated messages with arbitrary sequencing constraints and covers the formatting of messages that are to be sent as well as the parsing of the messages that have been received. The crux of our conversation model is the notion of a conversation policy, which is a machine-readable specification of a pattern of message exchange in a conversation. Our model supports nesting and composition of conversation policies to provide a dynamic, adaptable, incremental, open-ended, and extensible mechanism for business process integration. We discuss the current implementation of this conversation model and early experience in applying the model to solve customer problems. The implementation utilizes distributed object technology.

Advances in electronic commerce and agent technology are pushing the world rapidly toward ever-increasing e-business automation. The logical development of this movement is agent based electronic commerce, in which software agents act as autonomous (or semi-autonomous) businesses in their own right, buying and selling information goods and services online. We review some of the foreseeable developments and challenges in the growth of agent based electronic commerce.

One scenario of the future of computation populates the Internet with vast numbers of software agents providing, trading, and using a rich variety of information goods and services in an open, free-market economy. An essential task in such an economy is the retailing or brokering of information: gathering it from the right producers and distributing it to the right consumers. This article investigates one crucial aspect of brokers' dynamical behavior, their price-setting mechanisms, in the context of a simple information-filtering economy. We consider only the simplest cases in which a broker sets its price and product parameters based solely on the system's current state, without explicit prediction of the future. Analytical and numerical results show that the system's dynamical behavior in such "myopic" cases is generally an unending cycle of disastrous competitive "wars" in price/product space. These in turn are directly attributable to the existence of multiple peaks in the brokers' profitability landscapes, a feature whose generality is likely to extend far beyond our model.