In the coming big data era, stress test to IT systems under extreme data volume is crucial to the adoption of computing technologies in every corner of the cyber world. Appropriately generated benchmark datasets provide the possibility for administrators to evaluate the capacity of the systems when real datasets hard obtained have not extreme cases. Traditional benchmark data generators, however, mainly target at producing relation tables of arbitrary size following fixed distributions. The output of such generators are insufficient when it is used to measure the stability of the architecture with extremely dynamic and heavy workloads, caused by complicated/hiden factors in the generation mechanism of real world, e.g. dependency between stocks in the trading market and collaborative human behaviors on the social network. In this paper, we present a new framework, called Chronos, to support new demands on streaming data benchmarking, by generating and simulating realistic and fast data streams in an elastic manner. Given a small group of samples with timestamps, Chronos reproduces new data streams with similar characteristics of the samples, preserving column-wise correlations, temporal dependency and order statistics of the snapshot distributions at the same time. To achieve such realistic requirements, we propose 1) a column decomposition optimization technique to partition the original relation table into small sub-tables with minimal correlation information loss, 2) a generative and extensible model based on Latent Dirichlet Allocation to capture temporal dependency while preserving order statistics of the snapshot distribution, and 3) a new generation and assembling method to efficiently build tuples following the expected distribution on the snapshots. To fulfill the vision of elasticity, we also present a new parallel stream data generation mechanism, facilitating distributed nodes to collaboratively generate tuples with minimal synchronization overhead and excellent load balancing. Our extensive experimental studies on real world data domains confirm the efficiency and effectiveness of Chronos on stream benchmark generation and simulation.

Business Intelligence (BI) is recognized as one of the most important IT applications in the coming big data era. In recent years, non-uniform memory access (NUMA) has become the de-facto architecture of multiprocessors on the new generation of enterprise servers. Such new architecture brings new challenges to optimization techniques on traditional operators in BI. Aggregation, for example, is one of the basic building blocks of BI, while its processing performance with existing hash-based algorithms scales poorly in terms of the number of cores under NUMA architecture. In this paper, we provide new solutions to tackle the problem of parallel hash-based aggregation, especially targeting at domains of extremely large cardinality. We propose a NUMA-aware radix partitioning (NaRP) method which divides the original huge relation table into subsets, without invoking expensive remote memory access between nodes of the cores. We also present a new efficient aggregation algorithm (EAA), to aggregate the partitioned data in parallel with low cache coherence miss and locking costs. Theoretical analysis as well as empirical study on an IBM X5 server prove that our proposals are at least two times faster than existing methods.

MaxStream is a federated stream processing system that seamlessly integrates multiple autonomous and heterogeneous Stream Processing Engines (SPEs) and databases. In this paper, we propose to demonstrate the key features of MaxStream using two application scenarios, namely the Sales Map & Spikes business monitoring scenario and the Linear Road Benchmark, each with a different set of requirements. More specifically, we will show how the MaxStream Federator can translate and forward the application queries to two different commercial SPEs (Coral8 and StreamBase), as well as how it does so under various persistency requirements.

Real-time pattern matching over event streams has gained much more attention recently due to the analytical capability demanded in many operation-critical applications such as credit card fraud detection, algorithmic stock trading and RFID tracking. One of the common but important requirements in the above-mentioned applications is fast response. Usually, there are a large number of pattern queries subscribed in the system, running continuously and concurrently. However, not much research has been done on the scheduling algorithms and management to improve the overall response time of these queries. To address this challenge, we focus on the study of how to improve the average response time of multiple pattern queries. We first propose two static scheduling algorithms: Event-based (EBS) and Run-based (RBS) Scheduling and discuss what would be a better choice under different system configurations. We then come up with a hybrid method called Fast Response Time Scheduling (FRTS) to dynamically manage the scheduling in order to further reduce the average response time. The experimental results of these scheduling algorithms have shown that the FRTS method can improve 5 times average response time comparing with the basic methods in some cases.

As IT systems become more and more complex and as business operations become increasingly automated, there is a growing need from business managers to have better control on business operations and on how these are aligned with business goals. This paper describes iBOM, a platform for business operation management developed by HP that allows users to i) analyze operations from a business perspective and manage them based on business goals; ii) define business metrics, perform intelligent analysis on them to understand causes of undesired metric values, and predict future values; iii) optimize operations to improve business metrics. A key aspect is that all this functionality is readily available almost at the click of the mouse. The description of the work proceeds from some specific requirements to the solution developed to address them. We also show that the platform is indeed general, as demonstrated by subsequent deployment domains other than finance.

In this paper we propose a novel approach and a platform for dynamic service selection in composite Web services. The problem we try to solve is that of selecting, for each composite service execution and for each step in the execution, the service that maximizes the probability of reaching a user-defined goal. We first underline the limitations of a priori approaches based on having each service provider declare non-functional parameters and on trying to select services based on some utility functions over these parameters. Then, we propose an approach that overcomes these limitations by tackling the problem a posteriori: we analyze past executions of the composite service and build, using data mining techniques, a set of context-sensitive service selection models to be applied at each stage in the composite service execution. We show the architecture of a prototype that implements this approach and we discuss its benefits over the a priori approach.

Business-to-business (B2B) e-commerce is emerging as a new market with tremendous potential. Organizations are trying to link services across organizational boundaries in order to electronically trade goods and services. Standards such as RosettaNet, CBL, ED1, OB1, and cXML, describe how electronic B2B interactions should be carried on so that dynamic trade partnerships can be established and transactions can be executed across organizations. While the development of standards is a fundamental step towards enabling e-business, the problem of linking B2B interactions with internal business processes is still a challenge. In addition, as the industry standards evolve continuously based on changing needs, organizations have to adopt new standards quickly. In this paper we describe how workflow technology can be extended in order to support B2B interactions and to link them with the internal workflows. The proposed framework can be used to speed up both the development of new business processes that support B2B interaction standards and the enhancement of the existing business processes by the addition of B2B interaction capability.

Supply-chain management is a crucial activity in every company. Surprisingly, today, most of the supply-chain activities are carried out manually, and IT support is often limited to having a set of (disconnected) data repositories. In addition, business-to-business (B2B) communications are performed via phone, fax or e-mail. Increasing the operational efficiency of the supply chain results in huge savings and is the key to remaining competitive or even gaining a competitive advantage. Furthermore, a more efficient supply chain also enables revenue growth, which is often impossible to sustain with the current manual operations. In this paper, we discuss the requirements and challenges for e-business applications that support supply-chain management. Then, we propose an architecture that meets the requirements and enables solutions that deliver results quickly and that evolve with the business and IT environment. Both the requirements and the architecture are the results of several different types of supply-chain automation projects in which we have been involved.

No abstract available.

Summary form only given. We are interested in Workflow Management Systems (WFMS), and particularly, in Resource Management (RM) of WFMS. A WFMS consists of coordinating executions of multiple activities, instructing who (resource) do what (activity) and when. The "when" part is taken care of by the workflow engine which orders the executions of activities based on a process definition. The "who" part is handled by the resource manager that aims at finding suitable resources at the run-time for the accomplishment of an activity as the engine steps through the process definition. Resources of different kinds (human and material, for example) constitute the information system of our interest, their management consists of resource modeling and effective allocation upon users' requests. Since resource allocation needs to follow certain general guidelines (authority, security, for example)-no matter who or what application issues requests: so those general guidelines are better considered as part of the resources' semantics. That is the reason why we are interested in resource policy management in RM. Resource policies are general guidelines every individual resource allocation must observe. They differ from process specific policies which are only applied to a particular process. The policy manager is a module within the resource manager, responsible for efficiently managing a (potentially large) set of policies and enforcing them in resource allocation. We propose to enforce policies by query rewriting.

Article Free Access Share on Flexible specification of workflow compensation scopes Authors: Weimin Du Hewlett-Packard Laboratories, 1501 Page Mill Road, Palo Alto, CA Hewlett-Packard Laboratories, 1501 Page Mill Road, Palo Alto, CAView Profile , Jim Davis Hewlett-Packard Laboratories, 1501 Page Mill Road, Palo Alto, CA Hewlett-Packard Laboratories, 1501 Page Mill Road, Palo Alto, CAView Profile , Ming-Chien Shan Hewlett-Packard Laboratories, 1501 Page Mill Road, Palo Alto, CA Hewlett-Packard Laboratories, 1501 Page Mill Road, Palo Alto, CAView Profile Authors Info & Claims GROUP '97: Proceedings of the 1997 ACM International Conference on Supporting Group WorkNovember 1997 Pages 309–316https://doi.org/10.1145/266838.267342Published:16 November 1997Publication History 24citation445DownloadsMetricsTotal Citations24Total Downloads445Last 12 Months4Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

SONET (Synchronous Optical NETwork) has been proposed as the backbone of future information superhighway infrastructure. SONET network management, however, is a complex process that involves many heterogeneous systems and applications, as well as human interactions. In this paper, we describe a prototype system developed at Hewlett-Packard (HP) that provides a service for configuring large SONET networks. The prototype differs from the existing systems in that it employs the HP OpenPM (Open Process Management) workflow system to define, execute and monitor network management processes. Using OpenPM (a middleware service that enables the automation of activities supporting complex enterprise business processes in a distributed heterogeneous computing environment) as a reliable and efficient workflow execution engine, this prototype supports efficient distributed network management and easy integration of legacy applications. The paper describes how an example network configuration management process is modeled, executed and monitored using OpenPM.

Workflow builders are designed to facilitate development of automated processes and support flexible applications that can be updated, enhanced or completely revamped. The Hewlett-Packard WorkManager is an open product data management solution with workflow management capabilities. WorkManager supports the entire product lifecycle by providing a single, logical repository for all data, and it manages and tracks enterprise-wide processes. With a strong information management platform at its core, WorkManager provides central administration capabilities, including supervision and intervention, where necessary. Because enterprise data is usually fragmented and stored in a variety of legacy systems, and different organizations have different amount of control over their data, an enterprise workflow system needs to support processes accessing data from different sites and applications. This paper describes the architecture of distributed workflow, Hewlett-Packard's solution to the enterprise workflow problem. The architecture is an extension of the existing WorkManager architecture. Its development is based on user requirements and four high-level user models. The user models and the architecture are described.>

Execution of multidatabase queries differs from that of traditional queries in that sort merge and hash joins are more often favored, as nested loop join requires repeated accesses to external data sources. As a consequence, left deep join trees obtained by traditional (e.g., System-R style) optimizers for multidatabase queries are often suboptimal, with respect to response time, due to the long delay for a sort merge (or hash) join node to produce its last result after the subordinate join node did. In this paper, we present an optimization strategy that first produces an optimal left deep join tree and then reduces the response time using simple tree transformations. This strategy has the advantages of guaranteed minimum total resource usage, improved response time, and low optimization overhead. We describe a class of basic transformations that is the cornerstone of our approach. Then we present algorithms that effectively apply basic transformations to balance a left deep join tree, and discuss how the technique can be incorporated into existing query optimizers.

A complete and efficient implementation of linear, one-side recursive queries in Iris, an object-oriented database management system, is described. It is shown that recursion can be easily and efficiently added to a large class of existing database management systems. A B-tree type access path called the B++ tree that has been implemented to support the computation of recursive functions in Iris is also described. The perforamnce of B++ trees is reviewed.>

In a 1976 book, “Algorithms + Data Structures = Programs” [15], Niklaus Wirth defined programs to be algorithms and data structures. Of course, by now we know that man does not live from programs alone, and that there is a second fundamental computer science equation: “Programs + Databases = Information Systems.”

article Free Access Share on Pegasus architecture and design principles Author: Ming-Chien Shan Hewlett-Packard Laboratories Hewlett-Packard LaboratoriesView Profile Authors Info & Claims ACM SIGMOD RecordVolume 22Issue 2June 1, 1993 pp 422–425https://doi.org/10.1145/170036.170111Online:01 June 1993Publication History 9citation343DownloadsMetricsTotal Citations9Total Downloads343Last 12 Months15Last 6 weeks6 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

A novel relational query optimization technique for use in shared memory multiprocessor database systems is described. A collection of practical algorithms for allocating computational resources to parallel select-project filter (SPJ) query execution plans is presented. The computational resources considered include disk bandwidth, memory buffers and general-purpose processors. The goal of the allocation algorithms is to produce minimum duration execution strategies with computational resource requirements that are less than the given system bounds. Preliminary experimental results indicate that the algorithms can be realized and are effective in producing good execution plans. Disk bandwidth appears to be the critical system resource. The most effective means to decrease complex query response time appears to be by reducing disk contention. This can be achieved by increasing the total number of disks and/or rearranging the placement of data on disks.>