433794
A Framework for Document-Driven Workflow Systems
We propose and demonstrate the feasibility of a framework for document-driven workflow systems that requires no explicit control flow and the execution of the process is driven by input documents. The framework can assist workflow designers to discover the data dependencies between tasks in a process and achieve more efficient control flow design. The framework also provides an architecture to separate the workflow system from application data and facilitate inter-organizational processes. Document-driven workflow systems are more flexible than traditional control flow processes, easier to verify and work better for ad hoc workflows. We also implemented a prototype workflow system using the framework entirely in a RDBMS using Transact-SQL in Microsoft SQL Server 2000. A detailed comparison with control driven workflows has also been done.
14897390
Meta workflows as a control and coordination mechanism for exception handling in workflow systems
A higher level control and coordination mechanism is required for exception handling in workflow systems. This paper describes such a framework based on events, states, and a new kind of process called a meta workflow. Meta workflows have five kinds of meta activities and facilitate control over base workflows. We describe the framework and illustrate it with examples to show its features. The paper gives an architecture for incorporating it into existing workflows and also provides a formal semantics of execution. This framework can be used in Web services, supply chains, and inter-organizational applications where coordination requirements are complex, and flexible and adaptable workflows are needed. It is also useful for handling not just failure recovery but also various kinds of special situations, which arise frequently in web-based applications.
45847616
EROICA: A Rule-Based Approach to Organizational Policy Management in Workflow Systems
Conventional workflow management systems have been criticized for being too rigid in dealing with changes in organizational policies, in particular for the lack of flexible mechanisms for handling complex role resolution. In this paper we describe a rule-based approach (EROICA) for managing organizational policies in workflow systems. Our approach extends the well-known ECA (event-condition-action) approach used in database systems by elevating roles, objects and time intervals to first class citizens, hence the term EROICA (event-role-object-interval-condition-action). In this paper, we focus on the development of a flexible role resolution mechanism that operates under various business constraints specified with EROICA rules. We further discuss the issues of architecture and implementation and demonstrate that the EROICA framework is promising in making next generation of workflow systems more powerful and flexible.
16012186
A fine-grained, controllable, user-to-user delegation method in RBAC
This paper addresses the issues surrounding user-to-user delegation in RBAC. We show how delegations can be incorporated into the RBAC model in a simple and straightforward manner. A special feature of the model is that it allows fine-grained control over what rights a user wishes to delegate as opposed to delegation at the role level where all the rights of a role must be delegated. In addition, the model provides a rich set of controls regarding further delegations of a right, generic constraints that further control delegations, and an innovative model for revocations. Properties of both delegation and revocation are discussed, and our work is compared with other related research.
206778468
A performance study of general grid structures for replicated data
Recently, there has been considerable interest in the study of replica-control protocols which are based on organizing several copies of an object into logical structures, such as rectangular grids. In addition to high availability, another objective in exploiting such structures is to improve the degree of load sharing in a system. The authors extend the scope of grid structures to general grids, which allow holes in various positions of a rectangular structure and are useful to consider because they often produce availabilities that are higher than solid grids, where every position must be occupied by a node. In addition to proposing an improvement to the existing grid protocol, new insights are offered into the performance of the grids, from both availability and load sharing points of view. Algorithms for designing grids to maximize availability independently and also in conjunction with a load sharing constraint are given.<<ETX>>
59757838
Operating System Support for Data Management.
2987975
Data streaming algorithms for efficient and accurate estimation of flow size distribution
Knowing the distribution of the sizes of traffic flows passing through a network link helps a network operator to characterize network resource usage, infer traffic demands, detect traffic anomalies, and accommodate new traffic demands through better traffic engineering. Previous work on estimating the flow size distribution has been focused on making inferences from sampled network traffic. Its accuracy is limited by the (typically) low sampling rate required to make the sampling operation affordable. In this paper we present a novel data streaming algorithm to provide much more accurate estimates of flow distribution, using a "lossy data structure" which consists of an array of counters fitted well into SRAM. For each incoming packet, our algorithm only needs to increment one underlying counter, making the algorithm fast enough even for 40 Gbps (OC-768) links. The data structure is lossy in the sense that sizes of multiple flows may collide into the same counter. Our algorithm uses Bayesian statistical methods such as Expectation Maximization to infer the most likely flow size distribution that results in the observed counter values after collision. Evaluations of this algorithm on large Internet traces obtained from several sources (including a tier-1 ISP) demonstrate that it has very high measurement accuracy (within 2%). Our algorithm not only dramatically improves the accuracy of flow distribution measurement, but also contributes to the field of data streaming by formalizing an existing methodology and applying it to the context of estimating the flow-distribution.
14590041
Designing Access Methods for Bitemporal Databases
By supporting the valid and transaction time dimensions, bitemporal databases represent reality more accurately than conventional databases. The authors examine the issues involved in designing efficient access methods for bitemporal databases, and propose the partial-persistence and the double-tree methodologies. The partial-persistence methodology reduces bitemporal queries to partial persistence problems for which an efficient access method is then designed. The double-tree methodology "sees" each bitemporal data object as consisting of two intervals (a valid-time and a transaction-time interval) and divides objects into two categories according to whether the right endpoint of the transaction time interval is already known. A common characteristic of both methodologies is that they take into account the properties of each time dimension. Their performance is compared with a straightforward approach that "sees" the intervals associated with a bitemporal object as composing one rectangle, which is stored in a single multidimensional access method. Given that some limited additional space is available, the experimental results show that the partial-persistence methodology provides the best overall performance, especially for transaction timeslice queries. For those applications that require ready, off-the-shelf, access methods, the double-tree methodology is a good alternative.
62758879
Exploiting Underlying Structure for Detailed Reconstruction of an Internet-scale Event
Network "telescopes" that record packets sent to unused blocks of Internet address space have emerged as an important tool for observing Internet-scale events such as the spread of worms and the backscatter from flooding attacks that use spoofed source addresses. Current telescope analyses produce detailed tabulations of packet rates, victim population, and evolution over time. While such cataloging is a crucial first step in studying the telescope observations, incorporating an understanding of the underlying processes generating the observations allows us to construct detailed inferences about the broader "universe" in which the Internet-scale activity occurs, greatly enriching and deepening the analysis in the process. In this work we apply such an analysis to the propagation of the Witty worm, a malicious and well-engineered worm that when released in March 2004 infected more than 12,000 hosts world-wide in 75 minutes. We show that by carefully exploiting the structure of the worm, especially its pseudo-random number generation, from limited and imperfect telescope data we can with high fidelity: extract the individual rate at which each infectee injected packets into the network prior to loss; correct distortions in the telescope data due to the worm's volume overwhelming the monitor; reveal the worm's inability to fully reach all of its potential victims; determine the number of disks attached to each infected machine; compute when each infectee was last booted, to sub-second accuracy; explore the "who infected whom" infection tree; uncover that the worm specifically targeted hosts at a US military base; and pinpoint Patient Zero, the initial point of infection, i.e., the IP address of the system the attacker used to unleash Witty.
7308298
Data streaming algorithms for accurate and efficient measurement of traffic and flow matrices
The traffic volume between origin/destination (OD) pairs in a network, known as traffic matrix, is essential for efficient network provisioning and traffic engineering. Existing approaches of estimating the traffic matrix, based on statistical inference and/or packet sampling, usually cannot achieve very high estimation accuracy. In this work, we take a brand new approach in attacking this problem. We propose a novel data streaming algorithm that can process traffic stream at very high speed (e.g., 40 Gbps) and produce traffic digests that are orders of magnitude smaller than the traffic stream. By correlating the digests collected at any OD pair using Bayesian statistics, the volume of traffic flowing between the OD pair can be accurately determined. We also establish principles and techniques for optimally combining this streaming method with sampling, when sampling is necessary due to stringent resource constraints. In addition, we propose another data streaming algorithm that estimates flow matrix, a finer-grained characterization than traffic matrix. Flow matrix is concerned with not only the total traffic between an OD pair (traffic matrix), but also how it splits into flows of various sizes. Through rigorous theoretical analysis and extensive synthetic experiments on real Internet traffic, we demonstrate that these two algorithms can produce very accurate estimation of traffic matrix and flow matrix respectively.
16277175
Oncology Ontology in the NCI Thesaurus
The National Cancer Institute's Thesaurus (NCIT) has been created with the goal of providing a controlled vocabulary which can be used by specialists in the various sub-domains of oncology. It is intended to be used for purposes of annotation in ways designed to ensure the integration of data and information deriving from these various sub-domains, and thus to support more powerful cross-domain inferences. In order to evaluate its suitability for this purpose, we examined the NCIT's treatment of the kinds of entities which are fundamental to an ontology of colon carcinoma. We here describe the problems we uncovered concerning classification, synonymy, relations and definitions, and we draw conclusions for the work needed to establish the NCIT as a reference ontology for the cancer domain in the future.