7923805
A reference model for team-enabled workflow management systems
Abstract Today's workflow systems assume that each work item is executed by a single worker. From the viewpoint of the system, a worker with the proper qualifications selects a work item, executes the associated work, and reports the result. There is usually no support for teams, i.e., groups of people collaborating by jointly executing work items (e.g., the program committee of a conference, the management team of a company, a working group, and the board of directors). In this paper, we propose the addition of a team concept to today's workflow management systems. Clearly, this involves a marriage of workflow and groupware technology. To shed light on the introduction of teams, we extend the traditional organizational meta model with teams and propose a team-enabled workflow reference model. For this reference model and to express constraints with respect to the distribution of work to teams, we use object constraint language (OCL).
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.
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>>
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.
42238558
A crash recovery algorithm based on multiple logs that exploits parallelism
The paper describes an efficient algorithm for recovery based on multiple logs. The standard WAL algorithm is designed to work with a single log. Since each transaction is required to write a commit record to the log, it imposes limits on the maximum achievable throughput even if group commits are allowed. These limits are well below the needs of high transaction rate systems in airlines and in other areas. Another problem with a 'single log' algorithm is that the tail of the log is a 'hot spot' because of severe contention for it. It is shown that both these problems are solved by extending the write-ahead logging method into a multiple log algorithm which allows transactions to write to one of several logs, and also permits each log to perform checkpoints and I/O operations in parallel. A further advantage of multiple logs is that parallelism can be exploited at recovery time. An algorithm is outlined that speeds up recovery by scanning the multiple logs in parallel.<<ETX>>
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.
10184291
Efficient and scalable query routing for unstructured peer-to-peer networks
Searching for content in peer-to-peer networks is an interesting and challenging problem. Queries in Gnutella-like unstructured systems that use flooding or random walk to search must visit O(n) nodes in a network of size n, thus consuming significant amounts of bandwidth. In this paper, we propose a query routing protocol that allows low bandwidth consumption during query forwarding using a low cost mechanism to create and maintain information about nearby objects. To achieve this, our protocol maintains a lightweight probabilistic routing table at each node that suggests the location of each object in the network. Following the corresponding routing table entries, a query can reach the destination in a small number of hops with high probability. However, maintaining routing tables in a large and highly dynamic network requires non-traditional mechanisms. We design a novel data structure called an exponentially decaying bloom filter (EDBF) that encodes such probabilistic routing tables in a highly compressed manner, and allows for efficient aggregation and propagation. The search primitives provided by our system can be used to search for single keys or multiple keywords with equal ease. Analytical modeling of our design predicts significant improvements in search efficiency, verified through extensive simulations in which we observed an order of magnitude reduction in query path length over previous proposals.
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.
15446858
A new approach for asynchronous distributed rate control of elastic sessions in integrated packet networks
We develop a new class of asynchronous distributed algorithms for the explicit rate control of elastic sessions in an integrated packet network. Sessions can request for minimum guaranteed rate allocations (e.g., minimum cell rates in the ATM context), and, under this constraint, we seek to allocate the max-min fair rates to the sessions. We capture the integrated network context by permitting the link bandwidths available to elastic sessions to be stochastically time varying. The available capacity of each link is viewed as some statistic of this stochastic process [e.g., a fraction of the mean, or a large deviations-based equivalent service capacity (ESC)]. The ESC is obtained so as to satisfy an overflow probability constraint on the buffer length. For fixed available capacity at each link, we show that the vector of max-min fair rates can be computed from the root of a certain vector equation. A distributed asynchronous stochastic approximation technique is then used to develop a provably convergent distributed algorithm for obtaining the root of the equation, even when the link flows and the available capacities are obtained from on-line measurements. The switch algorithm does not require per connection monitoring, nor does it require per connection marking of control packets. A virtual buffer based approach for on-line estimation of the ESC is utilized. We also propose techniques for handling large variations in the available capacity owing to the arrivals or departures of CBR/VBR sessions. Finally, simulation results are provided to demonstrate the performance of this class of algorithms in the local and wide area network context.
31048080
Advertising data analysis using rough sets model
This study explores the use of rough-set methods for marketing decision support systems in the retail business. A tutorial presentation of Rough Set Data Analysis (RSDA) in the context of knowledge discovery from time series databases is given. We show how an RSDA model can be used to develop a marketing decision support system which can capture the complex relationships between marketing factors, such as advertising and promotion, and the total impact on sales levels in order to find influential advertising strategies. This information is used by the business manager to make faster and better strategy decisions for the business to survive in the rapidly changing and competitive environments. The data set used for RSDA application example contains weekly investments in different media categories: TV, radio, cinema, morning press, evening press, popular press, special interest press, and outdoor posters; for seven makes of cars in the Swedish market.
1630993
Join-distinct aggregate estimation over update streams
There is growing interest in algorithms for processing andquerying continuous data streams (i.e., data that is seenonly once in a fixed order) with limited memory resources.Providing (perhaps approximate) answers to queries over suchstreams is a crucial requirement for many application environments;examples include large IP network installations where performancedata from different parts of the network needs to be continuouslycollected and analyzed.
The ability to estimate the number of distinct (sub)tuples inthe result of a join operation correlating two data streams (i.e.,the cardinality of a projection with duplicate elimination over ajoin) is an important requirement for several data-analysisscenarios. For instance, to enable real-time traffic analysis andload balancing, a network-monitoring application may need toestimate the number of distinct (<i>source</i>,destination) IP-address pairs occurring in the stream of IP packetsobserved by router <i>R</i><inf>1</inf>,where the source address is also seen in packets routed through adifferent router <i>R</i><inf>2</inf>.Earlier work has presented solutions to the individual problems ofdistinct counting and join-size estimation (without duplicateelimination) over streams. These solutions, however, arefundamentally different and extending or combining them to handleour more complex "Join-Distinct" estimation problem is far fromobvious. In this paper, we propose the <i>first</i>space-efficient algorithmic solution to the general Join-Distinctestimation problem over continuous data streams (our techniques canactually handle general <i>update streams</i>comprising tuple deletions as well as insertions). Our estimatorsare probabilistic in nature and rely on novel algorithms forbuilding and combining a new class of hash-based synopses (termed"JD <i>sketches</i>") for individual update streams. Wedemonstrate that our algorithms can provide low error,high-confidence Join-Distinct estimates using only small space andsmall processing time per update. In fact, we present lower boundsshowing that the space usage of our estimators is within smallfactors of the best possible for the Join-Distinct problem.Preliminary experimental results verify the effectiveness of ourapproach.