Narrow Results

In a real-time distribute transactional system, customers generate transactions, which should be scheduled to be executed on different servers. The transactions have temporal constraints and must be executed before their deadlines. To schedule these transactions the circulating mutisequencer, the multi-tokens and the consensus algorithms have been considered to obtain a global view of the system. In this paper, mathematical models are developed to obtain the average stay time of a transaction within the system. These models introduce a bulk arrival M/G/1 station with K classes of customers where bulks are considered according to FIFO discipline and customers (actions) are scheduled according to EDF within a group and with the HOL discipline for the algorithm operating. The response time distribution is also computed. This allowed us to determine the minimum relative deadline, to affect to a generated transaction, to guarantee a given probability p that the transaction does not miss its deadline. The system is then called p-feasible. This study enables to determine the number of tokens to use for the multi-tokens algorithm, for a given number of servers and shows that the circulating mutisequencer algorithm presents the best results.

A use case represents a unit of the functionality specification of a system. Industrial object-oriented projects have applied use cases to capture user requirements. Use cases can be used throughout the whole process of object-oriented software development [14]. But, the problem of how to write use cases is still puzzling even software experts [6]. It reflects the lack of a systematic approach to capturing use cases. The set of use cases in a use case model is unstructured regarding the structure of the problem addressed by an application. This paper presents a notion of a use case pattern and proposes using a use case pattern to guide use case capturing. A use case pattern encodes reusable knowledge on the structure and function of a specific class of applications. It guides the work of use case gathering. We illustrate the approach to use case modeling with several use case patterns.

Data mining is the process of extracting desirable knowledge or interesting patterns from existing databases for specific purposes. Most conventional data-mining algorithms identify the relationships among transactions using binary values. Transactions with quantitative values are however commonly seen in real-world applications. We proposed a fuzzy mining algorithm by which each attribute used only the linguistic term with the maximum cardinality int he mining process. The number of items was thus the same as that of the original attributes, making the processing time reduced. The fuzzy association rules derived in this way are not complete. This paper thus modifies it and proposes a new fuzzy data-mining algorithm for extrating interesting knowledge from transactions stored as quantitative values. The proposed algorithm can derive a more complete set of rules but with more computation time than the method proposed. Trade-off thus exists between the computation time and the completeness of rules. Choosing an appropriate learning method thus depends on the requirement of the application domains.

Web service composition, that recursively constructs a composite web service out of the existing services based on a business workflow has been acknowledged as a promising approach to meet the user demands, whenever a single service alone cannot fulfil the needs. In view of frequent failures in the internet environment where the composed service is executed, reliability of the composed service must be ensured. The reliability is determined by the behavioral or transactional properties of component services. The component services for each activity of the workflow must be selected based on their behavior so that their execution results in a consistent termination. Service selection must happen at run-time in order to consider the services available in a service registry at the time of execution. Towards this need, a dynamic transaction aware web service selection approach is proposed in this paper. Further, whenever user requirements change, a long running transaction must be interrupted and cancelled which is not addressed by any of the existing works. Hence, service cancellability property is proposed in this paper and incorporated in the dynamic selection approach. The overhead of the proposed run-time selection approach is assessed and the impact of increased services on its performance is also measured.

For advanced and complicated knowledge processing, we need to integrate various kinds of problem-solvers such as constraint solvers, databases, and application programs. A heterogeneous distributed cooperative problem solving system HELIOS achieves this integration by introducing capsule and environment modules. To integrate heterogeneous problem-solvers that may be implemented in different languages and may have different knowledge representations, those heterogeneity should be absorbed. Capsules and environments are introduced into HELIOS for this purpose. A capsule surrounds each problem-solver and translates the contents of communication to and from the internal representation and a common representation. We call an encapsulated problem-solver an agent. An environment is a module which provides a field giving common representation, and agents communicate and cooperate with each other in each environment. Since an encapsulated environment with its agents can be considered as an agent, agent-environment structures can be nested in HELIOS. For negotiation between agents, negotiation protocol can be defined in each environment. A negotiation strategy that suits the given negotiation protocol can be defined in each capsule of an agent. In this framework, we define a transaction-based negotiation protocol. To check the validity of HELIOS design and its implementation model on computers connected by network, we implemented an experimental version of HELIOS on UNIX workstations.

Mobile computing and workgroup computing are emerging technologies which have so far been treated independently. Current approaches to support cooperative work neglect the special characteristics of mobile environments like limited bandwidth or temporary disconnection. On the other hand, approaches to support disconnected operation rely on the assumption that the degree of data-sharing is low which is obviously not appropriate for cooperative work. In this paper, we utilize the COACT cooperative transaction model to provide support for parallel activities in mobile environments. We present a system architecture that is able to cope with the special characteristics of mobile environments and a formal framework for the consistent information exchange between mobile users. The paper shows how the COACT history merge algorithm reduces conflicts by exploiting operation semantics and offering consistent sequences of operations. We believe that our new approach is a viable solution to the growing demand for cooperation in mobile environments.

In order to support the interaction betweeen coexisting traditional short transactions and long cooperative transactions, we propose a novel timestamp ordering approach. With this timestamp ordering method, short transactions can be processed in the traditional way, as if there were no cooperative transactions. Therefore they will not be blocked by cooperative transactions. Cooperative transactions will not be aborted when there is a conflict with short transactions. Rather, they will incorporate the recent updates into their own processing. The serializabilities, among short transactions, and between a cooperative transaction (group) and other short transactions, are all preserved.

In the role-based access control model, a role is a set of access rights. A subject doing jobs is granted roles showing the jobs in an enterprise. A transaction issued by a subject is associated with a subset of roles granted to the subject, which is named purpose. A method with a more significant purpose is performed before another method with a less significant purpose. We discuss which purpose is more significant than another purpose. We discuss two types of Role-Ordering (RO) schedulers SRO and PRO where multiple conflicting transactions are serializable in the significant order of subjects and purposes, respectively. We evaluate the RO schedulers compared with the traditional two-phase locking protocol in terms of throughput.

With lower operational costs, many small and medium-sized enterprises (SMEs) trade via e-commerce, but without the abilities to develop the expensive payment system. Therefore, a cash flow service provider plays critical roles to complete the online transactions. A cash flow service provider must precisely predict those outsourcing customers to serve the customers well under the correctly prepared facilities. Since the adaptive neuro-fuzzy inference systems (ANFIS) have demonstrated prediction efficiency for fuzzy circumstances in many fields, this study attempts to innovate deploying the ANFIS model on the time series predictions for e-commerce cash flow service customers. Moreover, this study takes an e-commerce cash flow service provider in Taiwan for numerical analysis. For the ANFIS predictions, an acceptable prediction error rate of 5.6% is achieved. The results show that fashion industry tops the highest customers share for outsourcing the cash flow services; and the credit cards top the highest share in the payment media choices.

While B2C via cloud computing has grown rapidly, information security and trustworthy computation are still major issues in today’s industrial realm. As a result, the routine workflow process varies dynamically over the course of data transactions, resulting in uncertainty. Consumers’ private information becomes easily vulnerable due to such data uncertainty. Intruders/fake marketers may permeate deeply into their current profiles due to the Internet, which leads to the creation of fictitious online markets that, in turn, drive more demand. This evolving business interaction leverages new interlopes to target customers’ data more precisely. However, it is still lacking in terms of complete techniques for dealing with such issues. These days, uncertain B2C workflows are greatly aided by Blockchain technology, especially to most of its security-enhancing characteristics. Despite numerous existing studies that have recommended employing Blockchain to handle B2C records, it is necessary to employ the technology in such business sectors to offer secured record management, workflow and keep data with high confidentiality and integrity intact. In this study, we suggest a Distributed Decentralized Security Scheme (DDSS) that manages and secures uncertain datasets through Blockchain technology in the B2C sector. To improve the safety of data workflows, the proposed approach enables the user to verify the authenticity of the records they require. A smart contract or special chain-code is used to dictate the parameters of the suggested system, ensuring security. The findings and discussions explain that the suggested scheme is far more effective than the previous strategies and has a greater level of confidentiality and integrity strength.

In big data, the frequent item set mining is an important framework for many applications. Several techniques were used to mine the frequent item sets, but for the collapsed and complex data, it is difficult. Hence, the current research work aimed to model a novel Frequent Pattern Growth-Hybrid Ant Colony and African Buffalo Model (FPG-HACABM) is developed to overcome this issue and to reduce the execution time. Moreover, the Fitness function of HACABM is utilized to calculate the support count of each item and to improve the classification accuracy. Thus the proposed models classify the frequently utilized items accurately and arranged those items in descending order. This helps to run the big data transactional application effectively without any delay. Finally, the key metrics are validated with the existing models and better results are attained by achieving a high accuracy rate of 99.82% and less execution time of 0.0018 ms.

Traditional transaction systems within auto service chains exhibit several shortcomings, which are untraceable, opaque, and inefficient. To mitigate these challenges, a transaction system based on a consortium blockchain for the auto service value chain is devised to guarantee transaction authenticity and reliability. Initially, a smart contract is a computer protocol that is automatically executed. It integrates into the Byzantine fault-tolerant IBFT consensus algorithm to accomplish transactions in real time and enhance a higher degree of security. Subsequently, the IBFT is fine-tuned to enhance the consortium blockchain performance. In addition, multiple primary nodes execute the IBFT algorithm concurrently via multithreading to mitigate latency and improve throughput. Lastly, experimental results demonstrate that IBFT notably surpasses other consensus algorithms in both throughput and latency.

This paper presents a model of persistency for the Eiffel language and its implementation by FLOO system. This model supports in a transparent way a “contagious” and incremental handling of persistency within a transactional framework. After having defined the context and the constraints of the modelization which had been retained, we present main characteristics of the model which is implemented through routines located in class inherited by all classes of an application. Then, persistent-programming style, which is induced by this model, is illustrated with some basic examples.

Implementation of FLOO system, which uses O2 DBMS as persistent object's server is presented briefly. This choice allows to benefit from capabilities provided by O2 such as an incremental loading, an optimized indexing, its transactional framework using a client/server architecture and its interfacing with other object oriented languages such as C++, for application interoperability. But the strong linking between Eiffel and O2, which is mandatory for an elegant integration of our model in the Eiffel world, means to solve non trivial translation problems for building an O2 image starting from an Eiffel class, and need an adaptation of Eiffel run-time. We end this paper with a first assesment of the project and with perspectives according to ‘ODMG’93 works.

In order to solve the Web Service Transaction Management, the author proposed and realized a kind of compensation-based transaction mechanism, which developed the Transaction engine. It takes advantage of pre-compensation and WS-Transaction specification s' two-phase commitment to parse the database operation statements participant transaction, to do a scene preservation possible changes in the database, and generating the statement set for compensation automatically. When need to cancel the transaction, the management center will rollback automatically according to the client vote and compensate information, which can better solve the problem of Web Service transactions.