Catálogo de publicaciones - libros

The concept of XML views is proposed to integrate heterogeneous data sources in XML, and a global XML view can represent the distributed heterogeneous data sources as single XML document. XQuery is one of the standard query languages for searching XML data. How to process efficiently of global XQuery queries, which are written under a global XML view, emerges as a new research topic. Popular techniques of distributed query processing are based on decomposition, and static decomposition is one of the processing techniques for the traditional query language. However, XQuery has a complex syntax such as FOR clauses that are not supported by other query languages, and its structural complexity causes some considerations for the decomposition of global XQuery queries. In this paper, we propose a method to decompose a global XQuery query into local XQuery queries and to construct the result of the global XQuery query from the results of the local XQuery queries.

This paper describes formal verification and quantitative performance evaluation for validating of query pattern-based relational schema-to-XML Schema translation (QP-T) algorithm. Many translation algorithms such as FT, NeT, CoT, ConvRel, and VP-T have been introduced on structural and/or semantic aspect for exact and effective translation. However, conventional algorithms consider only explicit referential integrity specified by relational schema or limitations regarding on reflection of implicit referential integrity information. It causes several problems such as incorrect translation, abnormal relational model transition, and so on. The QP-T algorithm analyzes query pattern and extract implicit referential integrities by interrelationship of equi-join in user queries. The QP-T algorithm can make up for weak points of the VP-T algorithm and create more exact XML Schema as a result by using with VP-T algorithm together.

Stream applications such as sensor data processing, financial tickers and Internet traffic analysis require that information, naturally, occur as a stream of data values. Due to a late and out-of-order arrival of infinite, unbound and multiple input streams, processing continuous queries over them may lead to producing an incorrect answer or delaying query execution. Hence to minimize this waiting time, previous works have used timeout technique without considering the frequency of timeouts. It results in decreasing the accuracy of query execution results, since the more the frequency of timeouts, the more the loss of data. We propose an AP-STO method using StB that stores operator’s state and a window time-out method based on the waiting time for the next tuple by resetting the size of a window according to the frequency of timeouts. It reduces a data lost rate and increases the tuples output-rate. We compare AP-STO method with an existing method and use output-rate and response time as criteria for performance evaluation. Our proposed method shows a substantial improvement in system performance in terms of the accuracy of query execution and the increment of tuples output-rate per a query due to the reduction in loss rate of data.

Formal concept analysis has been successfully applied as a data mining framework whereby target patterns come in the form of intent families and implication bases. Since their extraction is a challenging task, especially for large datasets, parallel techniques should be helpful in reducing the computational effort and increasing the scalability of the approach. In this paper we describe a way to parallelize a recent divide-and-conquer method computing both the intents and the implication basis of dataset. Wile intents admit a straightforward computation, adding the basis — whose definition is recursive — poses harder problems, in particular, for parallel design. A first, and by no means final, solution relies on a partition of the basis that allows the crucial and inherently sequential step of redundancy removal to be nevertheless split into parallel subtasks. A prototype implementation of our method, called , shows a nearly linear acceleration w.r.t. its sequential counter-part.

We have been developing a secure and reliable distributed storage system, which uses a secret sharing scheme. In order to efficiently store data in the system, this paper introduces an optimal share transfer problem, and proves it to be, generally, NP-hard. It is also shown that the problem can be resolved into a Steiner tree problem. Finally, through computational experiments we perform the comparison of heuristic algorithms for the Steiner tree problem.

Congestion Control is a necessary tool in Transaction Processing Systems (TPS), to avoid excessive degradation of response times. But it should have an autonomic behavior, adapting automatically to request characteristics to deliver the best possible service. Given that every request has either explicit or implicit deadlines (maximum acceptable response times), we analyze strategies that target request deadlines and throughput. These include maximum throughput seeker strategies, strategies using feedback control on miss rate and an additional proposal for preventive control of miss rates and throughput. Another goal of our proposal is for the control to be external and it should not rely on analytic models for control (because the predictions may be erroneous due to physical system issues). We analyze and compare alternative designs for the control including our own proposals and related ones. Our experiments consider both varied request inter-arrival and duration distributions and a real transaction processing benchmark.

In sensor networks, a huge amount of data is collected by millions of sensors and small mobile devices need to be processed fast. And database which stores those data always should be able to response for any requirement. Spatial database cluster provides high performance and high availability. That suits sensor networks because spatial database cluster can efficiently manage and process much amount of data. The previous system, however, should write external logs every transaction for high availability in all nodes. So, all of update transactions are slowly processed because of writing external logs. Also, recovery time of the failed node is increased because external logs for all of database are written in only single storage. In this paper, we propose the cluster recovery of spatial database cluster. The proposed method has cluster logs in each table unit for consistency among nodes. Also, the cluster log is written just in case any node is failed. Therefore the proposed method is processed more fast because all update transactions don’t write cluster logs. And the proposed method provides fast recovery because each table can be recovered concurrently.

The intent of this paper is to propose an energy-efficient routing protocol with data transmission security for wireless sensor networks. We create an energy and distance aware sink-rooted tree in the network which is used for secure data transmissions from the source sensors to the base station. We mainly focus on ensuring authenticity and confidentiality of the sensor reports by adopting one-way hash chain and pre-loaded shared secret keys. To achieve data freshness, there is an optional key refreshment mechanism in our protocol. Along with the detailed description of our protocol, we present an analysis and performance evaluation of our proposal.

Self-healing key distribution is a potential candidate to establish session keys for secure communication to large and dynamic groups in highly mobile, volatile and hostile wireless network, where frequent membership changes may be necessary and ability to revoke users during certain exchanges is desirable. The main property of self-healing key distribution scheme is that even if during a certain session some broadcast messages are lost due to network faults, the users are capable of recovering lost session keys on their own, without requesting additional transmission from the group manager. In this paper, we propose a scalable self-healing key distribution with revocation capability. Our proposed scheme has improvement in storage overhead over the previous approaches with the same communication cost required by the most optimal previous scheme. The scheme is supported by a proper security analysis in an appropriate security model. We prove that it is unconditionally secure and achieve both forward secrecy and backward secrecy. Our proposed self-healing key distribution is not restricted to sessions in phase. Besides, we develop a construction for self-healing key distribution that enables key recovery from a single broadcast message.

We propose two deterministic key predistribution schemes in a Wireless Sensor Network (WSN), in which sensor nodes are deployed randomly. Both the schemes are based on Partially Balanced Incomplete Block Designs (PBIBD). An important feature of our scheme is that every pair of nodes can communicate directly, making communication faster and efficient. The number of keys per node is of the order of , where is the number of nodes in the network. Our second design has the added advantage that we can introduce new nodes in the network keeping the key pool fixed. We study the resiliency of the network under node compromise and show that our designs give better results than the existing ones.