query processing algorithm

Top PDF query processing algorithm:

QoS Aware Query Processing Algorithm for Wireless Sensor Networks

QoS Aware Query Processing Algorithm for Wireless Sensor Networks

Abstract—In sensor networks, continuous query is commonly used for collecting periodical data from the objects under monitoring. This sort of queries needs to be carefully designed, in order to minimize the power consumption and maximize the lifetime of the sensor nodes. Data reduction techniques can be employed to decrease the size and frequency of data to be transferred in the network, and therefore save energy. This paper presents a novel method for optimizing sliding window based continuous queries. In particular, we deal with two categories of aggregation operations: stepwise aggregation (e.g. MAX, MIN, SUM, COUNT, AVERAGE, etc.) and direct aggregation (e.g. MEDIAN). Our approach is, by using packet merging or compression techniques, to reduce the data size to the best extent, so that the total performance is optimal. A QoS weight item is specified together with a query, in which the importance of the four factors, power, delay, accuracy and error rate can be expressed. Then an optimal query plan can be obtained by studying all the factors simultaneously, leading to the minimum cost. System models for energy and time consumptions of communication are created. Problem is formalized and algorithm is described in detail. Finally, experiments are conducted to validate the effectiveness of the proposed method.
Show more

10 Read more

Intelligent Location Dependent Query Processing Algorithm for Retrieving Medical Information in Mobile Cloud

Intelligent Location Dependent Query Processing Algorithm for Retrieving Medical Information in Mobile Cloud

In spite of the availability of relational database systems for health record maintenance, a web based solution is necessary for providing e-health services and to make cost effective treatment methods. Moreover, the cloud database systems provide facilities for large scale real time data storage and retrieval features. They also provide distributed query processing facilities using map- reduce procedures. In addition, the existing database systems require the provision of queries from nodes available in fixed networks. Hence, it is necessary to propose a data model that includes cloud storage, security, mobility and rules to provide effective cloud based services.
Show more

7 Read more

Generalizing the Optimality of Multi-Step k-NN Query Processing with RASP Data Perturbation in the Cloud

Generalizing the Optimality of Multi-Step k-NN Query Processing with RASP Data Perturbation in the Cloud

There are two clearly separated groups: the trustedparties and the untrusted parties. The trusted partiesinclude the data/service owner, the in-house proxyserver, and the authorized users who can only submitqueries. The data owner exports the perturbed data tothe cloud. Meanwhile, the authorized users can submit range queries or kNN queries to learn statistics orfind some records. The untrusted parties include thecurious cloud provider who hosts the query servicesand the protected database. The RASP-perturbed datawill be used to build indices to support query processing. There are a number of basic procedures in this framework: (1) F (D) is the RASP perturbation that transforms the original data D to the perturbed data D′ ; (2) Q(q) transforms the original query q to the protected form q′ that can be processed on the perturbed data; (3) H (q′ , D′ ) is the query processing algorithm that returns the result R′ . When the statistics such as SUM or AVG of a specific dimension are needed, RASP can work with partial homomorphic encryption such as Paillier encryption [25] to compute these statistics on the encrypted data, which are then recovered with the procedure G (R′).
Show more

12 Read more

Accelerating XML Query Processing on Views

Accelerating XML Query Processing on Views

Another research direction was to construct index or access methods to query XML documents, also improving query processing. Some studies investigated constructing index methods to query XML documents [12-15]. Bruno et al. [12] and Jiang et al. [13] used a structure join method to determine element relationships based on the numbering scheme. This method has good performances for an ancestor-descendant axis, but it might fetch useless nodes for a parent-child axis, because all descendant nodes must be accessed to check if they are real children. Therefore, Huang and Wang developed an efficient query processing algorithm for retrieving XML documents [14]. Hsu et al. also proposed a path clustering method based on the concept of summary indexes for the processing of both structural and content queries on XML documents [15]. Karthiga and Gunasekaran [16] used tree-based association rules to mine the semantics from XML documents, which provide information on both the structure and the content of XML documents. The mined knowledge is used to provide the quick answers to queries and an approach called path based indexing is used to improve the speed of data retrieval. Alghamdi et al. [17], and Thi Le et al. [18] proposed approaches to optimizing twig queries by utilizing the semantics/constraints defined in XML schemas. Furthermore, Ordonez focused on the optimization of linear recursive queries in SQL [19]. Subramaniam and Haw [20] proposed an XML labeling scheme that helps quick determination of structural relationship among XML nodes and supports dynamic updates without relabeling nodes in case of update occurrences. Belgamwar et al. [21] follows an upside down approach which explicitly stores the values and only reconstructs the internal nodes, if needed. As a solution, they proposed a compressed internal storage format for native XML database systems where the inner structure of the gathered documents is virtualized. Ferro and Silvello [22] introduced a new paradigm where traditional approaches based on traversing trees are replaced by a brand new one based on basic set operations which directly return the desired subtree, avoiding to create it. Tudor [23] proposed an optimization model for XML data processing based on a heuristic algorithm to extract data from XPath views.
Show more

12 Read more

Construction of Private Methodical Query Services in the Cloud with RASP Data Commotion

Construction of Private Methodical Query Services in the Cloud with RASP Data Commotion

RASP denotes Random Space Perturbation. It also combines OPE, random projection and random noise injection. Here OPE denotes Order Preserving Encryption is used for data that allows any comparison. And that comparison will be applied for the encrypted data; this will be done without decryption. Random projection is mainly used to process the high dimensional data into low dimensional data representations. It contains features like good scaling potential and good performances. Random noise injection is mainly used to adding noise to the input to get proper output when we compare it to the estimated power. The RASP method and its combination provide confidentiality of data and this approach is mainly used to protect the multidimensional range of queries in secure manner and also with indexing and efficient query processing will be done. RASP has some important features. In RASP the use of matrix multiplication does not protect the dimensional values so no need to suffer from the distribution based attack.
Show more

11 Read more

Stochastic Heuristic Optimization based Multi Query Processing in Wireless Sensor Network using Genetic Algorithm

Stochastic Heuristic Optimization based Multi Query Processing in Wireless Sensor Network using Genetic Algorithm

that it is rigid to suppress useless data as early as possible. For instance, an area satisfies all the conditions except size of requirement. However, it is difficult to decide the boundary of a result area locally. Furthermore, to explain an area in sensor network for query processing is an additional challenge, Informer Homed Routing (IHR) nodes as described in [12] selected a limited number of targets in the data transmission message may be considered as corrupted or lost, because of imperfections in point-to-point communication, especially if the communication medium is wireless. In IHR algorithm, instead of transferring of data information to the primary cluster head and manufacture backup of cluster head concurrently, the collector node only send data when it found the primary cluster head failed. In this work, focus is made on generating the multi-query processing based on closeness of nodes required to answer the user query. The closeness of nodes is based on query formation plan. As a result, the query plan is generated using the Gaussian probability density function and with the application of genetic algorithm. The GA population consists of several chromosomes and the best chromosome is used to generate the next population (i.e.,) next query processing. The GA based approach in sensor network converges quickly towards the optimal query processing plans for an observed crossover and mutation rate. Mutation allows new genetic patterns (i.e.,) tuple to be introduced in the new chromosomes (i.e.,) in a new multi-query statement. The GA crossover operation combines the operations which is responsible for the transfer of genetic inheritance for query processing on sensor network. Based on the stochastic heuristic optimization fitness values, the population transforms into the future query processing form. Initially, each fitness parameter is assigned a random weight and is updated accordingly. The rationale behind the SHO-GA framework is that multi-query processing with lesser query delay is more efficient. The structure of this paper is as follows. In Section 1, describes the basic problems in multi-query processing on sensor network. In Section 2, present an overall view of the Stochastic Heuristic Optimization based multi-query processing using Genetic Algorithm. Section 3 and 4 outline experiment results with parametric factors and present the result graph for research questions. Finally, Section 6 concludes the work with better multi-query processing result outcome .
Show more

7 Read more

Improving Query Performance of Holistic Aggregate Queries for Real Time Data Exploration

Improving Query Performance of Holistic Aggregate Queries for Real Time Data Exploration

The previous section discussed the different types of approximation techniques which are most com- monly used for data stream processing. However these same techniques (e.g. sampling) are often also applied in the field of data warehousing, OLAP and decision support systems (DSS’s). However they can often be optimized even further since in most cases the full data set is known before hand (a priori) and updates are relatively infrequent, which generally means that the complexity of updates is significantly simplified whilst the query processing part of any algorithm can be further optimized. Since the full extent of the dataset is known a priori and updates are quite infrequent the use of additional data structures are very common with algorithms for optimizing query performance for data warehouses. These additional data structures come in all kinds of forms, such as trees, hash tables, lists, etc, and are used by the query engine to be able to compute the answer for any aggregation query using the separate data structures instead of the full data set, thereby achieving a (sub-)linear performance.
Show more

76 Read more

Title: Confidential and Secure Query Services in the Cloud with RASP

Title: Confidential and Secure Query Services in the Cloud with RASP

A straightforward method is to encrypt datasets before exporting them to the cloud. However, searchable encryption is very challenging, showing limited successes in some specific areas such as document search [4]. Boneh et al. [2] showed that it is possible to construct a public-key system for range query, which is one of the basic database queries (another popular one is k nearest neighbor (kNN) query as we will discuss). However, it requires a significant amount of storage and computational costs, only applicable to linear scan of the entire database. Database queries such as range and kNN queries normally demand fast processing time (logarithmic or sub linear time complexity) with the support of indexing structures. However, if not impossible, there is no efficient indexing structure developed for encrypted data yet, which renders the current encryption schemes [2] unusable for search in large databases. We recently proposed the RAndom Space Perturbation (RASP) method [5] for the protection of tabular data, which is secure under the assumption of limited adversarial knowledge - only the perturbed data and the data distributions are known by adversaries. This assumption is appropriate in the context of cloud computing. The RASP perturbation is a unique combination of Order Preserving Encryption (OPE) [1], dimensionality expansion, noise injection, and random projection, which provides sufficient protection for the privacy of query services in the cloud. It has a number of unique features, such as preserving the topology of range query, non-deterministic results for duplicate records, and resilience to distributional attacks [5]. We develop the secure half-space query transformation method that casts any enclosed range in the original space to an irregularly shaped range in the perturbed space. Therefore, we are able to use a two-stage range query processing method: an existing multidimensional index, such as R*-Tree in the perturbed space is used to find out the records in the bounding box of the irregularly shaped range, which is then filtered with the transformed query condition. This processing strategy is fast and secure under the security assumption.
Show more

9 Read more

Different Syntactic Methods and Clustering For Web Service Integration

Different Syntactic Methods and Clustering For Web Service Integration

Numerous syntactic approaches were applied to take advantage of Trend 2 and 3 when matching services. The Levenshtein distance (LD) (besides called the edit distance) assesses of similarity between two strings. LD is the smallest number of deletions, insertions, or substitutions which is necessary to transform a original string into a target string. The larger the LD, the more dissimilarity of the strings depends on LD. From preexisting sources, we adapt implementations of the LD algorithm from preexisting sources. The LD algorithm is successful when evaluating abbreviations with full strings. LD is also booming for similar strings that are changed to create uniqueness. There were a number of occurrences where zeros are substituted for the letter O or numbers are added to the end of a message name.
Show more

6 Read more

Systematic exploration of efficient query plans for automated database restructuring

Systematic exploration of efficient query plans for automated database restructuring

Queries, views, and rewritings with grouping and aggregation. Queries, views, and rewritings with grouping and aggregation can be treated in stage one of our architecture using a surprisingly minor extension of our algorithms of Section 4. The extension is based on the formal results in the previous work [27, 38] by some of the authors of this paper; the intuition is as follows. For a given subquery, our algorithm simulates a “covering view,” as discussed in Section 4. Such a view may also have grouping and aggregation in it, see [38] for the local conditions for building aggregate views for subqueries of an aggreate query. Aggregations must also be accounted for when building merged views, but this does not increase the search space of plans, because for any two parent views with selection conditions and aggregations, we create only one merged view with the combined selection conditions (i.e., a disjunction of the selection conditions of the parent views) and attributes to which grouping/aggregation apply.
Show more

24 Read more

Securing XML Query Processing Storage

Securing XML Query Processing Storage

processes several binary structural relationships that form a sequence, we call it sequence join algorithm. The basic idea of the algorithm is to synchronously read input lists to find first match of the node intervals and put it into the result list. If the intervals in two adjacent lists do not match, based on the result of their comparison, the record of one of the lists will be deleted. The propagation of changes goes from the last list back to first. The depth of the recursion is equal to the number of input lists, which relates to XML data tree input. For regular path expression a 1 /a 2 /…/a n , both approaches require n selection operators resulting
Show more

9 Read more

A RECOMMENDED QUERY PROCESSING FOR THE WEB GRAPH

A RECOMMENDED QUERY PROCESSING FOR THE WEB GRAPH

In general the recommendation search was taken as a process of query processing and with that query it has to recommend the information and based on that it will display the graph in the web sites. But here we are recommended the heat diffusion method for the web graphing to get the requirements and to get the suggestion of the graph. Basically it was adopted to recommend the graph in websites. Through this we can get thesemantic related objects and it helps to import the related information from the web browsers. And it was a least structural information provider, which increases more difficult situation to get the important information from the data providers. If we want to satisfy the web users with the provided information we need to require the more information about various situation we have to maintain the different web applications information.
Show more

6 Read more

Concise Query Processing in Uncertain Database

Concise Query Processing in Uncertain Database

Wireless communication technology has been rapidly increasing, it became quite common for people to view maps or get related services from the handheld devices, such as mobile phones and PDAs. Spatial databases have witnessed an increasing number of applications recently, due to the fast advance in the fields of mobile computing and embedded systems and the spread of the Internet .Range queries are often posed by user to retrieve the useful information from a spatial database. We present a novel idea that a concise representation of a specified size for the range query results, while incurring minimal information loss, shall be computed and returned to the user. Such a concise range query not only reduces communication costs, but also offers better usability to the users, providing an opportunity for interactive exploration. The usefulness of the concise range queries is confirmed by comparing it with other possible alternatives, such as sampling and clustering. In this proposed system, we include the entities and associate the object attributes such as restaurants, shopping places etc which represents a point within a Hilbert curve which facilitates in reducing search space for spatial data, and to provide a range for attribute such that all the information is retrieved with minimal loss. The proposed system also includes peer to peer system through which multiple spatial databases can be accessed in efficient time.
Show more

5 Read more

Hilbert Exclusion : improved metric search through finite isometric embeddings

Hilbert Exclusion : improved metric search through finite isometric embeddings

Typically S is too large to allow an exhaustive search. However such queries can often be performed efficiently by use of a metric index, one of a large family of data structures which make use of the triangle inequality property in order to arrange the set of objects S in such a way as to minimise the time required to retrieve the query result. Efficiency is primarily achieved by avoiding unnecessary distance calculations, although the efficient use of memory hierarchies is also extremely important. Both of these are optimised by structuring the set based on relative distances of objects from each other, so that triangle inequality can be used to determine subsets which do not need to be exhaustively checked. Such avoidance is normally referred to as exclusion.
Show more

27 Read more

Novel Distributed Query Optimization Model and Hybrid Query Optimization Algorithm

Novel Distributed Query Optimization Model and Hybrid Query Optimization Algorithm

Distributed and Parallel databases are fundamentally similar, distributed query optimization process was implemented around 1990s, a time at which communication over a network was prohibitively expensive and computer equipment was not cheap enough to be thrown at parallel processing. Techniques for exploiting parallelism were largely ignored. Apers et al. [5] discuss the independent parallelism but don’t define either pipelined or partitioned parallelism. Thus, for historical reasons, the concept of distributed execution differs from parallel execution. Since the space of possible executions for a query is different, the optimization problems are different. In [6], research work considered minimizing response time as an optimization objective, at other hand most project work, such as in SDD- 1, A* and R* Optimizer, focused on minimizing resource consumption. Techniques for distributing data using horizontal and vertical partitioning schemes were developed for distributed data that also find a use in exploit parallelism. The main motivation of the distributed databases is to present data which are distributed on networks of type LAN (Local Area Network) or of type WAN (Wide Area Network) in an integrated way to a user. The optimization process of a distributed query is composed of three steps: (i) the global optimization consists of determining the best execution site for each local sub-query considering data replication, (ii) finding the best inter-site operator scheduling, and (iii) placing these last ones. As for local optimization, it optimizes the local sub-queries on each site which are involved to the query evaluation. The inter-site operator scheduling and their placement are very important in a distributed environment because they allow reducing the data volumes exchanged on the network and consequently to reduce the communication costs. Hence, the estimation accuracy of the temporary relation sizes that must be transferred from a site to another one is important. In the rest of this section, we present global optimization methods of distributed queries. They differ by the objective function used by the optimization process and by the type of approach: static or dynamic.
Show more

11 Read more

A Review on Fast Query Processing Techniques and Algorithms

A Review on Fast Query Processing Techniques and Algorithms

ABSTRACT: Keyword search is very popular method for searching from large datasets nowadays. There are objects associated with different domains that are having their significances in variety of applications. Today, several trendy applications call for novel varieties of queries that aim to seek out objects satisfying both a spatial predicate, and a predicate on their associated texts. The presence of keywords in feature space allows for the development of new tools to query and explore from these multi-dimensional datasets. In normal web based applications search box is at the top of any browser or document. This will carried out the needs for the research to develop the Nearest Keyword Search methods. There are lots of application of nearest keyword based searching, and as the amount of data is growing on increasing. Lots of Research in different areas of keywords based searching in multi-dimensional environment are performed. This paper presents study related to the different terms in the nearest keyword searching (NKS) and multidimensional datasets. As lots of research work is being perform in the field of keyword based searching, this paper performs review on some of the important techniques.
Show more

7 Read more

SCHEDULING TRANSFERABLE OBJECTS FOR QUERY PROCESSING IN WSN

SCHEDULING TRANSFERABLE OBJECTS FOR QUERY PROCESSING IN WSN

They all assumed that as long as the tour intersects with the communication disks of all sensor nodes, all the data collection jobs can be accomplished. This assumption is acceptable when dealing with applications such as temperature monitoring, where the sensory data size is small. However, due to the communication data-rate constraint and the travel speed of the ME, the resultant tour may not always be sufficient to accomplish all the data collection jobs, especially when the data volume to be collected is large, e.g., in audio/video sensor networks. Taking the communication time into account, Bhadauria et al. tackled the tour selection problem based on a two- ring communication model [4], which was formulated as a two-ring tour (TRT) problem. Constant approximation factor algorithms, which jointly consider the travel time and the communication time, were proposed. However, the approximation factor of the proposed algorithm was based on that of the TSPN subroutine adopted, which is relatively large when the neighborhoods are intersecting continuous disks, as we have discussed above.
Show more

8 Read more

Private kNN Query Processing in Cloud Enviroments

Private kNN Query Processing in Cloud Enviroments

ABSTRACT: Query processing that preserves both the data privacy of the owner and the query privacy of the client is a new research problem. It shows increasing importance as cloud computing drives more businesses to outsource their data and querying services. However, most existing studies, including those on data outsourcing, address the data privacy and query privacy separately and cannot be applied to this problem. In this paper, we propose a holistic and efficient solution that comprises a secure traversal framework and an encryption scheme based on privacy homomorphism. The framework is scalable to large datasets by leveraging an index-based approach. Based on this framework, we devise secure protocols for processing typical queries such as k-nearest-neighbor queries (kNN) on R- tree index. Moreover, several optimization techniques are presented to improve the efficiency of the query processing protocols. Our solution is verified by both theoretical analysis and performance study.
Show more

5 Read more

Statistics based Optimization Technique for Query Processing

Statistics based Optimization Technique for Query Processing

RDF represents the web data in triple (subject-predicate-object) model. SPARQL has a triple pattern of main component that makes it easy to match RDF triples, varying triple patterns are filtered using the Boolean conditions [8]. Many methods are developed to improve the efficiency of the query at low cost by optimizing the query [9 – 10]. The existing method uses the optimization technique for finding the relevant queries in semantic web. The optimization techniques such as PSO uses many features to identify the relevant query. The number of features tends to increases the query cost and memory storage. The proposed statistics method involves the use of statistics based optimization method in query optimization. The statistics method involves in the use of few features like triplet score. The statistics based optimization method helps to reduce the query cost of the semantic web.
Show more

5 Read more

A Caching Scheme In Location-Dependent Query Processing

A Caching Scheme In Location-Dependent Query Processing

Wireless technology is growing rapidly and its beneficial applications which cause use of PDAs, laptops, cell phones and etc. to access data anywhere and anytime, are very common nowadays. Mobile database is such a technology which confronts with some new problems, limitations and challenges (e.g., bandwidth limitations, missing connectivity, unreliable and asymmetric links). Moreover, in a mobile environment, upstream queries (i.e., from client to server) are more resource- consuming than the downstream queries (i.e., from server to client). So, there is a need to reduce the number of trips made to the server. Caching seems to be profitable in mobile environment. There are several types of queries. In this paper, the efficient processing of location-dependent queries and, in particular, a sub-class of queries called mobile nearest-neighbor (NN) search are focused on. A mobile NN search is issued by a mobile client to retrieve stationary service objects nearest to its user. It is an important function for LBSs, but the implementation is difficult since the clients are mobile and queries must be answered according to the client’s current locations. For example, “find the nearest restaurant” would return totally different answers to the same user when the query is issued at different locations. If a user keeps moving after he/she submits a query, the problem becomes more complicated because the user’s location is changing continuously and thus the results would change accordingly. How to answer a continuous query and provide an accurate answer is an open question. In this paper, a grid-partition index is proposed to support mobile nearest-neighbor search. In this indexing mechanism, both object-based index and solution-based index are used for searching nearest-neighbor data object. In addition, to enhance access efficiency of the system, a new caching scheme in which hybrid caching is combined with semantic caching, is proposed. This caching scheme stores a data object along with the valid spatial scope of the data object. Accordingly, this paper is continued as follows: theory background is studied in section 2. Related work is also studied in section 3. The proposed system is presented in section 4. Finally, this paper is concluded in section 5.
Show more

5 Read more

Show all 10000 documents...