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BI-FILTERED FORWARDING: A QUASI-OPTIMAL ROUTING ALGORITHM FOR query DELIVERY IN WIRELESS SENSOR NETWORKS

INTERNATIONAL JOURNAL ON SMART SENSING AND INTELLIGENT SYSTEMS 2013年第3期6卷 993-1011页

作者： Zhang, Junhu Zhu, Xiujuan Peng, Hui Qingdao Technol Univ Coll Comp Engn Qingdao Peoples R China Renmin Univ China Sch Informat Beijing Peoples R China

A quasi-optimal query propagation algorithm Bi-Filtered Forwarding (BFF) for quickly routing a query throughout a wireless sensor network is proposed in this paper. BFF is implemented in a limited flooding manner for guaranteeing quick query propagation and low message consumption in wireless sensor networks. The experimental results show that in comparison with the flooding algorithm, BFF can greatly reduce the redundant message consumption during the procedure of real time query propagation throughout a wireless sensor network.

关键词： Real time routing distributed query processing query propagation constrained flooding wireless sensor networks

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Preference-aware Skyline Service Discovery in the Mobile Cloud System

Preference-aware Skyline Service Discovery in the Mobile Clo...

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IEEE 24th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Go, Yunmin Song, Hwangjun POSTECH Pohang Univ Sci & Technol Div IT Convergence Engn Pohang South Korea POSTECH Pohang Univ Sci & Technol Dept Comp Sci & Engn Pohang South Korea

ISBN: (纸本)9781467362351

Recently, the mobile cloud computing received much attention since it can provide various and powerful services for the mobile user. The service discovery technology in mobile cloud computing is very important to efficiently provide the mobile services. In this paper, we proposed a novel preference-aware skyline service discovery system in the mobile cloud system. The objective of our system is to discover preferable services in the mobile cloud system. Our proposed mobile cloud system is composed of zone-based overlay network. In the overlay network, querying user generates the query with user preference extracted by a Singular Value Decomposition method from the user's service access history. The generated query is sent to the mobile cloud system, and then the query is handled by the distributed skyline query processing mechanism to discover user preferable services with low networking communication cost in the mobile cloud system. We conduct experiments to evaluate the performance of our proposed system.

关键词： Preference-aware Service discovery distributed query processing Mobile cloud system Skyline

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distributed query Plan Generation Using HBMO

Distributed Query Plan Generation Using HBMO

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7th Multi-Disciplinary International Workshop on Artificial Intelligence (MIWAI)

作者： Kumar, T. V. Vijay Arun, Biri Kumar, Lokendra Jawaharlal Nehru Univ Sch Comp & Syst Sci New Delhi 110067 India

ISBN: (纸本)9783642449499;9783642449482

processing a distributed query entails accessing data from multiple sites. The inter site communication cost, being the dominant cost, needs to be reduced in order to improve the query response time. This would require the query optimizer to devise a distributed query processing strategy that would, for a given distributed query, generate query plans involving fewer number of sites in order to reduce the inter site communication cost. In this paper, a distributed query plan generation algorithm, based on the honey bee mating optimization (HBMO) technique that generates query plans for a distributed query involving less number of sites and higher relation concentration in the participating sites, is presented. Further, experimental comparison of the proposed HBMO based DQPG algorithm with the GA based DQPG algorithm shows that the former is able to generate distributed query plans at a comparatively lesser total query processing cost, which in turn would lead to efficient processing of a distributed query.

关键词： distributed query processing Swarm Intelligence Honey Bee Mating Optimization

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Top-k query processing in Probabilistic Databases with Non-Materialized Views

Top-k Query Processing in Probabilistic Databases with Non-M...

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29th IEEE International Conference on Data Engineering (ICDE)

作者： Dylla, Maximilian Miliaraki, Iris Theobald, Martin Max Planck Inst Informat Campus E1-4 D-66123 Saarbrucken Germany Univ Antwerp B-2020 Antwerp Belgium

ISBN: (纸本)9781467349093;9781467349086

We investigate a novel approach of computing confidence bounds for top-k ranking queries in probabilistic databases with non-materialized views. Unlike related approaches, we present an exact pruning algorithm for finding the top-ranked query answers according to their marginal probabilities without the need to first materialize all answer candidates via the views. Specifically, we consider conjunctive queries over multiple levels of select-project-join views, the latter of which are cast into Datalog rules which we ground in a top-down fashion directly at query processing time. To our knowledge, this work is the first to address integrated data and confidence computations for intensional query evaluations in the context of probabilistic databases by considering confidence bounds over first-order lineage formulas. We extend our query processing techniques by a tool-suite of scheduling strategies based on selectivity estimation and the expected impact on confidence bounds. Further extensions to our query processing strategies include improved top-k bounds in the case when sorted relations are available as input, as well as the consideration of recursive rules. Experiments with large datasets demonstrate significant runtime improvements of our approach compared to both exact and sampling-based top-k methods over probabilistic data.

关键词： query analysis confidence Bound Database View Exact distributed query processing relational query processing

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Mobile Agent-based Dynamic Resource Allocation Method for query Optimization in Data Grid Systems

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7th KES Conference on Agent and Multi-Agent Systems - Technologies and Applications (KES-AMSTA)

作者： Epimakhov, Igor Hameurlain, Abdelkader Morvan, Franck Yin, Shaoyi Univ Toulouse 3 Inst Rech Informat Toulouse IRIT F-31062 Toulouse France

ISBN: (纸本)9781614992547;9781614992530

Resource allocation is one of the principal stages of query processing in relational data grid systems. Specific characteristics of the data grid environment, such as dynamicity, heterogeneity and large scale, impose serious restrictions to the resource allocation process. Static resource allocation before the query execution may be far from optimal due to the dynamic changes of the system. One possible optimization is to adjust dynamically the allocation of resources during the query execution. Some methods of dynamic resource allocation have been proposed, however, most of them use centralized control mechanisms. In this study we argue that the decentralized approach meets better the requirements of the data grid systems. In this study we propose a decentralized method of dynamic resource allocation that is based on the mobile agent paradigm. We consider the participating nodes as autonomous and independent elements of the system, each of which can detect if it is overloaded and make the decision to react. Then we consider each relational operation as a mobile agent running on the allocated node, meaning that, it keeps track of its own status and can migrate to another node at any time. A two-level cooperation mechanism between such autonomous nodes and autonomous operations is described in detail. Performance evaluation proves the efficiency of the proposed method.

关键词： Data grid systems distributed query processing optimization resource allocation load balancing scheduling

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A Novel distributed Skyline query based Service Discovery in the Mobile P2P Cloud

A Novel Distributed Skyline Query based Service Discovery in...

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International Conference on ICT Convergence (ICTC) - Future Creative Convergence Technologies for New ICT Ecosystems

作者： Go, Yunmin Song, Hwangjun POSTECH Pohang Univ Sci & Technol Div IT Convergence Engn Pohang South Korea POSTECH Pohang Univ Sci & Technol Dept Comp Sci & Engn Pohang South Korea

ISBN: (纸本)9781479906987

In this paper, we propose a novel service discovery system based on user preference in the mobile P2P cloud. The goal of our system is to find preferable services from the users with similar user preference. The proposed system is constructed over the region-based overlay network. The querying user draws user preference and generates query using the user's service access history. And then, in the mobile P2P cloud, the generated query is handled by the proposed distributed query processing on the basis of skyline query to find preferable services.

关键词： User preference Service discovery mobile P2P cloud skyline distributed query processing

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Scalable Matching and Ranking for Network Search

Scalable Matching and Ranking for Network Search

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9th International Conference on Network and Service Management (CNSM)

作者： Uddin, Misbah Stadler, Rolf Clemm, Alexander KTH Royal Inst Technol ACCESS Linnaeus Ctr Stockholm Sweden Cisco Syst San Jose CA 95134 USA

ISBN: (纸本)9783901882531

Network search makes operational data available in real-time to management applications. In contrast to traditional monitoring, neither the data location nor the data format needs to be known to the invoking process, which simplifies application development, but requires an efficient search plane inside the managed system. The search plane is realized as a network of search nodes that process search queries in a distributed fashion. This paper introduces matching and ranking for network search queries. We are proposing a semantic for matching and ranking, which is configurable to support different types of management applications-from exact matching for database-style queries to loose, approximate matching, which is appropriate for exploratory purposes. We describe an echo protocol for efficient distributed query processing that supports matching and ranking. Further, we present the design of a search node, which maintains a real-time database of operational information and allows for parallel processing of search queries. A prototype implementation on a cloud testbed shows that the network search system, on a 9-node cluster with 24 core servers, executes 200 global search queries/sec with the 75th percetile latency below 100 milliseconds and with a CPU utilization below 5%. The performance measurements, together with our design, suggest that a system of 100,000 servers processing the same load would exhibit the same overhead per server and a query latency of below 1 sec.

关键词： Network search matching and ranking distributed query processing distributed management in-network management

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Constrained Skyline query processing against distributed Data Sites

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IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 2011年第2期23卷 204-217页

作者： Chen, Lijiang Cui, Bin Lu, Hua Peking Univ Key Lab High Confidence Software Technol Minist Educ Beijing 100871 Peoples R China Peking Univ Dept Comp Sci Beijing 100871 Peoples R China Aalborg Univ Dept Comp Sci DK-9220 Aalborg Denmark

The skyline of a multidimensional point set is a subset of interesting points that are not dominated by others. In this paper, we investigate constrained skyline queries in a large-scale unstructured distributed environment, where relevant data are distributed among geographically scattered sites. We first propose a partition algorithm that divides all data sites into incomparable groups such that the skyline computations in all groups can be parallelized without changing the final result. We then develop a novel algorithm framework called PaDSkyline for parallel skyline query processing among partitioned site groups. We also employ intragroup optimization and multifiltering technique to improve the skyline query processes within each group. In particular, multiple (local) skyline points are sent together with the query as filtering points, which help identify unqualified local skyline points early on a data site. In this way, the amount of data to be transmitted via network connections is reduced, and thus, the overall query response time is shortened further. Cost models and heuristics are proposed to guide the selection of a given number of filtering points from a superset. A cost-efficient model is developed to determine how many filtering points to use for a particular data site. The results of an extensive experimental study demonstrate that our proposals are effective and efficient.

关键词： Constrained skyline query filtering point distributed query processing

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Preference-aware Skyline Service Discovery in the Mobile Cloud System

Preference-aware Skyline Service Discovery in the Mobile Clo...

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IEEE International Symposium on Personal, Indoor and Mobile Radio Communications

作者： Yunmin Go Hwangjun Song Division of IT Convergence Engineering POSTECH (Pohang University of Science and Technology) Pohang Republic of Korea Department of Computer Science and Engineering POSTECH (Pohang University of Science and Technology) Pohang Republic of Korea

ISBN: (纸本)9781467362337

关键词： Preference-aware Service discovery distributed query processing Mobile cloud system Skyline

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query Planning for Continuous Aggregation Queries over a Network of Data Aggregators

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IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 2012年第6期24卷 1065-1079页

作者： Gupta, Rajeev Ramamritham, Krithi IBM India Private Ltd 4 IBM Res Inst Area New Delhi 110070 India Indian Inst Technol Dept Comp Sci & Engn Bombay 400076 Maharashtra India

Continuous queries are used to monitor changes to time varying data and to provide results useful for online decision making. Typically a user desires to obtain the value of some aggregation function over distributed data items, for example, to know value of portfolio for a client;or the AVG of temperatures sensed by a set of sensors. In these queries a client specifies a coherency requirement as part of the query. We present a low-cost, scalable technique to answer continuous aggregation queries using a network of aggregators of dynamic data items. In such a network of data aggregators, each data aggregator serves a set of data items at specific coherencies. Just as various fragments of a dynamic webpage are served by one or more nodes of a content distribution network, our technique involves decomposing a client query into subqueries and executing subqueries on judiciously chosen data aggregators with their individual subquery incoherency bounds. We provide a technique for getting the optimal set of subqueries with their incoherency bounds which satisfies client query's coherency requirement with least number of refresh messages sent from aggregators to the client. For estimating the number of refresh messages, we build a query cost model which can be used to estimate the number of messages required to satisfy the client specified incoherency bound. Performance results using real-world traces show that our cost-based query planning leads to queries being executed using less than one third the number of messages required by existing schemes.

关键词： Algorithms continuous queries distributed query processing data dissemination coherency performance

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