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CACHING HINTS IN distributed SYSTEMS

IEEE TRANSACTIONS ON SOFTWARE ENGINEERING 1987年第1期13卷 48-54页

作者： TERRY, DB Computer Science Laboratory Xerox Palo Alto Research Center

Caching reduces the average cost of retrieving data by amortizing the lookup cost over several references to the data. Problems with maintaining strong cache consistency in a distributed system can be avoided by treating cached information as hints. A new approach to managing caches of hints suggests maintaining a minimum level of cache accuracy, rather than maximizing the cache hit ratio, in order to guarantee performance improvements. The desired accuracy is based on the ratio of lookup costs to the costs of detecting and recovering from invalid cache entries. Cache entries are aged so that they get purged when their estimated accuracy falls below the desired level. The age thresholds are dictated solely by clients' accuracy requirements instead of being suggested by data storage servers or system administrators.

关键词： Resource Location Cache Consistency Caching Computer Communication Networks data Accuracy database management distributed data management distributed Systems Functional Lifetimes Hints

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Federating queries in SPARQL 1.1: Syntax, semantics and evaluation

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JOURNAL OF WEB SEMANTICS 2013年第1期18卷 1-17页

作者： Buil-Aranda, Carlos Arenas, Marcelo Corcho, Oscar Polleres, Axel UPM Fac Informat Ontol Engn Grp Madrid Spain PUC Dept Comp Sci Santiago Chile Siemens AG Osterreich A-1210 Vienna Austria

Given the sustained growth that we are experiencing in the number of SPARQL endpoints available, the need to be able to send federated SPARQL queries across these has also grown. To address this use case, the W3C SPARQL working group is defining a federation extension for SPARQL 1.1 which allows for combining graph patterns that can be evaluated over several endpoints within a single query. In this paper, we describe the syntax of that extension and formalize its semantics. Additionally, we describe how a query evaluation system can be implemented for that federation extension, describing some static optimization techniques and reusing a query engine used for data-intensive science, so as to deal with large amounts of intermediate and final results. Finally we carry out a series of experiments that show that our optimizations speed up the federated query evaluation process. (c) 2012 Elsevier B.V. All rights reserved.

关键词： SPARQL 1.1 distributed data management distributed query processing RDF

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An adaptive object-oriented approach to integration and access of heterogeneous information sources

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distributed AND PARALLEL dataBASES 1997年第2期5卷 167-205页

作者： Liu, L Pu, C OREGON GRAD INST DEPT COMP SCI & ENGNPORTLANDOR 97291

A large-scale interoperable database system operating in a dynamic environment should provide Uniform access to heterogeneous information sources, Scalability to the growing number of information sources, Evolution and Composability of software and information sources, and Autonomy of participants, both information consumers and information producers. We refer to these set of properties as the USECA properties [29]. To address the research issues presented by such systems in a systematic manner, we introduce the distributed Interoperable Object Model (DIOM). DIOM promotes an adaptive approach to interoperation via intelligent mediation [46, 47], aimed at enhancing the robustness and scalability of the services provided for integrating and accessing heterogeneous information sources. DIOM's main features include (1) the recursive construction and organization of information access through a network of application-specific mediators, (2) the explicit use of interface composition meta operations (such as specialization, generalization, aggregation, import and hide) to support the incremental design and construction of consumer's domain query model, (3) the deferment of semantic heterogeneity resolution to the query result assembly time instead of before or at the time of query formulation, and (4) the systematic development of the query mediation framework and the procedure of each query processing step from query routing, query decomposition, parallel access planning, query translation to query result assembly. To make DIOM concrete, we outline the DIOM-based information mediation architecture, which includes important auxiliary services such as domain-specific metadata library and catalog functions, object linking databases, and associated query services. Several practical examples and application scenarios illustrate the flavor of DIOM query mediation framework and the usefulness of DIOM in multi database query processing.

关键词： interoperability distributed data management object-oriented data model intelligent integration of heterogeneous information sources query mediation

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Client-centric consistency formalization and verification for system with large-scale distributed data storage

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2010年第8期26卷 1180-1188页

作者： Zhu, Yuqing Wang, Jianmin Tsinghua Univ Sch Software Beijing 100084 Peoples R China Tsinghua Univ Dept Comp Sci & Technol Beijing 100084 Peoples R China

Customized consistency is necessary in systems with large-scale distributed data storage, which have to make a tradeoff between consistency and performance. Client-centric consistency is intuitive for applications to specify their consistency requirements, but the properties of system implementations that satisfy client-centric consistency are not clear. So constraints on implementation and costs in performance are not known. In this paper, we formally define the four client-centric consistencies and their basis, i.e. eventual consistency, borrowing the framework from the theory of database concurrency control. Based on their definitions, we prove relations among these consistencies. Such relations imply how the implementation of one consistency can be made upon another. Besides, with these formal definitions, we can make simple consistency verification on system implementations. (c) 2010 Elsevier B.V. All rights reserved.

关键词： Consistency Replication Availability distributed data management

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Schedulability and performance analysis of the similarity stack protocol

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IEEE TRANSACTIONS ON COMPUTERS 2003年第5期52卷 658-669页

作者： Kuo, TW Mok, AK Natl Taiwan Univ Dept Comp Sci & Informat Engn Taipei 106 Taiwan Univ Texas Dept Comp Sci Austin TX 78712 USA

We propose a class of real-time data access protocols called SSP (Similarity Stack Protocol). The correctness of SSP schedules is justified by the concept of similarity which allows different but sufficiently timely data to be used in a computation without adversely affecting the outcome. SSP schedules are deadlock-free, subject to limited blocking, and do not use locks, We give a schedulability bound for SSP and also report simulation results which show that SSP is especially useful for scheduling real-time data access on multiprocessor systems. Finally, we present a variation of SSP which can be implemented in an autonomous fashion in the sense that scheduling decisions can be made with local information only.

关键词： real-time databases concurrency control real-time data access data similarity Delta-serializability distributed data management process scheduling

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Probabilistic Approach Processing Scheme Based on BLAST for Improving Search Speed of Bioinformatics

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WIRELESS PERSONAL COMMUNICATIONS 2019年第2期105卷 405-426页

作者： Jeong, Yoon-Su Shin, Seung-Soo Mokwon Univ Dept Informat Commun Engn 88 Doanbuk Ro Daejeon 35349 South Korea Tongmyong Univ Dept Informat Secur 428 Sinseonno Busan 48520 South Korea

As researchers on bioinformatics using heuristic algorithms have been increasingly studied, information management used in various bioinformatics fields (new drug development, medical diagnosis, agricultural product improvement, etc.) has been studied mainly on BLAST algorithm. However, many of the algorithms that are being used in the large genome database use a complete sorting procedure, which takes a lot of time to search the database for proteins or nucleic acid sequences, which causes many problems in processing large amounts of bio information. We propose a BLAST-based probabilistic access processing method that can manage, analyze and process a large amount of bio data distributed based on information communication infrastructure and IT technology. The proposed method aims to improve the accessibility of data by linking weighted bioinformatics information with probability factors to easily access large capacity bio data. In addition, the proposed scheme classifies the priority information allocated to the bioinformatics information by hierarchical grouping according to the degree of similarity, thereby ensuring high accuracy of the search results of the bioinformatics information, and at the same time, the goal is to obtain low processing time by classifying information (type, attribute, priority, etc.) into weights by property. Previous researchers have suggested clustering algorithms for fragmentation of genetic information to solve the problem of haplotype assembly in genetics, or proposed particle swarm optimization methods similar to existing genetic algorithms using heuristic clustering method based on MEC model. In the performance evaluation, the proposed method improved the accuracy by average 13.5% and the efficiency of the data retrieval by average 19.7% more than previous scheme. The overhead of Bioinformatics information processing was 8.8% lower and the processing time was average 13.5% lower.

关键词： Bioinformatics BLAST Probability distributed data management Algorithm Cloud Networking Computing

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Detector control system for Daya Bay Reactor Neutrino Experiment

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Science China(Technological Sciences) 2013年第8期56卷 1966-1973页

作者： ZHANG ShuHua WANG YiFang YE Mei LI XiaoNan ZHANG YinHong XU Jun MIN Jian DU XiaoFeng ZENG Lei Institute of High Energy Physics Chinese Academy of Sciences

The Daya Bay Reactor Neutrino Experiment is to measure the smallest mixing angle θ*** experiment contains three major experiment halls,Daya Bay near site,Linao near site and far site,and two major kinds of detectors,antineutrino detector which is to detect the antineutrinos by the inverse beta-decay reaction in Gd-LS,and muon detector which is to study and reject cosmogenic *** goal of the detector control system(DCS)is to operate and detect the detectors and keep them running in *** consideration of the limited fund of this system and manpower of working on this system,the LabVIEW is chosen to develop the detector control *** architecture of DCS adopts the distributed data management which is based on client-server *** server part is to detect and operate parameters from hardware,save data to database and release data to clients,the client is to receive data from the *** detector control system contains three parts:the hardware part,the local control system and the global control *** local control system includes high voltage supply system,low voltage supply system,VME crate system,temperature and humidity system,gas pressure system,and so on.

关键词： antineutrino detector muon detector detector control system distributed data management client-server model

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Self-Organized Formation and Evolution of Peer-to-Peer Networks

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INFORMS JOURNAL ON COMPUTING 2013年第3期25卷 502-516页

作者： Li, Yung-Ming Tan, Yong De, Prabuddha Natl Chiao Tung Univ Inst Informat Management Hsinchu 300 Taiwan Univ Washington Michael G Foster Sch Business Seattle WA 98195 USA Purdue Univ Krannert Sch Management W Lafayette IN 47907 USA

Peer-to-peer (P2P) networks are social networks for pooling network and information resources and are considered superior conduits for distributed computing and data management. In this paper, we utilize the theories of social networks and economic incentives to investigate the formation of P2P networks with rational participating agents (active peers). The paper proposes a framework for multilevel formation dynamics, including an individual level (content-sharing decision and group selection) and a group level (membership admission, splitting, and interconnection). It is found that if the network size (the number of peer nodes) is sufficiently large, the stable (self-selected equilibrium) free-riding ratio could be nonzero, contrary to the common belief that everybody should free ride. The efficient (welfare-maximizing) free-riding ratio is not necessarily zero;that is, a certain degree of free riding is beneficial and should be tolerated. The sharing level in a network increases (decreases) with the download (upload) capacities of its peer nodes. In addition, the heterogeneity of content availability and upload capacity discourages sharing activities. Although the sharing level of a stable group is typically lower than that of an efficient group, the self-formed network may have a larger or smaller group size than what is efficient, depending on the structure of the group admission decision process. It is also observed that self-organized interconnections among groups lead to network inefficiency because the network may be over- or underlinked. To recover the efficiency loss during the formation process, we propose internal transfer mechanisms to force stable networks to become efficient.

关键词： peer-to-peer networks distributed data management distributed computing self-organization network formation and evolution stability efficiency incentive mechanism

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Effective peer-to-peer design for supporting range query in Internet of Things applications

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COMPUTER COMMUNICATIONS 2020年 150卷 506-518页

作者： Djellabi, Brahim Younis, Mohamed Amad, Mourad Bejaia Univ Fac Exact Sci Comp Sci Dept LaMOS Res Unit Bejaia 06000 Algeria Univ Maryland Baltimore Cty Dept Comp Sci & Elect Engn Baltimore MD 21250 USA Bouira Univ Comp Sci Dept LIMPAF Lab Bouira 10000 Algeria

The Internet of Things (IoT) refers to the internetworking of diverse devices in an ad-hoc manner to support pervasive applications. IoT devices often generate a wealth of data that ought to be accessible and managed in a distributed manner. Such operational model requires architecture that supports contextual and information centric retrieval of data, and efficient data storage. In this paper, we argue that peer-to-peer (P2P) overlays are well suited for IoT systems. However, existing P2P systems do not efficiently handle queries of data within a range, which is a popular access pattern in IoT applications. Moreover, many of the IoT devices are constrained in their computational resources and consequently the data management model has to cope with such limitation. Existing P2P solutions do not factor the heterogeneity of the involved nodes and assume abundant storage space. This paper opts to fill the technical gap and proposes an effective P2P solution for efficient handling of range queries in IoT (RQIOT). RQIOT employs a data distribution model based on both consistent and order-preserving hashing and introduces a novel scheme for capacity management of the involved devices. The simulation results have confirmed the effectiveness and scalability of RQIOT, and the superiority of its performance over competing approaches.

关键词： Peer-to-peer systems Consistent hashing Internet of Things distributed hash table Range query distributed data management

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AUTOPLACER: Scalable Self-Tuning data Placement in distributed Key-Value Stores

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ACM TRANSACTIONS ON AUTONOMOUS AND ADAPTIVE SYSTEMS 2015年第4期9卷 1–30页

作者： Paiva, Joao Ruivo, Pedro Romano, Paolo Rodrigues, Luis Univ Lisbon Inst Super Tecn INESC ID P-1000029 Lisbon Portugal Red Hat Inc London England

This article addresses the problem of self-tuning the data placement in replicated key-value stores. The goal is to automatically optimize replica placement in a way that leverages locality patterns in data accesses, such that internode communication is minimized. To do this efficiently is extremely challenging, as one needs not only to find lightweight and scalable ways to identify the right assignment of data replicas to nodes but also to preserve fast data lookup. The article introduces new techniques that address these challenges. The first challenge is addressed by optimizing, in a decentralized way, the placement of the objects generating the largest number of remote operations for each node. The second challenge is addressed by combining the usage of consistent hashing with a novel data structure, which provides efficient probabilistic data placement. These techniques have been integrated in a popular open-source key-value store. The performance results show that the throughput of the optimized system can be six times better than a baseline system employing the widely used static placement based on consistent hashing.

关键词： Performance distributed data management data placement probabilistic algorithms machine learning

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