59766135
Improving Responsiveness for Wide-Area Data Access
Improving Resp onsiveness for WideArea Data AccessLaurent AmsalegPhilipp e BonnetMichael J FranklinINRIABullUniversity of MarylandAnthonyTomasicTolga UrhanINRIAUniversity of MarylandAbstractIn a widearea environment the time rquird to obtain data from remote sources can varyunpredictably due to network congestion link failure or other problems Traditional techniquesfor query optimization and query execution do not cope wel l with such unpredictabilityThestatic nature of those techniques prevents them from adapting to remote access delays that ariseat runtime In this paper we describe two separate but relatedtechniques aimed at tackling thisproblem The rst technique cal led Query Scrambling hides relatively short intermittent delaysby dynamical ly adjusting query execution plans onthey The second technique addresses thelongerterm unavailability of data sources by al lowing the return of partial query answers whensome of the data needed to ful ly answer a query are missingIntro ductionThe continued dramatic growth in global interconnectivity via the Internet has made aroundtheclo ckondemand access to widelydistribu ted data a common exp ectation for many computer users Advances in resource discoery heterogeneous data management and semistructured data managementare providingsemanticto ols to enable the access and correlation of data from diverse widelydistributedsources A limiting factor of suchwork however is the diculty of providing resp onsive data access tousers due to the highly varying resp onsetime and availabilitycharacteristics of remote data sources ina widearea environment Data access over widearea networks inolves a large numb er of data sourcesintermediate sites and communications links all of which are vulnerable to congestion and failuresSuch problems can intro duce signicant and unpredictabledelaysin the access of information fromremote sourcesCurrent distributed query pro cessing approaches p erform p o orly in the widearea environmentThey p ermit unexp ected delays to directly increase the query resp onse time allowing query executionCopyright IEEE Personal use of this material is permitted However permission to reprintrepublish this material for advertising or promotional purposes or for creating new col lective works for resale or rdistribution to serversor lists or to reuse any copyrightedcomponent of this work in other works must be obtainedfrom the IEEEBulletin of the IEEE Computer So cietyTechnical Committee on Data EngineeringThis work was partially supp orted by the NSF under Grant IRI by Bellcore and by an IBM SharedUniversity Researchaward Laurent Amsaleg did this work while he was at the Univy of Maryland and was supp ortedin part by an INRIA Fellowship Philipp e Bonnet and AnthonyTomasic p erformed this work in the context of Dyadean RD jointventure b etween Bull and INRIA
2033914
Data Staging for On-Demand Broadcast
:A>@<b_DCGAdPBEG>R<:c\A8:Q@L]J.A8<0H(L[MOz:CTL0PBc:zbP[<bc4EGADCG ? >@_DA8EHGbP[HP[CTA>@<::ADCTAD<.HTQRJz:CTL0PBcb_DPBEwHw_DPBbP[zbQRA bP0EqPBc\A>Uc\ADPBCGAdP$c:P]HFP z:CGL.PBc:_8PBEwHP[<P]HGHGCFPB_ HG>@?BA4c:P]HFP c\A8QR>@?BA8CGJ P[QRHGA8CG<kP]HG>@?BA2MSLBCQ@PBCG0A&_Q@>RA8<.H  LB:a:QUP]HT>RL0<bE8`v:ADCTAbP0Evz ADAD<Ew>@B<:>Rk_8P[<.HvyL0CGZ HGL]P[CFc:EOc\A8?BA8QRL0:>R<b$LB<\QR>@<:Az:CTL0P0c:_DP0EKHET_F:Adc\a:QR >@<:P[Q@BLBCT>RHG:E MSLBCEGJ\EKHTADE :ADCTA!P[Q@Q c:P]HFP >RHGADEOPBCGAyCGAdPBc\>@QRJPY?]PB>RQUP[z:Q@A>@<¡HG:AEGADCT?BADCd¢ E6P[>@< ADLBCTJB` :A8EGA£EwHGabc:>RAdE(>@B<bLBCTA HG:Ac:P]HFP2P[<: P[0ADAD<.H>UETEwa:AdEOHTbP]HP[CT>@EGA:A8<HG:A c:P[HTP HTL£z A z:CTL0P0c:_DP0EKH£akEKH&z A L0z\HTPB>R<bA8c MSCGL0¤EGA8_DLB<bcbP[CTJ EwHGLBCFP[0A LBC,CTADL[HTA Q@L\_DP]HT>RL0<bE8`¥<¦HT:>@E4bPBkA8C8V  A§:CTLB L0EGA HG:CTADA_LB:Q@ADA8<0HFP[CTJ ̈EGLBQ@a\HG>@LB<kE HGL EGab_F ̈©Ba[«a ¬­«aD®B ̄±°.®_L0<b_A8CG<kED2§L0: LBCGHGa:<:>UEw HG>U_ ET_F:A8c:a:QR>@<:kVEGADCT?BA8C2_DP0_F:>R<bbVP[<bc bCGADMSAHT_F: >@<:b`&bA8EGAHGA8_Fb<:>@3.a:AdE$A ́\:Q@LB>RH:>@<.HTE$:CTL]? >@c:A8c z J,HG:AET_F:A8c\abQR>@<:,P[Q@BLBCT>RHG:,`$μ¶c:AHTPB>RQ@A8c kA8Cw MSLBCTP[<b_DA AD?]P[Q@abP]HT>RL0< akEw>@<:P[<·¥K ̧o1 a:QRHG>U_DPBEwHw zbP0EwAdc HGAdEKHTzkAdc EG:L]vE$HTbP]HHG:AdEwA4c:P]HFP EwHTPBB>@<: HGAd_F:<:>U3.a:A8Ev_8P[< c\CFP[P]HT>@_8P[Q@QRJA8<:bPB<b_A HT:A$kA8Cw MSLBCTP[<b_DA L[M£P Q@PBCG0AEG_8P[Q@A,LB<\c\ADPB<bcz:CTL0P0c  _DP0EKHvEGJ\EKHTAD,`
7889988
Crash recovery in client-server EXODUS
In this paper, we address the correctness and performance issues that arise when implementing logging and crash recovery in a page-server environment. The issues result from two characteristics of page-server systems: 1) the fact that data is modified and cached in client database buffers that are not accessible by the server, and 2) the performance and cost trade-offs that are inherent in a client-server environment. We describe a recovery system that we have implemented for the client-server version of the EXODUS storage manager. The implementation supports efficient buffer management policies, allows flexibility in the interaction between clients and the server, and reduces the server load by generating log records at clients. We also present a preliminary performance analysis of the implementation.
2815522
Efficient Filtering of XML Documents for Selective Dissemination of Information
Information Dissemination applications are gaining increasing popularity due to dramatic improvements in communications bandwidth and ubiquity. The sheer volume of data available necessitates the use of selective approaches to dissemination in order to avoid overwhelming users with unnecessaryinformation. Existing mechanisms for selective dissemination typically rely on simple keyword matching or “bag of words” information retrieval techniques. The advent of XML as a standard for information exchangeand the development of query languages for XML data enables the development of more sophisticated filtering mechanisms that take structure information into account. We have developed several index organizations and search algorithms for performing efficient filtering of XML documents for large-scale information dissemination systems. In this paper we describe these techniques and examine their performance across a range of document, workload, and scale scenarios.
1006062
The design of an acquisitional query processor for sensor networks
We discuss the design of an acquisitional query processor for data collection in sensor networks. Acquisitional issues are those that pertain to where, when, and how often data is physically acquired (sampled) and delivered to query processing operators. By focusing on the locations and costs of acquiring data, we are able to significantly reduce power consumption over traditional passive systems that assume the a priori existence of data. We discuss simple extensions to SQL for controlling data acquisition, and show how acquisitional issues influence query optimization, dissemination, and execution. We evaluate these issues in the context of TinyDB, a distributed query processor for smart sensor devices, and show how acquisitional techniques can provide significant reductions in power consumption on our sensor devices.
2567437
Dynamic Query Operator Scheduling for Wide-Area Remote Access
Distributed databases operating over wide-area networks such as the Internet, must deal with the unpredictable nature of the performance of communication. The response times of accessing remote sources can vary widely due to network congestion, link failure, and other problems. In such an unpredictable environment, the traditional iterator-based query execution model performs poorly. We have developed a class of methods, called query scrambling, for dealing explicitly with the problem of unpredictable response times. Query scrambling dynamically modifies query execution plans on-the-fly in reaction to unexpected delays in data access. In this paper we focus on the dynamic scheduling of query operators in the context of query scrambling. We explore various choices for dynamic scheduling and examine, through a detailed simulation, the effects of these choices. Our experimental environment considers pipelined and non-pipelined join processing in a client with multiple remote data sources and delayed or possibly bursty arrivals of data. Our performance results show that scrambling rescheduling is effective in hiding the impact of delays on query response time for a number of different delay scenarios.
14470215
Genetic epidemiology, parallel algorithms, and workstation networks
Many interesting problems in genetic epidemiology are formulated as non-linear optimization problems using the Gemini/Almini library of routines. Because of the wide availability of networked workstations, we investigate cost-effectively improving the performance of the Gemini/Almini library by exploiting parallelism with a set of workstations connected via a local area network. Instrumentation of the Gemini/Almini optimization routines reveals significant potential for improving performance via parallelism. Using these instrumentation results, we identify promising targets of parallelism and discuss two preliminary implementations that demonstrate the potential benefits of cost-effective parallel implementations. By applying parallelism to the Almini/Gemini routines, we hope to potentially improve the performance of a large number of genetic epidemiological applications.<<ETX>>
8725841
Design Tradeoffs for Embedded Network Processors
Demands for flexible processing have moved general-purpose processing into the data path of networks. With the development of System-On-a-Chip technology, it is possible to put a number of processors with memory and I/O components on a single ASIC. We present a performance model of such a system and show how the number of processors, cache sizes, and the tradeoffs between the use of on-chip SRAM and DRAM can be optimized in terms of computation per unit chip area for a given workload. Based on a telecommunications benchmark the results of such an optimization are presented and design tradeoffs for Systems-on-a-Chip are identified and discussed.
583321
Performance models for network processor design
To provide a variety of new and advanced communications services, computer networks are required to perform increasingly complex packet processing. This processing typically takes place on network routers and their associated components. An increasingly central component in router design is a chip-multiprocessor (CMP) referred to as "network processor" or NP. In addition to multiple processors, NPs have multiple forms of on-chip memory, various network and off-chip memory interfaces, and other specialized logic components such as CAMs (content addressable memories). The design space for NPs (e.g., number of processors, caches, cache sizes, etc.) is large due to the diverse workload, application requirements, and system characteristics. System design constraints relate to the maximum chip area and the power consumption that are permissible while achieving defined line rates and executing required packet functions. In this paper, an analytic performance model that captures the processing performance, chip area, and power consumption for a prototypical NP is developed and used to provide quantitative insights into system design trade offs. The model, parameterized with a networking application benchmark, provides the basis for the design of a scalable, high-performance network processor and presents insights into how best to configure the numerous design elements associated with NPs
14211318
An architecture for fast processing of large unstructured data sets
This paper presents a general system architecture tailored to perform searching, filtering, compression, encryption, and other operations on unstructured data streaming from a disk system. The system achieves high performance on such applications by providing for parallelism, hardware-application specialization and reconfiguration, and hardware placement near the disk systems. A limited prototype of a single compute node has been implemented and is described. The prototype is tailored to applications involving complex searching and its performance is compared to a pure software implementation having the same search capabilities. Performance is considered in terms of data set size, query string hit rate and query complexity. Performance results as a function of these parameters are presented and the results indicate that, for data set sizes above 1.4 MB, the prototype compute node is between one and two orders of magnitude faster than a pure software implementation. At high data set sizes, on an individual node, speedups of about 200 and a sustained throughput of 300 MB/sec have been achieved.
61655346
Statistics on Logic Simulation
The high costs associated with logic simulation of large VLSI based systems have led to the need for new computer architectures tailored to the simulation task. Such architectures have the potential for significant speedups over standard software based logic simulators. Several commercial simulation engines have been produced to satisfy needs in this area. To properly explore the space of alternative simulation architectures, data is required on the simulation process itself. This paper presents a framework for such data gathering activity by first examining possible sources of speedup in the logic simulation task, examining the sort of data needed in the design of simulation engines, and then presenting such data. The data contained in the paper includes information on subtask times found in standard discrete event simulation algorithms, event intensities, queue length distributions and simultaneous event distributions.