175021
Research in Data Broadcast and Dissemination
The proliferation of the Internet and intranets, the development of wireless and satellite networks, and the availability of asymmetric, high-bandwidth links to the home, have fueled the development of a wide range of new “dissemination-based” applications. These applications involve the timely distribution of data to a large set of consumers, and include stock and sports tickers, traffic information systems, electronic personalized newspapers, and entertainment delivery. Dissemination-oriented applications have special characteristics that render traditional client-server data management approaches ineffective. These include: 
 
 
tremendous scale. 
 
 
a high-degree of overlap in user data needs. 
 
 
asymmetric data flow from sources to consumers.
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.
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.
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.
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.
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,`
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.
206622431
Pin Limitations and Partitioning of VLSI Interconnection Networks
Multiple processor interconnection networks can be characterized as having N' inputs and N' outputs, each being B' bits wide. A major implementation constraint of large networks in the VLSI environment is the number of pins available on a chip, Np. Construction of large networks requires partitioning of the N' * N' * B' network into a collection of N * N switch modules with each input and output port being B (B ≤ B') bits wide. If each module corresponds to a single chip, then a large network can be implemented by interconnecting the chips in a particular manner. This correspondence presents a methodology for selecting the optimum values of N and B given values of N', B', Np, and the number of control lines per port. Models for both banyan and crossbar networks are developed and arrangements yielding minimum: 1) number of chips, 2) average delay through the network, and 3) product of number of chips and delay, are presented.
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.
2563843
An algebraic approach to IP traceback
We present a new solution to the problem of determining the path a packet traversed over the Internet (called the traceback problem) during a denial-of-service attack. This article reframes the traceback problem as a polynomial reconstruction problem and uses algebraic techniques from coding theory and learning theory to provide robust methods of transmission and reconstruction.
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.