9803668
Distributing layered encoded video through caches
The efficient distribution of stored information has become a major concern in the Internet which has increasingly become a vehicle for the transport of stored video. Because of the highly heterogeneous access to the Internet, researchers and engineers have argued for layered encoded video. We investigate delivering layered encoded video using caches. Based on a stochastic knapsack model we develop a model for the layered video caching problem. We propose heuristics to determine which videos and which layers in the videos should be cached. We evaluate the performance of our heuristics through extensive numerical experiments. We also consider two intuitive extensions to the initial problem.
32291503
On Nonblocking Multirate Interconnection Networks
In a recent paper, Melen and Turner [SIAM J. Comput., 18 (1989), pp. 301–313] determined sufficient conditions for multirate interconnection networks to be strictly nonblocking and rearrangeable. They considered the continuous bandwidth case, which permits the bandwidth of a connection to take an arbitrary value in a given closed interval. In this paper, simple necessary and sufficient conditions for multirate interconnection networks to be strictly nonblocking for both discrete and continuous bandwidth cases are determined. New results for rearrangeable multirate networks with discrete bandwidth requirements are also given.
15937667
A dynamic programming methodology for managing prerecorded VBR sources in packet-switched networks
Broadband networks will increasingly carry prerecorded traffic, such as high-fidelity audio, short multimedia clips, and full-length movies. We study how to manage the transmission and transport of traffic from prerecorded VBR sources so that network resources are efficiently utilized and end users receive satisfactory service. Specifically, we study Piecewise Constant-Rate Transmission and Transport (PCRTT), whereby the server transmits and the network transports each connection's packets at different constant rates over a small number of intervals. We show how Dynamic Programming (DP) can be applied to find optimal PCRTT rates and intervals for a wide variety of optimization criteria, including criteria which explicitly account for delays to user interaction (pause, fast forward, and rewind). We also introduce two admission policies for PCRTT: peak-rate admission and packing admission. For peak-rate admission, for each video the network allocates an end-to-end CBR connection; the rate of the CBR connection is equal to the maximum PCRTT rate. For packing admission, for each video the network reserves a series of CBR connections of different rates over specific time intervals. Using public domain MPEG traces, we present several numerical examples which illustrate the traffic management schemes and the DP methodology.
18166886
On Routing in ATM Networks
Alternative routing of calls has long been acknowledged as a means of increasing call throughput and robustness in the telephone network. Given these performance gains, it is natural to consider dynamic routing of Virtual Circuits (VCs) in Asynchronous Transfer Mode (ATM) networks. Unlike telephone networks, VCs have heterogeneous bandwidth characteristics and Quality of Service requirements that the routing algorithm must take into account in order to optimize performance. In this paper we attempt to classify ATM networks according to the network characteristics that have the greatest bearing on the performance of dynamic routing algorithms; we also discuss appropriate routing algorithms for diierent classes of ATM network. The classiication is based on the degree of heterogeneity of the sources and the degree of statistical multiplexing.
6975415
Distributing Layered Encoded Video through Caches
The efficient distribution of stored information has become a major concern in the Internet which has increasingly become a vehicle for the transport of stored video. Because of the highly heterogeneous access to the Internet, researchers and engineers have argued for layered encoded video. We investigate delivering layered encoded video using caches. Based on the stochastic knapsack theory, we develop a model for the layered video caching problem. We propose heuristics to determine which videos and which layers in the videos should be cached in order to maximize the revenue from the streaming service. We evaluate the performance of our heuristics through extensive numerical experiments. We find that, for typical scenarios, the revenue increases nearly logarithmically with the cache size and linearly with the link bandwidth that connects the cache to the origin servers. We also consider service models with request queuing and negotiations about the delivered stream quality and find that both extensions provide only small revenue increases.
31310473
Packet multiplexers with adversarial regulated traffic
We consider a finite-buffer packet multiplexer to which traffic arrives from several independent sources. The traffic from each of the sources is regulated, i.e., the amount of traffic that can enter the multiplexer is constrained by known regulator constraints. The regulator constraints depend on, the source and are more general than those resulting from cascaded leaky buckets. We assume that the traffic is adversarial to the extent permitted by the regulators. For lossless multiplexing, we show that if the original multiplexer is lossless it is possible to allocate bandwidth and buffer to the sources so that the resulting segregated systems are lossless. For lossy multiplexing, we use our results for lossless multiplexing to estimate the loss probability of the multiplexer. Our estimate involves transforming the original system into two independent resource systems, and using adversarial sources for the two independent resources to obtain a bound on the loss probabilities for the transformed system. We show that the adversarial sources are not extremal on-off sources, even when the regulator consists of a peak rate controller in series with a leaky bucket. We explicitly characterize the form of the adversarial source for the transformed problem. We also provide numerical results for the case of the simple regulator.
9861347
Conjunctive selection conditions in main memory
We consider the fundamental operation of applying a conjunction of selection conditions to a set of records. With large main memories available cheaply, systems may choose to keep the data entirely in main memory, in order to improve query and/or update performance.The design of a data-intensive algorithm in main memory needs to take into account the architectural characteristics of modern processors, just as a disk-based method needs to consider the physical characteristics of disk devices. An important architectural feature that influences the performance of main memory algorithms is the branch misprediction penalty. We demonstrate that branch misprediction has a substantial impact on the performance of an algorithm for applying selection conditions.We describe a space of "query plans" that are logically equivalent, but differ in terms of performance due to variations in their branch prediction behavior. We propose a cost model that takes branch prediction into account, and develop a query optimization algorithm that chooses a plan with optimal estimated cost. We also develop an efficient heuristic optimization algorithm.We provide experimental results for a case study based on an event notification system. Our results show the effectiveness of the proposed optimization techniques. Our results also demonstrate that significant improvements in performance can be obtained by applying a methodology that takes branch misprediction latency into account.
14305268
Relations with relation names as arguments: algebra and calculus
We consider a version of the relational model in which relation names may appear as arguments of other relations. Allowing relation names as arguments provides enhanced modelling capabilities, allowing some object-oriented features to be expressed within the relational model. We extend relational algebra with operators for accessing relations, and also define a relational calculus based on the logic HiLog. We prove two equivalence results between extensions of relational algebra provide higher expressive power than relational algebra on any given database. Finally, we argue that the extensions proposed here are relatively easy to provide in practice, and should be expressible within modern query languages.
38852147
On Negation in HiLog
Abstract The logic HiLog of Chen, Kifer, and Warren has a second order syntax, while its semantics is first order. HiLog programs with negative literals in the body are considered. A stable-model semantics and a well-founded semantics for this class of program are defined, and it is shown that these semantics generalize the stable-model semantics and the well-founded semantics, respectively, for range-restricted normal programs. A second order property called preservation under extensions is proposed and investigated. Preservation under extensions ensures that the semantics of a program is not changed when rules having no symbols in common with the program are appended to the program. It is shown that for normal programs, domain independence and preservation under extensions are equivalent, while for HiLog programs, preservation under extensions is strictly stronger. Range restrictedness is generalized to HiLog programs in two ways, and it is shown that range restricted HiLog programs are preserved under extensions with respect to the well-founded semantics. Conditions under which the well-founded semantics is two-valued are investigated, and the class of modularly stratified programs is generalized to HiLog. An extension of magic-set techniques to modularly stratified HiLog programs is described.
2564021
Database research at Columbia University
Columbia University has a number of projects that touch on database systems issues. In this report, we describe the Columbia Fast Query Project (Section 2), the JAM project (Section 3), the CARDGIS project (Section 4), the Columbia Internet Information Searching Project (Section 5), the Columbia Content-Based Visual Query project (Section 6), and projects associated with Columbia’s Programming Systems Laboratory (Section 7).
8569541
Partitioned optimization of complex queries
Performing complex analysis on top of massive data stores is essential to most modern enterprises and organizations and requires significant aggregation over different attribute sets (dimensions) of the participating relations. Such queries may take hours or days, a time period unacceptable in most cases. As a result, it is important to study these queries and identify special frequent cases that can be evaluated with specialized algorithms. Understanding complex aggregate queries leads to better execution plans and, consequently, performance. The idea of partitioning is fundamental and central in aggregate queries. This concept can be used to define a class of queries called group queries. The main characteristic of a group query is that it can be evaluated in a partitioned (or groupwise) fashion, i.e. the underlying relation(s) can be partitioned (based on a set of attributes) into disjoint groups and each group can be processed separately, possibly in parallel. For example, a query that performs a complex operation (e.g. joins and/or selections and/or aggregations) within each group is a group query. To express it in SQL, one has to join/correlate several views and/or subqueries on the grouping attributes. A naive plan (where the joins are executed) may be very expensive, even for relatively small base relations. On the other hand, a groupwise evaluation can lead to huge performance gains. We present a syntactic criterion to identify group queries in SQL and show that every group query can be expressed in a way that satisfies this criterion. This work is based on Chatziantoniou and Ross [Querying Multiple Features of Groups in Relational Databases. in: 22nd International Conference on Very Large Databases, VLDB, 1996, pp. 295-306]. The concept of group queries is useful not only in terms of evaluation, but also in terms of analyzing a complex decision support query that aggregates over different sets of attributes. In such a case the query may be decomposable to one or more query components, where each component is a group query. This observation allows parallel execution, multi-query processing and identification of special cases. We present in this paper two algorithms to decompose a complex aggregate query to its group query components. The value of groupwise processing has been recently recognized by the research community and implemented in at least a major commercial system. To be of use however in a relational system, partitioned evaluation has to be modeled as a relational operator. We review three different approaches for such an operator and propose a generalized groupwise operator. We also perform some experiments to show that naive optimization with the new operator incorporated without taking into consideration decompositions to group query components does not always lead to the most efficient plans. An extended syntax is another way to identify special frequent cases and apply efficient algorithms. Having specific operators for common operations contributes to the succinctness and optimizability of certain queries (e.g. datacubes). An extended syntax is presented with emphasis for multi-feature queries, a frequent and practical subclass of group queries that is amenable to specialized evaluation, involving (potentially repeated) selection, grouping and aggregation over the same groups.