45021908
Video-on-Demand Over ATM: Constant-Rate Transmission and Transport
We introduce a specific transport and transmission scheme for video-on-demand (VoD) called constant-rate transmission and transport (CRTT). CRTT establishes a constant bit-rate (CBR) virtual channel between the video provider and the viewer's set-top box (STB) and then transmits cells from the provider into this channel at a constant rate. Since we assume that the number of cells in a frame is variable, CRTT requires that some number of cells be built up in an STB buffer before the commencement of playback. The build up, cell transmission rate, and the set-top memory size must be chosen so that there is no starvation or overflow at the STB. We develop fundamental relationships between these parameters for viable CRTT. We then apply the theory to an MPEG encoding of Star Wars and find that the minimal STB memory far CRTT is 23 Mbytes. We also consider varying the constant rate over a small number of intervals. We find, for example, that for Star Wars approximately 2 Mbytes of set-top memory suffices with 32 constant-rate intervals.
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.
22940589
Asynchronous voice: a personal account
Asynchronous voice is the interactive communication process of people leaving voice messages for other people and the other people responding with their voice messages. A primitive form of asynchronous voice is a kind of telephone tag in which people use voice mail to have an interactive conversation. The author gives a personal account of his work with asynchronous voice and asynchronous learning.
369703
Object replication strategies in content distribution networks
Recently, the Internet has witnessed the emergence of content distribution networks (CDNs). In this paper, we study the problem of optimally replicating objects in CDN servers. In our model, each Internet autonomous system (AS) is a node with finite storage capacity for replicating objects. The optimization problem is to replicate objects so that when clients fetch objects from the nearest CDN server with the requested object, the average number of ASs traversed is minimized. We formulate this problem as a combinatorial optimization problem. We show that this optimization problem is NP complete. We develop four natural heuristics and compare them numerically using real Internet topology data. We find that the best results are obtained with heuristics that have all the CDN servers cooperating in making the replication decisions. We also develop a model for studying the benefits of cooperation between nodes, which provides insight into peer-to-peer content distribution.
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.
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.
31185043
Inferring negative information from disjunctive databases
We propose criteria that any rule for inferring negative information from disjunctive databases should satisfy, and examine existing rules from this viewpoint. We then present a new inference rule, the ‘disjunctive database rule’ (DDR), and compare it to the existing rules with respect to the criteria. In particular, the DDR is equivalent to the CWA for definite databases, it infers no more negative information than the GCWA, and it interprets disjunction inclusively rather than exclusively. We generalize the DDR to a class of layered databases, describe an implementation of the DDR, ‘negation as positive failure’, and study its soundness and completeness properties.
578243
A Faceted Query Engine Applied to Archaeology
In this demonstration, we describe a system for storing and querying faceted hierarchies. We have developed a general faceted domain model and a query language for hierarchically classified data. We present here the use of our system on two real archaeological datasets containing thousands of artifacts. Our system is a sharable, evolvable resource that can provide global access to sizeable datasets in queriable format, and can serve as a valuable tool for data analysis and research in many application domains.
7456263
Reusing invariants: a new strategy for correlated queries
Correlated queries are very common and important in decision support systems. Traditional nested iteration evaluation methods for such queries can be very time consuming. When they apply, query rewriting techniques have been shown to be much more efficient. But query rewriting is not always possible. When query rewriting does not apply, can we do something better than the traditional nested iteration methods? In this paper, we propose a new invariant technique to evaluate correlated queries efficiently. The basic idea is to recognize the part of the subquery that is not related to the outer references and cache the result of that part after its first execution. Later, we can reuse the result and combine it with the result of the rest of the subquery that is changing for each iteration. Our technique applies to arbitrary correlated subqueries.
This paper introduces algorithms to recognize the invariant part of a data flow tree, and to restructure the evaluation plan to reuse the stored intermediate result. We also propose an efficient method to teach an existing join optimizer to understand the invariant feature and thus allow it to be able to generate better join plans in the new context. Some other related optimization techniques are also discussed. The proposed techniques were implemented within three months on an existing real commercial database system.
We also experimentally evaluate our proposed technique. Our evaluation indicates that, when query rewriting is not possible, the invariant technique is significantly better than the traditional nested iteration method. Even when query rewriting applies, the invariant technique is sometimes better than the query rewriting technique. Our conclusion is that the invariant technique should be considered as one of the alternatives in evaluating correlated queries since it fills the gap left by rewriting techniques.
9519416
Selection conditions in main memory
We consider the fundamental operation of applying a compound filtering condition 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 for conjunctive conditions. We also develop an efficient heuristic optimization algorithm. We also show how records can be ordered to further reduce branch misprediction effects.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.
7960269
Fast joins using join indices
Abstract. Two new algorithms, “Jive join” and “Slam join,” are proposed for computing the join of two relations using a join index. The algorithms are duals: Jive join range-partitions input relation tuple ids and then processes each partition, while Slam join forms ordered runs of input relation tuple ids and then merges the results. Both algorithms make a single sequential pass through each input relation, in addition to one pass through the join index and two passes through a temporary file, whose size is half that of the join index. Both algorithms require only that the number of blocks in main memory is of the order of the square root of the number of blocks in the smaller relation. By storing intermediate and final join results in a vertically partitioned fashion, our algorithms need to manipulate less data in memory at a given time than other algorithms. The algorithms are resistant to data skew and adaptive to memory fluctuations. Selection conditions can be incorporated into the algorithms. Using a detailed cost model, the algorithms are analyzed and compared with competing algorithms. For large input relations, our algorithms perform significantly better than Valduriez's algorithm, the TID join algorithm, and hash join algorithms. An experimental study is also conducted to validate the analytical results and to demonstrate the performance characteristics of each algorithm in practice.