12744017
Foundations of Aggregation Constraints
We introduce a new constraint domain, aggregation constraints, which is useful in database query languages, and in constraint logic programming languages that incorporate aggregate functions. We study the fundamental problem of checking if a conjunction of aggregation constraints is solvable, and present undecidability results for many different classes of aggregation constraints. We describe a complete and minimal axiomatization of the class of aggregation constraints over finite multisets of reals, which permits a natural reduction from the class of aggregation constraints to the class of mixed integer/real, non-linear arithmetic constraints. We then present a polynomial-time algorithm that directly checks for solvability of a useful class of aggregation constraints, where the reduction-based approach does not lead to efficient checks for solvability.
7567374
Foundations of Aggregation Constraints
We introduce a new constraint domain, aggregation constraints, which is useful in database query languages, and in constraint logic programming languages that incorporate aggregate functions. We study the fundamental problem of checking if a conjunction of aggregation constraints is solvable, and present undecidability results for many different classes of aggregation constraints. We describe a complete and minimal axiomatization of the class of aggregation constraints over finite multisets of reals, which permits a natural reduction from the class of aggregation constraints to the class of mixed integer/real, non-linear arithmetic constraints. We then present a polynomial-time algorithm that directly checks for solvability of a useful class of aggregation constraints, where the reduction-based approach does not lead to efficient checks for solvability.
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.
9401708
Complex Aggregation at Multiple Granularities
Datacube queries compute simple aggregates at multiple granularities. In this paper we examine the more general and useful problem of computing a complex subquery involving multiple dependent aggregates at multiple granularities. We call such queries multi-feature cubes. An example is Broken down by all combinations of month and customer, find the fraction of the total sales in 1996 of a particular item due to suppliers supplying within 10% of the minimum price (within the group), showing all subtotals across each dimension. We classify multi-feature cubes based on the extent to which fine granularity results can be used to compute coarse granularity results; this classification includes distributive, algebraic and holistic multi-feature cubes. We provide syntactic sufficient conditions to determine when a multi-feature cube is either distributive or algebraic. This distinction is important because, as we show, existing datacube evaluation algorithms can be used to compute multi-feature cubes that are distributive or algebraic, without any increase in I/O complexity. We evaluate the CPU performance of computing multi-feature cubes using the datacube evaluation algorithm of Ross and Srivastava. Using a variety of synthetic, benchmark and real-world data sets, we demonstrate that the CPU cost of evaluating distributive multi-feature cubes is comparable to that of evaluating simple datacubes. We also show that a variety of holistic multi-feature cubes can be evaluated with a manageable overhead compared to the distributive case.
16656102
Groupwise Processing of Relational Queries
In this paper, we define and examine a particular class of queries called group queries. Group queries are natural queries in many decisionsupport applications. The main characteristic of a group query is that it can be executed in a groupby-group fashion. In other words, the underlying relation(s) can be partitioned (based on some set of attributes) into disjoint groups, and each group can be processed separately. We give a syntactic criterion to identify these queries and prove its sufficiency. We also prove the strong result that every group query has an equivalent formulation that satisfies our syntactic criterion. We describe a general evaluation technique for group queries, and demonstrate how an optimizer can determine this plan. We then consider more complex queries whose components are group queries with potentially different partitioning attributes. We give two methods to identify group query components within such a query. We also give some performance results for group queries expressed in standard SQL, comparing a commercial database system with our optimized plan on top of the same commercial system. These results indicate that there are significant potential performance improvements.
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.
986287
A probability collectives approach to weighted clustering algorithms for ad hoc networks
The Weighted Clustering Algorithm has been proposed for mobile ad hoc wireless networks to select a subset of the nodes to be local purveyors of media access control services to the rest of the nodes. The nodes selected are called clusterheads, and each clusterhead services the other nodes within its radio range. The underlying optimal assignment problem is NP-hard. We introduce a new metaheuristic known as probability collectives to the problem of assigning clusterheads. This is an agent-based approach, with each node in the network acting in a quasi-autonomous way. This new approach shows improved clustering results, particularly with regard to the distribution and balance of cluster sizes.
8164608
Unified framework for optimal video streaming
We study the problem of how to stream layered video (live and stored) over a lossy packet network in order to optimize the video quality that is rendered at the receiver. We present a unified framework that combines scheduling, FEC error protection, and decoder error concealment. In the context of the unified framework, we study both the case of a channel with perfect state information and the case of a channel with imperfect state information (delayed or lost feedback). We adapt the theory of infinite-horizon, average-reward Markov decision processes (MDPs) with average-cost constraints to the problem. Based on simulations with MPEG-4 FGS video, we show that (1) optimizing together scheduling, FEC error correction and error concealment improves performance significantly and (2) policies with static error protection give near-optimal performance. We also find that degradations in quality for a channel with imperfect state information are small; thus our MDP approach is suitable for networks with long end-to-end delays
8942941
Improving the WWW: Caching or Multicast?
Abstract We consider two schemes for the distribution of popular Web documents. In the first scheme the sender repeatedly transmits the Web document into a multicast address, and receivers asynchronously join the corresponding multicast tree to receive a copy. In the second scheme, the document is distributed to the receivers through a hierarchy of Web caches. We develop analytical models for both schemes, and use the models to compare the two schemes in terms of latency and bandwidth usage. We find that except for documents that change very frequently, hierarchical caching gives lower latency and uses less bandwidth than multicast. For rapidly changing documents, multicast distribution reduces latency, saves network bandwidth, and reduces the load on the origin server. Furthermore, if a document is updated randomly rather than periodically, the relative performance of CMP improves. Therefore, the best overall performance is achieved when the Internet implements both solutions, hierarchical caching and multicast.
5328792
Interactive video streaming with proxy servers
We study caching strategies for proxies that cache VBR-encoded continuous media objects for highly interactive streaming applications. First, we develop a model for streaming VBR-encoded continuous media objects. This model forms the basis for a stream admission control criterion and our study of caching strategies. We find that unlike conventional web caches, proxy caches for continuous media objects need to replicate or stripe objects to achieve high hit rates. We develop novel caching strategies that either implicitly or explicitly track the request pattern and cache (and replicate) objects accordingly. Our numerical results indicate that our caching strategies achieve significantly higher hit rates than caching without object replication.
14659770
Guaranteeing statistical QoS to regulated traffic: the single node case
Multimedia traffic can typically tolerate some loss but has rigid delay constraints. A natural QoS requirement for a multimedia connection is a prescribed bound on the the fraction of traffic that exceeds an end-to-end delay limit. We propose and analyze a traffic management scheme which guarantees QoS to multimedia traffic while simultaneously allowing for a large connection-carrying capacity. We study our traffic management scheme in the context of a single node. In order for the node to guarantee QoS, each connection's traffic is regulated. In order to support many connections, the link statistically multiplexes the connections' traffic. The scheme consists of (i) cascaded leaky-buckets for traffic regulation, (ii) smoothers at the ingresses, and (iii) bufferless statistical multiplexing within the node. For this scheme we show that loss probabilities are minimized with simple one-buffer smoothers which operate at specific minimum rates. We also show that the worst-case input traffic is extremal on-off traffic for all connections. These two results lead to a straightforward scheme for guaranteeing QoS to regulated traffic. Using MPEG video traces, we present numerical results which demonstrate the methodology. Finally, we compare the bufferless scheme with buffered statistical multiplexing.