16559893
A Syntactic Stratification Condition Using Constraints
Stratiication conditions for logic programs aim to ensure a two-valued semantics by restricting the class of allowable programs. Previous stratiication conditions suuer from one of two problems. Some (such as modular stratiication and weak stratiication) are semantic, and cannot be recognized without examining the facts in addition to the rules of the program. Others (such as stratiication and local stratii-cation) are syntactic, but do not allow a number of useful examples. A nonsemantic version of modular stratiication, i.e., whether a program is modularly stratiied for all extensional databases, is shown to be undecidable. We propose a condition that generalizes local stratiication, that ensures a two-valued well-founded model, and that can be syntactically determined from the rules and some constraints on the facts in the program. We call this condition \Universal Constraint Stratiication." While not every modularly stratiied program is universally constraint stratiied, all of the well-known practical examples of modularly stratiied programs are universally constraint stratiied under appropriate natural constraints. In addition, there exist universally constraint stratiied programs that are not modularly stratiied.
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.
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.
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.
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.
10455339
Pollution in P2P file sharing systems
One way to combat P2P file sharing of copyrighted content is to deposit into the file sharing systems large volumes of polluted files. Without taking sides in the file sharing debate, in this paper we undertake a measurement study of the nature and magnitude of pollution in the FastTrack P2P network, currently the most popular P2P file sharing system. We develop a crawling platform which crawls the majority of the FastTrack Network's 20,000+ supernodes in less than 60 minutes. From the raw data gathered by the crawler for popular audio content, we obtain statistics on the number of unique versions and copies available in a 24-hour period. We develop an automated procedure to detect whether a given version is polluted or not, and we show that the probabilities of false positives and negatives of the detection procedure are very small. We use the data from the crawler and our pollution detection algorithm to determine the fraction of versions and fraction of copies that are polluted for several recent and old songs. We observe that pollution is pervasive for recent popular songs. We also identify and describe a number of anti-pollution mechanisms.
8733679
Stochastic Fluid Theory for P2P Streaming Systems
We develop a simple stochastic fluid model that seeks to expose the fundamental characteristics and limitations of P2P streaming systems. This model accounts for many of the essential features of a P2P streaming system, including the peers' realtime demand for content, peer churn (peers joining and leaving), peers with heterogeneous upload capacity, limited infrastructure capacity, and peer buffering and playback delay. The model is tractable, providing closed-form expressions which can be used to shed insight on the fundamental behavior of P2P streaming systems. The model shows that performance is largely determined by a critical value. When the system is of moderate-to-large size, if a certain ratio of traffic loads exceeds the critical value, the system performs well; otherwise, the system performs poorly. Furthermore, large systems have better performance than small systems since they are more resilient to bandwidth fluctuations caused by peer churn. Finally, buffering can dramatically improve performance in the critical region, for both small and large systems. In particular, buffering can bring more improvement than can additional infrastructure bandwidth.
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.
19447750
Local search scheduling algorithms for maximal throughput in packet switches
We consider the (generalized) packet switch scheduling problem, where the switch service configuration has to be dynamically chosen based on observed queue backlogs, so as to maximize the throughput. A class of recently developed 'projective' scheduling algorithms, which substantially generalize the well-known maximum weight matching (MWM) algorithms for crossbar switches, are explored from the perspective of complexity. The typically huge number of possible switch configurations that the scheduler has to consider in each timeslot has been previously observed to lead to an impractical computational requirement. We introduce a new class of projective schedules based on 'local search' concepts. In particular, rather than searching the entire (typically huge) set of available service configurations to find the best one, the new scalable scheduling algorithms search 'locally' over a small neighborhood of service configurations to find a 'better' one in each time slot. We show that local projective scheduling algorithms can provide dramatic reduction in complexity without causing any loss of throughput (although they may observe higher delay). We explore the nature and structure of such schedules, which show a much higher promise for practical implementation than their global versions.
16090619
Optimal load balancing and scheduling in a distributed computer system
A broadcast communication network that interconnects multiple hosts N considered. A job generated by a host is either generic, m which case It can be processed at any of the hosts in the network, or dedicated, m which case it must be processed at the host from which it originates. It is assumed that each host can generate several types of dedicated jobs, where each type imposes a constraint on its average response time. The optimal design objective is twofold: First, to redistribute the generic jobs among the host computers in order to minimize the average response time, which shall be referred to as the load-balancing problem; second, for each host computer, to design a control that schedules the dedicated and the generic Jobs so that the response-time constraints are met for each of the dedicated traffic types. Despite its complexity, the model described above has some attractive features. Specifically, for a given allocation of the generic traffic, the scheduhng problem at each host can be solved as a polymatroid optimization problem. The underlying polymatroid structure leads to an efficient algorithm to determine, as a function of the offered load of generic traffic, the average delay of the generic jobs at any given host. Further analysis reveals that the delay functions at each of the hosts are convex and increasing. Therefore, an allocation algorlthm can be employed to solve the system-level load-balancing problem. An example is provided mdlcating that a substantial improvement m performance can be obtained by incorporating scheduling into the load-balancing procedure.