11741717
Cost-based unbalanced R-trees
Cost-based unbalanced R-trees (CUR-trees) are a cost-function-based data structure for spatial data. CUR-trees are constructed specifically to improve the evaluation of intersection queries, the most basic selection query in an R-tree. A CUR-tree is built taking into account a given query distribution for the queries and a cost model for their execution. Depending on the expected frequency of access, objects or subtrees are stored higher up in the tree. After each insertion in the tree, local reorganizations of a node and its children have their expected query cost evaluated, and a reorganization is performed if this is beneficial. No strict balancing of the trees applies, allowing the tree to unfold solely based on the result of the cost evaluation. We present our cost-based approach and describe the evaluation and reorganization operations based on the cost function. We present a cost model for in-memory access costs and we present three different query models. In our experiments, we compare the performance of the CUR-tree to the R-tree and the R*-tree. The CUR-tree is able to significantly improve intersection query performance, without unacceptably increasing the cost of building the tree. The use of R-trees for in-memory data reflects the high (and growing) cost of bringing data from RAM into the CPU cache relative to the cost of other computations.
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.
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.
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.
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.
15587034
Packet Scheduling Across Networks of Switches
Recent developments in computer and communication networks require scheduling decisions to be made under increasingly complex system dynamics. We model and analyze the problem of packet transmissions through an arbitrary network of buffered queues, and provide a framework for describing routing and migration. This paper introduces an intuitive geometric description of stability for these networks and describes some simple algorithms which lead to maximal throughput. We show how coordination over sequential timeslots by algorithms such as those based on a round robin can provide considerable advantages over a randomized scheme.
6259994
Hierarchical Peer-To-Peer Systems
Structured peer-to-peer (P2P) lookup services organize peers into a flat overlay network and offer distributed hash table (DHT) functionality. Data is associated with keys and each peer is responsible for a subset of the keys. In hierarchical DHTs, peers are organized into groups, and each group has its autonomous intra-group overlay network and lookup service. Groups are organized in a top-level overlay network. To find a peer that is responsible for a key, the top-level overlay first determines the group responsible for the key; the responsible group then uses its intra-group overlay to determine the specific peer that is responsible for the key. We provide a general framework for hierarchical DHTs with scalable overlay management. We specifically study a two-tier hierarchy that uses Chord for the top level. Our analysis shows that by using the most reliable peers in the top level, the hierarchical design significantly reduces the expected number of hops. We also present a method to construct hierarchical DHTs that map well to the Internet topology and achieve short intra-group communication delay. The results demonstrate the feasibility of locality-based peer groups, which allow P2P systems to take full advantage of the hierarchical design.
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.
7149127
Optimal multiplexing of heterogeneous traffic with hard constraint
Considered are optimal dynamic policies for multiplexing &Kgr; + 1 heterogeneous traffic types onto a single communication channel. The packet types arrive to the channel according to independent Poisson processes. The service requirements are exponential with type dependent means. The optimization criterion is to minimize a linear combination of the average delays for packet types 1 to &Kgr;, while simultaneously subjecting the average delay of type-0 packets to a hard constraint. The optimal multiplexing policy is shown to be a randomized modification of the “μc rule”. The optimization problem is thereby reduced to a problem of finding the optimal randomization factor; an algorithm, which can be implemented in real time, is given to do this for two particular cases.
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.