7132341
HASE: A Hybrid Approach to Selectivity Estimation for Conjunctive Predicates
Current methods for selectivity estimation fall into two broad categories, synopsis-based and sampling-based. Synopsis-based methods, such as histograms, incur minimal overhead at query optimization time and thus are widely used in commercial database systems. Sampling-based methods are more suited for ad-hoc queries, but often involve high I/O cost because of random access to the underlying data. Though both methods serve the same purpose of selectivity estimation, their interaction in the case of selectivity estimation for conjuncts of predicates on multiple attributes is largely unexplored. Our work aims at taking the best of both worlds, by making consistent use of synopses and sample information when they are both present. To achieve this goal, we propose HASE, a novel estimation scheme based on a powerful mechanism called generalized raking. We formalize selectivity estimation in the presence of single attribute synopses and sample information as a constrained optimization problem. By solving this problem, we obtain a new set of weights associated with the sampled tuples, which has the nice property of reproducing the known selectivities when applied to individual predicates. We discuss different variants of the optimization problem and provide algorithms for solving it. We also provide asymptotic error bounds on the estimate. Extensive experiments are performed on both synthetic and real data, and the results show that HASE significantly outperforms both synopsis-based and sampling-based methods.
13475547
Towards estimating the number of distinct value combinations for a set of attributes
Accurately and efficiently estimating the number of distinct values for some attribute(s) or sets of attributes in a data set is of critical importance to many database operations, such as query optimization and approximation query answering. Previous work has focused on the estimation of the number of distinct values for a single attribute and most existing work adopts a data sampling approach. This paper addresses the equally important issue of estimating the number of distinct value combinations for multiple attributes which we call COLSCARD (for COLumn Set CARDinality). It also takes a different approach that uses existing statistical information (e.g., histograms) available on the individual attributes to assist estimation. We start with cases where exact frequency information on individual attributes is available, and present a pair of lower and upper bounds on COLSCARD that are consistent with the available information, as well as an estimator of COLSCARD based on probability. We then proceed to study the case where only partial information (in the form of histograms) is available on individual attributes, and show how the proposed estimator can be adapted to this case. We consider two types of widely used histograms and show how they can be constructed in order to obtain optimal approximation. An experimental evaluation of the proposed estimation method on synthetic as well as two real data sets is provided.
1886676
Monitoring k-nearest neighbor queries over moving objects
Many location-based applications require constant monitoring of k-nearest neighbor (k-NN) queries over moving objects within a geographic area. Existing approaches to this problem have focused on predictive queries, and relied on the assumption that the trajectories of the objects are fully predictable at query processing time. We relax this assumption, and propose two efficient and scalable algorithms using grid indices. One is based on indexing objects, and the other on queries. For each approach, a cost model is developed, and a detailed analysis along with the respective applicability is presented. The object-indexing approach is further extended to multi-levels to handle skewed data. We show by experiments that our grid-based algorithms significantly outperform R-tree-based solutions. Extensive experiments are also carried out to study the properties and evaluate the performance of the proposed approaches under a variety of settings.
16363205
Approximating Longest Cycles in Graphs with Bounded Degrees
Jackson and Wormald conjecture that if $G$ is a 3-connected $n$-vertex graph with maximum degree $d\ge 4$, then $G$ has a cycle of length $\Omega(n^{\log_{d-1}2})$. We show that this conjecture holds when $d-1$ is replaced by $\max\{64,4d+1\}$. Our proof implies a cubic algorithm for finding such a cycle.
16035202
An efficient transistor optimizer for custom circuits
We present an equation-based transistor size optimizer that minimizes delay of custom circuits. Our method uses static timing analysis to find the critical paths and numerical methods to optimize transistor sizes continuously without using simulation. Consequently, it is faster than simulation-based optimizers, and more general than standard cell optimizers. We demonstrate its efficacy and accuracy on a complete dynamic adder presented, where we achieve a 54% speed-up, and final critical path delay that match Spice within 1%.
11486473
Circumference of Graphs with Bounded Degree
Karger, Motwani, and Ramkumar Algorithmica, 18 (1997), pp. 82--98] have shown that there is no constant approximation algorithm to find a longest cycle in a Hamiltonian graph, and they conjectured that this is the case even for graphs with bounded degree. On the other hand, Feder, Motwani, and Subi [SIAM J. Comput., 31 (2002), pp. 1596--1607] have shown that there is a polynomial time algorithm for finding a cycle of length $n^{\log_32}$ in a 3-connected cubic n-vertex graph. In this paper, we show that if G is a 3-connected n-vertex graph with maximum degree at most d, then one can find, in O(n3) time, a cycle in G of length at least $\Omega(n^{\log_b2})$, where $b=2(d-1)^2+1$.
8993397
A Novel Hybrid Crypto-Biometric Authentication Scheme for ATM Based Banking Applications
This paper studies the smartcard based fingerprint encrytion/auth-entication scheme for ATM banking systems. In this scheme, the system authenticates each user by both his/her possession (smartcard) and biometrics (fingerprint). A smartcard is used for the first layer of authentication. Based on the successful pass of the first layer authentication, a subsequent process of the biometric fingerprint authentication proceeds. The proposed scheme is fast and secure. Computer simulations and statistical analyze are presented.
8830976
A distributed adaptive cache update algorithm for the dynamic source routing protocol
On-demand routing protocols use route caches to make routing decisions. Due to mobility, cached routes easily become stale. To address the cache staleness issue, prior work in DSR used heuristics with ad hoc parameters to predict the lifetime of a link or a route. However, heuristics cannot accurately predict timeouts because topology changes are unpredictable. In this paper, we propose to proactively disseminate the broken link information to the nodes that have that link in their caches. We define a new cache structure called a cache table and present a distributed cache update algorithm. Each node maintains in its cache table the information necessary for cache updates. When a link failure is detected, the algorithm notifies all reachable nodes that have cached the link in a distributed manner. The algorithm does not use any ad hoc parameters, thus making route caches fully adaptive to topology changes. We show that the algorithm outperforms DSR with path caches and with Link-MaxLife, an adaptive timeout mechanism for link caches. We conclude that proactive cache updating is the key to the adaptation of on-demand routing protocols to mobility.