1251651
Obtaining shorter regular expressions from finite-state automata
We consider the use of state elimination to construct shorter regular expressions from finite-state automata (FAs). Although state elimination is an intuitive method for computing regular expressions from FAs, the resulting regular expressions are often very long and complicated. We examine the minimization of FAs to obtain shorter expressions first. Then, we introduce vertical chopping based on bridge states and horizontal chopping based on the structural properties of given FAs. We prove that we should not eliminate bridge states until we eliminate all non-bridge states to obtain shorter regular expressions. In addition, we suggest heuristics for state elimination that leads to shorter regular expressions based on vertical chopping and horizontal chopping.
10385992
A New Linearizing Restriction in the Pattern Matching Problem
In the pattern matching problem, there can be a quadratic number of matching substrings in the size of a given text. The linearizing restriction finds, at most, a linear number of matching substrings. We first explore two well-known linearizing restriction rules, the longest-match rule and the shortest-match substring searchrule, and show that both rules give the same result when a pattern is an infix-free set even though they have different semantics. Then, we introduce a new linearizing restriction, the leftmost non-overlapping match rule that is suitable for find-and-replace operations in text searching, and propose an efficient algorithm when the pattern is a regular language according to the new match rule.
8730288
On the existence of prime decompositions
We investigate factorizations of regular languages in terms of prime languages. A language is said to be strongly prime decomposable if any way of factorizing it yields a prime decomposition in a finite number of steps. We give a characterization of the strongly prime decomposable regular languages and using the characterization we show that every regular language over a unary alphabet has a prime decomposition. We show that there exist non-regular unary languages that do not have prime decompositions. We also consider infinite factorizations of unary languages.
18390270
Adaptive Retransmission for Distributed Detection in Wireless Sensor Networks
An approach combining distributed detection with error-correcting codes has recently been proposed to design a fault-tolerant classification system in wireless sensor networks. The detection result of each sensor must be transmitted to a fusion center for making a final decision. The mis-classification probability using this approach is high when the transmission channel is highly noisy. This work proposes a novel adaptive retransmission algorithm to improve the mis classification probability. The fusion center calculates reliability of each received detection result while making the final decision. When the final decision is not reliable, the sensor which has sent the received result with the lowest reliability will be asked to retransmit its detection result by the fusion center. Simulation results show that the misclassification probability can be effectively reduced through the retransmission
8807170
Power-efficient data fusion assurance using direct voting mechanism in wireless sensor networks
Wireless sensor networks place sensors into an area to collect data and send them back to a base station. Data fusion, which fuses the collected data before they are sent to the base station, is usually implemented over the network. Since the sensor is typically placed in locations accessible to malicious attackers, information assurance of the data fusion process is very important. A witness-based approach has been proposed to validate the fusion data. In this approach, the base station receives the fusion data and "votes" on the data from a randomly chosen sensor node. The vote comes from other sensor nodes, called as "witnesses," to verify the correctness of the fusion data. Because the base station obtains the vote through the chosen node, the chosen node could forge the vote if it is compromised. Thus, the witness node must encrypt the vote to prevent this forgery. Compared with the vote, the encryption requires more bits, increasing transmission burden from the chosen node to the base station. The chosen node consumes more power. This work improves the witness-based approach using direct voting mechanism. The witness node transmits the vote directly to the base station. Forgery is not a problem in this scheme. Moreover, fewer bits are necessary to represent the vote, significantly reducing the power consumption. Performance analysis and simulation results indicate that the proposed approach can achieve a 40 times better overhead than the witness-based approach
18991175
Performance Analysis and Code Design for Minimum Hamming Distance Fusion in Wireless Sensor Networks
Distributed classification fusion using error-correcting codes (DCFECC) has recently been proposed for wireless sensor networks operating in a harsh environment. It has been shown to have a considerably better capability against unexpected sensor faults than the optimal likelihood fusion. In this paper, we analyze the performance of a DCFECC code with minimum Hamming distance fusion. No assumption on identical distribution for local observations, as well as common marginal distribution for the additive noises of the wireless links, is made. In addition, sensors are allowed to employ their own local classification rules. Upper bounds on the probability of error that are valid for any finite number of sensors are derived based on large deviations technique. A necessary and sufficient condition under which the minimum Hamming distance fusion error vanishes as the number of sensors tends to infinity is also established. With the necessary and sufficient condition and the upper error bounds, the relation between the fault-tolerance capability of a DCFECC code and its pair-wise Hamming distances is characterized, and can be used together with any code search criterion in finding the code with the desired fault-tolerance capability. Based on the above results, we further propose a code search criterion of much less complexity than the minimum Hamming distance fusion error criterion adopted earlier by the authors. This makes the code construction with acceptable fault-tolerance capability for a network with over a hundred of sensors practical. Simulation results show that the code determined based on the new criterion of much less complexity performs almost identically to the best code that minimizes the minimum Hamming distance fusion error. Also simulated and discussed are the performance trends of the codes searched based on the new simpler criterion with respect to the network size and the number of hypotheses
46047704
A New Decoding Algorithm for Complete Decoding of Linear Block Codes
In this paper we present and describe an improved version of the Zero-Neighbors algorithm, which we call the Zero-Coverings algorithm. We also present a method for finding a smallest subset of codewords ( Zero-Coverings) which need to be stored to perform the Zero-Coverings algorithm. For some short codes, the sizes of Zero-Coverings are obtained by computer searches; for long codes, an asymptotic bound on the sizes of such subsets is also given.
2350989
Privacy-Preserving Multivariate Statistical Analysis: Linear Regression and Classification
Multivariate statistical analysis is an important data analysis technique that has found applications in various areas. In this paper, we study some multivariate statistical analysis methods in Secure 2-party Computation (S2C) framework illustrated by the following scenario: two parties, each having a secret data set, want to conduct the statistical analysis on their joint data, but neither party is willing to disclose its private data to the other party or any third party. The current statistical analysis techniques cannot be used directly to support this kind of computation because they require all parties to send the necessary data to a central place. In this paper, We define two Secure 2-party multivariate statistical analysis problems: Secure 2-party Multivariate Linear Regression problem and Secure 2-party Multivariate Classification problem. We have developed a practical security model, based on which we have developed a number of building blocks for solving these two problems.