1671028
A key management scheme for wireless sensor networks using deployment knowledge
To achieve security in wireless sensor networks, it is important to he able to encrypt messages sent among sensor nodes. Keys for encryption purposes must he agreed upon by communicating nodes. Due to resource constraints, achieving such key agreement in wireless sensor networks is nontrivial. Many key agreement schemes used in general networks, such as Diffie-Hellman and public-key based schemes, are not suitable for wireless sensor networks. Pre-distribution of secret keys for all pairs of nodes is not viable due to the large amount of memory used when the network size is large. Recently, a random key pre-distribution scheme and its improvements have been proposed. A common assumption made by these random key pre-distribution schemes is that no deployment knowledge is available. Noticing that in many practical scenarios, certain deployment knowledge may be available a priori, we propose a novel random key pre-distribution scheme that exploits deployment knowledge and avoids unnecessary key assignments. We show that the performance (including connectivity, memory usage, and network resilience against node capture) of sensor networks can he substantially improved with the use of our proposed scheme. The scheme and its detailed performance evaluation are presented in this paper.
10463694
Balanced-energy sleep scheduling scheme for high density cluster-based sensor networks
In order to conserve battery power in very dense sensor networks, some sensor nodes may be put into the sleep state while other sensor nodes remain active for the sensing and communication tasks. However, determining which of the sensor nodes should be put into the sleep state is non-trivial. As the goal of allowing nodes to sleep is to extend network lifetime, we propose and analyze a Balanced-energy Scheduling (BS) scheme in the context of cluster-based sensor networks. The BS scheme aims to evenly distribute the energy load of the sensing and communication tasks among all the nodes in the cluster, thereby extending the time until the cluster can no longer provide adequate sensing coverage. Two related sleep scheduling schemes, the Distance-based Scheduling (DS) scheme and the Randomized Scheduling (RS) scheme are also studied in terms of the coefficient of variation of their energy consumption. Analytical and simulation results are presented to evaluate the proposed BS scheme. It is shown that the BS scheme extends the cluster's overall network lifetime significantly while maintaining a similar sensing coverage compared with the DS and the RS schemes for sensor clusters.
661428
Scheduling Sleeping Nodes in High Density Cluster-based Sensor Networks
In order to conserve battery power in very dense sensor networks, some sensor nodes may be put into the sleep state while other sensor nodes remain active for the sensing and communication tasks. In this paper, we study the node sleep scheduling problem in the context of clustered sensor networks. We propose and analyze the Linear Distance-based Scheduling (LDS) technique for sleeping in each cluster. The LDS scheme selects a sensor node to sleep with higher probability when it is farther away from the cluster head. We analyze the energy consumption, the sensing coverage property, and the network lifetime of the proposed LDS scheme. The performance of the LDS scheme is compared with that of the conventional Randomized Scheduling (RS) scheme. It is shown that the LDS scheme yields more energy savings while maintaining a similar sensing coverage as the RS scheme for sensor clusters. Therefore, the LDS scheme results in a longer network lifetime than the RS scheme.
16511980
On the Design of Soft-Decision Fusion Rule for Coding Approach in Wireless Sensor Networks
In this work, two soft-decision fusion rules, which are respectively named the maximum a priori (MAP) and the suboptimal minimum Euclidean distance (MED) fusion rules, are designed based on a given employed sensor code and associated local classification. Their performance comparison with the distributed classification fusion using soft-decision decoding (DCSD) proposed in an earlier work is also performed. Simulations show that when the number of faulty sensors is small, the MAP fusion rule remains the best at either low sensor observation signal-to-noise ratios (OSNRs) or low communication channel signal-to-noise ratios (CSNRs), and yet, the DCSD fusion rule gives the best performance at middle to high OSNRs and high CSNRs. However, when the number of faulty sensor nodes grows large, the least complex MED fusion rule outperforms the MAP fusion rule at high OSNRs and high CSNRs.
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.
69690
New Encoding/Decoding Methods for Designing Fault-Tolerant Matrix Operations
Algorithm-based fault tolerance (ABFT) can provide a low-cost error protection for array processors and multiprocessor systems. Several ABFT techniques (weighted check-sum) have been proposed to design fault-tolerant matrix operations. In these schemes, encoding/decoding uses either multiplications or divisions so that overhead is high. In this paper, new encoding/decoding methods are proposed for designing fault-tolerant matrix operations. The unique feature of these new methods is that only additions and subtractions are used in encoding/decoding. In this paper, new algorithms are proposed to construct error detecting/correcting codes with the minimum Hamming distance 3 and 4. We will show that the overhead introduced due to the incorporation of fault tolerance is drastically reduced by using these new coding schemes.
27623648
Twinned principal curves
Principal Curves are extensions of Principal Component Analysis and are smooth curves, which pass through the middle of a data set. We extend the method so that, on pairs of data sets which have underlying non-linear correlations, we have pairs of curves which go through the 'centre' of data sets in such a way that the non-linear correlations between the data sets are captured. The core of the method is to iteratively average the current local projections of the data points which produces an increasingly sparsified set of nodes. The Twinned Principal Curves are generated in three ways: by joining up the nodes in order, by performing Local Canonical Correlation Analysis and by performing Local Exploratory Correlation Analysis (Koetsier et al., 2002). The latter two are shown to improve the forecasting capability of the method but at an increased computational load. We show that it is crucial to terminate the algorithm after a small number of iterations for the first method and investigate several criteria for doing so.
18478207
Prefix-Free Regular-Expression Matching
We explore the regular-expression matching problem with respect to prefix-freeness of the pattern. We show that the prefix-free regular expression gives only linear number of matching substrings in the size of a given text. Based on this observation, we propose an efficient algorithm for the prefix-free regular-expression matching problem. Furthermore, we suggest an algorithm to determine whether or not a given regular language is prefix-free.
38202538
Infix-free Regular Expressions and Languages
We study infix-free regular languages. We observe the structural properties of finite-state automata for infix-free languages and develop a polynomial-time algorithm to determine infix-freeness of ...
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.
14156578
Shorter Regular Expressions from Finite-State Automata
We consider the use of state elimination to construct shorter regular expressions from finite-state automata. Although state elimination is an intuitive method for computing regular expressions from finite-state automata, the resulting regular expressions are often very long and complicated. We examine the minimization of finite-state automata to obtain shorter expressions first. Then, we introduce vertical chopping based on bridge states and horizontal chopping based on the structural properties of given finite-state automata. 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 lead to shorter regular expressions based on vertical chopping and horizontal chopping. 
 
Note that we have omitted almost all proofs in this preliminary version.