The concept of M-convex functions has recently been generalized for functions defined on constant-parity jump systems. The b-matching problem and its generalization provide canonical examples of M-convex functions on jump systems. In this paper, we propose a steepest descent algorithm for minimizing an M-convex function on a constant-parity jump system.

In this work we present an energy efficient leader election protocol for anonymous radio network populated with n mobile stations. Previously, Nakano and Olariu have presented a leader election protocol that terminates, with probability exceeding 1- (f ≥ 1), in log log n+o(log log n)+O(log f) time slots [14]. As the above protocol works under the assumption that every station has the ability to transmit and monitor the channel at the same time, it requires every station to be equipped with two transceivers. This assumption, however, is unrealistic for most mobile stations due to constraints in cost, size, and energy dissipation. Our main contribution is to show that it is possible to elect a leader in an anonymous radio network where each station is equipped with a single transceiver. Quite surprisingly, although every station has only one transceiver, our leader election protocol still runs, with probability exceeding 1- (f ≥ 1), in log log n+o(log log n)+O(log f) time slots. Moreover, our leader election protocol needs only expected O(n) total awake time slots, while Nakano and Olariu's protocol needs expected O(nlog log n) total awake time slots. Since every leader election protocol needs at least Ω(n) awake time slots, our leader election protocol is optimal in terms of the expected awake time slots.

The medium access control (MAC) protocol is the main determiner of the system throughput in Wireless Local Area Networks (WLANs). The MAC technique of the IEEE 802.11 protocol is called Distributed Coordination Function (DCF). DCF is based on a carrier sense multiple access with collision avoidance (CSMA/CA) scheme with binary slotted exponential backoff. Each station generates a random backoff interval before transmitting a packet to minimize the probability of collision with packets being transmitted by other stations. However, when the number of stations increases, the system throughput decreases. This paper proposes a new backoff algorithm that uses finish tags. The proposed algorithm uses the finish tag of each station to control the backoff intervals so as to improve system throughput. The finish tag is updated when a packet reaches the front of its flow, and it is attached to the packet just prior to transmission. When a station receives packets with older finish tags, its backoff time interval is increased. For this reason, the more the stations there are, the larger the backoff time becomes. Simulations confirm that the proposal improves system throughput of a IEEE 802.11 network under saturation conditions.

Suppose that we have a timetable of a round-robin tournament with a number of teams, and distances among their homes. The home-away assignment problem is to find a home-away assignment that minimizes the total traveling distance of the teams. We propose a formulation of the home-away assignment problem as an integer program, and a rounding algorithm based on Bertsimas, Teo and Vohra's dependent randomized rounding method [2]. Computational experiments show that our method quickly generates feasible solutions close to optimal.

In this paper, we will report practical modifications of the side-channel analysis to (EC)DSA [1],[2],[5],[34] that Leadbitter et al. have proposed in [16]. To apply the analyses, we assume that the window method is used in the exponentiation or elliptic curve (EC) scalar multiplication and the side-channel information described in Sect. 3.2 can be collected. So far, the method in [16] hasn't been effective when the size q of a cyclic group used in (EC)DSA is 160 bit long and the window size w < 9. We show that the modified method we propose in this paper is effective even when q is 160 bit long and w=4. This shows that our method is effective for various practical implementations, e.g., that in resource restricted environment like IC card devises. First, we estimate the window size w necessary for the proposed analyses (attacks) to succeed. Then by experiment of the new method, we show that private keys of (EC)DSA can be obtained under the above assumptions, in practical time and with sufficient success rate. The result raises the necessity of countermeasures against the analyses (attacks) in the window method based implementation of (EC)DSA.

A naive coding of floorplans needs 2m bits for each floorplan. In this paper we give a new simple coding of floorplans, which needs only 5m/3 bits for each floorplan.

An improved genetic algorithm for solving the graph planarization problem is presented. The improved genetic algorithm which is designed to embed a graph on a plane, performs crossover and mutation conditionally instead of probability. The improved genetic algorithm is verified by a large number of simulation runs and compared with other algorithms. The experimental results show that the improved genetic algorithm performs remarkably well and outperforms its competitors.

Maurer and Yacobi proposed an ID-Based key distribution scheme in 1991. In this scheme, the private key for each user is generated by solving discrete logarithm problem. We examine the realizability of this scheme. We show that this scheme can be practical by appropriate parameter setting.

The aim of this research is the efficient cryptanalysis of the Shrinking Generator through its characterization by means of Linear Hybrid Cellular Automata. This paper describes a new known-plaintext attack based on the computation of the characteristic polynomials of sub-automata and on the generation of the Galois field associated to one of the Linear Feedback Shift Registers components of the generator. The proposed algorithm allows predicting with absolute certainty, many unseen bits of the keystream sequence, thanks to the knowledge of both registers lengths, the characteristic polynomial of one of the registers, and the interception of a variable number of keystream bits.

Let H be a graph with a designated vertex s, where edges are weighted by nonnegative reals. Splitting edges e={u,s} and e'={s,v} at s is an operation that reduces the weight of each of e and e' by a real δ>0 while increasing the weight of edge {u,v} by δ. It is known that all edges incident to s can be split off while preserving the edge-connectivity of H and that such a complete splitting is used to solve many connectivity problems. In this paper, we give an O(mn+n2log n) time algorithm for finding a complete splitting in a graph with n vertices and m edges.

Given a graph G=(V,E), a set of vertices S ⊆ V covers v ∈ V if the edge connectivity between S and v is at least a given number k. Vertices in S are called sources. The source location problem is a problem of finding a minimum-size source set covering all vertices of a given graph. This paper presents a new variation of the problem, called maximum-cover source-location problem, which finds a source set S with a given size p, maximizing the sum of the weight of vertices covered by S. It presents an O(np + m + nlog n)-time algorithm for k=2, where n=|V| and m=|E|. Especially it runs linear time if G is connected. This algorithm uses a subroutine for finding a subtree with the maximum weight among p-leaf trees of a given vertex-weighted tree. For the problem we give a greedy-based linear-time algorithm, which is an extension of the linear-time algorithm for finding a longest path of a given tree presented by E. W. Dijkstra around 1960. Moreover, we show some polynomial solvable cases, e.g., a given graph is a tree or (k-1)-edge-connected, and NP-hard cases, e.g., a vertex-cost function is given or G is a digraph.

In this letter, a new addressing scheme for hexagonal networks is proposed. Using the new addressing scheme, many routing algorithms designed for networks using square-based topologies such as mesh and torus can also be applied to hexagonal networks. Methods of applying the turn model to hexagonal networks are derived, with some new minimal and partial adaptive routing algorithms obtained. Simulations of the new routing algorithms under different working conditions are carried on hexagonal networks of various sizes. The results show that the proposed algorithms can offer lower packet delay and loss rate than the popular dimension order routing algorithm.

We propose transformation of a parity-check matrix of any low-density parity-check code. A code with transformed parity-check matrix is an equivalent of a code with the original parity-check matrix. For the binary erasure channel, performance of a message-passing algorithm with a transformed parity-check matrix is better than that with the original matrix.

We consider the classification problem to construct a classifier c:{0,1}n{0,1} from a given set of examples (training set), which (approximately) realizes the hidden oracle y:{0,1}n{0,1} describing the phenomenon under consideration. For this problem, a number of approaches are already known in computational learning theory; e.g., decision trees, support vector machines (SVM), and iteratively composed features (ICF). The last one, ICF, was proposed in our previous work (Haraguchi et al., (2004)). A feature, composed of a nonempty subset S of other features (including the original data attributes), is a Boolean function fS:{0,1}S{0,1} and is constructed according to the proposed rule. The ICF algorithm iterates generation and selection processes of features, and finally adopts one of the generated features as the classifier, where the generation process may be considered as embodying the idea of boosting, since new features are generated from the available features. In this paper, we generalize a feature to an extended Boolean function fS:{0,1,*}S{0,1,*} to allow partial knowledge, where * denotes the state of uncertainty. We then propose the algorithm ICF* to generate such generalized features. The selection process of ICF* is also different from that of ICF, in that features are selected so as to cover the entire training set. Our computational experiments indicate that ICF* is better than ICF in terms of both classification performance and computation time. Also, it is competitive with other representative learning algorithms such as decision trees and SVM.

In this paper, a 2-D iteratively reweighted least squares lattice algorithm, which is robust to the outliers, is introduced and is applied to defect detection problem in textured images. First, the philosophy of using different optimization functions that results in weighted least squares solution in the theory of 1-D robust regression is extended to 2-D. Then a new algorithm is derived which combines 2-D robust regression concepts with the 2-D recursive least squares lattice algorithm. With this approach, whatever the probability distribution of the prediction error may be, small weights are assigned to the outliers so that the least squares algorithm will be less sensitive to the outliers. Implementation of the proposed iteratively reweighted least squares lattice algorithm to the problem of defect detection in textured images is then considered. The performance evaluation, in terms of defect detection rate, demonstrates the importance of the proposed algorithm in reducing the effect of the outliers that generally correspond to false alarms in classification of textures as defective or nondefective.

Recently, various decoding algorithms with Low Density Parity Check (LDPC) codes have been proposed. Most algorithms can be divided into a hard decision algorithm and a soft decision algorithm. The Weighted Bit Flipping (WBF) algorithm that is between a hard decision and a soft decision algorithms has been proposed. The Bootstrapped WBF and Modified WBF algorithms have been proposed to improve the error rate performance and decoding complexity of the WBF algorithm. In this letter, we apply the Bootstrap step to the Modified WBF algorithm. We show that the Bootstrapped modified WBF algorithm outperforms the WBF, Bootstrapped WBF, and Modified WBF algorithms. Moreover, we show that the Bootstrapped modified WBF algorithm has the lowest decoding complexity.

Genetic Algorithm (GA) and other Evolutionary Algorithms (EAs) have been successfully applied to solve constrained minimum spanning tree (MST) problems of the communication network design and also have been used extensively in a wide variety of communication network design problems. Choosing an appropriate representation of candidate solutions to the problem is the essential issue for applying GAs to solve real world network design problems, since the encoding and the interaction of the encoding with the crossover and mutation operators have strongly influence on the success of GAs. In this paper, we investigate a new encoding crossover and mutation operators on the performance of GAs to design of minimum spanning tree problem. Based on the performance analysis of these encoding methods in GAs, we improve predecessor-based encoding, in which initialization depends on an underlying random spanning-tree algorithm. The proposed crossover and mutation operators offer locality, heritability, and computational efficiency. We compare with the approach to others that encode candidate spanning trees via the Pr?fer number-based encoding, edge set-based encoding, and demonstrate better results on larger instances for the communication spanning tree design problems.

Let G = (D ∪ S,E) be an undirected graph with a vertex set D ∪ S and an (undirected) edge set E, where the vertex set is partitioned into two subsets, a demand vertex set D and a supply vertex set S. We assume that D ≠ and S ≠ in this paper. Each demand or supply vertex v has a positive real number d(v) or s(v), called the demand or supply of v, respectively. For any subset V' ⊆ D ∪ S, the demand of V' is defined by d(V') = Σv∈V'∩Dd(v) if V' ∩ D ≠ or d(V') = 0 if V' ∩ D = . Let s(S) = Σv∈S s(v). Any partition π = {V1,..., Vr} (|S| r |D ∪ S|) of D ∪ S is called a feasible partition of G if and only if π satisfies the following (1) and (2) for any k = 1,..., r: (1) |Vk ∩ S|1, and (2) if Vk ∩ S = {uk} then the induced subgraph G[Vk] of G is connected and d(Vk)s(uk). The demand d(π) of π is defined by d(π)=d(Vk). The "Maximum-Supply Partitioning Problem (MSPP)" is to find a feasible partition π of G such that d(π) is maximum among all feasible partitions of G. We implemented not only existing algorithms for obtainity heuristic or optimum solutions to MSPP but also those that are corrected or improved from existing ones. In this paper we show comparison of their capability based on computational experiments.

The k-edge-connectivity augmentation problem for a specified set of vertices of a graph with degree constraints, kECA-SV-DC, is defined as follows: "Given an undirected multigraph G = (V,E), a specified set of vertices S ⊆V and a function g: V → Z+ ∪{∞}, find a smallest set E' of edges such that (V,E ∪ E') has at least k edge-disjoint paths between any pair of vertices in S and such that, for any v ∈ V, E' includes at most g(v) edges incident to v, where Z+ is the set of nonnegative integers." This paper first shows polynomial time solvability of kECA-SV-DC and then gives a linear time algorithm for 2ECA-SV-DC.

In this paper, we propose a partially-parallel LDPC decoder which achieves a high-efficiency message-passing schedule. The proposed LDPC decoder is characterized as follows: (i) The column operations follow the row operations in a pipelined architecture to ensure that the row and column operations are performed concurrently. (ii) The proposed parallel pipelined bit functional unit enables the column operation module to compute every message in each bit node which is updated by the row operations. These column operations can be performed without extending the single iterative decoding delay when the row and column operations are performed concurrently. Therefore, the proposed decoder performs the column operations more frequently in a single iterative decoding, and achieves a high-efficiency message-passing schedule within the limited decoding delay time. Hardware implementation on an FPGA and simulation results show that the proposed partially-parallel LDPC decoder improves the decoding throughput and bit error performance with a small hardware overhead.