In this paper, we study efficient scheduling algorithms that are suitable for ATM networks. In ATM networks, all packets have a fixed small length of 53 bytes and they are transmitted at very high rate. Thus time complexity of a scheduling algorithm is quite important. Most scheduling algorithms proposed so far have a complexity of O(log N) per packet, where N denotes the number of connections sharing the link. In contrast, weighted round robin (WRR) has the advantage of having O(1) complexity; however, it is known that its delay property gets worse as N increases. To solve this problem, in this paper we propose two new variants of WRR, uniform round robin (URR) and idling uniform round robin (I-URR). Both disciplines provide end-to-end delay and fairness bounds which are independent of N. Complexity of URR, however, slightly increases as N increases, while I-URR has complexity of O(1) per packet. I-URR also works as a traffic shaper, so that it can significantly alleviate congestion on the network. We also introduce a hierarchical WRR discipline (H-WRR) which consists of different WRR servers using I-URR as the root server. H-WRR efficiently accommodates both guaranteed and best-effort connections, while maintaining O(1) complexity per packet. If several connections are reserving the same bandwidth, H-WRR provides them with delay bounds that are close to those of weighted fair queueing.

In static multiprocessor scheduling, heuristic algorithms have been widely used. Instead of gaining execution speed, most of them show non promising solutions since they search only a part of solution spaces. In this paper, we propose a scheduling algorithm using the genetic algorithm (GA) which is a well-known stochastic search algorithm. The proposed algorithm, named ordered-deme GA (OGA), is based on the multiple subpopulation GA, where a global population is divided into several subpopulations (demes) and each demes evolves independently. To find better schedules, the OGA orders demes from the highest to the lowest deme and migrates both the best and the worst individuals at the same time. In addition, the OGA adaptively assigns different mutation probabilities to each deme to improve search capability. We compare the OGA with well-known heuristic algorithms and other GAs for random task graphs and the task graphs from real numerical problems. The results indicate that the OGA finds mostly better schedules than others although being slower in terms of execution time.

This paper presents a heuristic algorithm called CLASSIC for the minimization of the control memory width in microprogrammed processors or the instruction memory width of application-specific VLIW (Very Long Instruction Word) processors. CLASSIC results in nearly optimal solutions with the time complexity of O(n2), where n denotes the number of microoperations. In this paper, we also propose the so-called incompleteness relations which are exploited for the minimization of the control memory width. Experiments using various examples have shown that CLASSIC always achieves smaller microprogram widths compared to the earlier techniques based on the maximal compatibility class or the minimal AND/OR set. The results show that CLASSIC can reduce the control memory width by 34.2% on average compared with a heuristic compatibility class algorithm.

Asynchronous, distributed, decision-making (ADDM) systems constitute a special class of distributed problems and are characterized as large, complex systems wherein the principal elements are the geographically-dispersed entities that communicate among themselves, asynchronously, through message passing and are permitted autonomy in local decision-making. A fundamental property of ADDM systems is stability that refers to their behavior under representative perturbations to their operating environments, given that such systems are intended to be real, complex, and to some extent, mission critical systems, and are subject to unexpected changes in their operating conditions. ADDM systems are closely related to autonomous decentralized systems (ADS) in the principal elements, the difference being that the characteristics and boundaries of ADDM systems are defined rigorously. This paper introduces the concept of stability in ADDM systems and proposes an intuitive yet practical and usable definition that is inspired by those used in Control Systems and Physics. A comprehensive stability analysis on an accurate simulation model will provide the necessary assurance, with a high level of confidence, that the system will perform adequately. An ADDM system is defined as a stable system if it returns to a steady-state in finite time, following perturbation, provided that it is initiated in a steady-state. Equilibrium or steady-state is defined through placing bounds on the measured error in the system. Where the final steady-state is equivalent to the initial one, a system is referred to as strongly stable. If the final steady-state is potentially worse then the initial one, a system is deemed marginally stable. When a system fails to return to steady-state following the perturbation, it is unstable. The perturbations are classified as either changes in the input pattern or changes in one or more environmental characteristics of the system such as hardware failures. Thus, the key elements in the study of stability include steady-state, perturbations, and stability. Since the development of rigorous analytical models for most ADDM systems is difficult, if not impossible, the definitions of the key elements, proposed in this paper, constitute a general framework to investigate stability. For a given ADDM system, the definitions are based on the performance indices that must be judiciously identified by the system architect and are likely to be unique. While a comprehensive study of all possible perturbations is too complex and time consuming, this paper focuses on a key subset of perturbations that are important and are likely to occur with greater frequency. To facilitate the understanding of stability in representative real-world systems, this paper reports the analysis of two basic manifestations of ADDM systems that have been reported in the literature --(i) a decentralized military command and control problem, MFAD, and (ii) a novel distributed algorithm with soft reservation for efficient scheduling and congestion mitigation in railway networks, RYNSORD. Stability analysis of MFAD and RYNSORD yields key stable and unstable conditions.

We show how to apply the Feng-Rao decoding algorithm and the Feng-Rao bound for the Ω-construction of algebraic geometry codes to the L-construction. Then we give examples in which the L-construction gives better linear codes than the Ω-construction in certain range of parameters on the same curve.

With conventional dynamic routing algorithms, many query messages are required in a distributed environment for efficient multicast routing of any traffic volume. We have developed a dynamic routing algorithm that uses a predetermined path search in which an appropriate multicast path is dynamically constructed by searching only a few nodes. This algorithm can construct an efficient multicast tree for any traffic volume. Simulation has shown that the proposed algorithm is advantageous compared with conventional dynamic routing algorithms when nodes are added to or removed from the multicast group during steady-state simulation.

This paper proposes a new scheduling algorithm named TWFQ (Two-phased Weighted Fair Queueing) not only to maintain the fair utilization of available bandwidth but also to improve the performance of CDV and cell loss probability. The TWFQ algorithm makes use of the cell inter-arrival time of each connection for determining the cell service order among connections, which contributes to get a small CDV. To achieve low cell loss probability, the TWFQ allows connections, which suffer from the more bursty input traffic, to send the cell with more opportunities by using two scheduling phases. Through simulations, we show that the proposed algorithm achieves good performance in terms of CDV and cell loss probability, while other performance criteria are preserved in an acceptable level.

Investigations were carried out on metalorganic-chemical-vapor-deposition (MOCVD)-grown strained AlGaN/ GaN/sapphire structures using X-ray diffratometry. While AlGaN with lower AlN molar fraction (< 0.1) is under the in-plane compressive stress, it is under the in-plane tensile stress with high AlN molar fraction (> 0.1). Though tensile stress caused the cracks in AlGaN layer with high AlN molar fraction, we found that the cracks dramatically reduced when the GaN layer quality was not good. Using this technique, we fabricated a GaInN multi-quantum-well (MQW) surface emitting diodes were fabricated on 15 pairs of AlGaN/GaN distributed Bragg reflector (DBR) structures. The reflectivity of 15 pairs of AlGaN/GaN DBR structure has been shown as 75% at 435 nm. Considerably higher output power (1.5 times) has been observed for DBR based GaInN MQW LED when compared with non-DBR based MQW structures.

For a given graph G=(V, E), edge capacities c(e) for edges e E, and flow-demands d(v) for nodes v V, a problem of finding the minimum size source-set S V such that the maximum flow-amount between S and v is greater than or equal to d(v) for every v V is called generalized plural cover problem (GPC). For this problem, O(np s(n,m)) time algorithm is presented, where n, m, and p is the number of nodes, edges, and different values of d(v), respectively, and s(n,m) is the time required to solve the maximum flow problem of a graph with n nodes and m edges. This algorithm also constructs a set of optimal solutions in the same time. This property is convenient for applying it to real problems, because other constraints can also be taken into account.

The problem we consider in this paper is whether the Menezes-Okamoto-Vanstone (MOV) reduction for attacking elliptic curve cryptosystems can be realized for genera elliptic curves. In realizing the MOV reduction, the base field Fq is extended so that the reduction to the discrete logarithm problem in a finite field is possible. Recent results by Balasubramanian and Koblitz suggest that, if l q-1, such a minimum extension degree is the minimum k such that l|qk-1, which is equivalent to the condition under which the Frey-Ruck (FR) reduction can be applied, where l is the order of the group in the elliptic curve discrete logarithm problem. Our point is that the problem of finding an l-torsion point required in evaluating the Weil pairing should be considered as well from an algorithmic point of view. In this paper, we actually propose a method which leads to a solution of the problem. In addition, our contribution allows us to draw the conclusion that the MOV reduction is indeed as powerful as the FR reduction under l q-1 not only from the viewpoint of the minimum extension degrees but also from that of the effectiveness of algorithms.

We consider the problem of finding a minimum weight k-connected spanning subgraph of a given edge-weighted graph G for k=3. The problem is known to be NP-hard for k 2, and there are an O(n2m) time 3-approximation algorithm due to Nutov and Penn and an O(n8) time 2-approximation algorithm due to Dinitz and Nutov, where n and m are the numbers of vertices and edges in G, respectively. In this paper, we present a 7/3-approximation algorithm which runs in O(n2m) time.

The minimum distance of a linear code C is a useful metric property for estimating the error correction upper bound of C and the maximum likelihood decoding of a linear code C is also of practical importance and of theoretical interest. These problems are known to be NP-hard to approximate within any constant relative error to the optimum. As a problem related to the above, we consider the maximization problem MAX-WEIGHT: Given a generator matrix of a linear code C, find a codeword c C with its weight as close to the maximum weight of C as possible. It is shown that MAX-WEIGHT PTAS unless P=NP, however, no nontrivial approximation upper and lower bounds are known. In this paper, we investigate the complexity of MAX-WEIGHT to make the approximation upper and lower bounds more precise, and show that (1) MAX-WEIGHT is APX-complete; (2) MAX-WEIGHT is approximable within relative error 1/2 to the optimum; (3) MAX-WEIGHT is not approximable within relative error 1/10 to the optimum unless P=NP.

PID control schemes have been widely used in most of process control systems. Most of these processes are often treated as first-order systems with dead times. And also, in many cases, PID parameters are usually tuned based on the process parameters, i. e. , the time constant, the dead time and the process gain. However, since these process parameters can not be obtained exactly, it is well known that it is difficult to find the suitable PID parameters in practice. In this paper, we propose a genetic tuning scheme of PID parameters for first-order systems with large dead times. The authors have already proposed a tuning method of PID parameters using a genetic algorithm (GA), which was based on the relationship between PID control and generalized minimum variance control(GMVC) laws. In practice, for large dead time systems, first-order low pass pre-filters are often used. The proposed method is an extended version of the previously proposed method mentioned above to the system with a pre-filter due to the large dead time, i. e. , a tuning method of both PID parameters and the pre-filter using a GA. The proposed control scheme is numerically evaluated on some simulation examples.

Let S be a set of n points in the plane and CH(S) be the convex hull of S. We consider the problem of constructing an approximate convex hull which contains CH(S) with strong convexity. An ε-convex δ-superhull of S is a convex polygon P satisfying the following conditions: (1) P has at most O(n) vertices, (2) P contains S, (3) no vertex of P lies farther than δ outside CH(S), and (4) P remains convex even if its vertices are perturbed by as much as ε. The parameters ε and δ represent the strength of convexity of P and the degree of approximation of P to CH(S), respectively. This paper presents the first parallel method for the problem. We show that an ε-convex (8+42)ε-superhull of S can be constructed in O(log n) time using O(n) processors, or in O(log n) time using O(n/log n) processors if S is sorted, in the EREW-PRAM model. We implement the algorithm and find that the average performance is even much better: the results are more strongly convex and much more approximate to CH(S) than the theoretical analysis shows.

In this paper, we propose a method for detecting conserved domains from a set of amino acid sequences that belong to a protein family. This method detects the domains as follows: first, generate fixed-length subsequences from the sequences; second, construct a weighted graph that connects any two of the subsequences (vertices) having higher similarity than a pre-defined threshold; third, search for the maximum-density subgraph for each connected component of the graph; finally, explore conserved domains in the sequences by combining the results of the previous step. From the performance results obtained by applying the method to several protein families that have complex conserved domains, we found that our method was able to detect those domains even though some domains were weakly conserved.

This paper studies the "usefulness" of initial conditions for distributed algorithms on anonymous networks. In the literature, several initial conditions such as making one vertex a leader, giving the number of vertex to each vertices, and so on, have been considered. In this paper, we study a relation between the initial condition by considering transformation algorithm from one initial condition to another. For such transformation algorithms, we consider in this paper, both deterministic and randomized distributed algorithms. For each deterministic and randomized transformation type, we show that the relation induces an infinite lattice structure among equivalence classes of initial conditions.

Let l be a positive integer, and let G be a graph with nonnegative integer weights on edges. Then a generalized vertex-coloring, called an l-coloring of G, is an assignment of colors to the vertices of G in such a way that any two vertices u and v get different colors if the distance between u and v in G is at most l. In this paper we give an algorithm to find an l-coloring of a given graph G with the minimum number of colors. The algorithm takes polynomial time if G is a partial k-tree and both l and k are bounded integers.

We have developed a new efficient neural network-based algorithm for Alife application in a competitive world whereby the effects of interactions among organisms are evaluated in a weak form by exploiting the position of nearest food elements into consideration but not the positions of the other competing organisms. Two online learning algorithms, an instructive ASL (adaptive supervised learning) and an evaluative feedback-oriented RL (reinforcement learning) algorithm developed have been tested in simulating Alife environments with various neural network algorithms. The constructive compound neural network algorithm FuzGa guided by the ASL learning algorithm has proved to be most efficient among the methods experimented including the classical constructive cascaded CasCor algorithm of [18],[19] and the fixed non-constructive fuzzy neural networks. Adopting an adaptively selected best sequence of feedback action period Δα which we have found to be a decisive parameter in improving the network efficiency, the ASL-guided FuzGa had a performance of an averaged fitness value of 541.8 (standard deviation 48.8) as compared with 500(53.8) for ASL-guided CasCor and 489.2 (39.7) for RL-guided FuzGa. Our FuzGa algorithm has also outperformed the CasCor in time complexity by 31.1%. We have elucidated how the dimensionless parameter food availability FA representing the intensity of interactions among the organisms relates to a best sequence of the feedback action period Δα and an optimal number of hidden neurons for the given configuration of the networks. We confirm that the present solution successfully evaluates the effect of interactions at a larger FA, reducing to an isolated solution at a lower value of FA. The simulation is carried out by thread functions of Java by ensuring the randomness of individual activities.

This paper presents a server-based approach to maintaining software integrity for all computer classroom workstations. The approach takes several advantages: (1) applicable to the FAT (file allocation table) and NTFS file systems, (2) renovating all workstations to workable state, (3) quickly adding or removing software systems to or from all workstations for teachers conducting new courses, and (4) automatically changing computer name and IP (Internet Protocol) address to an appointed one. The basic concept of the server-based maintenance approach is to install whole software systems, including operating system and applications, on a normal workstation, to make one image copy of the workstation's hard disk and store it onto network server, and to restore the image file from the server to the remaining workstations. In order to change computer name and IP automatically, this paper presents a searching heuristic for finding their locations in the image file. The heuristic is modified from Boyer-Moore (BM) algorithm and can improve the BM algorithm's performance over 9%.

There are the following three targets to be achieved in a software project from the three viewpoints of process management (or progress management), cost management, and quality management for software project to be successful: (a) drafting a software development plan based on accurate estimation, (b) early detection of risks that the project includes based on correct situation appraisal, (c) early avoidance of risks that the project includes. In this paper, the authors propose a method and facilities to project risks in a software project through Kepner-Tregoe program, and propose schedule re-planning by using genetic algorithm for avoiding the projected risks. Furthermore the authors show, from the results of execution of the system, that the system is effective in early avoidance of risks that the software project includes.