Sharif Digital Repository

A communication protocol consists of a sequence of messages used by peer entities to communicate. Each entity in a network is equipped by at least one protocol stack. Due to the need for on-the-fly reconfiguration of protocol stack in future communication and computation devices, formalizing substitutability and compatibility of protocol entities are important in correctness assessment of dynamic reconfiguration. In this paper, we extend Constraint Automata and propose I/O-Constraint Automata to model behavior of protocols and propose enough formalism for substitutability and compatibility relations between protocols. We introduce input-blocking property of communication protocols, and show... 

Applying an appropriate formal model to specify software architecture makes a reliable foundation to formally verify non-functional properties and therefore, leads to early detection of defects. In this paper we make a comparison between automata-based models and evaluate their abilities to model different aspects of components interaction in software architectures. We try to use Team automata as a middleware to formally specify well-known architectural descriptions in UML2.0. A Limitation of current automata models, so called "actions interleaving" is also discussed and some approaches to overcome this limitation described. © Springer-Verlag Berlin Heidelberg 2007  

In this paper, an adaptive random search method, based on continuous action-set learning automata, is studied for solving stochastic optimization problems in which only the noisecorrupted value of a function at any chosen point in the parameter space is available. First, a new continuous action-set learning automaton is introduced and its convergence properties are studied. Then, applications of this new continuous action-set learning automata to the minimization of a penalized Shubert function and pattern classification are presented. © Sharif University of Technology  

In this paper, we first propose two learning automata based decentralized dynamic guard channel algorithms for cellular mobile networks. These algorithms use learning automata to adjust the number of guard channels to be assigned to cells of network. Then, we introduce a new model for nonstationary environments under which the proposed algorithms work and study their steady state behavior when they use LR-I learning algorithm. It is also shown that a learning automaton operating under the proposed nonstationary environment equalizes its penalty strengths. Computer simulations have been conducted to show the effectiveness of the proposed algorithms. The simulation results show that the... 

A Santha-Vazirani (SV) source is a sequence of random bits where the conditional distribution of each bit, given the previous bits, can be partially controlled by an adversary. Santha and Vazirani show that deterministic randomness extraction from these sources is impossible. In this paper, we study the generalization of SV sources for nonbinary sequences. We show that unlike the binary case, deterministic randomness extraction in the generalized case is sometimes possible. We present a necessary condition and a sufficient condition for the possibility of deterministic randomness extraction. These two conditions coincide in “non-degenerate” cases. Next, we turn to a distributed setting. In... 

Constraint automata are the first-proposed operational semantics of Reo coordination language. They can be composed not only by all well-defined composition operators of labeled transition systems but also by two new operators. The new operators are joining of constraint automata with respect to their common port names and hiding a port name in all transition labels. The operations of these two extra operators depend on the internal structures of the transition labels, while in the others each transition label is considered as a simple entity. An equivalence relation between transition systems is a congruence relation if the replacement of the components of a model by the equivalent ones... 

Reconfigurability for a component of a distributed component-based system means ability to replace the component with a new one, in presence of the other components. In this context, substitutability and compatibility of components should be analyzed. In this paper, we use I/O-Constraint Automata to model behavior of components and propose enough formalism for substitutability and compatibility analysis. We show that in the context of distributed non-blocking components, there is a relation weaker than usual simulation relation in automata theory for notion of substitutability. We illustrate the relation between substitutability and compatibility to reason about the reconfigurability of a... 

A component-based computing system consists of two main parts: a set of components and a coordination subsystem. Reo is an exogenous coordination language for compositional construction of the coordination subsystem. Constraint automaton has been defined as the operational semantics of Reo. The main goal of this paper is to prepare a model checking method for verifying linear time temporal properties of component-based systems whose coordinating subsystems are modeled by Reo and components are modeled by labeled transition systems. For this purpose, we introduce modified definitions of constraint automata and their composition operators by which, every constraint automaton can be considered... 

In this paper, a new fixed structure learning automaton (FSSA), with a tuning parameter for amount of its rewards, is presented and its behavior in stationary environments will be studied. This new automaton is called TFSLA (Tunable Fixed Structured Learning Automata). The proposed automaton characterizes by star shaped transition diagram and each branch of the star contains N states associated with a particular action. TFSLA is tunable, so that the automaton can receive reward flexibly, even when it accepted penalty according to its previous action. Experiments show that TFSLA converges to the optimal action faster than some older FSSAs (e.g. Krinsky and Krylov) and the analytic examination... 

In this paper, we first introduce a network of learning automata, which we call it as distributed learning automata and then propose some iterative algorithms for solving stochastic shortest path problem. These algorithms use distributed learning automata to find a policy that determines a path from a source node to a destination node with minimal expected cost (length). In these algorithms, at each stage distributed learning automata determines which edges to be sampled. This sampling method may result in decreasing unnecessary samples and hence decreasing the running time of algorithms. It is shown that the shortest path is found with a probability as close as to unity by proper choice of... 

In this paper, we present a new fixed structure learning automaton (FSSA), called IJA, and study its steady state behavior in stationary environments. The proposed automaton characterizes by star shaped transition diagram and each branch of the star contains N states associated with a particular action. This new automaton is an improvement of the Krinsky FSSA and not only ε-optimal and expedient, but also converges to the optimal action faster than the old one. © 2006 IEEE  

Constraint automaton is a formalism to capture the operational semantics of the channel based coordination language Reo. In general constraint automaton can be used as a formalism for modeling coordination of some components. In this paper we introduce a standard linear temporal logic and two fragments of it for expressing the properties of the systems modeled by constraint automata and show that the equivalence relation defined by Valmari et al. is the minimal compositional equivalence preserving that fragment of linear time temporal logic which has no next-time operator and has an extra operator distinguishing deadlocks and a slight modification of this equivalence is the minimal... 

The thermal field and the grain structure of a cored superalloy turbine blade, which has been directionally solidified with the liquid metal cooling (LMC) process, has been simulated in three dimensions using a cellular automaton (CA) coupled with finite-element (CAFE) model. The cooling induced by the liquid aluminum bath has been replaced by a heat-transfer coefficient, whose temperature- and time-dependence has been adjusted on the basis of natural convection simulations and dimensionless analyses. The simulated grain structure and crystallographic texture have been compared with the microstructure, and the electron back-scattered diffraction (EBSD) results were obtained for a real blade.... 

Estimation of distribution algorithms have evolved as a technique for estimating population distribution in evolutionary algorithms. They estimate the distribution of the candidate solutions and then sample the next generation from the estimated distribution. Bayesian optimization algorithm is an estimation of distribution algorithm, which uses a Bayesian network to estimate the distribution of candidate solutions and then generates the next generation by sampling from the constructed network. The experimental results show that the Bayesian optimization algorithms are capable of identifying correct linkage between the variables of optimization problems. Since the problem of finding the... 

Motion planning is a key factor in enhancing the autonomy level of unmanned flying vehicles. A new dynamic hybrid algorithm is developed to solve the motion planning problem in real-time using a heuristic optimization approach. The proposed algorithm effectively combines desired features such as rapid convergence to an optimal path with reduced computational effort. In addition to the terrain obstacles, the proposed algorithm is able to avoid random threats that may arise sporadically in the terrain. Using the maneuver automaton concept, nonlinear dynamic model and performance constraints are also considered in the process of motion planning to further ensure feasible trajectories.... 

Reo is an exogenous coordination language for synthesizing components participating in a component-based system. The notion of Bchi automaton over streams of records (BAR for short) is a proposed operational semantics for Reo that covers several aspects of coordination strategies such as synchronization, context dependencies and fairness constraints. In this paper and for the purpose of modeling real-time coordination systems specified by Reo, we present a timed version of BARs as the acceptors of timed streams of records. We show that timed BAR and its streams of records based semantics are more standard and also more expressive than timed constraint automaton which is the first proposed... 

In this paper, we propose an adaptive call admission algorithm based on learning automata. The proposed algorithm uses a learning automaton to specify the acceptance/rejection of incoming new calls. It is shown that the given adaptive algorithm converges to an equilibrium point which is also optimal for uniform fractional channel policy. To study the performance of the proposed call admission policy, the computer simulations are conducted. The simulation results show that the level of QoS is satisfied by the proposed algorithm and the performance of given algorithm is very close to the performance of uniform fractional guard channel policy which needs to know all parameters of input traffic.... 

This paper utilizes IJA stochastic learning automaton for detecting noise and tuning value of alpha parameter which is used for image sharpening via gas diffusion model. The method has been applied to gray-scale images in an automatic and adaptive fashion. It is shown that the IJA automaton detects noise and can reform it appropriately. It glides the image to find the pattern of noise and replace it by the relevant characteristics of neighborhood to carry out the local restoration. Then, the automaton makes the image sharp with gas diffusion model by learning alpha parameter. The IJA automaton calculates appropriate local value for each pixel. Finally, experiments are presented and... 

Named Data Networking (NDN) is a new information-centric networking architecture in which data or content is identified by a unique name and saved pieces of the content are used in the cache of routers. Certainly, routing is one of the major challenges in these networks. In NDN, to achieve the required data for users, interest messages containing the names of data are sent. Because the source and destination addresses are not included in this package, routers forward them using the names that carried in packages. This forward will continue until the interest package is served. In this paper, we propose a routing algorithm for NDN. The purpose of this protocol is to choose a path with the...