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In this paper, we focus on trade-offs between storage cost and rekeying cost for secure multicast. Membership in secure multicast groups is dynamic and requires multiple updates in a single time frame. We present a family of algorithms that provide a trade-off between the number of keys maintained by users and the time required for rekeying due to revocation of multiple users. We show that some well-known...
In this paper an Iterative Learning Control (ILC) algorithm is proposed for a certain class of Linear Parameter Varying (LPV) systems whose dynamics change between iterations. Consistency of the algorithm in the presence of stochastic disturbances is shown. The proposed algorithm is tested in simulation and the obtained tracking performance is compared with that obtained using a standard Linear Time...
This paper is concerned with understanding the connection between the existing Internet congestion control algorithms and the optimal control theory. The available resource allocation controllers are mainly devised to derive the state of the system to a desired equilibrium point and, therefore, they are oblivious to the transient behavior of the closed-loop system. This work aims to investigate what...
Motivated by the growing demand of accuracy and low computational time in optimizing functions in various fields of engineering, an approach has been presented using the technique of parallel computing. The parallelization has been carried out on one of the simplest and flexible optimization algorithms, namely the particle swarm optimization (PSO) algorithm. PSO is a stochastic population global optimizer...
With the rapidly growing number of Web services throughout the Internet, Service Oriented Architecture (SOA) enables a multitude of service providers (SP) to provide loosely coupled and inter-operable services at different Quality of Service (QoS) levels. This paper considers the services are published to a QoS-aware registry. The structure of composite service is described as a Service Orchestration...
Retrieving similar data has drawn many research efforts in the literature due to its importance in data mining, database and information retrieval. This problem is challenging when the data is incomplete. In previous research, data incompleteness refers to the fact that data values for some dimensions are unknown. However, in many practical applications (e.g., data collection by sensor network under...
Based on the analysis of defects of traditional evolutionary algorithms in solving global optimization of non-linear or multi-modal function, a novel evolutionary algorithm called multi-stage evolutionary algorithm (MSEA) is proposed. MSEA has many new features. It develops some new operators such as multi-parent crossover operator with elite-preservation, dynamical mutation operator, space contraction...
Based on the max-min ant system solving the Pseudo-Boolean Optimization problem, we improved the process of solving the problem. An memory array is introduced to record changes of each bit string, memory array to be used for optimization of the solution of the current iteration. Such improvements will help improve the convergence rate of Max-Min ant colony algorithm. The improved algorithm was applied...
In this paper we present an empirical, comparative performance, analysis of fourteen variants of Differential Evolution (DE) and Dynamic Differential Evolution (DDE) algorithms to solve unconstrained global optimization problems. The aim is to compare DDE, which employs a dynamic evolution mechanism, against DE and to identify the competitive variants which perform reasonably well on problems with...
Network reconstruction, i.e., obtaining network structure from data, is a central theme in systems biology, economics, and engineering. Previous work introduced dynamical structure functions as a tool for posing and solving the problem of network reconstruction between measured states. While recovering the network structure between hidden states is not possible since they are not measured, in many...
In this paper we propose centralized feedback control laws for mobile sensor networks so that sensor trajectories cover a given domain as uniformly as possible. The design of the feedback law is based on a measure for uniformity of the trajectories given as a distance between a certain delta-like distribution on the trajectories and a desired probability distribution. The design of control is of Lyapunov-type...
We investigate three stochastic problems (linear dynamics quadratic criterion, minimum-cost path, equipment replacement) with time-delayed control dynamics. We show how the concept of ??stage lookahead?? helps to reduce the number of arguments in the optimal value function of dynamic programming in order to alleviate the so-called curse of dimensionality.
In this paper an automatic multilevel thresholding approach, based on binary particle swarm optimization, is proposed. The proposed approach automatically determines the "optimum" number of the thresholds and simultaneously searches the optimal thresholds, by optimizing a function which uses the gray level thresholds as parameters. The algorithm starts with large number initial thresholds,...
When a task is received by an agent organization in multi-agent system (MAS), it should be partitioned into multiple subtasks which will be assigned to suitable agents to be pursued. A goal model of autonomous agent organization (GMAAO) is proposed in which a trigger mechanism of event is added to the traditional "AND/OR" task decomposition tree to deal with the event-driven feature of MAS,...
This paper presents reports a design and development of the interactive map using Scalable Vector Graphics (SVG) that can be used to find the shortest path. Using our interactive map, the user will be able to set the route or path to the desired location. If that path is congested, the map will find the second shortest path to the user. In the usability study, we have tested the map with the mean...
With the amounts of contents and users increasing, the content-based service systems have to face the overloading problem. Load balancing technology using the information of user behavior is often used to resolve this problem. The major purpose of this paper is to build a time serial model of user behavior in content-based service systems, and propose a dissimilar measurement for this model. Finally...
Attribute reduction in rough set theory is an important feature selection method, which can apply successfully in data mining and machine leaning .etc. In this paper, a new algorithm of attribute reduction is proposed which based on bitmap and granular computing. At first, in order to reduce the research space, we need not to compute the record vectors if only the number of corresponding class vector...
This paper presents an application of Ant Colony System Algorithm (ACS) to solve electrical distribution planning problems. This model constitutes an improved version of the ant system algorithm, permitting to generate food routes from their nest, and where a set of artificial ants are cooperating in order to find a good route through the data exchange contained by the pheromone deposits in several...
In this paper, we address the problem of self-adaptation in internet-scale service-oriented systems. Services need to adapt by selecting the best neighboring services solely based on local, limited information. In such complex systems, the global significance of the various selection parameters dynamically changes. We introduce a novel metric measuring the distribution and potential impact of service...
The resource-constrained project scheduling problem (RCPSP) is a typical combinatorial optimization problem. Base on the general model of ant colony algorithm for solving the RCPSP, this paper presents a new 2opt called PC-2opt which guarantees precedence constraints between activities. PC-2opt, which needn't to calculate the location of successors, could be directly used to solve the RCPSP, and improve...
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