2426410
Network information flow
We introduce a new class of problems called network information flow which is inspired by computer network applications. Consider a point-to-point communication network on which a number of information sources are to be multicast to certain sets of destinations. We assume that the information sources are mutually independent. The problem is to characterize the admissible coding rate region. This model subsumes all previously studied models along the same line. We study the problem with one information source, and we have obtained a simple characterization of the admissible coding rate region. Our result can be regarded as the max-flow min-cut theorem for network information flow. Contrary to one's intuition, our work reveals that it is in general not optimal to regard the information to be multicast as a "fluid" which can simply be routed or replicated. Rather, by employing coding at the nodes, which we refer to as network coding, bandwidth can in general be saved. This finding may have significant impact on future design of switching systems.
45808479
Recursive Construction of Distributors by Merging
3106412
On the Design of Perceptual MPEG-Video Encryption Algorithms
In this paper, some existing perceptual encryption algorithms of MPEG videos are reviewed and some problems, especially security defects of two recently proposed MPEG-video perceptual encryption schemes, are pointed out. Then, a simpler and more effective design is suggested, which selectively encrypts fixed-length codewords in MPEG-video bit streams under the control of three perceptibility factors. The proposed design is actually an encryption configuration that can work with any stream cipher or block cipher. Compared with the previously-proposed schemes, the new design provides more useful features, such as strict size-preservation, on-the-fly encryption and multiple perceptibility, which make it possible to support more applications with different requirements. In addition, four different measures are suggested to provide better security against known/chosen-plaintext attacks
31495802
A New Hybrid GA/SA Algorithm for the Job Shop Scheduling Problem
Among the modern heuristic methods, simulated annealing (SA) and genetic algorithms (GA) represent powerful combinatorial optimization methods with complementary strengths and weaknesses. Borrowing from the respective advantages of the two paradigms, an effective combination of GA and SA, called Genetic Simulated Algorithm (GASA), is developed to solve the job shop scheduling problem (JSP). This new algorithm incorporates metropolis acceptance criterion into crossover operator, which could maintain the good characteristics of the previous generation and reduce the disruptive effects of genetic operators. Furthermore, we present two novel features for this algorithm to solve JSP. Firstly, a new full active schedule (FAS) based on the operation-based representation is presented to construct schedule, which can further reduce the search space. Secondly, we propose a new crossover operator, named Precedence Operation Crossover (POX), for the operation-based representation. The approach is tested on a set of standard instances and compared with other approaches. The Simulation results validate the effectiveness of the proposed algorithm.
36253673
A fuzzy goal programming approach to multi-objective optimization problem with priorities
Abstract In goal programming problem, the general equilibrium and optimization are often two conflicting factors. This paper proposes a generalized varying-domain optimization method for fuzzy goal programming (FGP) incorporating multiple priorities. According to the three possible styles of the objective function, the varying-domain optimization method and its generalization are proposed. This method can generate the results consistent with the decision-maker (DM)’s expectation, that the goal with higher priority may have higher level of satisfaction. Using this new method, it is a simple process to balance between the equilibrium and optimization, and the result is the consequence of a synthetic decision between them. In contrast to the previous method, the proposed method can make that the higher priority achieving the higher satisfactory degree. To get the global solution of the nonlinear nonconvex programming problem resulting from the original problem and the varying-domain optimization method, the co-evolutionary genetic algorithms (GAs), called GENOCOPIII, is used instead of the SQP method. In this way the DM can get the optimum of the optimization problem. We demonstrate the power of this proposed method by illustrative examples.
8736073
Using Feature-Oriented Analysis to Recover Legacy Software Design for Software Evolution
Most design recovery approaches start from analysing source code. Nonetheless, it is very difficult to get adequate design information only depending on source code. Additional available information is required and Feature Oriented Analysis (FOA) is a way to reach this aim. FOA addresses the understanding of features in software systems and defines mechanisms for carrying a feature from the problem domain into the solution domain. Using feature as the first-class entity for software evolution can improve program comprehension and design recovery. In this paper, an approach is proposed to recover software design based on the feature model, which is a kind of legacy system knowledge. The features will first be located and mapped to the implementation module so that feature-oriented components can be identified and retrieved, and then, through the analysis of the feature relations, the design model of legacy system can be recovered and used for the future evolution.
40576003
GloStra - a hybrid system for developing global strategy and associated Internet strategy
An intelligent hybrid system, called GloStra (developed by the author), for developing global marketing strategy and associated Internet marketing strategy is reported in this paper. The hybrid system is built to integrate the strengths of expert systems, fuzzy logic, artificial neural networks and decision support technology; and to link the development of global marketing strategy with the formulation of associated Internet marketing strategy. In the paper, the system architecture, the functional modules of the hybrid system and other associated technical issues are addressed. The directions for further research in this field are also highlighted.