A bi-level programming model for protection of hierarchical facilities under imminent attacks

Disorders caused by deliberate sabotage and terrorist attacks have always been considered as a major threat by the governments. Hence, identifying and planning for strengthening of critical facilities have become a priority for more security and safety. This paper presents a bi-level formulation of the r-interdiction median problem with fortification for critical hierarchical facilities. In the developed bi-level formulation, the defender, as the leader, decides to protect a certain number of facilities in each level of the hierarchical system in order to minimize the impact of the most disruptive attacks to unprotected facilities. On the other hand the attacker, as the follower, with full information about protected facilities, makes his interdiction plan to maximize the total post-attack cost incurred to the defender. We develop three metaheuristic algorithms and an exhaustive enumeration method to solve the introduced problem. Extensive computational tests on a set of randomly generated instances demonstrate the effectiveness of the developed algorithms.     

BiTE: a dynamic bi-level traffic engineering model for load balancing and energy efficiency in data center networks

Applied Intelligence - With the recent significant growth of virtualization and cloud services, the data center network (DCN) as the underlying infrastructure is more important. The increasing and...     

A clique-superposition model for social networks

How does a social network evolve? Sociologists have studied this question for many years.According to some famous sociologists,social links are driven by social intersections.Actors who affiliate with the shared intersections tend to become interpersonally linked and form a cluster.In the social network,an actor cluster could be a clique or a group of several smaller-sized cliques.Thus we can conclude that a social network is composed of superposed cliques of different sizes.However,sociologists did not verify the theory in large scale data due to lack of computing ability.Motivated by this challenge,incorporated with the theory,we utilize data mining technologies to study the evolution patterns of large scale social networks in real world.Then,we propose a novel Clique-superposition generative model,which generates undirected weighted networks.By extensive experiments,we demonstrate that our model can generate networks with static and time evolving patterns observed not only in earlier literature but also in our work.     

A robust continuous model for evidential reasoning

A 2-D model for evidential reasoning is proposed, in which the belief function of evidence is represented as a belief density function which can be in a continuous or discrete form. A vector form of mutual dependency relationship of the evidence is considered and a dependency propagation theorem is proved. This robust method can resolve the conflicts resulting from either the mutual dependency among evidences or the structural dependency in an inference network due to the evidence combination order. Belief conjunction, belief combination, belief propagation procedures, and AND/OR operations of an inference network based on the proposed 2-D model are all presented, followed by some examples demonstrating the advantages of this method over the conventional methods.     

A new continuous model for job-shop scheduling

In this paper arguments are presented for the use of a new continuous model for job-shop scheduling. In this model each job is regarded as infinitely divisible. Formulating the job-shop problem in this way leads to optimal control problems of a type which recent work has shown to be efficiently solvable. Solutions to these continuous problems can be used to generate heuristic loading rules. Some simulation results from small job-shops are presented. These demonstrate that loading rules based on the continuous model perform well in practice.     

A random close packing based algorithm for the generation of continuous random networks

We present a generally applicable method for the modeling of covalent amorphous networks. The algorithm proceeds by generating random close packings of anions, followed by an optimal placement of the cations. As examples, we apply the algorithm to a-SiO₂, a-Si₃N₄, a-SiO_3/2N_1/3, and a-B₂O₃.     

A generative model for time evolving networks

Time evolving networks have some properties in common with complex networks, while some characteristics are specific to their time evolving nature. A number of interesting properties have been observed in time-varying complex networks such as densification power-law, shrinking diameter, scale-free degree distribution, big clustering coefficient and the emergence of community structure. Existing generative models either fail to simulate all the properties or undermine the social interactions between the existing nodes over time. In this paper, we propose a generative model called socializing graph model (SGM) for those networks that evolve over time. It is an iterative procedure consisting of two steps. In the first step, we add one new node to the network at every timestamp and connect it to an existing node using a preferential attachment rule. In the second step, we add a number of edges between the existing nodes in order to reflect the emergence of social interactions between nodes over time and mimic the evolution of real networks. We present empirical results to show that SGM generates realistic prototypes of evolving networks.

     

A versatile model for predicting the performance of deflection-routing networks

Deflection routing can be used in networks whose stations have the same number of input and output links. Fixed-length packets arrive synchronously on the station's input links at the beginning output link that offers the shortest path to its destination. Since the number of packet buffers at each output link is finite, the simultaneous contention of two packets for the last buffer of the common output link must be resolved by “deflecting” one of the packets according to a specified criterion (e.g. at random, by destination proximity, or by packet age). Deflection routing can therefore be used with as few as one packet buffer per output link.

The potentially unbounded number of routes that a given packet can take makes analyzing the performance of such networks difficult. Using independence assumptions, we develop an efficient, high-fidelity performance model of deflection routing that allows us to estimated the mean end-to-end packet delay in a network that has any given two-connected topology, a single packet buffer at each output port, and an arbitrary traffic matrix.     

A model for the protocol design of back-end storage networks

This work presents a formal design for the system protocols of back-end storage networks. Such design relies on predicate-transition nets (PrT-nets). These nets actually represent an extension of Petri nets and can provide reasonable means for precise modeling of complex systems. The given model has demonstrated that by using PrT-nets the protocols of back-end networks can be constructed and interpreted in a natural manner. In that model we employed mainly two types of tokens, one to simulate user programs and requests and the other to express synchronization and control. To build up the model we used a modular approach. Each module is represented by a phase in the protocol net so that the complete design can eventually realize the required system specifications. Also, an insight into the design is emphasized and the validation of the protocol is pointed out. Accordingly, a well-behaved system is obtained so that the shared data is free from inconsistency, deadlocks, and residual signals.     

A new multi-objective bi-level programming model for energy and locality aware multi-job scheduling in cloud computing

How to reduce power consumption of data centers has received worldwide attention. By combining the energy-aware data placement policy and locality-aware multi-job scheduling scheme, we propose a new multi-objective bi-level programming model based on MapReduce to improve the energy efficiency of servers. First, the variation of energy consumption with the performance of servers is taken into account; second, data locality can be adjusted dynamically according to current network state; last but not least, considering that task-scheduling strategies depend directly on data placement policies, we formulate the problem as an integer bi-level programming model. In order to solve the model efficiently, specific-design encoding and decoding methods are introduced. Based on these, a new effective multi-objective genetic algorithm based on MOEA/D is proposed. As there are usually tens of thousands of tasks to be scheduled in the cloud, this is a large-scale optimization problem and a local search operator is designed to accelerate convergent speed of the proposed algorithm. Finally, numerical experiments indicate the effectiveness of the proposed model and algorithm.     

Performance analysis for range expansion in heterogeneous networks

In this paper, the uplink and downlink performance of a two-tier heterogeneous network （HetNet） with range expansion （RE） is analyzed. Different from previous works, base stations （BSs） are modeled as a spatial Poisson point process. This model can not only capture the irregularity of the BS deployment but also lead to closed form expressions. With the analytical results, the impacts of several key parameters on the coverage and throughput performance are investigated. Our results justifies the effectiveness of RE and Pico deployment. Based on our analyses, certain attention should be made on the RE design to balance the uplink and downlink performance. Our analyses are corroborated by simulations and can thus serve as a flexible and quick guidance for system design without complicated and time-consuming system-level platform construction and simulation.     

Constraint-based learning for non-parametric continuous bayesian networks

Annals of Mathematics and Artificial Intelligence - Modeling high-dimensional multivariate distributions is a computationally challenging task. In the discrete case, Bayesian networks have been...     

A new co-evolutionary decomposition-based algorithm for bi-level combinatorial optimization

Bi-Level Optimization Problems (BLOPs) are a class of challenging problems with two levels of optimization tasks. The main goal is to optimize the upper level problem which has another optimization problem as a constraint. The latter is called the lower level problem. In this way, the evaluation of each upper level solution requires finding an (near) optimal solution to the corresponding lower level problem, which is computationally very expensive. Many real world applications are bi-level by nature, ranging from logistics to software engineering. Further, proposed bi-level approaches have been restricted to solve linear BLOPs. This fact has attracted the evolutionary computation community to tackle such complex problems and many interesting works have recently been proposed. Unfortunately, most of these works are restricted to the continuous case. Motivated by this observation, we propose in this paper a new Co-evolutionary Decomposition Algorithm inspired from Chemical Reaction Optimization algorithm, called E-CODBA (Energy-based CODBA), to solve combinatorial bi-level problems. Our algorithm is based on our previous works within this research area. The main idea behind E-CODBA is to exploit co-evolution, decomposition, and energy laws to come up with good solution(s) within an acceptable execution time. The statistical analysis of the experimental results on the Bi-level Multi-Depot Vehicle Routing Problem (Bi-MDVRP) show the out-performance of our E-CODBA against four recently proposed works in terms of effectiveness and efficiency.     

一个无线传感器网络的网络分割模型

首先指出网络分割会影响网络连通性，并进而影响网络的通信效率；接着从物理层和MAC协议入手，讨论了导致无线传感器网络网络分割问题的通信因素。为了定量地刻画网络分割，定义了网络分割比，并分析了影响网络分割比的物理及几何因素。通过试验采集的大量数据及曲线族拟合法，建立了一个无线传感器网络的网络分割模型，定量地确定了网络节点数、面积比与网络分割比的数学关系。     

A u-IT collaboration evaluation model for value networks

The paradigm of competition between companies has been changed from the competition between individual businesses to the one between the supply chain management. To gain a comparative advantage in this supply chain management, IT collaboration, which has an important strategic location for cooperation between manufacturers, sectors, systems, applications, and processes and supports them, has begun to emerge as an important key. To date, however, most of the studies have searched factors constructing collaborative networks between companies, and there are few studies on performance analysis for activating collaborative networks between companies. Accordingly, this study would like to conduct performance analysis on collaborative networks between companies for measuring performance of constructing concrete collaborative networks and activating improved collaborative network systems from an industrial viewpoint. In detail, it would like to design a model for determinants to make construct collaborative networks and to analyze the utilization level and performance of collaborative networks between companies. In addition, it conducts correlation analysis on determinants of collaborative networks to improve performance of these collaborative networks.     

A model for multilevel security in computer networks

A model is presented that precisely describes the mechanism that enforces the security policy and requirements for a multilevel secure network. The mechanism attempts to ensure secure flow of information between entities assigned to different security classes in different computer systems connected to the network. The mechanism also controls the access to the network devices by the subjects (users and processes executed on behalf of the users) with different security clearances. The model integrates the notions of nondiscretionary access control and information flow control to provide a trusted network base that imposes appropriate restrictions on the flow of information among the various devices. Utilizing simple set-theoretic concepts, a procedure is given to verify the security of a network that implements the model     

一种新的无线传感器网络分簇模型

从工业现场应用的角度对无线传感器网络进行研究,提出了一种新的双簇头分级模型。该模型在单簇头模型的基础上增加了一个冗余簇头节点,在簇头节点电池耗尽或出现故障之时,冗余簇头节点能够实时切换成簇头节点以维持簇稳定工作。介绍了双簇头分级模型的工作原理、覆盖范围和能耗管理,并且对该模型的性能进行了实验仿真,实验结论证明双簇头分级模型比之单簇头分级模型有更好的稳定性和安全性,以及长的生存时间而更适合应用于工业现场。