Rong-Hong Jan

Reliability Optimization Problems with Multiple Constraints

This paper presents a class of reliability optimization problems with multiple-choice constraints. We assume that at least one design alternative can be chosen as redundancy for each subsystem. A 2-phase solution method is presented for solving these problems. In phase I, we decompose a problem into n subproblems. These subproblems can be solved by dynamic programming, independently. That is, these subproblems can be solved by parallelism. In phase II, we solve a 0-1 multiple-choice knapsack problem which is generated from phase I. We use a combinatorial tree which always satisfies the multiple-choice constraints. The 2-phase solution method is illustrated with a numerical example.

Adaptive Topology Control for Mobile Ad Hoc Networks

In MANETs, mobile devices are usually powered by batteries with limited energy supplies. Topology control is a promising approach, which conserves energy by either reducing transmission power for each node or preserving energy-efficient routes for the entire network. However, there is empirically a trade-off between the energy efficiency of the nodes and routes in a topology. Besides, it may consume considerable energy to maintain the topology due to node mobility. In this paper, we propose an adaptive topology control protocol for mobile nodes. The protocol allows each node to decide whether to support energy-efficient routing or conserve its own energy. Moreover, it can drastically shrink the broadcasting power of beacon messages for mobile nodes. We prove that any reconstruction and change of broadcasting radius converge in four and five beacon intervals, respectively. The experimental results show that our protocol can significantly reduce the total energy consumption for each successfully transmitted packet, and prolong the life times of nodes, especially in high mobility environments.

Nonlinear integer bilevel programming

Abstract In many decentralized organizations, resource planning with sequential decision making can be formulated as a multi-level programming problem. In such cases, the decision variables are partitioned among the decision makers. Each of the decision makers optimizes his/her own objective function. This paper presents an algorithm using parametric analysis to solve a typical kind of nonlinear integer multilevel programming problems, called separable integer monotone bilevel programming (SIMBP), and then extends the algorithm for solving a parametric SIMBP problem. A numerical example with application of reliability optimization is given to illustrate the solution method.

A MAC Protocol for Multi-Channel Multi-Interface Wireless Mesh Network Using Hybrid Channel Assignment Scheme

In recent years, Wireless Mesh Network (WMN) which uses a multi-hop configuration to extend the reach of the last-mile access to Internet has come into public notice. WMN improves network performance by the use of multiple orthogonal (non-overlapping) channels and multiple wireless interfaces. However, the Medium Access Control (MAC) protocol in IEEE 802.11 standard was designed and suited for only one channel and one interface. In this paper, we present a new MAC protocol which is specially designed for multi-channel and multi-interface WMNs. The proposed MAC protocol employs a hybrid channel assignment strategy to solve the rendezvous problem and a waiting time scheme for updating network allocation vectors (NAVs) to solve the multichannel hidden terminal problem. Simulation results show that the proposed protocol can achieve a better utilization of both interfaces and channels.

Parametric Programming Applied to Reliability Optimization Problems

In practical reliability optimization models, finding an optimal solution to the model is not the only requirement. One may also be interested in solutions that are close to optimum, or one may want to know what happens if a change is made in the model. This paper presents new reliability optimization models which can be formulated as parametric nonlinear integer programming problems. Solution methods are illustrated with examples and flow charts.

An optimization model for web content adaptation

This paper considers Web content adaptation with a bandwidth constraint for server-based adaptive Web systems. The problem can be stated as follows: Given a Web page P consisting of n component items d1,d2,...,dn and each of the component items di having Ji versions di1,di2,...,diJi, for each component item di select one of its versions to compose the Web page such that the fidelity function is maximized subject to the bandwidth constraint. We formulate this problem as a linear multi-choice knapsack problem (LMCKP). This paper transforms the LMCKP into a knapsack problem (KP) and then presents a dynamic programming method to solve the KP. A numerical example illustrates this method and shows its effectiveness.

Parametric nonlinear integer programming: The right-hand side case

Abstract In this paper, we present algorithms for solving families of nonlinear integer programming problems in which the problems are related by having identical objective coefficients and constraint matrix coefficients. We consider two types of right-hand sides which have the forms b (1) and b i + θ i d i where { b (1) } 1=1,…, l is a given set of vectors, bi + θidi is a parametric function and the parameter θi varies from zero to one. The approach consists primarily of solving the most relaxed problem using branch and search method and then finding the optimal solutions of the proposed parametric programming problems. The application of this methodology to a parametric chance-constrained problem1is illustrated with applications in system reliability optimization problems.

A multiple power-level approach for wireless sensor network positioning

Wireless sensor networks enhance our ability to monitor the physical world. Many recent researches on wireless sensor networks have focused on aspects such as routing, node cooperation, and energy consumption. In addition to these topics, the positioning service is also an important function in sensor networks. This paper presents a multiple power-level positioning algorithm, discusses its capabilities, and evaluates its performance in various environments. The simulation results show that the proposed algorithm exhibits better accuracy than do traditional single power-level methods. In critical situations such as reference node failure, unstable radio transmission range and beacon collision, the proposed algorithm still performs well. Finally, the positioning method is implemented on a sensor network test bed, and the actual measurements show that, the average estimation error is 2.5m when three power-levels are used and adjacent reference nodes are 12m apart in an outdoor environment.

Efficient Broadcast Mechanism for Cooperative Collision Avoidance Using Power Control

Improving driver’s safety has been an active research area in wireless communication. In particular, the vehicle cooperative collision avoidance (CCA) is one of the most important issues in safety applications. A variety of broadcast protocols has been proposed for vehicular network. However, there is only a few of them dedicatedly designed for the CCA system. In this paper, we propose a novel broadcast mechanism for CCA using the power control technique. The power control rule is based on the safe distance between vehicles. Simulation results show that our approach can significantly reduce the delivery delay and avoid car collision.

Role and channel assignments for wireless mesh networks using hybrid approach

The wireless mesh network has been considered one of the most promising techniques to extend the broadband access to the last mile. To utilize multiple channels on more than one interface, a number of approaches have been proposed. In particular, the hybrid strategy that combines the benefits of high channel diversity and low coordination cost has seen growing interest in recent studies. In this paper, we define two optimization problems, named the role assignment and the semi-fixed channel assignment, to characterize the unique feature in the hybrid strategy. We proved that the two problems are NP-hard even if the transmission ranges of interfaces are equal. In order to solve our problems in reasonable time, we design efficient algorithms. For the role assignment problem, we give an 1/2-approximate algorithm to find a nearly optimal solution. For the semi-fixed channel assignment problem, a heuristic algorithm, based on transferring from a coloring-based problem, is proposed. Experimental results show that optimizing the defined problems is indeed beneficial to improve the network throughput, and the proposed algorithms are significantly superior to existing methods.