Anycast refers to the transmission of data from a source node to (any) one member in the group of designed recipients in a network. When the physical network and the set of anycast requests are given, the Anycast Routing and Wavelength Assignment (ARWA) problem is to find a set of light-paths, one for each source, for anycasting messages to any one of the member in the anycast destination group such that not any path using the same wavelength passes through the same link. The goal of the ARWA problem is to minimize the number of used wavelengths. In this paper, the ARWA problem is formulated and studied; since ARWA problem is NP-hard, a three-phase genetic algorithm is proposed to solve it. This algorithm is used to find the close-to-optimal solution. Simulated results show that the proposed algorithm is able to achieve good performance.

In this paper, the optimal assignment problem which assigns cells in PCS (Personal Communication Service) to switches on ATM (Asynchronous Transfer Mode) network is investigated. The cost considered in this paper has two components: one is the cost of handoff that involves two switches, and the other is the cost of cabling. This problem assumes that each cell in PCS can be assigned to two switches in ATM network. This problem is modelled as dual-homing cell assignment problem, which is a complex integral linear programming (ILP) problem. Since finding an optimal solution of this problem is NP-hard, a hybrid method which combines several heuristics and a stochastic search method (based on a simulated annealing(SA) approach) is proposed to solve this problem. The solution method consists of three phases: Primary Assignment Decision Phase (PADP), Secondary Assignment Decision Phase (SADP) and Refinement Phase (RP). The PADP and SADP are used to find good initial assignment, then domain-dependent heuristics are encoded into perturbations of SA in Refinement Phase to improve the result. Simulation results show that the proposed hybrid method is robust for this problem.

Personal Communication Network (PCN) is an emerging wireless network that promises many new services for the telecommunication industry. The high speed backbone network (ATM or WDM) is one possible approach to provide broadband wireless transmission with PCN's using the ATM switching networks for interconnection of PCN cells. The wireless ATM backbone network design problem is that of allocating backbone links among ATM switches to reduce the effects of terminal mobility on the performance of ATM-based PCN's. In this paper, the wireless ATM backbone network design (WABND) problem is formulated and studied. The goal of the WABND is to minimize the location update cost under constraints. Since WABND is NP-hard, a heuristic algorithm and a genetic algorithm are proposed to solve it. These algorithms are used to find the close-to-optimal solution. Simulated results show that the proposed algorithms are able to achieve good performance.

Anycast refers to the transmission of data from a source node to (any) one member in the group of designed recipients in a network. When the physical network and the set of anycast requests are given, the WDM anycast routing problem (WARP) is to find a set of light-paths, one for each source, for anycasting messages to one of the member in the anycast destination group such that not any path using the same wavelength passes through the same link. The goal of the WARP is to minimize the number of used wavelengths. In this paper, the WARP is formulated and studied, since WARP is NP-hard, several heuristic algorithms and a hybrid method which combines heuristic and simulated annealing techniques are proposed to solve it. These algorithms are used to find the close-to-optimal solution. Simulated results show that the proposed algorithms are able to achieve good performance.

In this paper, we investigate the optimal assignment problem of cells in PCS (Personal Communication Service) to switches on a ATM (Asynchronous Transfer Mode) network. Given cells and switches on an ATM network (whose locations are fixed and known), the problem is to group cells into clusters and assign these clusters to switches in an optimum manner. This problem is modeled as a complex integer programming problem. Since finding an optimal solution of this problem is NP-hard, a heuristic solution model consists of three phases (Cell Pre-Partitioning Phase, Cell Exchanging Phase, and Cell Migrating Phase) is proposed. Experimental results show that Cell Exchanging and Cell Migrating Phases can really reduce total cost near 44% on average.