Exact Algorithm to Solve the Minimum Cost Multi-Constrained Multicast Routing Problem

The optimal solution of the multi-constrained QoS multicast routing problem is a tree-like hierarchical structure in the topology graph. This multicast route contains a feasible path from the source node to each of the destinations with respect to a set of QoS constraints while minimizing a cost function. Often, it is a tree. In other cases, the hierarchies can return several times to nodes and links of the topology graph. Similarly to Steiner problem, finding such a structure is an NP-hard problem. The usual tree and topology enumeration algorithms applied for the Steiner problem cannot be used to solve the addressed problem. In this paper, we propose an exact algorithm based on the Branch and Bound principle and improved by the Lookahead technique. We show relevant properties of the optimum hierarchy permitting efficient pruning of the search space. To our knowledge, our paper is the first to propose an exact algorithm for this non-trivial multi-constrained optimal multicast route computation. Simulations illustrate the efficiency of the proposed pruning operations. The analysis of the execution time shows that in simple topologies and with tight QoS constraints the exact algorithm requires relatively little execution time. With loose constraints the computation time cannot be tolerated even for off-line route computation. In these cases, the solution is close to a Steiner tree and heuristics can be applied. These results can serve as basis for the design of efficient, polynomial-time routing algorithms.

Algorithm for multi-constrained path selection based on experimental analysis

It is a challenging problem to provide quality-of-service （QoS） guarantees in next generation high-speed network, and the QoS routing is one of the key issues of the problem. For the problem of multi-constrained QoS routing in high-speed network, especially under the inaccurate link state information, the success ratio of the different constraint combination is analyzed statistically, and a constraint analysis method based on the computer simulation is proposed. Furthermore, the approximately equal loose-tight order relation between each two constraints is constructed, and then an algorithm based on the experimental analysis is presented. Finally, the simulation result demonstrates that the algorithm has the higher success ratio, and the theoretical analysis proves its correctness and universality.

Mission-Oriented Configuration Model of Aircraft Carrying Spares and Dynamic Optimization Policy

Spare parts are critical to scheduled maintenance and fault repair, and can directly affect the readiness and combat capability of equipment. Equipmentrs capacity of carrying spares is influenced by its storage space and scales, so it is necessary to consider economic factors, e.g. spares cost, as well as non-economic ones, such as spares volume, mass and scale, when optimizing spares configuration. Aiming at this problem, the optimization model based on multi-constraints for carrying spares is built by METRIC theory and system analysis. Through the introduction of Lagrange factors, the spares cost is transformed to shadow price, and the optimization method for carrying spares and the dynamic adjustment policy of Lagrange factors are proposed. The result of a given example is analyzed, and demonstrates that the proposed model can be optimized with all constraints, and the research can provide a new way for carrying spares optimization.

Genetic algorithm for pareto optimum-based route selection

A quality of service （QoS） or constraint-based routing selection needs to find a path subject to multiple constraints through a network. The problem of finding such a path is known as the multi-constrained path （MCP） problem, and has been proven to be NP-complete that cannot be exactly solved in a polynomial time. The NPC problem is converted into a multiobjective optimization problem with constraints to be solved with a genetic algorithm. Based on the Pareto optimum, a constrained routing computation method is proposed to generate a set of nondominated optimal routes with the genetic algorithm mechanism. The convergence and time complexity of the novel algorithm is analyzed. Experimental results show that multiobjective evolution is highly responsive and competent for the Pareto optimum-based route selection. When this method is applied to a MPLS and metropolitan-area network, it will be capable of optimizing the transmission performance.

SIMULATED ANNEALING BASED POLYNOMIAL TIME QOS ROUTING ALGORITHM FOR MANETS

Multi-constrained Quality-of-Service (QoS) routing is a big challenge for Mobile Ad hoc Networks (MANETs) where the topology may change constantly. In this paper a novel QoS Routing Algorithm based on Simulated Annealing (SA_RA) is proposed. This algorithm first uses an energy function to translate multiple QoS weights into a single mixed metric and then seeks to find a feasible path by simulated annealing. The pa- per outlines simulated annealing algorithm and analyzes the problems met when we apply it to Qos Routing (QoSR) in MANETs. Theoretical analysis and experiment results demonstrate that the proposed method is an effective approximation algorithms showing better performance than the other pertinent algorithm in seeking the (approximate) optimal configuration within a period of polynomial time.

Improved ant colony-based multi-constrained QoS energy-saving routing and throughput optimization in wireless Ad-hoc networks

In order to establish a route supporting multi-constrained quality of service（QoS）, increase network throughput and reduce network energy consumption, an improved ant colony-based multi-constrained QoS energy-saving routing algorithm（IAMQER） is proposed. The ant colony algorithm, as one of the available heuristic algorithms, is used to find the optimal route from source node to destination node. The proposed IAMQER algorithm, which is based on the analysis of local node information such as node queue length, node forwarding number of data packets and node residual energy, balances the relationship between the network throughput and the energy consumption, thus improving the performance of network in multi-constrained QoS routing. Simulation results show that this IAMQER algorithm can find the QoS route that reduce average energy consumption and improves network packet delivery ratio under the end-to-end delay and packet loss ratio constraints.

A novel and effective multi-constrained QoS routing scheme in WMNs

Multi-constrained quality of service(QoS)routing aims at finding an optimal path that satisfies a set of QoS parameters,as an NP complete problem,which is also a big challenge for wireless mesh networks(WMNs).Heuristic algorithms with polynomial and pseudo-polynomial-time complexities are often used to deal with this problem.However,existing solutions,most of which suffered either from excessive computational complexities or from low performance,were proposed only for wired networks and cannot be used directly in wireless mesh networks.In this paper,we propose a novel routing scheme based on mean field annealing(MFA-RS)to solve this problem.MFA-RS first uses a function of two QoS parameters,wireless link’s delay and transmission success rate as the cost function,and then seeks to find a feasible path by MFA.Because MFA-RS uses a set of deterministic equations to replace the stochastic process in simulated annealing(SA)and uses saddle point approximation in the calculation of the stationary probability distribution at equilibrium,the convergence time is much less than the routing scheme based on SA(SA-RS).Simulation results demonstrate that MFA-RS is an effective algorithm and is very fit for WMNs.

Optimization and analysis of winglet configuration for solar aircraft

Installing winglets can notably improve the aerodynamic performance of solar aircraft.This paper proposes a multi-constraints optimization method of winglets for solar aircraft,aiming to enhance the corresponding uninterrupted cruising capability.An optimization objective function is formed and is separately studied in aerodynamic and structural terms.Qualitative analysis shows that the winglet design parameters are restricted by four special constraints(geometry,aerodynamics,energy and stability)of solar aircraft.The optimization process is constructed on the basis of a multi-island genetic algorithm,and carried out for a 15 m wingspan solar aircraft.Although the designed winglet is not as good as the traditional winglet in terms of drag and structural weight,the designed winglet provides a better 24 h cruising capability.The sensitivity between the objective function and the design parameters is investigated,and the winglet effects vary with respect to the wing aspect ratio(AR=10,15,19.6).The effect of the constraints is analysed quantitatively,and some basic laws are obtained.Moreover,the feasible design region and the possible optimal design parameters of winglets for different wing configurations are explored.The calculation results show that when the aspect ratio exceeds a certain value,the winglets will not benefit the aircraft.