Normal Measure Based Multi-Constrained Path Selection
基于矢量测量的多约束路径选择

Multi-constrained path (MCP) selection is one of the great challenges that QoS routing (QoSR) faces. Existing algorithms cannot make a good tradeoff among computation complexity, response speed and preventing from losing feasible solutions. Furthermore, neither linear path length function (LPLF) nor non-linear path length function (NLPLF) alone can solve QoS routing problems. A novel normal measure based path length function is defined and based on it, a normal measure based MCP (NMMCP) algorithm is proposed to solve m-constrained MCP problems. NMMCP makes a good tradeoff not only between on-demand computation and pre-computation, but also between LPLF and NLPLF based algorithms. By introducing Pareto optimal mechanism, NMMCP has nonlinear look-ahead ability. Extensive simulations show that NMMCP is very efficient when both performance and computation cost are taken into account.