Optimization decomposition approach for layered QoS scheduling in grid computing
The paper presents optimization decomposition based layered Quality of Service (QoS) scheduling for computational grid. Cross layer joint QoS scheduling is studied by considering the global problem as decomposed into three sub-problems: resource allocation at the fabric layer, service composing at the collective layer, and user satisfaction degree at the application layer. The paper proposes a complete solution from optimization modeling, Lagrange relaxation based decomposition, to solutions for each sub-problem Lagrange relaxation based decomposition. These aspects match the vertical organization of the considered grid system: each layer trade with adjacent layers to find a global optimum of the whole grid system. Through multi-layer QoS joint optimization approach, grid global QoS optimization can be achieved. The cross layer policy produces an optimal set of grid resources, service compositions, and users payments at the fabric layer, collective layer and application layer, respectively, to maximize global grid QoS. The owner of each layer obtains inputs from other layers, tries to maximize its own utility and provides outputs back to other layers. This iterative process lasts until presumably all layers arrive at the same solution.
optimization decomposition layered qos scheduling grid computing optimization modeling