Market-based self-optimization for autonomic service overlay networks

Rather than managing their heterogeneity and dynamic behavior through centralized intervention, overlay nodes can be programmed to self-organize and self-manage the network. To achieve the highest performance within a service overlay, they are further expected to self-optimize the network, by cooperatively providing and allocating resources in an optimal manner. However, since nodes are inherently selfish about resources they contribute or consume, self-optimization could not be achieved if they are not given the correct incentives. In this paper, we investigate the effectiveness of a market-based incentive mechanism in directing nodes´ behavior and enabling self-optimizations. We have designed an intelligent market model for a service overlay network, based on which individual nodes, being service producers and consumers, determine their own resource contributions, consumptions, or service prices based on their own utility maximization goals. We also propose optimal decision making solutions for nodes to achieve their self-interests; in particular, service providers are provided with a control-based pricing solution based on system identification techniques. With the multicast streaming application as an example, we show through simulations that, even when selfish nodes all seek their maximal utilities, the resulting network still achieves close-to-optimal performance in both steady and dynamic states. The results also indicate that, by encouraging nodes to behave selfishly and intelligently in a designed market, self-optimization in other autonomic systems may be facilitated in the presence of node selfishness.