Cloud computing is an emerging computing paradigm that may have a significant impact on various aspects of the development of information infrastructure. In a Cloud environment, different types of network resources need to be virtualized as a series of service components by network virtualization, and these service components should be further composed into Cloud services provided to end users. Therefore Quality of Service (QoS) aware service composition plays a crucial role in Cloud service provisioning. This paper addresses the problem on how to compose a sequence of service components for QoS guaranteed service provisioning in a virtualization-based Cloud computing environment. The contributions of this paper include a system model for Cloud service provisioning and two approximation algorithms for QoS-aware service composition. Specifically, a system model is first developed to characterize service provisioning behavior in virtualization-based Cloud computing, then a novel approximation algorithm and a variant of a well-known QoS routing procedure are presented to resolve QoS-aware service composition. Theoretical analysis shows that these two algorithms have the same level of time complexity. Comparison study conducted based on simulation experiments indicates that the proposed novel algorithm achieves better performance in time efficiency and scalability without compromising quality of solution. The modeling technique and algorithms developed in this paper are general and effective; thus are applicable to practical Cloud computing systems.

The cognitive radio technique promises to manage and allocate the scarce radio spectrum in the highly varying and disparate modern environments. This paper considers a cognitive radio scenario composed of two queues for the primary (licensed) users and cognitive (unlicensed) users. According to the Markov process, the system state equations are derived and an optimization model for the system is proposed. Next, the system performance is evaluated by calculations which show the rationality of our system model. Furthermore, discussions among different parameters for the system are presented based on the experimental results.

It has been shown that power control is an efficient approach to achieve the quality of service (QoS) requirement in wireless networks. In this letter, we present a utility function that denotes the QoS and energy efficiency of each wireless terminal. We propose a framework of power control based on the game theory for the QoS of wireless mesh networks (WMNs). In this framework, all players do their best to maximize their own utility. Furthermore, we present a Nash Equilibrium (NE) point of the power control game. We prove that the equilibrium is inefficient, and we propose a distributed power control algorithm that improves the total utility with respect to the NE point. Finally, the proposed framework is evaluated by a numerical experiment, the results of which show the rationality of our system model and the efficiency of our power control algorithm.