## 1 Introduction  
Next generation networks are increasingly being characterized by the convergence of heterogeneous fixed and wireless access network technologies such as WiMAX, WLAN, xDSL, and Passive Optical Networks, _etc._ towards interconnectivity with IP-based core networks. The management and control of network resources in such converged domains so as to provide the QoS that will in turn deliver satisfactory end user QoE poses significant technical challenges, given the complexity introduced by the integration of diverse QoS control mechanisms that may be deployed within each access technology on the end-to-end transport path. A promising network management approach that can be employed to overcome the challenges is the Policy-Based Network Management (PBNM) paradigm. PBNM allows for configuration and control of the network as a whole thus eliminating the need to individually manage each network entity. Thus, PBNM can simplify the administration of complex operational characteristics of a network, including QoS, access control, network security, and IP address allocation [1]. PBNM systems generally use hierarchical structures and will facilitate the management of next generation networks [2]. Moreover, PBNM provides the means for application transparency across existing and emerging access technologies which permit applications to be transport layer-agnostic when deployed [3]. It is also an effective means to equip networks with the ability to provide an automatic response to network conditions according to _pre-defined policies_, and is considered the best approach to ease the complex network configuration process involved in the integration of network services into a single large network [4,5]. These advantages of the PBNM approach and its well documented potential to facilitate QoS management in converged networks motivates its adoption as the underlying design paradigm for our proposed QoS management framework, CNQF (Converged Networks QoS Framework). CNQF is a PBNM framework designed to provide homogeneous, unified, end-to-end QoS management over heterogeneous access technologies, together with scalable and adaptive resource control. From the operational point of view, CNQF comprises of distributed _Policy Decision Points_ (PDPs) which handle various management and control decisions driven by _high-level declarative policies_ and enforced at _Policy Enforcement Points_ (PEPs) such as gateways, routers, access points, switches _etc._ within the converged network's management domain. CNQF will benefit operators through providing support for critical policy control and adaptation functionality needed to deliver a wide variety of high-value services with guaranteed QoS across fixed and wireless access technologies. Furthermore, functionalities for _context-aware_ resource control have been incorporated within the CNQF architecture as a crucial PBNM enhancing feature to enable value-added capability to intelligently manage network resources and potentially increase revenue for network providers. Our previous work presented the proposed CNQF architecture, detailing the subsystems, elements, and their interaction whilst also exemplifying some use case scenarios for _context-driven QoS control_[6]. In this paper we present the implementation of CNQF in Java, validating key elements functionality within a policy-driven QoS control scenario. Furthermore, the paper also presents an experimental evaluation of _fuzzy logic based resource-adaptive admission control for tiered services management_ built into the CNQF framework prototype. Incorporating fuzzy logic into the PBNM framework potentially allows not only intelligent and adaptive resource control under dynamicoperational conditions but also an intuitive and cost-effective means to integrate operator policies with extensible rule-based control. The paper is organized as follows. Related work is reviewed next in Section 2, while Section 3 summarizes the CNQF framework architecture.