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|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|10404||2006||11 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Computer Communications, Volume 29, Issue 6, 31 March 2006, Pages 730–740
A significant issue in current research pursuits is the formulation of the requirements and basic design options for the next-generation wireless network architecture. The next-generation of wireless systems will support a diverse set of access technologies and mobile devices, formulating a broad heterogeneous environment with increased requirements on network support operations. It is expected that the demanding breed of multimedia applications will even more considerably require Quality of Service support throughout the end-to-end path. This paper first provides a tutorial approach on next-generation wireless network architectures and more specifically on end-to-end QoS provision. We claim that dynamic resource management in the Core Network is a necessity due to the increased heterogeneity of the new environment. We subsequently present our proposal regarding a dynamic resource management scheme that is based on the concept of the Resource Pools. The Resource Pool concept is deeply analysed within the paper and simulation results prove its correctness and appropriateness.
The next-generation wireless networks will be principally formed through the evolution and convergence of current mobile communication systems and the IP technology. The foreseen architecture will retain the well-known bi-level structure, consisting of a multi-domain Core Network (CN) offering IP connectivity and services, and a set of wired and wireless Access Networks (AN) offering the last mile connectivity services to mobile users. The convergence concept has gained significant attention during the last years in the research, industrial and standardisation community, leading to a number of convergence scenarios and propositions, like in Refs. ,  and . The fundamental characteristic of next-generation networks is heterogeneity. Heterogeneity is the result of the different operations and capabilities of the multiple converged access networks, the reconfiguration and adaptation capabilities of end-user devices and applications, as well as the interworking model resulting from the various handover scenarios and the existence of multiple providers. The architecture of next-generation wireless networks will therefore have to deal with heterogeneity. The latter imposes strict requirements that have to be satisfied in order to provide a smooth and seamless service. These requirements affect the basic operations of the core network, including mobility management, network resource and Quality of Server (QoS) management, and overall AAA operation control, among others. This paper focuses on network resource management for QoS provisioning in a heterogeneous next-generation wireless network environment. The main motivation of our work is that the heterogeneous nature of such environment necessitates the existence of a dynamic resource management layer in the core network of the architecture, as briefly explained hereafter. In third generation (3G) or previous systems, the CN is not considered the bottleneck of the overall network. In such networks the bottleneck is always the pure wireless part of the AN, allowing the operators to properly dimension the remainder network (the wired part of the AN as well as the CN) so that minimum congestion will occur in that. Dimensioning here does not necessarily mean over-provisioning as one could claim, but instead a more or less static management of CN resources, according to predicted traffic patterns, and based on the standard CN's QoS capabilities. This is eventually true for any homogeneous wireless network that gives to the administrator the opportunity to study the traffic patterns, predict the traffic demands and at last appropriately dimension the network. Dimensioning in homogeneous wireless networks, although possible, is indeed very demanding and difficult, mainly due to user mobility. Dimensioning is, however, far more difficult for heterogeneous networks that expose dissimilar traffic patterns stemming from the multiple available access networks. Moreover, user mobility does not only entail an intra-system handover, but it may involve an inter-system one, resulting in considerable adaptation of the traffic involved. Furthermore, with the advent of ad hoc wireless networks, which can be configured on demand, dimensioning and provisioning of the core network becomes even more intense. Due to the aforementioned facts, dynamic resource management in the core of next-generation wireless networks appears to be a necessity. There is common consensus on the fact that CN will be a pure IP-based network, meaning that all CN operations will be based on mechanisms and protocols developed and used in the IP world. The chief standardisation body regarding IP is the Internet Engineering Task Force (IETF) . Concentrating on QoS, which is the focal point of this paper, IETF has basically defined two frameworks: the Integrated Services (IntServ) and the Differentiated Services (DiffServ). The former offers QoS guarantees with the aid of the RSVP protocol but exposes scalability problems, while the latter provides only soft-QoS-guarantees. The introduction of the Bandwidth Broker (BB) concept by the Internet2 QBone  was an effort to basically cater for resource management and admission control over DiffServ networks. However, the BB architecture has not been standardized in IETF. As it will be presented in Section 2, current research trends favour the BB-enhanced DiffServ framework compared to IntServ and RSVP. Our work, presented in this paper, is also based on this framework. The dynamic resource management presented in this paper is based on the concept of Resource Pools. Resource Pools (RPs) try to overcome the scalability problems of the centralised BB concept, by introducing a distributed and highly scalable resource management scheme, and cater for a dynamic distribution of resources to the different heterogeneous access networks connected to the CN based on real traffic demands. The fundamental idea is to organize a number of Edge Routers1 (ERs) sharing a common bottleneck element into groups, which are called RPs. Those groups will provide a dynamic and efficient way for sharing and shifting the available resources between RPs based on real traffic demands. In the context of the RPs model, some algorithms are proposed to cater for dynamic (re)-distribution of resources among RPs, in case the real resource demand is not met by the initial provisioning scheme. Those algorithms derive from the AQUILA  framework, which comprises a wired network, but are further enhanced to encounter the requirements introduced by the heterogeneous wireless segments. The rest of the paper is structured as follows. Section 2 presents a tutorial-in-nature approach for the next-generation wireless network architecture, identifying the basic network elements and operations, discussing the control layer needs for QoS provisioning and the network services provisioning issue, and lastly summarizing the state of the art and current trends in end-to-end QoS. Section 3 explains the dynamic resource management mechanism, while Section 4 presents some simulation results that prove its appropriateness. Finally, Section 5 contains the conclusions and future work.
نتیجه گیری انگلیسی
This article briefly discussed the end-to-end QoS provisioning process within the heterogeneous next-generation wireless network environment. It presented the emerging next-generation network architecture and highlighted some important issues regarding QoS provisioning within this architecture. The main contribution of the paper deals with a dynamic resource management scheme for the Core Network of the next-generation wireless network architecture. The paper provided justifications on the need for such scheme and then analytically illustrated its operation, and its major performance parameters. A simulation model has been developed and results are presented in order to prove the appropriateness and correctness of the scheme. The scheme supports an on-demand redistribution of resources, in order to take care of prioritised situations, like that occurred during a handoff. Simulations showed that the RPs achieve blocking probability targets with reasonable resources and distribute resources in a fair manner. The gain of RP is approximately 90% in terms of adaptation activity rate, meaning that only the 10% of primary resource reservation requests trigger an adaptation action. One possible extension of the proposed dynamic resource management scheme is to cater for precautionary measures in cases of handoff. Although the scheme already supports prioritised treatment of handoff resource needs, a possible further enhancement is to take into account the prediction of user movement, based on the notion of ‘mobile’ network services as well as on the appropriate mobility prediction algorithms. This would allow pre-allocating a specific portion of resources to the RPs that are going to need them in the near future with a high probability. Such an a priori allocation of resources would allow for less signalling traffic during a handoff, compared to the current situation, which implies that a handoff may cause an on-demand re-allocation of resources. However, we have to study the trade-off between the activity gain and the possible overall utilisation aggravation due to the pre-allocation of resources at an RP. Another important issue for future work would be the extension of the application of the RP concept within the Access Network. In other words, one could extent the Resource Pool Leaf at e.g. the cell level. In this way, one could expect an overall superior management of the network resources, although interworking with radio resource management mechanisms would be inevitable. However, even though we may expect an increased complexity of the resource management scheme, this extension may alleviate the common RRM mechanisms that will be most probably employed in next-generation wireless network architectures.