Multi Criteria based Joint Admission Control for Heterogeneous Wireless Networks
Multi Criteria based Joint Admission Control for Heterogeneous Wireless Networks
复制标题
基于多标准的异构无线网络联合准入控制
DOI：
--
复制
发表时间：
2012
期刊：
影响因子：
--
通讯作者：
M. Alkhawlani
中科院分区：
文献类型：
--
作者：
M. Alkhawlani
异构无线网络（HWN）被定义为一种新型无线网络，任何人都可以根据用户标准，通过任何服务提供商的任何网络，以最高效、最优的方式与其他人随时随地进行通信，或享受任何网络运营商的任何服务。支持各种应用和服务以及在HWN中提供无处不在的覆盖的需要需要更复杂和智能的无线电资源管理技术，其使得能够在不同的无线电接入技术之间进行协调。本文研究了HWN中最重要的无线资源管理机制--联合接纳控制（Joint Admission Control，JAC），JAC负责处理HWN中所有新的或切换的业务请求，并检查进入的业务请求是否被接纳。然后，它分配所需的资源，并保证服务的服务质量（QoS）约束。本文提出了一种基于VIKOR决策支持系统的算法来解决现代HWN网络中的JAC问题。该算法的目的是减少不同的，不精确的，和矛盾的测量JAC标准来自不同的来源的影响。对JAC算法进行了性能分析，并与传统算法进行了比较。这些结果表明，我们开发的算法有显着的改善。
Heterogeneous Wireless Network (HWN) is defined as a new type of wireless networks where anyone can communicate with anyone else, anywhere and anytime, or enjoy any service of any network operator, through any network of any service provider in the most efficient and optimal way according to the user criteria. The needs for supporting various applications and services and for providing ubiquitous coverage in the HWN require more complex and intelligent radio resource management techniques that enable the coordination among the different radio access technologies. This paper considers the most important radio resource management mechanism in HWN that is Joint Admission Control (JAC). JAC handles all new or handoff service requests in the HWN and checks whether the incoming service requests to be admitted. Then, it allocates the required resources and guarantees the Quality of Service (QoS) constraints for the service. This paper develops a VIKOR decision support system based algorithm to address the JAC problem in the modern HWN networks. The proposed algorithm aims to decrease the influence of the dissimilar, imprecise, and contradictory measurements for the JAC criteria coming from different sources. A performance analysis is done and the results are compared with traditional algorithms for JAC. These results demonstrate a significant improvement with our developed algorithm.