دانلود مقاله ISI انگلیسی شماره 43959
ترجمه فارسی عنوان مقاله

بهینه سازی کار مدیریت جابجایی در شبکه های چهار شهر سرمایه دار جهان

عنوان انگلیسی
Optimizing the mobility management task in networks of four world capital cities
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
43959 2015 11 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Journal of Network and Computer Applications, Volume 51, May 2015, Pages 18–28

ترجمه کلمات کلیدی
مدیریت محل های تلفن همراه - برنامه ریزی مناطق ثبت نام - بهینه سازی تکاملی چندهدفه
کلمات کلیدی انگلیسی
Mobile location management; Registration areas planning; Multiobjective evolutionary optimization
پیش نمایش مقاله
پیش نمایش مقاله  بهینه سازی کار مدیریت جابجایی در شبکه های چهار شهر سرمایه دار جهان

چکیده انگلیسی

In this paper, we study one of the most important management tasks in any Public Land Mobile Network: the mobile location management. In this management task, the network cells are grouped into logical areas (called the Registration Areas) in order to avoid the overload of the signaling network. The proper dimensioning of these Registration Areas is an important engineering issue that is modeled as a bi-objective optimization problem. In previous works by other authors, the Registration Areas planning problem was optimized by using the linear aggregation of the objective functions. This technique allows simplifying the optimization problem but has several drawbacks. That is why, we use our versions of two multiobjective optimization algorithms. Furthermore, a multiobjective approach provides a wide range of solutions among which the network operator could select the one that best meets its real requirements. With the aim of studying the mobile location management in realistic mobile environments, we have generated four novel mobile activity traces by importing four real networks topologies into a mobile networks simulation tool. Experimental results show that our proposals are very interesting because they achieve better solutions than the single-objective optimization algorithms proposed by other authors in a very less execution time.