تلفن: ۰۴۱۴۲۲۷۳۷۸۱
تلفن: ۰۹۲۱۶۴۲۶۳۸۴

دانلود رایگان مقاله انگلیسی رویکرد آموزشی زمانبندی دیدگاه غیر متمرکز – نشریه الزویر

عنوان فارسی: رویکرد آموزشی زمانبندی دیدگاه غیر متمرکز
عنوان انگلیسی: A learning approach to decentralised beacon scheduling
تعداد صفحات مقاله انگلیسی : 34 تعداد صفحات ترجمه فارسی : ترجمه نشده
سال انتشار : 2016 نشریه : الزویر - Elsevier
فرمت مقاله انگلیسی : PDF کد محصول : E41
محتوای فایل : PDF حجم فایل : 500 Kb
رشته های مرتبط با این مقاله: مهندسی فناوری اطلاعات
گرایش های مرتبط با این مقاله: شبکه های کامپیوتری
مجله: شبکه های ad hoc
دانشگاه: موسسه همیلتون، دانشگاه منوث، ایرلند
کلمات کلیدی: برنامه ریزی در Beacon، محدودیت رضایت غیر متمرکز، عمل جراحی تصادم آزاد
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چکیده

Abstract

Beaconing is usually employed to allow network discovery and to maintain synchronisation in mesh networking protocols, such as those defined in the IEEE 802.15.4e and IEEE 802.11s standards. Thus, avoiding persistent or consecutive collisions of beacons is crucial in order to ensure correct network operation. Beacons are also used in receiver-initiated medium access protocols to advertise that nodes are awake. Consequently, effective beacon scheduling can enable duty-cycle operation and reduce energy consumption. In this work, we propose a completely decentralised and low-complexity solution based on learning techniques to schedule beacon transmissions in mesh networks. We show the algorithm converges to beacon collision-free operation almost surely in finite time and evaluate converge times in different mesh network scenarios.

نتیجه گیری

9. Final Remarks

We have presented a completely decentralised and parsimonious mechanism for collision free-operation of beacon transmissions based on learning. The solution aims to solve crucial problems in current wireless mesh networks, such as those based on IEEE 802.15.4e and IEEE 802.11s standards, where beacon transmissions may successively collide making it difficult to discover neighbouring nodes and maintain synchronisation. It can also be used to efficiently support broadcast traffic in receiver-initiated WSNs. The proposed algorithm converges almost surely in finite time and the actual time to convergence in the scenarios of interest is low, making it quite practical for mesh networks involving sporadic mobility. We have also defined how to select the learning parameter in order to: i) keep the time to convergence low and ii) maintain the protocol simplicity and low overhead. Finally, we have considered the practical implications of deploying the presented mechanism considering non-ideal channel conditions as well as taking into account its integration in current standardisation efforts. We believe the proposed approach can be readily implemented in IEEE 802.15.4e and IEEE 802.11s, among others, with some changes in the standards.