نویسندگان | فرشته دهقانی,ناصر موحدی نیا |
---|---|
نشریه | Wireless Networks |
ضریب تاثیر (IF) | ثبت نشده |
نوع مقاله | Full Paper |
تاریخ انتشار | 2023-11-24 |
رتبه نشریه | علمی - پژوهشی |
نوع نشریه | الکترونیکی |
کشور محل چاپ | ایران |
نمایه نشریه | JCR |
چکیده مقاله
In recent years, content-centric networks (CCN) have introduced the significant feature of in-network caching, which saves transmission energy consumption in content distribution. However, because of the extra logic needed for the caching mechanism, one of these networks’ main challenges is optimizing the trade-off between transmission and caching energy consumption. Moreover, in an energy-aware CCN, less popular content is cached near the content provider despite more popular content caching near end users. Therefore, in real-time or delay-sensitive traffic with less popularity, this caching strategy degrades the quality of service, drops delayed chunks, and wastes energy consumption. Accordingly, designing an appropriate content caching policy to improve energy efficiency and service quality is a long-term goal of the green CCN. This paper considers minimizing energy consumption and the queuing delay in CCN as a multi-objective optimization problem. Thus, to drive the proposed approach, called ED-CCN-MOP, the CCN queuing delay for receiving the Interest and Data packets is analyzed and formulated. Furthermore, the ED-CCN-MOP model is solved using the proposed Non-dominated Sorting Markov Approximation (NSMA) method. According to the numerical results, the NSMA algorithm outperforms the NSGA-II, NSGA-III, and MODA algorithms by about 49%, 46%, and 38%, respectively, in terms of their average energy-delay-product metric with the possibility of distributed implementation. Furthermore, the quality of NSMA solutions is evaluated and compared using performance metrics. The results of this evaluation indicate that NSMA consistently achieves a high level of performance.
tags: resource allocation, Analysis of CCN queuing delay, Energy-aware caching strategy in green CCN , Markov approximation approach, Multiobjective optimization