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Showing papers by "Sonia Fahmy published in 2021"


Journal ArticleDOI
TL;DR: In this article, the authors discuss the challenges encountered by network orchestrators in allocating resources to disparate 5G network slices, and propose the use of artificial intelligence to make core placement and scaling decisions that meet the requirements of network slices deployed on shared infrastructure.
Abstract: Network slicing enables communication service providers to partition physical infrastructure into logically independent networks. Network slices must be provisioned to meet the service-level objectives (SLOs) of disparate offerings, such as enhanced mobile broadband, ultrareliable low-latency communications, and massive machine-type communications. Network orchestrators must customize service placement and scaling to achieve the SLO of each network slice. In this article, we discuss the challenges encountered by network orchestrators in allocating resources to disparate 5G network slices, and propose the use of artificial intelligence to make core placement and scaling decisions that meet the requirements of network slices deployed on shared infrastructure. We explore how artificial intelligence-driven scaling algorithms, coupled with functionality-aware placement, can enable providers to design closed-loop solutions to meet the disparate SLOs of future network slices.

6 citations


Journal ArticleDOI
TL;DR: A powerful computational framework is developed that can compute an optimized competitive ratio based on the class of affine policies and a robustification procedure is designed to produce an online algorithm that can attain good performance for both average-case and worst-case inputs.
Abstract: We investigate competitive online algorithms for online convex optimization (OCO) problems with linear in-stage costs, switching costs and ramp constraints. While OCO problems have been extensively studied in the literature, there are limited results on the corresponding online solutions that can attain small competitive ratios. We first develop a powerful computational framework that can compute an optimized competitive ratio based on the class of affine policies. Our computational framework can handle a fairly general class of costs and constraints. Compared with other competitive results in the literature, a key feature of our proposed approach is that it can handle scenarios where infeasibility may arise due to hard feasibility constraints. Second, we design a robustification procedure to produce an online algorithm that can attain good performance for both average-case and worst-case inputs. We conduct a case study on Network Functions Virtualization (NFV) orchestration and scaling to demonstrate the effectiveness of our proposed methods.

5 citations


Proceedings ArticleDOI
10 May 2021
TL;DR: CoRE as mentioned in this paper uses non-linear sampling in both the spatial and temporal domains to achieve robustness to view direction prediction error and transient wireless network bandwidth fluctuation, which reduces data transfer amounts, stalls, and H.264 decoding overhead, increases frame rates, and eliminates missing pixels.
Abstract: We propose CoRE, a 360° video streaming approach that reduces bandwidth requirements compared to transferring the entire 360° video. CoRE uses non-linear sampling in both the spatial and temporal domains to achieve robustness to view direction prediction error and to transient wireless network bandwidth fluctuation. Each CoRE frame samples the environment in all directions, with full resolution over the predicted field of view and gradually decreasing resolution at the periphery, so that missing pixels are avoided, irrespective of the view prediction error magnitude. A CoRE video chunk has a main part at full frame rate, and an extension part at a gradually decreasing frame rate, which avoids stalls while waiting for a delayed transfer. We evaluate a prototype implementation of CoRE through trace-based experiments and a user study, and find that, compared to tiling with low-resolution padding, CoRE reduces data transfer amounts, stalls, and H.264 decoding overhead, increases frame rates, and eliminates missing pixels.

4 citations