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The utilization of newer spectrum bands such as in 5G and 6G networks, has the potential to inadvertently cause interference to passive sensing applications operating in the adjacent portions of spectrum. One such application that has received a lot of attention has been passive weather sensing where leakage from 5G mmWave band transmissions in the 26 GHz spectrum could potentially impact the observations of passive sensors on weather prediction satellites. To mitigate problems such as the above, we present a design framework that can be employed in mmWave networks by using filtennas (or filtering antennas) at the transmitter along with integrated resource allocation to minimize leakage into adjacent channels. Specifically, we propose an Iterative Leakage Aware Water Filling solution to allocate power and bandwidth in a system employing filtennas that guarantees performance requirements while reducing the leakage. In addition, a key contribution of this work is the characterization of the leakage function based on the order of filtennas which is incorporated in our resource allocation framework.
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Adaptive Risk-Aware Resource Orchestration for 5G Microservices over Multi-Tier Edge-Cloud Systems
Modern fifth-generation (5G) networks are increasingly moving towards architectures characterized by softwarization and virtualization. This paper addresses the complexities and challenges in deploying applications and services in the emerging multi-tiered 5G network architecture, particularly in the context of microservices-based applications. These applications, characterized by their structure as directed graphs of interdependent functions, are sensitive to the deployment tiers and resource allocation strategies, which can result in performance degradation and susceptibility to failures. Additionally, the threat of deploying potentially malicious applications exacerbates resource allocation inefficiencies. To address these issues, we propose a novel optimization framework that incorporates a probabilistic approach for assessing the risk of malicious applications, leading to a more resilient resource allocation strategy. Our framework dynamically optimizes both computational and networking resources across various tiers, aiming to enhance key performance metrics such as latency, accuracy, and resource utilization. Through detailed simulations, we demonstrate that our framework not only satisfies strict performance requirements but also surpasses existing methods in efficiency and security.
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- Award ID(s):
- 2226232
- PAR ID:
- 10628435
- Publisher / Repository:
- IEEE
- Date Published:
- ISSN:
- 2694-2941
- ISBN:
- 979-8-3503-0405-3
- Page Range / eLocation ID:
- 359 to 364
- Format(s):
- Medium: X
- Location:
- Denver, CO, USA
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/ICCWorkshops59551.2024.10615649
