| NSF Org: |
ECCS Div Of Electrical, Commun & Cyber Sys |
| Recipient: |
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| Initial Amendment Date: | September 9, 2020 |
| Latest Amendment Date: | August 9, 2023 |
| Award Number: | 2030101 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Huaiyu Dai
hdai@nsf.gov (703)292-4568 ECCS Div Of Electrical, Commun & Cyber Sys ENG Directorate For Engineering |
| Start Date: | October 1, 2020 |
| End Date: | September 30, 2025 (Estimated) |
| Total Intended Award Amount: | $450,000.00 |
| Total Awarded Amount to Date: | $808,000.00 |
| Funds Obligated to Date: |
FY 2022 = $50,000.00 FY 2023 = $308,000.00 |
| History of Investigator: |
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| Recipient Sponsored Research Office: |
3 RUTGERS PLZ NEW BRUNSWICK NJ US 08901-8559 (848)932-0150 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
98 Frelinghuysen Road Piscataway NJ US 08854-3925 |
| Primary Place of Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): |
SII-Spectrum Innovation Initia, Special Projects - CNS, Networking Technology and Syst, CCSS-Comms Circuits & Sens Sys |
| Primary Program Source: |
01002223DB NSF RESEARCH & RELATED ACTIVIT 01002021DB NSF RESEARCH & RELATED ACTIVIT |
| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.041, 47.049, 47.070 |
ABSTRACT
The rapid growth of mobile multimedia applications and the Internet of Things (IoTs) have placed severe demands on wireless network infrastructures such as ultra-low latency, user experience continuity, and high reliability. Mobile devices are nowadays the predominant medium of access to Internet services due to an increase in their computation and communication capabilities. However, enabling applications that require real-time, in-the-field data collection and processing using mobile devices is still challenging due to (1) the insufficient computing capabilities and unavailability of aggregated/global data on individual mobile devices and (2) the communication cost and response time involved in offloading data to remote computing resources for centralized computation. In light of these limitations, the Mobile Edge Computing (MEC) concept has emerged, which aims at uniting telco, IT, and cloud computing to deliver cloud services directly from the network edge.. Edge Computing allows for the execution of applications in close proximity to the end users, which reduces the end-to-end delay and the costly backhaul bandwidth consumption back to a centralized cloud computing environment. The flexibility of Next Gen (NG)-Radio Access Networks (RAN) allows a move from a "full centralization" to a "distributed approach" in MEC.
The proposed xl_NGRAN framework for 5G (virtualized) cellular networks makes optimized cross-layer decisions for on-demand resource allocation and in-network content caching, and navigates the tradeoffs among radio resources, system cost, LTE/WiFi technology coexistence, and caching service. With a cloud-based framework, and specifically via NG-RAN virtualization, network resources including physical infrastructure and spectrum are abstracted in such a way as to provide a developing platform to support various services, thus maximizing resource utilization. The framework performance will be assessed via three research tasks and one validation/assessment plan considering Augmented Reality (AR)-based applications in a smart-device context. In Task 1, resource-allocation solutions will be designed, while considering LTE/WiFi coexistence requirements, to minimize the power consumption at both the cell sites and the Central Unit (CU) pool by dynamically adapting the Distributed Unit (DU) density and size of the Virtual Machines (VMs) hosting the DU pool based on traffic fluctuations. In Task 2, functional splitting will be enabled thought cross-layer design; a novel dynamic radio-resource allocation and the flexible functional split will be introduced to optimize the accumulated data rate and network power consumption in NG-RANs. In Task 3, the joint problem of service caching and task-offloading assignment will be studied in a dense network where each user can exploit the degrees of freedom in offloading different portions of its computation task to nearby DUs.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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