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Emerging wireless technologies are envisioned to support a variety of applications that require simultaneously maintaining low latency and high reliability. Non-orthogonal multiple access techniques constitute one candidate for grant-free transmission alleviating the signaling requirements for uplink transmissions. In open-loop transmissions over fading channels, in which the transmitters do not have access to the channel state information, the existing approaches are prone to facing frequent outage events. Such outage events lead to repeated re-transmissions of the duplicate information packets, penalizing the latency. This paper proposes a multi-access broadcast approach in which each user splits its information stream into several information layers, each adapted to one possible channel state. This approach facilitates preventing outage events and improves the overall transmission latency. Based on the proposed approach, the average queuing delay of each user is analyzed for different arrival processes at each transmitter. First, for deterministic arrivals, closed-form lower and upper bounds on the average delay are characterized analytically. Secondly, for Poisson arrivals, a closed-form expression for the average delay is delineated using the Pollaczek-Khinchin formula. Based on the established bounds, the proposed approach achieves less average delay than single-layer outage approaches. Under optimal power allocation among the encoded layers, numerical evaluations demonstrate that the proposed approach significantly minimizes average sum delays compared to traditional outage approaches, especially under high arrival rates.
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Load Balancing and Generalized Split State Reconciliation in Event Driven Systems
Event driven applications are often built with message queuing systems that provide no temporal upper bound on message delivery. However, many modern event driven applications, like a system inferring traffic conditions and generating recommendations to road users based on sensor data, are latency sensitive. Traditional message queuing systems use static load assignment algorithms that guarantee event ordering while mostly ignoring a temporal upper bound on message delivery. Another class of message queuing systems use stateless operators which deliver messages (events) quickly but pass the burden of stream state management to user applications. Synchronous communication patterns, on the other hand, provide an upper bound for message delivery while ensuring message ordering but unnecessarily bind limited resources reducing efficiency. In this paper we explore load balancing choices in asynchronous systems and their impact on queuing delay. We then propose a load balancing framework, SMALOPS, for event driven applications with dynamically changing load and quick message delivery requirements. Our experiments confirm that with smarter load balancing, the \mathbf9 9 % ile response times for events can be improved by as much as 73 %, compared to traditional message queuing systems. SMALOPS introduces the following:•A load balancing algorithm that can significantly reduce queuing delay in message delivery systems.•Mechanisms enabling consumers to recover stream state when either the message delivery system does not support stateful operators or the state has been split by moving streams between operators.
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- Award ID(s):
- 1837382
- PAR ID:
- 10588702
- Publisher / Repository:
- IEEE
- Date Published:
- ISBN:
- 979-8-3503-6387-6
- Page Range / eLocation ID:
- 127 to 132
- Format(s):
- Medium: X
- Location:
- Aarhus, Denmark
- 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/ACSOS61780.2024.00031
