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1. Eiffel: Efficient and Flexible Software Packet Scheduling

   Saeed, Ahmed; Zhao, Yimeng; Dukkipati, Nandita; Ammar, Mostafa; Zegura, Ellen; Harras, Khaled; Vahdat, Amin (February 2019, Proceedings of the 16th USENIX Symposium on Networked Systems Design and Implementation (NSDI ’19))

   Packet scheduling determines the ordering of packets in a queuing data structure with respect to some ranking function that is mandated by a scheduling policy. It is the core component in many recent innovations to optimize network performance and utilization. Our focus in this paper is on the design and deployment of packet scheduling in soft-ware. Software schedulers have several advantages over hardware including shorter development cycle and flexibility in functionality and deployment location. We substantially improve current software packet scheduling performance,while maintaining flexibility, by exploiting underlying features of packet ranking; namely, packet ranks are integers and, at any point in time, fall within a limited range of values.We introduce Eiffel, a novel programmable packet scheduling system. At the core of Eiffel is an integer priority queue based on the Find First Set (FFS) instruction and designed to support a wide range of policies and ranking functions efficiently. As an even more efficient alternative, we also pro-pose a new approximate priority queue that can outperform FFS-based queues for some scenarios. To support flexibility,Eiffel introduces novel programming abstractions to express scheduling policies that cannot be captured by current, state-of-the-art scheduler programming models. We evaluate Eiffel in a variety of settings and in both kernel and userspace deployments. We show that it outperforms state of the art systems by 3-40x in terms of either number of cores utilized for network processing or number of flows given fixed processing capacity 

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2. Recorp: Receiver-oriented Policies for Industrial Wireless Networks

   https://doi.org/10.1145/3460618  

   Brummet, Ryan; Hossain, Md Kowsar; Chipara, Octav; Herman, Ted; Stewart, David E. (July 2021, ACM Transactions on Sensor Networks)

   Future Industrial Internet-of-Things (IIoT) systems will require wireless solutions to connect sensors, actuators, and controllers as part of high data rate feedback-control loops over real-time flows. A key challenge in such networks is to provide predictable performance and adaptability in response to link quality variations. We address this challenge by developing RECeiver ORiented Policies (Recorp), which leverages the stability of IIoT workloads by combining offline policy synthesis and run-time adaptation. Compared to schedules that service a single flow in a slot, Recorp policies share slots among multiple flows by assigning a coordinator and a list of flows that may be serviced in the same slot. At run-time, the coordinator will execute one of the flows depending on which flows the coordinator has already received. A salient feature of Recorp is that it provides predictable performance: a policy meets the end-to-end reliability and deadline of flows when the link quality exceeds a user-specified threshold. Experiments show that across IIoT workloads, policies provided a median increase of 50% to 142% in real-time capacity and a median decrease of 27% to 70% in worst-case latency when schedules and policies are configured to meet an end-to-end reliability of 99%. 

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3. Distributed Scheduling Algorithms for Optimizing Information Freshness in Wireless Networks

   Talak, Rajat; Karaman, Sertac; Modiano, Eytan (July 2018, SPAWC)

   Age of Information (AoI), measures the time elapsed since the last received information packet was generated at the source. We consider the problem of AoI minimization for singlehop flows in a wireless network, under pairwise interference constraints and time varying channel. We consider simple, yet broad, class of distributed scheduling policies, in which a transmission is attempted over each link with a certain attempt probability. We obtain an interesting relation between the optimal attempt probability and the optimal AoI of the link, and its neighboring links. We then show that the optimal attempt probabilities can be computed by solving a convex optimization problem, which can be done distributively. 

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4. Recorp: Receiver-Oriented Policies for Industrial Wireless Networks

   https://doi.org/10.1109/IoTDI49375.2020.00020  

   Brummet, Ryan; Chipara, Octav; Herman, Ted (April 2020, 2020 IEEE/ACM Fifth International Conference on Internet-of-Things Design and Implementation (IoTDI))

   The next generation of Industrial Internet-of-Things (IIoT) systems will require wireless solutions to connect sensors, actuators, and controllers as part of feedback-control loops over real-time flows. A key challenge in such networks is to provide predictable performance and adaptability to variations in link quality. We address this challenge by developing Receiver Oriented Policies (RECORP), which leverages the stability of IIoT workloads to build a solution that combines offline policy synthesis and run-time adaptation. Compared to schedules that service a single flow in a slot, RECORP policies share slots among multiple flows by assigning a coordinator and a set of candidate flows in the same slot. At run-time, the coordinator will dynamically execute one of the flows depending on what flows the coordinator has already received. The net effect of this strategy is that a node can dynamically repurpose the retransmissions remaining after receiving the data of an incoming flow to service other incoming flows opportunistically. Therefore, the flows that are executed in a slot can be adapted in response to the variable link conditions observed at run-time. Furthermore, RECORP also provides predictable performance: a policy meets the end-to-end reliability and deadline constraints of flows given probabilistic link qualities. When RECORP policies and schedules are configured to meet the same end-to-end reliability target of 99%, larger-scale multihop simulations show that across typical IIoT workloads, policies provided a median improvement of 1.63 to 2.44 times in real-time capacity as well as a median reduction of 1.45 to 2.43 times in worst-case latency. 

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5. Average Age of Information in Update Systems with Active Sources and Packet Delivery Errors

   https://doi.org/10.1109/LWC.2020.2983397  

   Farazi, S.; Klein, A.; Brown, D. (August 2020, IEEE wireless communications letters)

   This paper studies the “age of information” (AoI) in a multi-source status update system where N active sources each send updates of their time-varying process to a monitor through a server with packet delivery errors. We analyze the average AoI for stationary randomized and round-robin scheduling policies. For both of these scheduling policies, we further analyze the effect of packet retransmission policies, i.e., retransmission without re- sampling, retransmission with resampling, or no retransmission, when errors occur. Expressions for the average AoI are derived for each case. It is shown that the round-robin schedule policy in conjunction with retransmission with resampling when errors occur achieves the lowest average AoI among the considered cases. For stationary randomized schedules with equiprobable source selection, it is further shown that the average AoI gap to round-robin schedules with the same packet management policy scales as O(N). Finally, for stationary randomized policies, the optimal source selection probabilities that minimize a weighted sum average AoI metric are derived. 

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