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1. Utility-based scheduling for public displays with live content

   https://doi.org/10.1145/3321335.3324940  

   Bushman, Kristi; Labrinidis, Alexandros (June 2019, Proceedings of the 8th ACM International Symposium on Pervasive Displays - PerDis'19)

   The pervasiveness of public displays is prompting an increased need for "fresh" content to be shown, that is highly engaging and useful to passerbys. As such, live or time-sensitive content is often shown in conjunction with "traditional" static content, which creates scheduling challenges. In this work, we propose a utility-based framework and a novel scheduling algorithm for handling live and non-live content on public displays. We also experimentally evaluate our proposed algorithm against a number of alternatives under a variety of workloads. 

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2. Optimal Joint Offloading and Wireless Scheduling for Parallel Computing with Deadlines

   Qin, Xudong; Xu, Weijian; Li, Bin (June 2019, International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt))

   In this paper, we consider the problem of joint offloading and wireless scheduling design for parallel computing applications with hard deadlines. This is motivated by the rapid growth of compute-intensive mobile parallel computing applications (e.g., real-time video analysis, language translation) that require to be processed within a hard deadline. While there are many works on joint computing and communication algorithm design, most of them focused on the minimization of average computing time and may not be applicable for mobile applications with hard deadlines. In this work, we explicitly take hard deadlines for computing tasks into account and develop a joint offloading and scheduling algorithm based on the stochastic network optimization framework. The proposed algorithm is shown to achieve average energy consumption arbitrarily close to the optimal one. However, this algorithm involves a strong coupling between offloading and scheduling decisions, which yields significant challenges on its implementation. Towards this end, we first successfully decouple the offloading and scheduling decisions in the case with one time slot deadline by exploring the intrinsic structure of the proposed algorithm. Based on this, we further implement the proposed algorithm in the general setups. Simulations are provided to corroborate our findings. 

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3. Efficient Deterministic Federated Scheduling for Parallel Real-Time Tasks

   https://doi.org/10.1109/RTCSA50079.2020.9203660  

   Dinh, Son; Gill, Christopher; Agrawal, Kunal (August 2020, 2020 IEEE 26th International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA))

   null (Ed.)

   Federated scheduling is a generalization of partitioned scheduling for parallel tasks on multiprocessors, and has been shown to be a competitive scheduling approach. However, federated scheduling may waste resources due to its dedicated allocation of processors to parallel tasks. In this work we introduce a novel algorithm for scheduling parallel tasks that require more than one processor to meet their deadlines (i.e., heavy tasks). The proposed algorithm computes a deterministic schedule for each heavy task based on its internal graph structure. It efficiently exploits the processors allocated to each task and thus reduces the number of processors required by the task. Experimental evaluation shows that our new federated scheduling algorithm significantly outperforms other state-of-the-art federated-based scheduling approaches, including semi-federated scheduling and reservation-based federated scheduling, that were developed to tackle resource waste in federated scheduling, and a stretching algorithm that also uses the tasks' graph structures. 

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4. Simultaneous Multithreading and Hard Real Time: Can it be Safe?

   https://doi.org/10.4230/DARTS.6.1.1  

   Osborne, S.; Anderson, J. (July 2020, Proceedings of the 32nd Euromicro Conference on Real-Time Systems)

   The applicability of Simultaneous Multithreading (SMT) to real-time systems has been hampered by the difficulty of obtaining reliable execution costs in an SMT-enabled system. This problem is addressed by introducing a scheduling framework, called CERT-MT, that combines scheduling-aware timing analysis with a cyclic-executive scheduler in a way that minimizes SMT-related timing variations. The proposed scheduling-aware timing analysis is based on maximum observed execution times and accounts for the uncertainty inherent in measurement-based timing analysis. The timing analysis is found to work for tasks with and without SMT, though some adjustments are required in the former case. A large-scale schedulability study is presented that shows CERT-MT can schedule systems with total utilizations approaching 1.4 times the core count, without sacrificing safety. 

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5. User Scheduling and Power Allocation for Content Delivery in Caching Helper Networks

   https://doi.org/10.1109/ICC40277.2020.9148874  

   Choi, Minseok; Molisch, Andreas F.; Kim, Joongheon (June 2020, IEEE Int. Conf. Comm.)

   This paper proposes a user scheduling and power allocation method for content delivery in wireless caching helper networks without any stringent constraint on the interference model. For supporting delay-sensitive and time-varying user demands, the actual delivery quantity of the requested content should be dynamically controlled by advanced scheduling and power allocation. In addition, it is difficult for a central unit to control the content delivery due to a lack of knowledge of the entire time-varying network; therefore, a belief-propagation (BP)-based algorithm that facilitates distributed decisions on user scheduling and power allocation at every caching helper is presented. The proposed delivery scheme maximizes power efficiency while limiting the average delay of user request satisfactions by managing interference among users well. Simulation results show that the proposed scheme provides almost the same delay performance as the exhaustively found optimal one at the expense of little power consumption. 

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