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In this paper, an operating system scheduling algorithm based on Double DQN (Double Deep Q network) is proposed, and its performance under different task types and system loads is verified by experiments. Compared with the traditional…

Machine Learning · Computer Science 2025-04-01 Xiaoxuan Sun , Yifei Duan , Yingnan Deng , Fan Guo , Guohui Cai , Yuting Peng

We present a lightweight and interpretable decision framework for dynamic edge server selection in latency-critical applications that explicitly accounts for tail risk and switching stability. Each candidate server is characterised by…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-04-24 Mohan Liyanage , Arnova Abdullah , Eldiyar Zhantileuov , Rolf Schuster

We introduce a novel data-driven method to mitigate the risk of cascading failures in delayed discrete-time Linear Time-Invariant (LTI) systems. Our approach involves formulating a distributionally robust finite-horizon optimal control…

Optimization and Control · Mathematics 2023-10-19 Guangyi Liu , Arash Amini , Vivek Pandey , Nader Motee

We examine optimal execution models that take into account both market microstructure impact and informational costs. Informational footprint is related to order flow and is represented by the trader's influence on the flow imbalance…

Trading and Market Microstructure · Quantitative Finance 2014-10-21 Kyle Bechler , Mike Ludkovski

Edge computing operates between the cloud and end users and strives to provide low-latency computing services for simultaneous users. Redundant use of multiple edge nodes can reduce latency, as edge systems often operate in uncertain…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-11-26 Pei Peng , Emina Soljanin

Time series analysis has gained significant attention due to its critical applications in diverse fields such as healthcare, finance, and sensor networks. The complexity and non-stationarity of time series make it challenging to capture the…

Machine Learning · Computer Science 2024-10-31 Guancen Lin , Cong Shen , Aijing Lin

Traditional AI alignment primarily focuses on individual model outputs; however, autonomous agents in long-horizon workflows require sustained reliability across entire interaction trajectories. We introduce APEMO (Affect-aware Peak-End…

Artificial Intelligence · Computer Science 2026-02-23 Hanjing Shi , Dominic DiFranzo

We consider the problem of remanufacturing planning in the presence of statistical estimation errors. Determining the optimal remanufacturing timing, first and foremost, requires modeling of the state transitions of a system. The estimation…

Optimization and Control · Mathematics 2021-03-19 Zhicheng Zhu , Yisha Xiang , Ming Zhao , Yue Shi

A heterogeneous architecture composed by a host and an accelerator must frequently deal with situations where several independent tasks are available to be offloaded onto the accelerator. These tasks can be generated by concurrent…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-07-03 A. J. Lázaro-Muñoz , J. M. González-Linares , J. Gómez-Luna , N. Guil

The safety and resilience of civil infrastructure systems are increasingly threatened by compounded risks from various hazard events and structural deterioration due to environmental stressors. This study presents a comprehensive…

Systems and Control · Electrical Eng. & Systems 2026-04-28 Sudhir P. Jodha , Konstantinos G. Papakonstantinou

Current large language model agent frameworks prioritize autonomy but lack the governability mechanisms required for enterprise deployment. High-risk write operations proceed without independent review, complex tasks lack acceptance…

Artificial Intelligence · Computer Science 2026-05-12 Kai Pan , Rong Hou

One of the major challenges in distributed systems is establishing consistency among replicated data in a timely fashion. While the consistent ordering of events has been extensively researched, the time span to reach a consistent state is…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-10-29 Moritz Schattka

Real-life parallel machine scheduling problems can be characterized by: (i) limited information about the exact task duration at scheduling time, and (ii) an opportunity to reschedule the remaining tasks each time a task processing is…

Optimization and Control · Mathematics 2023-11-22 Izack Cohen , Krzysztof Postek , Shimrit Shtern

Accurately estimating workload runtime is a longstanding goal in computer systems, and plays a key role in efficient resource provisioning, latency minimization, and various other system management tasks. Runtime prediction is particularly…

Machine Learning · Computer Science 2025-03-11 Tianshu Huang , Arjun Ramesh , Emily Ruppel , Nuno Pereira , Anthony Rowe , Carlee Joe-Wong

The rapid growth of large language model (LLM) services imposes increasing demands on distributed GPU inference infrastructure. Most existing scheduling systems follow a reactive paradigm, relying solely on the current system state to make…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-09-17 Chengze Du , Zhiwei Yu , Heng Xu , Haojie Wang , Bo liu , Jialong Li

The demand for stringent interactive quality-of-service has intensified in both mobile edge computing (MEC) and cloud systems, driven by the imperative to improve user experiences. As a result, the processing of computation-intensive tasks…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-07-28 Ngoc Hung Nguyen , Van-Dinh Nguyen , Anh Tuan Nguyen , Nguyen Van Thieu , Hoang Nam Nguyen , Symeon Chatzinotas

Shared resource interference is observed by applications as dynamic performance asymmetry. Prior art has developed approaches to reduce the impact of performance asymmetry mainly at the operating system and architectural levels. In this…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-09-24 Jing Chen , Pirah Noor Soomro , Mustafa Abduljabbar , Madhavan Manivannan , Miquel Pericas

Time delays pose an important challenge in networked control systems, which are now ubiquitous. Focusing on switched systems, we introduce a framework that provides an upper bound for errors caused by switching delays. Our framework is…

Systems and Control · Computer Science 2017-12-27 Kengo Kido , Sean Sedwards , Ichiro Hasuo

Power consumption is a critical consideration in high performance computing systems and it is becoming the limiting factor to build and operate Petascale and Exascale systems. When studying the power consumption of existing systems running…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-01-27 Radim Vavřík , Antoni Portero , Štěpán Kuchař , Martin Golasowski , Simone Libutti , Giuseppe Massari , William Fornaciari , Vít Vondrák

In modern computer systems, jobs are divided into short tasks and executed in parallel. Empirical observations in practical systems suggest that the task service times are highly random and the job service time is bottlenecked by the…

Performance · Computer Science 2017-02-08 Yin Sun , C. Emre Koksal , Ness B. Shroff