SIGMETRICS

Every year, the Association for Computing Machinery (ACM) spearheads a series of Student Research Competitions (SRCs) at ACM-sponsored or co-sponsored conferences. These SRCs provide graduate (Masters or PhD program) and undergraduate students an ...

Hyperparameters refer to a set of parameters of a machine learning model that are fixed and not adjusted during training. A fundamental problem in this context is hyperparameter tuning which refers to the problem of identifying the best values for a set ...

Queueing networks serve as a popular performance model in the analysis of business processes and computer systems [4]. Solving queueing network models helps the decision making of system designers. System response time and throughput are two key ...

Multiserver queueing theory emphasizes one-server-per-job models, such as the M/G/k. Such models were popular for decades in the study of computing systems. However, oneserver- per-job models no longer reflect the behavior of many modern computing ...

Motivation. Microservices architecture has become more prevalent in cloud-based applications where small, looselycoupled service components work together to handle user requests [1]. This architecture differs greatly from traditional monolithic ...

As edge computing capabilities increase, model learning deployments in a heterogeneous edge environment have emerged. We consider an experimental design network, as introduced by Liu et al., in which network routing and rate allocation is designed to aid ...

Blockchains are siloed by nature. A longtime limitation of blockchain technology is that individual cryptocurrencies are bound to their own chains. Users and applications need to transfer arbitrary data and funds across blockchains. At its peak in 2021, ...

Wireless sensors have already been used for a long time in military, health, and agricultural environments [6]. Despite the advances in precision agriculture, wireless sensor networks remain a distant reality for small farmers, mainly greenhouse farmers, ...

Exoskeleton fit evaluation using pose estimation is necessary to ensure exoskeletons promote productivity in industrial settings. However, both marker-based and markerless vision based systems consist of uncertainties in tracking human joints while a ...

Abstract-Multi-modal deep neural networks (DNNs) have become increasingly pervasive in many machine learning application domains due to their superior accuracy by fusing various modalities together. However, multi-modal DNNs present many unique ...

The ACM SIGMETRICS Doctoral Dissertation Award recognizes outstanding thesis research by doctoral candidates in the field of performance evaluation analysis of computer systems. Nominations for the 2023 award were sought from all faculty with graduating ...

Scheduling theory is a key tool for reducing latency (i.e. response time) in queueing systems. Scheduling, i.e. choosing the order in which to serve jobs, can reduce response time by an order of magnitude with no additional resources. Scheduling theory ...

Stochastic Processing Networks (SPNs) [24] are ubiquitous in engineering with applications in Data Centers (eg. packet routing), Telecommunication (eg. call centers), Transportation, etc. Stochastic Matching Networks (SMNs) are newly emerging variation ...

Sequential decision-making algorithms are ubiquitous in the design and optimization of large-scale systems due to their practical impact. The typical algorithmic paradigm ignores the sequential notion of these problems: use a historical dataset to ...

Augmented Reality (AR) devices offer a rich, immersive experience that provides the user with a blend of the physical and the synthetic, digitally augmented world. This augmentation is made possible by the AR device's sensors, which are constantly ...

Brief Biography: Zhongdong Liu is a final-year Ph.D. student in the Department of Computer Science at Virginia Tech. He received his B.S. degree in Mathematics and Applied Mathematics with honors from Northeast Forestry University in 2016. His research ...

Brief Biography: Tasmeen Zaman Ornee is a PhD candidate at the Electrical and Computer Engineering Department of Auburn University. She joined the Real-time Networking lab in Fall 2018. Her PhD supervisor is Prof. Yin Sun. She completed her M.Sc. in ...

Brief Biography: Abhin Shah is a final-year Ph.D. student in the department of Electrical Engineering and Computer Science atMIT, where he is a recipient ofMIT's Jacobs Presidential Fellowship. He has interned with Google Research (2021) and IBM Research ...

Brief Biography: Md Kamran Chowdhury Shisher is a final-year Ph.D. candidate in the Department of Electrical and Computer Engineering at Auburn University, Auburn, AL, USA. He expects to graduate by May 2024. His Ph.D. works are advised by Yin Sun. ...

Brief Biography: Vishrant Tripathi obtained his PhD from the EECS department at MIT, working with Prof. Modiano at the Lab for Information and Decision Systems (LIDS). He is currently working on building efficient data center networks at Google. His ...

Brief Biography: Jinhang Zuo is a joint postdoc at UMass Amherst and Caltech. He received his Ph.D. in ECE from CMU in 2022. His main research interests include online learning, resource allocation, and networked systems. He is the recipient of the CDS ...