119 citations · 884 across the 130 of their papers we have counts for
17 papers · 1 filter
Battle between Rate and Error in Minimizing Age of Information
Guidan Yao, Ahmed M. Bedewy, Ness B. Shroff
In this paper, we consider a status update system, in which update packets are sent to the destination via a wireless medium that allows for multiple rates, where a higher rate als…
Age-optimal Scheduling over Hybrid Channels
Jiayu Pan, Ahmed M. Bedewy, Yin Sun +1
We consider the problem of minimizing the age of information when a source can transmit status updates over two heterogeneous channels. Our work is motivated by recent developments…
Bandit Policies for Reliable Cellular Network Handovers in Extreme Mobility
Yuanjie Li, Esha Datta, Jiaxin Ding +2
The demand for seamless Internet access under extreme user mobility, such as on high-speed trains and vehicles, has become a norm rather than an exception. However, the 4G/5G mobil…
Multi-Armed Bandits with Dependent Arms
Rahul Singh, Fang Liu, Yin Sun +1
We study a variant of the classical multi-armed bandit problem (MABP) which we call as Multi-Armed Bandits with dependent arms. More specifically, multiple arms are grouped togethe…
A Partially Observable MDP Approach for Sequential Testing for Infectious Diseases such as COVID-19
Rahul Singh, Fang Liu, Ness B. Shroff
The outbreak of the novel coronavirus (COVID-19) is unfolding as a major international crisis whose influence extends to every aspect of our daily lives. Effective testing allows i…
Fleet Sizing and Charger Allocation in Electric Vehicle Sharing Systems
Yuntian Deng, Abhishek Gupta, Ness B. Shroff
In this paper, we propose a closed queueing network model for performance analysis of electric vehicle sharing systems with a certain number of chargers in each neighborhood. Depen…
Multi-Armed Bandits with Local Differential Privacy
Wenbo Ren, Xingyu Zhou, Jia Liu +1
This paper investigates the problem of regret minimization for multi-armed bandit (MAB) problems with local differential privacy (LDP) guarantee. In stochastic bandit systems, the…
The Sample Complexity of Best- Items Selection from Pairwise Comparisons
Wenbo Ren, Jia Liu, Ness B. Shroff
This paper studies the sample complexity (aka number of comparisons) bounds for the active best- items selection from pairwise comparisons. From a given set of items, the learne…
ACOUSTIC-TURF: Acoustic-based Privacy-Preserving COVID-19 Contact Tracing
Yuxiang Luo, Cheng Zhang, Yunqi Zhang +5
In this paper, we propose a new privacy-preserving, automated contact tracing system, ACOUSTIC-TURF, to fight COVID-19 using acoustic signals sent from ubiquitous mobile devices. A…
Performance Analysis of Modified SRPT in Multiple-Processor Multitask Scheduling
Wenxin Li, Ness Shroff
In this paper we study the multiple-processor multitask scheduling problem in both deterministic and stochastic models, where each job have several tasks and is complete only when…
Contextual Bandits with Side-Observations
Rahul Singh, Fang Liu, Xin Liu +1
We investigate contextual bandits in the presence of side-observations across arms in order to design recommendation algorithms for users connected via social networks. Users in so…
A Note on Load Balancing in Many-Server Heavy-Traffic Regime
Xingyu Zhou, Ness Shroff
In this note, we apply Stein's method to analyze the performance of general load balancing schemes in the many-server heavy-traffic regime. In particular, consider a load balancing…
A Note on Stein's Method for Heavy-Traffic Analysis
Xingyu Zhou, Ness Shroff
In this note, we apply Stein's method to analyze the steady-state distribution of queueing systems in the traditional heavy-traffic regime. Compared to previous methods (e.g., drif…
Asymptotically Optimal Load Balancing in Large-scale Heterogeneous Systems with Multiple Dispatchers
Xingyu Zhou, Ness Shroff, Adam Wierman
We consider the load balancing problem in large-scale heterogeneous systems with multiple dispatchers. We introduce a general framework called Local-Estimation-Driven (LED). Under…
Is Deadline Oblivious Scheduling Efficient for Controlling Real-Time Traffic in Cellular Downlink Systems?
Sherif ElAzzouni, Eylem Ekici, Ness Shroff
The emergence of bandwidth-intensive latency-critical traffic in 5G Networks, such as Virtual Reality, has motivated interest in wireless resource allocation problems for flows wit…
Learning in Markov Decision Processes under Constraints
Rahul Singh, Abhishek Gupta, Ness B. Shroff
We consider reinforcement learning (RL) in Markov Decision Processes in which an agent repeatedly interacts with an environment that is modeled by a controlled Markov process. At e…
Optimal Sampling and Scheduling for Timely Status Updates in Multi-source Networks
Ahmed M. Bedewy, Yin Sun, Sastry Kompella +1
We consider a joint sampling and scheduling problem for optimizing data freshness in multi-source systems. Data freshness is measured by a non-decreasing penalty function of \emph{…