We consider a class of restless multi-armed bandit problems (RMBP) that arises in dynamic multichannel access, user/server scheduling, and optimal activation in multi-agent systems. For this class of RMBP, we establish the indexability and obtain Whittle's index in closed-form for both discounted and average reward criteria. These results lead to a direct implementation of Whittle's index policy with remarkably low complexity. When these Markov chains are stochastically identical, we show that Whittle's index policy is optimal under certain conditions. Furthermore, it has a semi-universal structure that obviates the need to know the Markov transition probabilities. The optimality and the semi-universal structure result from the equivalency between Whittle's index policy and the myopic policy established in this work. For non-identical channels, we develop efficient algorithms for computing a performance upper bound given by Lagrangian relaxation. The tightness of the upper bound and the near-optimal performance of Whittle's index policy are illustrated with simulation examples.
This paper proposes using the uncertainty of information (UoI), measured by Shannon's entropy, as a metric for information freshness. We consider a system in which a central monitor observes multiple binary Markov processes through a communication channel. The UoI of a Markov process corresponds to the monitor's uncertainty about its state. At each time step, only one Markov process can be selected to update its state to the monitor; hence there is a tradeoff among the UoIs of the processes that depend on the scheduling policy used to select the process to be updated. The age of information (A…
Age of information is a new concept that characterizes the freshness of information at end devices. This paper studies the age of information from a scheduling perspective. We consider a wireless broadcast network where a base-station updates many users on stochastic information arrivals. Suppose that only one user can be updated for each time. In this context, we aim at developing a transmission scheduling algorithm for minimizing the long-run average age. To develop a low-complexity transmission scheduling algorithm, we apply the Whittle's framework for restless bandits. We successfully deri…
We study the problem of user association, i.e., determining which base station (BS) a user should associate with, in a dense millimeter wave (mmWave) network. In our system model, in each time slot, a user arrives with some probability in a region with a relatively small geographical area served by a dense mmWave network. Our goal is to devise an association policy under which, in each time slot in which a user arrives, it is assigned to exactly one BS so as to minimize the weighted average amount of time that users spend in the system. The above problem is a restless multi-armed bandit proble…
Partially Observable Restless Bandits for Age-Optimal Scheduling over Markov Channels
School of Electronics and Information Technology, Sun Yat-sen University(中山大学电子与信息工程学院);Guangzhou Huizhi Communication Co.,Ltd.(广州慧智通信有限公司);School of Electronics and Communication Engineering, Sun Yat-sen University(中山大学电子与通信工程学院);School of Cyber Science and Engineering Southeast University(东南大学网络空间安全学院);School of Information Engineering, Northwest A&F University(西北农林科技大学信息工程学院)
We consider a star-topology wireless network for status update where a central node collects status data from a large number of distributed machine-type terminals that share a wireless medium. The Age of Information (AoI) minimization scheduling problem is formulated by the restless multi-armed bandit. A widely-proven near-optimal solution, i.e., the Whittle's index, is derived in closed-form and the corresponding indexability is established. The index is then generalized to incorporate stochastic, periodic packet arrivals and unreliable channels. Inspired by the index scheduling policies whic…
Age of Information Optimization for Status Updates in Integrated Sensing and Communication Systems
CentraleSupélec, University of Paris-Saclay(巴黎萨克雷大学中央理工-高等电力学院);City St George’s School of Science and Technology, University of London(伦敦大学城市圣乔治科学与技术学院)
In this paper, we investigate a general delay-aware channel allocation problem where the number of channels is less than that of users. Due to the proliferation of delay sensitive applications, the objective of our problem is chosen to be the minimization of the total average backlog queues of the network in question. First, we show that our problem falls in the framework of Restless Bandit Problems (RBP), for which obtaining the optimal solution is known to be out of reach. To circumvent this difficulty, we tackle the problem by adopting a Whittle index approach. To that extent, we employ a L…
We investigate a pilot allocation problem in wireless networks over Markovian fading channels. In wireless systems, the Channel State Information (CSI) is collected at the Base Station (BS), in particular, this paper considers a pilot-aided channel estimation method (TDD mode). Typically, there are less available pilots than users, hence at each slot the scheduler needs to decide an allocation of pilots to users with the goal of maximizing the long-term average throughput. There is an inherent tradeoff in how the limited pilots are used: assign a pilot to a user with up-to-date CSI and good ch…
In an Internet-of-Things system where status data are collected from sensors and actuators for time-critical applications, the freshness of data is vital and can be quantified by the recently proposed age-of-information (AoI) metric. In this paper, we first consider a general scenario where multiple terminals share a common channel to transmit or receive randomly generated status packets. The optimal scheduling problem to minimize AoI is formulated as a restless multi-armed bandit problem. To solve the problem efficiently, we derive the Whittle's index in closed-form and establish the indexabi…
Mobile-edge computing (MEC) offloads computational tasks from wireless devices to network edge, and enables real-time information transmission and computing. Most existing work concerns a small-scale synchronous MEC system. In this paper, we focus on a large-scale asynchronous MEC system with random task arrivals, distinct workloads, and diverse deadlines. We formulate the offloading policy design as a restless multi-armed bandit (RMAB) to maximize the total discounted reward over the time horizon. However, the formulated RMAB is related to a PSPACE-hard sequential decision-making problem, whi…
We consider systems that require timely monitoring of sources over a communication network, where the cost of delayed information is unknown, time-varying and possibly adversarial. For the single source monitoring problem, we design algorithms that achieve sublinear regret compared to the best fixed policy in hindsight. For the multiple source scheduling problem, we design a new online learning algorithm called Follow-the-Perturbed-Whittle-Leader and show that it has low regret compared to the best fixed scheduling policy in hindsight, while remaining computationally feasible. The algorithm an…
5G radio access network (RAN) is consuming much more energy than legacy RAN due to the denser deployments of gNodeBs (gNBs) and higher single-gNB power consumption. In an effort to achieve an energy-conserving RAN, this paper develops a dynamic on-off switching paradigm, where the ON/OFF states of gNBs can be dynamically configured according to the evolvements of the associated users. We formulate the dynamic sleep control for a cluster of gNBs as a Markov decision process (MDP) and analyze various switching policies to reduce the energy expenditure. The optimal policy of the MDP that minimize…