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1. Minimizing Age-of-Information in Heterogeneous Multi-Channel Systems: A New Partial-Index Approach

   https://doi.org/10.1145/3466772.3467030  

   Zou, Yihan; Kim, Kwang Taik; Lin, Xiaojun; Chiang, Mung (July 2021, ACM MobiHoc 2021)

   null (Ed.)

   We study how to schedule data sources in a wireless time-sensitive information system with multiple heterogeneous and unreliable channels to minimize the total expected Age-of-Information (AoI). Although one could formulate this problem as a discrete-time Markov Decision Process (MDP), such an approach suffers from the curse of dimensionality and lack of insights. For single-channel systems, prior studies have developed lower-complexity solutions based on the Whittle index. However, Whittle index has not been studied for systems with multiple heterogeneous channels, mainly because indexability is not well defined when there are multiple dual cost values, one for each channel. To overcome this difficulty, we introduce new notions of partial indexability and partial index, which are defined with respect to one channel's cost, given all other channels' costs. We then combine the ideas of partial indices and max-weight matching to develop a Sum Weighted Index Matching (SWIM) policy, which iteratively updates the dual costs and partial indices. The proposed policy is shown to be asymptotically optimal in minimizing the total expected AoI, under a technical condition on a global attractor property. Extensive performance simulations demonstrate that the proposed policy offers significant gains over conventional approaches by achieving a near-optimal AoI. Further, the notion of partial index is of independent interest and could be useful for other problems with multiple heterogeneous resources. 

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2. Optimizing Age of Information in Wireless Networks with Throughput Constraints

   Kadota, Igor; Sinha, Abhishek; Modiano, Eytan (April 2018, IEEE Infocom)

   Age of Information (AoI) is a performance metric that captures the freshness of the information from the perspective of the destination. The AoI measures the time that elapsed since the generation of the packet that was most recently delivered to the destination. In this paper, we consider a singlehop wireless network with a number of nodes transmitting timesensitive information to a Base Station and address the problem of minimizing the Expected Weighted Sum AoI of the network while simultaneously satisfying timely-throughput constraints from the nodes. We develop three low-complexity transmission scheduling policies that attempt to minimize AoI subject to minimum throughput requirements and evaluate their performance against the optimal policy. In particular, we develop a randomized policy, a Max- Weight policy and a Whittle’s Index policy, and show that they are guaranteed to be within a factor of two, four and eight, respectively, away from the minimum AoI possible. In contrast, simulation results show that Max-Weight outperforms the other policies, both in terms of AoI and throughput, in every network configuration simulated, and achieves near optimal performance. 

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3. Timely Processing Of Updates From Multiple Sources

   https://doi.org/10.23919/WiOpt58741.2023.10349900  

   Ramani, Vishakha; Seskar, Ivan; Yates, Roy D (August 2023, IEEE)

   We consider a system where the updates from independent sources are disseminated via a publish-subscribe mechanism. The sources are the publishers and a decision process (DP), acting as a subscriber, derives decision updates from the source data. We derive the stationary expected age of information (AoI) of decision updates delivered to a monitor. We show that a lazy computation policy in which the DP may sit idle before computing its next decision update can reduce the average AoI at the monitor even though the DP exerts no control over the generation of source updates. This AoI reduction is shown to occur because lazy computation can offset the negative effect of high variance in the computation time. 

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4. An Easier-to-Verify Sufficient Condition for Whittle Indexability and Application to AoI Minimization

   Zhou, Sixiang; Lin, Xiaojun (May 2024, IEEE)

   We study a scheduling problem for a base-station transmitting status information to multiple user-equipments (UE) with the goal of minimizing the total expected Age-of-Information (AoI). Such a problem can be formulated as a Restless MultiArmed Bandit (RMAB) problem and solved asymptoticallyoptimally by a low-complexity Whittle index policy, if each UE’s sub-problem is Whittle indexable. However, proving Whittle indexability can be highly non-trivial, especially when the value function cannot be derived in closed-form. In particular, this is the case for the AoI minimization problem with stochastic arrivals and unreliable channels, whose Whittle indexability remains an open problem. To overcome this difficulty, we develop a sufficient condition for Whittle indexability based on the notion of active time (AT). Even though the AT condition shares considerable similarity to the Partial Conservation Law (PCL) condition, it is much easier to understand and verify. We then apply our AT condition to the stochastic-arrival unreliablechannel AoI minimization problem and, for the first time in the literature, prove its Whittle indexability. Our proof uses a novel coupling approach to verify the AT condition, which may also be of independent interest to other large-scale RMAB problems. 

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5. Updates with Multiple Service Classes

   Yates, Roy D.; Zhong, Jing; Zhang, Wuyang (July 2019, 2019 IEEE International Symposium on Information Theory (ISIT))

   A source submits status update jobs to a service fa- cility for processing and delivery to a monitor. The status updates belong to service classes with different service requirements. We model the service requirements using a hyperexponential service time model. To avoid class-specific bias in the service process, the system implements an M/G/1/1 blocking queue; new arrivals are discarded if the server is busy. Using an age-of-information (AoI) metric to characterize timeliness of the updates, a stochastic hybrid system (SHS) approach is employed to derive the overall average AoI and the average AoI for each service class. We observe that both the overall AoI and class-specific AoI share a common penalty that is a function of the second moment of the average service time and they differ chiefly because of their different arrival rates. We show that each high-probability service class has an associated age-optimal update arrival rate while low- probability service classes incur an average age that is always decreasing in the update arrival rate. 

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