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Age Aware Content Fetching and Broadcast in a Sensing-as-a-Service System

Ankita Koley, Anu Krishna, Chandramani Singh, V Mahendran

TL;DR

The work addresses age-aware content fetching and broadcasting in a Sensing-as-a-Service (S2aaS) system, where an SCSP balances content fetching costs and VAoI-based age costs under stochastic sensor updates and user requests. It derives an optimal threshold policy for homogeneous users via a fixed-point Bellman-based algorithm and extends to heterogeneous users with exponential complexity, motivating a scalable Whittle-index heuristic that decorrelates per-user decisions. The Whittle-index policy achieves near-optimal performance in simulations, scales linearly with the number of users, and is asymptotically optimal as the user count grows in homogeneous settings. Overall, the paper delivers a practical, threshold-based decision framework plus a scalable heuristic for joint fetching and broadcasting in VAoI-driven S2aaS deployments, with implications for real-time edge caching and broadcast strategies.

Abstract

We consider a Sensing-as-a-Service (S2aaS) system consisting of a sensor, a set of users, and a sensor cloud service provider (SCSP). The sensor updates its content each time it captures a new measurement. The SCSP occasionally fetches the content from the sensor, caches the latest fetched version and broadcasts it on being requested by the users. The SCSP incurs content fetching costs while fetching and broadcasting the contents. The SCSP also incurs an age cost if users do not receive the most recent version of the content after requesting. We study a content fetching and broadcast problem, aiming to minimize the time-averaged content fetching and age costs. The problem can be framed as a Markov decision process but cannot be elegantly solved owing to its multi-dimensional state space and complex dynamics. To address this, we first obtain the optimal policy for the homogeneous case with all the users having the same request probability and age cost. We extend this algorithm for heterogeneous case but the complexity grows exponentially with the number of users. To tackle this, we propose a low complexity Whittle index based algorithm, which performs very close to the optimal. The complexity of the algorithm is linear in number of users and serves as a heuristic for both homogeneous and heterogeneous cases.

Age Aware Content Fetching and Broadcast in a Sensing-as-a-Service System

TL;DR

The work addresses age-aware content fetching and broadcasting in a Sensing-as-a-Service (S2aaS) system, where an SCSP balances content fetching costs and VAoI-based age costs under stochastic sensor updates and user requests. It derives an optimal threshold policy for homogeneous users via a fixed-point Bellman-based algorithm and extends to heterogeneous users with exponential complexity, motivating a scalable Whittle-index heuristic that decorrelates per-user decisions. The Whittle-index policy achieves near-optimal performance in simulations, scales linearly with the number of users, and is asymptotically optimal as the user count grows in homogeneous settings. Overall, the paper delivers a practical, threshold-based decision framework plus a scalable heuristic for joint fetching and broadcasting in VAoI-driven S2aaS deployments, with implications for real-time edge caching and broadcast strategies.

Abstract

We consider a Sensing-as-a-Service (S2aaS) system consisting of a sensor, a set of users, and a sensor cloud service provider (SCSP). The sensor updates its content each time it captures a new measurement. The SCSP occasionally fetches the content from the sensor, caches the latest fetched version and broadcasts it on being requested by the users. The SCSP incurs content fetching costs while fetching and broadcasting the contents. The SCSP also incurs an age cost if users do not receive the most recent version of the content after requesting. We study a content fetching and broadcast problem, aiming to minimize the time-averaged content fetching and age costs. The problem can be framed as a Markov decision process but cannot be elegantly solved owing to its multi-dimensional state space and complex dynamics. To address this, we first obtain the optimal policy for the homogeneous case with all the users having the same request probability and age cost. We extend this algorithm for heterogeneous case but the complexity grows exponentially with the number of users. To tackle this, we propose a low complexity Whittle index based algorithm, which performs very close to the optimal. The complexity of the algorithm is linear in number of users and serves as a heuristic for both homogeneous and heterogeneous cases.
Paper Structure (24 sections, 9 theorems, 50 equations, 7 figures, 1 algorithm)

This paper contains 24 sections, 9 theorems, 50 equations, 7 figures, 1 algorithm.

Table of Contents

  1. Introduction
  2. Related work
  3. Our Contributions
  4. System Model
  5. Optimal Policy
  6. Computation of $\bar{\tau}(m)$s
  7. Description of Algorithm \ref{['alg:fixed_point']}
  8. Heterogeneous users
  9. Whittle index-based policy
  10. Single user problem
  11. Whittle index policy for the multi content problem
  12. Numerical Results
  13. Optimal Policy
  14. Properties of the optimal policy
  15. Effect of variation in the age cost coefficient $c_a$
  16. ...and 9 more sections

Key Result

Lemma 1

$\bar{h}_{av}(\tau)$ in non-decreasing in $\tau$.

Figures (7)

  • Figure 1: $f(\theta)$ is a non-increasing function of $\theta$ and there exists a fixed point.
  • Figure 2: Asymptotic optimality of WI policy for homogeneous users
  • Figure 3: Structure of the optimal policy
  • Figure 4: Variation in the optimal cost due to age cost
  • Figure 5: Variation in the optimal cost due to $C_f$
  • ...and 2 more figures

Theorems & Definitions (14)

  • Lemma 1
  • Theorem 1
  • Lemma 2
  • Theorem 2
  • Remark 1
  • Lemma 3
  • Definition 1: Passive sets
  • Definition 2: Whittle index
  • Lemma 4
  • Remark 2: Scalability
  • ...and 4 more