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

TL;DR

This paper addresses age-aware content fetching and broadcasting in a Sensing-as-a-Service system, proposing optimal and low-complexity heuristic algorithms to minimize combined content fetching and age costs.

Contribution

It introduces a Markov decision process framework, derives an optimal policy for homogeneous users, and develops a scalable Whittle index-based heuristic for heterogeneous users.

Findings

Optimal policy for homogeneous user case

Whittle index heuristic performs close to optimal

Linear complexity algorithm for large user sets

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.