A Whittle Index Approach to Minimizing Age of Multi-Packet Information in IoT Network

Age of information (AoI) captures the freshness of information and has been used broadly as an important performance metric in big data analytics in the Internet of Things (IoT). We consider a general scenario where a meaningful piece of information consists of multiple packets and the information is not complete until all related packets have been correctly received. Minimizing AoI in this general scenario is challenging in both scheduling algorithm design and theoretical analysis, because we need to track the history of received packets before a complete piece of information can be updated. We first analyse the necessary condition for optimal scheduling, based on which we present an optimal scheduling method. The optimal solution, however, has high time complexity. To address the problem, we investigate the problem with a special type of learning, i.e., learning in restless multi-armed bandits (RMAB), and propose a Whittle index-based scheduling method. We also propose a new transmission strategy based on erasure codes to improve the performance of scheduling policies in lossy networks. Performance evaluation results demonstrate that our solution outperforms other baseline policies such as greedy policy and naïve Whittle index policy in both lossless and lossy networks.