Optimal Policies for Status Update Generation in an IoT Device With Heterogeneous Traffic

Abstract

A large body of applications that involve monitoring, decision making, and forecasting require timely status updates for their efficient operation. Age of Information (AoI) is a newly proposed metric that effectively captures this requirement. Recent research on the subject has derived AoI optimal policies for the generation of status updates and AoI optimal packet queueing disciplines. Unlike previous research we focus on low-end devices that typically support monitoring applications in the context of the Internet of Things. We acknowledge that these devices host a diverse set of applications some of which are AoI sensitive while others are not.Furthermore, due to their limited computational resources they typically utilize a simple First-In First-Out (FIFO) queueing discipline. We consider the problem of optimally controlling the status update generation process for a system with a source-destination pair that communicates via a wireless link, whereby the source node is comprised of a FIFO queue and two applications, one that is AoI sensitive and one that is not. We formulate this problem as a dynamic programming problem and utilize the framework of Markov Decision Processes to derive optimal policies for the generation of status update packets. Due to the lack of comparable methods in the literature, we compare the derived optimal policies against baseline policies, such as the zerowait policy, and investigate the performance of all policies for a variety of network configurations. Results indicate that existing status update policies fail to capture the trade-off between frequent generation of status updates and queueing delay and thus perform poorly.

Age of Information Aware Communication Systems : Modeling and Performance Analysis

“…The problem of identifying the optimal sampling strategy of a communication system in relation to AoI, has attracted particular attention due to the connection it implies with estimation errors [76,77,78,79]. In [80] the authors formulate a dynamic programming problem and utilize the framework of Markov decision processes (MDP) to study the interaction of heterogeneous traffic flows in a shared queue.…”

Age of Information in a Multiple Access Channel with Heterogeneous Traffic and an Energy Harvesting Node

“…Since the status updates and regular information packets are associated with difference performance metrics, e.g., one with smallest AoI and the other with smallest delay, the impact of heterogeneous traffic on the AoI and the optimal update policy has been investigated in [24], [25]. The work in [26] investigates Nash and Stackelberg equilibrium strategies for DSRC and WiFi coexisting networks, where DSRC and WiFi nodes are age and throughput oriented, respectively.…”

Age of information performance of multiaccess strategies with packet management

“…Alternative measures of stale information that are by-products of AoI are studied for the M/M/1 queue in [26]. An expansion of the basic model that includes multiple sources sharing a common queue is considered in [27]- [29]. The analysis therein illustrated how combining multiple sources in a common queue is more efficient in terms of the average AoI of each source, than serving them separately.…”