Optimizing Information Freshness for Cooperative IoT Systems With Stochastic Arrivals

Li, Bohai; Wang, Qian; Chen, He; Zhou, Yong; Li, Yonghui

doi:10.1109/jiot.2021.3051417

Cited by 26 publications

(20 citation statements)

References 36 publications

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“…Deploying an intermediate node, typically called a relay, in such systems is indispensable and has an array of benefits, e.g., saving on power usage of wireless sensors and improving the transmission success probability. Recently, the AoI has been studied in relaying systems in [6], [10]- [14]. The work [6] studied the AoI minimization in a multi-source relaying system with the generate-at-will model (i.e., possibility of generating a new update in any time), under a transmission capacity constraint for each link.…”

Section: Introductionmentioning

confidence: 99%

“…In [13], the authors studied the AoI in a single-source energy harvesting relaying system with error-free channels, and they designed offline and online age-optimal policies. In [14], the authors considered a single-source relaying system with stochastic arrivals where the source communicates with the destination either through the direct link or via a relay. They proposed two different relaying protocols and analyzed the AoI performance.…”

Section: Introductionmentioning

confidence: 99%

“…Only a few works, such as [13] has incorporated a resource constraint in the relaying system in analysis of the AoI. Moreover, most of the discussed works consider single-source relaying systems, e.g., [10], [12]- [14]. Accordingly, the AoI in multi-source resource-constrained relaying systems has not been widely studied yet.…”

Section: Introductionmentioning

confidence: 99%

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Minimizing AoI in Resource-Constrained Multi-Source Relaying Systems with Stochastic Arrivals

Zakeri¹,

Moltafet²,

Leinonen³

et al. 2021

Preprint

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We consider a multi-source relaying system where the sources independently and randomly generate status update packets which are sent to the destination with the aid of a bufferaided relay through unreliable links. We formulate a stochastic optimization problem aiming to minimize the sum average age of information (AAoI) of sources under per-slot transmission capacity constraints and a long-run average resource constraint.To solve the problem, we recast it as a constrained Markov decision process (CMDP) problem and adopt the Lagrangian method. We analyze the structure of an optimal policy for the resulting MDP problem that possesses a switching-type structure. We propose an algorithm that obtains a stationary deterministic near-optimal policy, establishing a benchmark for the system. Simulation results show the effectiveness of our algorithm compared to benchmark algorithms.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Minimizing AoI in Resource-Constrained Multi-Source Relaying Systems with Stochastic Arrivals

Zakeri¹,

Moltafet²,

Leinonen³

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…Usually, in such data-driven field, data have greatest value when they are fresh. However, it is very difficult to capture the timeliness of status updates by using conventional performance metrics such as outage, throughput, and delay [8]. Therefore, to characterize the freshness of information status updates, the concept of age of information (AoI) has been introduced by S. Kaul et al in [9] and [10], which is defined as the elapsed time since the generation of the most recently received status update.…”

Section: Introductionmentioning

confidence: 99%

Improvement on Age of Information for Information Update Systems With HARQ Chase Combining and Sensor Harvesting-Transmitting Diversities

et al. 2021

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The age of information (AoI) has attracted increasing attentions as a new metric and tool to capture the timeliness of reception and freshness of data, which is different from the conventional metric such as outage, delay, and throughput. While most existing works focused on AoI analysis and optimizing method, the information update system design by utilizing diversity to reduce AoI is not fully exploited so far. Inspired by this fact, a novel information status update system is designed by jointing wireless energy harvesting diversity, status update transmitting diversity, and hybrid automatic repeat request (HARQ). Specially, the update system consists of two sensors that can be seen as an unified entity from the destination's perspective, and one destination. The two sensors, which have finite-size batteries and synchronously operate in half-duplex mode, harvest energy from a Bernoulli process source, and cooperatively deliver the status update to destination by sharing a common information source. To exploit the information of the unsuccessfully decoding update packet, the HARQ and chase combining (HARQ-CC) are jointly used at destination so that the HARQ-CC receiving diversity is also exploited. By using Bernoulli process energy arrival probability and sensor transmission probability, we first propose one novel sensor energy harvesting and update delivering model that can be represented by Markov Chain (MC) and develop one novel construction method of the transition matrix of sensor battery energy states. Considering the developed energy state transmission matrix column stochastic, irreducible, and aperiodic, we obtain the stationary distribution of sensor battery energy states so that the steady transmitting power is derived. Secondly, the average AoI of the dual-sensor status update system is derived in terms of a closed-form expression by accurately calculating the statistical descriptions of the maximum retransmission number (time) in HARQ-CC and the service time of one packet. The analytical results are validated by using the comparison from simulations. Moreover, compared with traditional single sensor system, the dual-sensor system not only harvests more energy, but also has smaller average AoI because of the joint exploitation of multi-diversity. Besides, the impact of the system parameters on harvested energy and average AoI is provided, which provides insights in terms of the optimal design of Internet of things system.

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“…In paper [24] the AoI in multihop networks was analyzed. Recently, the AoI of a three node status updating system was considered in [25], where a relay was added to cooperate the packet transmission from source to receiver. The authors showed that although two-hop transmission via the relay takes longer propagation delay, but the transmission success probability is raised, in particular when the direct line from source to destination is bad.…”

Section: Introductionmentioning

confidence: 99%

Age of Information in Relay-Assisted Status Updating Systems

Zhang,

2021

Preprint

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In this paper we consider the age of information (AoI) of a status updating system with a relay, where the updates are delivered to destination either from the direct line or the two-hop link via the relay. An updating packet generated at source is sent to receiver and the relay simultaneously. When the direct packet transmission fails, the relay replaces the source and retransmits the packet until it is eventually obtained at the receiver side. Assume that the propagation delay on each link is one time slot, we determine the stationary distribution of the AoI for three cases: (a) relay has no buffer and the packet delivery from relay cannot be preempted by fresher updates from source; (b) relay has no buffer but the packet substitution is allowable; (c) relay has size 1 buffer and the packet in buffer is refreshed when a newer packet is obtained. The idea is invoking a multiple-dimensional state vector which contains the AoI as a part and constituting the multiple-dimensional AoI stochastic process. We find the steady state of each multiple-dimensional AoI process by solving the system of stationary equations. Once the steady-state distribution of larger-dimensional AoI process is known, the stationary AoI distribution is also obtained as it is one of the marginal distributions of that process's steady-state distribution. For all the situations, we derive the explicit expression of AoI distribution, and calculate the mean and the variance of the stationary AoI. All the results are compared numerically, including the AoI performance of the non-relay state updating system. Numerical results show that adding the relay

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Optimizing Information Freshness for Cooperative IoT Systems With Stochastic Arrivals

Cited by 26 publications

References 36 publications

Minimizing AoI in Resource-Constrained Multi-Source Relaying Systems with Stochastic Arrivals

Minimizing AoI in Resource-Constrained Multi-Source Relaying Systems with Stochastic Arrivals

Improvement on Age of Information for Information Update Systems With HARQ Chase Combining and Sensor Harvesting-Transmitting Diversities

Age of Information in Relay-Assisted Status Updating Systems

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