Optimizing Information Freshness in Computing-Enabled IoT Networks

Xu, Chao; Yang, Howard H.; Wang, Xijun; Quek, Tony Q. S.

doi:10.1109/jiot.2019.2947419

Cited by 90 publications

(59 citation statements)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This helps to construct the decision making on the image conversion. The image conversion is works based on the sensing image by a rear image sensor [63].…”

Section: B Semi-automatic "Division B" Results Image Eventmentioning

confidence: 99%

An ontology enabled internet of things framework in intelligent agriculture for preventing post-harvest losses

Sanjeevi

Kumar

Prasanna

et al. 2020

Complex Intell. Syst.

View full text Add to dashboard Cite

Constituting the agriculture solid substance manufacture, the post-harvest sector processing schema is direct to preventing reduce the losses in intelligent agriculture. Many processing schemata will be preventing post-harvest losses on the agriculture solid substance manufacture, especially sekai-ichi apple is the regularly used fruit also used to make active in human-related activities of the sensory and control function consisting of an agricultural industry. Sekai-ichi apple is being a definite number of diseases induce, but it is to the highest degree of wastage involving in the Post-Harvest process. Especially sekai-ichi apple count loss is an unsafe many time because it not critically post-harvest. Regardless of consideration, the existing hierarchical model specified post-harvest losses prevention research has deficiencies to precise and quick detection of wastage for ensuring healthy separation of agriculture surroundings. This paper suggests a "Hierarchical Model within Ontology Enabled IoT" for distinguishable healthy separation of sekai-ichi apple by using Boosted Continuous Non-spatial whole Attribute Extraction (BCNAE). Sekai-ichi apple count loss is always safe on critically post-harvest. Proposed Post-Harvest hierarchical model specified post-harvest losses prevention and deficiencies to precise and quick detection of wastage for ensuring healthy separation of agriculture surroundings. In these suggestions, the separation cognitive operation takes the three levels of processing schemes such as lower level, middle level, and higher level. Firstly, the lower level is express agreements with the dynamic functioning for maintaining the definite number of manual induces. This lower level showing an absorption with the activity of manual separation by the human reliability determination. Secondly, the middle level is an express arrangement with the dynamic functioning for reducing the overfitting and accommodate to fitting the right shape deliberation. Middle level is establishing being generalized by concentrating the time-varying features in the occurrence of a change for the worse identification. Finally, the upper level is express for features refining with the help of the function of sekai-ichi apple image segmentation connection. This interpretability process helps to make the proven position of a prominent classification in a particular fruit on the agriculture solid substance. These three processing flow constructs the ontology structure with manually collected sekai-ichi apple images from a 3D sensor. The observational consequences express that the proposed BCNAE framework recognizes a detection performance carrying out with an optimized-separation ratio for time-variant of the separation process.

show abstract

“…This helps to construct the decision making on the image conversion. The image conversion is works based on the sensing image by a rear image sensor [63].…”

Section: B Semi-automatic "Division B" Results Image Eventmentioning

confidence: 99%

An ontology enabled internet of things framework in intelligent agriculture for preventing post-harvest losses

Sanjeevi

Kumar

Prasanna

et al. 2020

Complex Intell. Syst.

View full text Add to dashboard Cite

show abstract

“…The AoI jointly characterizes the packet delay and the packet intergeneration time, which distinguishes AoI from conventional metrics, such as delay and throughput. Such a superiority of AoI for evaluating the information freshness in various wireless networks has been demonstrated in recent studies [5]- [8] by resorting to queueing theory.…”

Section: Introductionmentioning

confidence: 91%

Age of Changed Information: Content-Aware Status Updating in the Internet of Things

Wang¹,

Lin²,

Xu³

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

In Internet of Things (IoT), the freshness of status updates is crucial for mission-critical applications. In this regard, it is suggested to quantify the freshness of updates by using Age of Information (AoI) from the receiver's perspective. Specifically, the AoI measures the freshness over time. However, the freshness in the content is neglected. In this paper, we introduce an agebased utility, named as Age of Changed Information (AoCI), which captures both the passage of time and the change of information content. By modeling the underlying physical process as a discrete time Markov chain, we investigate the AoCI in a time-slotted status update system, where a sensor samples the physical process and transmits the update packets to the destination. With the aim of minimizing the weighted sum of the AoCI and the update cost, we formulate an infinite horizon average cost Markov Decision Process. We show that the optimal updating policy has a special structure with respect to the AoCI and identify the condition under which the special structure exists. By exploiting the special structure, we provide a low complexity relative policy iteration algorithm that finds the optimal updating policy. We further investigate the optimal policy for two special cases. In the first case where the state of the physical process transits with equiprobability, we show that optimal policy is of threshold type and derive the closed-form of the optimal threshold. We then study a more generalized periodic Markov model of the physical process in the second case. Lastly, simulation results are laid out to exhibit the performance of the optimal updating policy and its superiority over the zero-wait baseline policy.

show abstract

“…[50] considered AoI in a general multi-hop network where the update packets do not necessarily arrive to the gateway node in the order of their generation times. Xu et al [51] calculated and optimized the average PAoI and found the optimal updating frequency in IoT network. The problem of optimizing link scheduling decisions to minimize the expected weighted sum AoI of the clients in the network was researched [52].…”

Section: Real-time Guaranteementioning

confidence: 99%

Ultra-reliable and low-latency communications: applications, opportunities and challenges

Feng

Lai

Luo

et al. 2021

Sci. China Inf. Sci.

View full text Add to dashboard Cite

In the upcoming 5G and beyond systems, ultra-reliable and low latency communication (URLLC) has been considered as the key enabler to support diverse mission-critical services, such as industrial automation, remote healthcare, and intelligent transportation. However, the two stringent requirements of URLLC: extremely low latency and ultra-strict reliability have posed great challenges in system designing. In this article, the basic concepts and the potential applications of URLLC are first introduced. Then, the state-ofthe-art research of URLLC in the physical layer, link layer and the network layer are overviewed. In addition, some potential research topics and challenges are also identified.

show abstract

Optimizing Information Freshness in Computing-Enabled IoT Networks

Cited by 90 publications

References 54 publications

An ontology enabled internet of things framework in intelligent agriculture for preventing post-harvest losses

An ontology enabled internet of things framework in intelligent agriculture for preventing post-harvest losses

Age of Changed Information: Content-Aware Status Updating in the Internet of Things

Ultra-reliable and low-latency communications: applications, opportunities and challenges

Contact Info

Product

Resources

About