Journal articles: 'Age-of-information (AoI)'

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Salimnejad, Mehrdad, and Nikolaos Pappas. "On the Age of Information in a Two-User Multiple Access Setup." Entropy 24, no. 4 (April 12, 2022): 542. http://dx.doi.org/10.3390/e24040542.

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This work considers a two-user multiple access channel in which both users have Age of Information (AoI)-oriented traffic with different characteristics. More specifically, the first user has external traffic and cannot control the generation of status updates, and the second user monitors a sensor and transmits status updates to the receiver according to a generate-at-will policy. The receiver is equipped with multiple antennas and the transmitters have single antennas; the channels are subject to Rayleigh fading and path loss. We analyze the average AoI of the first user for a discrete-time first-come-first-served (FCFS) queue, last-come-first-served (LCFS) queue, and queue with packet replacement. We derive the AoI distribution and the average AoI of the second user for a threshold policy. Then, we formulate an optimization problem to minimize the average AoI of the first user for the FCFS and LCFS with preemption queue discipline to maintain the average AoI of the second user below a given level. The constraints of the optimization problem are shown to be convex. It is also shown that the objective function of the problem for the first-come-first-served queue policy is non-convex, and a suboptimal technique is introduced to effectively solve the problem using the algorithms developed for solving a convex optimization problem. Numerical results illustrate the performance of the considered optimization algorithm versus the different parameters of the system. Finally, we discuss how the analytical results of this work can be extended to capture larger setups with more than two users.

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Hu, Huimin, Ke Xiong, Yu Zhang, Pingyi Fan, Tong Liu, and Shaoli Kang. "Age of Information in Wireless Powered Networks in Low SNR Region for Future 5G." Entropy 20, no. 12 (December 10, 2018): 948. http://dx.doi.org/10.3390/e20120948.

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Wireless powered communication technology has a great potential to power low-power wireless sensor networks and Internet of Things (IoT) for real-time applications in future 5G networks, where age of information (AoI) plays a very important performance metric. This paper studies the system average AoI of a wireless powered network, where a wireless-powered user harvests energy from a wireless power source (WPS) and then transmits data packets to its access point (AP) by using the harvested energy. The user generates data packets with some probability and adopts the first-come-first-served (FCFS) service policy. For such a system, by using the queuing theory and the probability models, we derive a closed-form expression of the system average AoI. We also formulate an optimization problem to minimize the AoI by optimizing the data packet generating probability, and find its solution by simple calculation and search. Simulation results demonstrate the correctness of our obtained analytical results. It also shows that, when the total distance of the two hops is fixed, the system average AoI increases linearly with the increment of the distance of the first hop, and a smaller data packet generating probability should be selected to match a bigger first-hop distance for achieving a smaller system average AoI. Moreover, a smaller data packet size also contributes to a smaller system average AoI.

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Sawwan, Abdalaziz, and Jie Wu. "On Edge Pruning of Communication Networks under an Age-of-Information Framework." Algorithms 15, no. 7 (June 29, 2022): 228. http://dx.doi.org/10.3390/a15070228.

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Effective non-repetitive routing among nodes in a network is an essential function in communication networks. To achieve that, pruning the links of the network is helpful with the trade-off of making the network less robust in transmitting messages while reducing redundancy to increase flow with limited network bandwidth, so we enhance the quality of service (QoS). In our paper, we study the case that if a link removal has either no effect or an insignificant effect on the Age of Information (AoI) of the messages delivered in the communication network. The pruning of such links can be applied to the k least significant links in terms of their impact on the AoI of the messages transmitted in the system. The objective of our work is to study the effect of pruning a number of links in a network on the AoI, in order to reduce the redundancy of the messages that may be received at the destination many times while transmitted only once. In our context, the objective of the communication system would be to maintain the information from the source as fresh as possible when it arrives at the destination while reducing the redundancy of messages. In this work, we introduce an efficient reduction method designed for series-parallel networks with links of exponentially distributed wait times. In addition, we consider the deterministic case and present the pruning technique when link removal would not affect the AoI. Lastly, we present a comprehensive simulation to study the effect of pruning the links on the AoI of the network and the redundancy of messages received by the destination.

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Wei, Kefeng, Lincong Zhang, and Shupeng Wang. "Intelligent Channel Allocation for Age of Information Optimization in Internet of Medical Things." Wireless Communications and Mobile Computing 2021 (August 30, 2021): 1–10. http://dx.doi.org/10.1155/2021/6645803.

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Along with the development of realtime applications, the freshness of information becomes significant because the overdue information is worthless and useless and even harmful to the right judgement of system. Therefore, The Age of Information (AoI) used for marking the freshness of information is proposed. In Internet of Medical Things (IoMT), which is derived from the requirement of Internet of Thins (IoT) in medicine, high freshness of medical information should be guaranteed. In this paper, we introduce the AoI of medical information when allocating channels for users in IoMT. Due to the advantages of Deep Q-learning Network (DQN) applied in resource management in wireless network, we propose a novel DQN-based Channel Allocation (DQCA) algorithm to provide the strategy for channel allocation under the optimization of the system cost considering the AoI and energy consumption of coordinator nodes. Unlike the traditional centralized channel allocation methods, the DQCA algorithm is distributed as each user performs the DQN process separately. The simulation results show that our proposed DQCA algorithm is superior to Greedy algorithm and Q-learning algorithm in terms of the average AoI, average energy consumption and system cost.

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Kallitsis, Georgios, Vasileios Karyotis, and Symeon Papavassiliou. "On the Potential of Enhancing Delay-Tolerant Routing Protocols via Age of Information." Future Internet 14, no. 8 (August 17, 2022): 242. http://dx.doi.org/10.3390/fi14080242.

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In this paper, we study the potential of using the metric of Age of Information (AoI) for enhancing delay-tolerant routing protocols. The latter have been proposed for alleviating the impact of long roundtrip time in networks operating in harsh environments, e.g., in distributed applications deployed in a desert/sparsely populated area without infrastructure, a space network, etc. Delay-tolerant routing protocols can prevent excessive packet timer expiration, but do not provide any packet delivery time guarantee. Thus, they are unsuitable for time-sensitive applications that are more intensely desired nowadays in the next generation networking applications. By incorporating AoI into the operation of delay-tolerant routing protocols, we aim at devising routing protocols that can cope with both long propagation times and challenges related to time-sensitivity in packet delivery. More specifically, in this work, we modify the operation of a well-known delay-tolerant routing protocol, namely FRESH, to make AoI-based packet forwarding decisions, aiming at achieving specific delay guarantees regarding the end-to-end delivery time. We investigate the advantages and disadvantages of such an approach compared to the traditional FRESH protocol. This work serves as a cornerstone for successfully demonstrating the potential of exploiting AoI in delay-tolerant routing and its applications.

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Chen, Dr Joy Iong Zong. "An Optimized Packet Transfer through Wireless Network Using Age of Information." IRO Journal on Sustainable Wireless Systems 2, no. 2 (May 18, 2020): 76–83. http://dx.doi.org/10.36548/jsws.2020.2.003.

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The cost for sampling a packet from transmission and transmitting the updates of the status using the wireless channel changes depending on the Age of Information (AoI) constraints. If any error occurs during the process of transmission, the decision lies with the scheduling algorithm to either retransmit the packet or to sample the packet again. Either way, the cost will include both transmission as well as sampling costs. However the aspect of sampling a new packet because of the error will result in increasing the cost of the system. With time average AoI constraint, we have devised a novel optimization technique that uses time average cost. In order to tackle this issue, we propose a decision making algorithm that decides in slots. The proposed algorithm arrives at one of the three solutions based on optimization technique. Accordingly, the user can either remain silent or transmit the old pack or sample the new packet. With the use of simulation results, the optimum performance of the proposed work in terms of AoI and timer average cost is observed and recorded.

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Wang, Zijing, Mihai-Alin Badiu, and Justin P. Coon. "Relationship between Age and Value of Information for a Noisy Ornstein–Uhlenbeck Process." Entropy 23, no. 8 (July 23, 2021): 940. http://dx.doi.org/10.3390/e23080940.

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The age of information (AoI) has been widely used to quantify the information freshness in real-time status update systems. As the AoI is independent of the inherent property of the source data and the context, we introduce a mutual information-based value of information (VoI) framework for hidden Markov models. In this paper, we investigate the VoI and its relationship to the AoI for a noisy Ornstein–Uhlenbeck (OU) process. We explore the effects of correlation and noise on their relationship, and find logarithmic, exponential and linear dependencies between the two in three different regimes. This gives the formal justification for the selection of non-linear AoI functions previously reported in other works. Moreover, we study the statistical properties of the VoI in the example of a queue model, deriving its distribution functions and moments. The lower and upper bounds of the average VoI are also analysed, which can be used for the design and optimisation of freshness-aware networks. Numerical results are presented and further show that, compared with the traditional linear age and some basic non-linear age functions, the proposed VoI framework is more general and suitable for various contexts.

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Ni, Yuanzhi, Lin Cai, and Yuming Bo. "Vehicular beacon broadcast scheduling based on age of information (AoI)." China Communications 15, no. 7 (July 2018): 67–76. http://dx.doi.org/10.1109/cc.2018.8424604.

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Oğuz, Tahir Kerem, Elif Tuğçe Ceran, Elif Uysal, and Tolga Girici. "Implementation and Evaluation of Age-Aware Downlink Scheduling Policies in Push-Based and Pull-Based Communication." Entropy 24, no. 5 (May 11, 2022): 673. http://dx.doi.org/10.3390/e24050673.

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As communication systems evolve to better cater to the needs of machine-type applications such as remote monitoring and networked control, advanced perspectives are required for the design of link layer protocols. The age of information (AoI) metric has firmly taken its place in the literature as a metric and tool to measure and control the data freshness demands of various applications. AoI measures the timeliness of transferred information from the point of view of the destination. In this study, we experimentally investigate AoI of multiple packet flows on a wireless multi-user link consisting of a transmitter (base station) and several receivers, implemented using software-defined radios (SDRs). We examine the performance of various scheduling policies under push-based and pull-based communication scenarios. For the push-based communication scenario, we implement age-aware scheduling policies from the literature and compare their performance with those of conventional scheduling methods. Then, we investigate the query age of information (QAoI) metric, an adaptation of the AoI concept for pull-based scenarios. We modify the former age-aware policies to propose variants that have a QAoI minimization objective. We share experimental results obtained in a simulation environment as well as on the SDR testbed.

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Pappalardo, Martina, Antonio Virdis, and Enzo Mingozzi. "Energy-Optimized Content Refreshing of Age-of-Information-Aware Edge Caches in IoT Systems." Future Internet 14, no. 7 (June 28, 2022): 197. http://dx.doi.org/10.3390/fi14070197.

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The Internet of Things (IoT) brings internet connectivity to everyday devices. These devices generate a large volume of information that needs to be transmitted to the nodes running the IoT applications, where they are processed and used to make some output decisions. On the one hand, the quality of these decisions is typically affected by the freshness of the received information, thus requesting frequent updates from the IoT devices. On the other hand, the severe energy, memory, processing, and communication constraints of IoT devices and networks pose limitations in the frequency of sensing and reporting. So, it is crucial to minimize the energy consumed by the device for sensing the environment and for transmitting the update messages, while taking into account the requirements for information freshness. Edge-caching can be effective in reducing the sensing and the transmission frequency; however, it requires a proper refreshing scheme to avoid staleness of information, as IoT applications need timeliness of status updates. Recently, the Age of Information (AoI) metric has been introduced: it is the time elapsed since the generation of the last received update, hence it can describe the timeliness of the IoT application’s knowledge of the process sampled by the IoT device. In this work, we propose a model-driven and AoI-aware optimization scheme for information caching at the network edge. To configure the cache parameters, we formulate an optimization problem that minimizes the energy consumption, considering both the sampling frequency and the average frequency of the requests sent to the device for refreshing the cache, while satisfying an AoI requirement expressed by the IoT application. We apply our caching scheme in an emulated IoT network, and we show that it minimizes the energy cost while satisfying the AoI requirement. We also compare the case in which the proposed caching scheme is implemented at the network edge against the case in which there is not a cache at the network edge. We show that the optimized cache can significantly lower the energy cost of devices that have a high transmission cost because it can reduce the number of transmissions. Moreover, the cache makes the system less sensitive to higher application-request rates, as the number of messages forwarded to the devices depends on the cache parameters.

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Zhang, Jixiang, and Yinfei Xu. "Age Analysis of Status Updating System with Probabilistic Packet Preemption." Entropy 24, no. 6 (June 2, 2022): 785. http://dx.doi.org/10.3390/e24060785.

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The age of information (AoI) metric was proposed to measure the freshness of messages obtained at the terminal node of a status updating system. In this paper, the AoI of a discrete time status updating system with probabilistic packet preemption is investigated by analyzing the steady state of a three-dimensional discrete stochastic process. We assume that the queue used in the system is Ber/Geo/1/2*/η, which represents that the system size is 2 and the packet in the buffer can be preempted by a fresher packet with probability η. Instead of considering the system’s AoI separately, we use a three-dimensional state vector (n,m,l) to simultaneously track the real-time changes of the AoI, the age of a packet in the server, and the age of a packet waiting in the buffer. We give the explicit expression of the system’s average AoI and show that the average AoI of the system without packet preemption is obtained by letting η=0. When η is set to 1, the mean of the AoI of the system with a Ber/Geo/1/2* queue is obtained as well. Combining the results we have obtained and comparing them with corresponding average continuous AoIs, we propose a possible relationship between the average discrete AoI with the Ber/Geo/1/c queue and the average continuous AoI with the M/M/1/c queue. For each of two extreme cases where η=0 and η=1, we also determine the stationary distribution of AoI using the probability generation function (PGF) method. The relations between the average AoI and the packet preemption probability η, as well as the AoI’s distribution curves in two extreme cases, are illustrated by numerical simulations. Notice that the probabilistic packet preemption may occur, for example, in an energy harvest (EH) node of a wireless sensor network, where the packet in the buffer can be replaced only when the node collects enough energy. In particular, to exhibit the usefulness of our idea and methods and highlight the merits of considering discrete time systems, in this paper, we provide detailed discussions showing how the results about continuous AoI are derived by analyzing the corresponding discrete time system and how the discrete age analysis is generalized to the system with multiple sources. In terms of packet service process, we also propose an idea to analyze the AoI of a system when the service time distribution is arbitrary.

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Mamduhi, Mohammad H., Jaya Prakash Champati, James Gross, and Karl H. Johansson. "Where Freshness Matters in the Control Loop: Mixed Age-of-Information and Event-Based Co-Design for Multi-Loop Networked Control Systems." Journal of Sensor and Actuator Networks 9, no. 3 (September 21, 2020): 43. http://dx.doi.org/10.3390/jsan9030043.

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In the design of multi-loop Networked Control Systems (NCSs), wherein each control system is characterized by heterogeneous dynamics and associated with a certain set of timing specifications, appropriate metrics need to be employed for the synthesis of control and networking policies to efficiently respond to the requirements of each control loop. The majority of the design approaches for sampling, scheduling, and control policies include either time-based or event-based metrics to perform pertinent actions in response to the changes of the parameters of interest. We specifically focus in this article on Age-of-Information (AoI) as a recently-developed time-based metric and threshold-based triggering function as a generic Event-Triggered (ET) metric. We consider multiple heterogeneous stochastic linear control systems that close their feedback loops over a shared communication network. We investigate the co-design across the NCS and discuss the pros and cons with the AoI and ET approaches in terms of asymptotic control performance measured by Linear-Quadratic Gaussian (LQG) cost functions. In particular, sampling and scheduling policies combining AoI and stochastic ET metrics are proposed. It is argued that pure AoI functions that generate decision variables solely upon minimizing the average age irrespective of control systems dynamics may not be able to improve the overall NCS performance even compared with purely randomized policies. Our theoretical analysis is validated through several simulation scenarios.

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Peng, Fuzhou, Xiang Chen, and Xijun Wang. "Channel Quality-Based Optimal Status Update for Information Freshness in Internet of Things." Entropy 23, no. 7 (July 18, 2021): 912. http://dx.doi.org/10.3390/e23070912.

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This paper investigates the status updating policy for information freshness in Internet of things (IoT) systems, where the channel quality is fed back to the sensor at the beginning of each time slot. Based on the channel quality, we aim to strike a balance between the information freshness and the update cost by minimizing the weighted sum of the age of information (AoI) and the energy consumption. The optimal status updating problem is formulated as a Markov decision process (MDP), and the structure of the optimal updating policy is investigated. We prove that, given the channel quality, the optimal policy is of a threshold type with respect to the AoI. In particular, the sensor remains idle when the AoI is smaller than the threshold, while the sensor transmits the update packet when the AoI is greater than the threshold. Moreover, the threshold is proven to be a non-increasing function of channel state. A numerical-based algorithm for efficiently computing the optimal thresholds is proposed for a special case where the channel is quantized into two states. Simulation results show that our proposed policy performs better than two baseline policies.

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Yang, Yaoqi, Xianglin Wei, Renhui Xu, Laixian Peng, Shuai Cheng, and Lin Ge. "Channel Access-Based Joint Optimization of AoI and SINR under Attack: Game Theory and Distributed Approach." Wireless Communications and Mobile Computing 2021 (July 19, 2021): 1–10. http://dx.doi.org/10.1155/2021/2803335.

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This paper focuses on the joint optimization of the Age of Information (AoI) and Signal to Interference plus Noise Ratio- (SINR-) oriented channel access problem under attack in the Wireless Sensor Networks (WSNs). Firstly, to overcome the uncertain, dynamic, and incomplete information constrains, an active probability model and a controlling channel model are proposed for the sensors and the receiving end, respectively. Secondly, to ensure the AoI and SINR of the data generated by the sensors when transmitted under attack, one utility function based on average AoI and SINR is defined. Then, considering the distributed feature of the channel access process, the joint optimization problem is formulated under the game theory structure. Then, a distributed learning algorithm is proposed to reach the Nash Equilibrium (NE) of the game. Finally, simulation results have verified the correctness and effectiveness of the proposed method.

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Okegbile, Samuel, and Bodhaswar Maharaj. "Age of Information and Success Probability Analysis in Hybrid Spectrum Access-Based Massive Cognitive Radio Networks." Applied Sciences 11, no. 4 (February 23, 2021): 1940. http://dx.doi.org/10.3390/app11041940.

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In this paper, we investigate users’ performance under the hybrid spectrum access model in the massive cognitive radio network (CRN), where multiple primary users (PUs) and secondary users (SUs) transmit on the same channel simultaneously. SUs first detect the state of the channel via channel sensing and select an appropriate channel access scheme (either underlay or overlay) for their transmissions based on the outcome of the channel sensing. When at least one PU is active, SUs transmit under the underlay channel access scheme by employing the power control technique to ensure that the interference generated in the primary network is below the pre-defined interference threshold. In the absence of PU, SUs transmit with full transmit power under the overlay channel access scheme, thereby maximizing their throughput. Using the tool of stochastic geometry, we obtained tractable analyses for important metrics such as success probability, throughput, and the average age of information (AoI) in both primary and secondary networks, while capturing the interference between the two networks. The obtained analyses offer an efficient way to understand the metrics of AoI, throughput and success probability in the hybrid spectrum access-based CRN. We further compared users’ performance under the hybrid spectrum access scheme with performances under overlay and underlay spectrum access schemes. The outcome of the numerical simulations shows that the hybrid spectrum access scheme can significantly improve the performance of users in the network, while also capturing more key features of real-life systems.

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Huang, Wenjun, Xu Li, and Yanan Liang. "Impact of Age Violation Probability on Neighbor Election-Based Distributed Slot Access in Wireless Ad Hoc Networks." Electronics 12, no. 2 (January 10, 2023): 351. http://dx.doi.org/10.3390/electronics12020351.

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In this paper, we propose an analytical model of neighbor election-based distributed slot access by considering the relationship between the age of information (AoI) and the slot access process of nodes in wireless ad hoc networks. A node first maintains the information updates from its neighbors by relaying and receiving messages and determines message transmission slots by holding elections with its relevant competing neighbors. We first find out and analyze the interaction relationship between the transmission probability of nodes, the competing probability of neighbor nodes, and the violation probability that AoI exceeds the timeliness threshold of the neighbor election. Next, we obtain the approximated expression of the competing probability and the age violation probability based on the comprehensive analysis of the neighbor election process. Numerical and simulation results show that our approximation is tighter than the one in the literature and also provides insights into enhancing the design of network-aware distributed multiple access schemes.

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Wang, Lixin, Fuzhou Peng, Xiang Chen, and Shidong Zhou. "Optimal Information Update for Energy Harvesting Sensor with Reliable Backup Energy." Entropy 24, no. 7 (July 11, 2022): 961. http://dx.doi.org/10.3390/e24070961.

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The timely delivery of status information collected from sensors is critical in many real-time applications, e.g., monitoring and control. In this paper, we consider a scenario where a wireless sensor sends updates to the destination over an erasure channel with the supply of harvested energy and reliable backup energy. We adopt the metric age of information (AoI) to measure the timeliness of the received updates at the destination. We aim to find the optimal information updating policy that minimizes the time-average weighted sum of the AoI and the reliable backup energy cost. First, when all the environmental statistics are assumed to be known, the optimal information updating policy exists and is proved to have a threshold structure. Based on this special structure, an algorithm for efficiently computing the optimal policy is proposed. Then, for the unknown environment, a learning-based algorithm is employed to find a near-optimal policy. The simulation results verify the correctness of the theoretical derivation and the effectiveness of the proposed method.

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Luan, Ning, Ke Xiong, Zhifei Zhang, Haina Zheng, Yu Zhang, Pingyi Fan, and Gang Qu. "Age-Aware Utility Maximization in Relay-Assisted Wireless Powered Communication Networks." Entropy 23, no. 9 (September 7, 2021): 1177. http://dx.doi.org/10.3390/e23091177.

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This article investigates a relay-assisted wireless powered communication network (WPCN), where the access point (AP) inspires the auxiliary nodes to participate together in charging the sensor, and then the sensor uses its harvested energy to send status update packets to the AP. An incentive mechanism is designed to overcome the selfishness of the auxiliary node. In order to further improve the system performance, we establish a Stackelberg game to model the efficient cooperation between the AP–sensor pair and auxiliary node. Specifically, we formulate two utility functions for the AP–sensor pair and the auxiliary node, and then formulate two maximization problems respectively. As the former problem is non-convex, we transform it into a convex problem by introducing an extra slack variable, and then by using the Lagrangian method, we obtain the optimal solution with closed-form expressions. Numerical experiments show that the larger the transmit power of the AP, the smaller the age of information (AoI) of the AP–sensor pair and the less the influence of the location of the auxiliary node on AoI. In addition, when the distance between the AP and the sensor node exceeds a certain threshold, employing the relay can achieve better AoI performance than non-relaying systems.

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Chen, Zhengchuan, Mingjun Xu, Min Wang, and Yunjian Jia. "Joint Optimization of Data Freshness and Fidelity for Selection Combining-Based Transmissions." Entropy 24, no. 2 (January 28, 2022): 200. http://dx.doi.org/10.3390/e24020200.

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Motivated by big data applications in the Internet of Things (IoT), abundant information arrives at the fusion center (FC) waiting to be processed. It is of great significance to ensure data freshness and fidelity simultaneously. We consider a wireless sensor network (WSN) where several sensor nodes observe one metric and then transmit the observations to the FC using a selection combining (SC) scheme. We adopt the age of information (AoI) and minimum mean square error (MMSE) metrics to measure the data freshness and fidelity, respectively. Explicit expressions of average AoI and MMSE are derived. After that, we jointly optimize the two metrics by adjusting the number of sensor nodes. A closed-form sub-optimal number of sensor nodes is proposed to achieve the best freshness and fidelity tradeoff with negligible errors. Numerical results show that using the proposed node number designs can effectively improve the freshness and fidelity of the transmitted data.

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Hahn, Jannik, and Olaf Stursberg. "Uncertain AoI in stochastic optimal control of constrained LTI systems." at - Automatisierungstechnik 70, no. 4 (March 25, 2022): 343–54. http://dx.doi.org/10.1515/auto-2021-0125.

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Abstract This paper addresses finite-time horizon optimal control of control structures with shared communication network. To cope with the uncertainties, induced by network imperfections and exogenous disturbances at the same time, an optimization-based control scheme is proposed. It uses a disturbance feedback and the Age of Information (AoI), a receiver-based measure of communication delays, as central aspects. The disturbance feedback is an extension of the control law used for balanced stochastic optimal control. Balanced optimality is understood as a compromise between minimizing expected deviations from the reference and the minimization of the uncertainty of future states. Time-varying state constraints as well as time-invariant input constraints are considered, and the controllers are synthesized by semi-definite programming.

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Diao, Xianbang, Wendong Yang, Jianchao Zheng, and Yueming Cai. "Joint Scheduling and Power Optimization for Complex Status Updates in Multiantenna UAV-Assisted Multiaccess Edge Computing." Wireless Communications and Mobile Computing 2022 (February 2, 2022): 1–20. http://dx.doi.org/10.1155/2022/8117391.

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The status information of complex status update applications (e.g., real-time environmental monitoring in disaster areas) can only be obtained after data processing. Therefore, the impact of data processing on age of information (AoI) cannot be ignored in complex status update applications. In this paper, complex status updates in emergency scenario are investigated, where some multiantenna unmanned aerial vehicles (UAVs) help resource-limited user devices (UDs) complete complex status updates which involve computing processes. To reduce average AoI, UDs’ energy consumptions, and UAVs’ energy consumptions in a balanced manner, the weighted sum of the three metrics is aimed to be minimized. Scheduling strategies (i.e., data transmission and computing start moments, service period, and flight radius) and power (i.e., data and pilot transmit power) allocation strategies are jointly optimized to reduce the weighted sum. The original problem is NP-hard. Thus, it is decoupled into some subproblems. Then, the near-optimal solution or stationary point of each subproblem is obtained by analyzing the characteristics of the subproblems. Finally, an iterative algorithm is proposed to alternately optimize the scheduling and power allocation strategies to obtain the suboptimal solution of the original problem. Simulation results show that the proposed algorithm can effectively reduce the average AoI and the energy consumptions of UDs and UAVs in a balanced way.

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Li, Xinmin, Jiahui Li, and Dandan Liu. "Energy-Efficient UAV Trajectory Design with Information Freshness Constraint via Deep Reinforcement Learning." Mobile Information Systems 2021 (December 23, 2021): 1–9. http://dx.doi.org/10.1155/2021/1430512.

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Unmanned aerial vehicle (UAV) technique with flexible deployment has enabled the development of Internet of Things (IoT) applications. However, it is difficult to guarantee the freshness of information delivery for the energy-limited UAV. Thus, we study the trajectory design in the multiple-UAV communication system, in which the massive ground devices send the individual information to mobile UAV base stations under the demand of information freshness. First, an energy-efficiency (EE) maximization optimization problem is formulated under the rest energy, safety distance, and age of information (AoI) constraints. However, it is difficult to solve the optimization problem due to the nonconvex objective function and unknown dynamic environment. Second, a trajectory design based on the deep Q-network method is proposed, in which the state space considering energy efficiency, rest energy, and AoI and the efficient reward function related with EE performance are constructed, respectively. Furthermore, to avoid the dependency of training data for the neural network, the experience replay and random sampling for batch are adopted. Finally, we validate the system performance of the proposed scheme. Simulation results show that the proposed scheme can achieve a better EE performance compared with the benchmark scheme.

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Zou, Peng, and Suresh Subramaniam. "On the Value of Information in Status Update Systems." Entropy 24, no. 4 (March 24, 2022): 449. http://dx.doi.org/10.3390/e24040449.

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The age of information (AoI) is now well established as a metric that measures the freshness of information delivered to a receiver from a source that generates status updates. This paper is motivated by the inherent value of packets arising in many cyber-physical applications (e.g., due to precision of the information content or an alarm message). In contrast to AoI, which considers all packets are of equal importance or value, we consider status update systems with update packets carrying values as well as their generated time stamps. A status update packet has a random initial value at the source and a deterministic deadline after which its value vanishes (called ultimate staleness). In our model, the value of a packet either remains constant until the deadline or decreases in time (even after reception) starting from its generation to the deadline when it vanishes. We consider two metrics for the value of information (VoI) at the receiver: sum VoI is the sum of the current values of all packets held by the receiver, whereas packet VoI is the value of a packet at the instant it is delivered to the receiver. We investigate various queuing disciplines under potential dependence between value and service time and provide closed form expressions for both average sum VoI and packet VoI at the receiver. Numerical results illustrate the average VoI for different scenarios and relations between average sum VoI and average packet VoI.

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Wang, Lehan, Jingzhou Sun, Yuxuan Sun, Sheng Zhou, and Zhisheng Niu. "A UoI-Optimal Policy for Timely Status Updates with Resource Constraint." Entropy 23, no. 8 (August 20, 2021): 1084. http://dx.doi.org/10.3390/e23081084.

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Timely status updates are critical in remote control systems such as autonomous driving and the industrial Internet of Things, where timeliness requirements are usually context dependent. Accordingly, the Urgency of Information (UoI) has been proposed beyond the well-known Age of Information (AoI) by further including context-aware weights which indicate whether the monitored process is in an emergency. However, the optimal updating and scheduling strategies in terms of UoI remain open. In this paper, we propose a UoI-optimal updating policy for timely status information with resource constraint. We first formulate the problem in a constrained Markov decision process and prove that the UoI-optimal policy has a threshold structure. When the context-aware weights are known, we propose a numerical method based on linear programming. When the weights are unknown, we further design a reinforcement learning (RL)-based scheduling policy. The simulation reveals that the threshold of the UoI-optimal policy increases as the resource constraint tightens. In addition, the UoI-optimal policy outperforms the AoI-optimal policy in terms of average squared estimation error, and the proposed RL-based updating policy achieves a near-optimal performance without the advanced knowledge of the system model.

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Peng, Yingsheng, Yong Liu, Dong Li, and Han Zhang. "Deep Reinforcement Learning Based Freshness-Aware Path Planning for UAV-Assisted Edge Computing Networks with Device Mobility." Remote Sensing 14, no. 16 (August 18, 2022): 4016. http://dx.doi.org/10.3390/rs14164016.

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As unmanned aerial vehicles (UAVs) can provide flexible and efficient services concerning the sparse network distribution, we study a UAV-assisted mobile edge computing (MEC) network. To satisfy the freshness requirement of IoT applications, the age of information (AoI) is incorporated as an important performance metric. Then, the path planning problem is formulated to simultaneously minimize the AoIs of mobile devices and the energy consumption of the UAV, where the movement randomness of IoT devices are taken into account. Concerning the dimension explosion, the deep reinforcement learning (DRL) framework is exploited, and a double deep Q-learning network (DDQN) algorithm is proposed to realize the intelligent and freshness-aware path planning of the UAV. Extensive simulation results validate the effectiveness of the proposed freshness-aware path planning scheme and unveil the effects of the moving speed of devices and the UAV on the achieved AoI.

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Choi, Jong-Young, and Young-Bae Ko. "An Adaptive Safety Message Transmission Algorithm Based on Age-of-Information and Collision Risk-Level with Adjacent Vehicles in IEEE802.11p/WAVE Vehicular Networks." Journal of Korean Institute of Communications and Information Sciences 47, no. 3 (March 31, 2022): 471–73. http://dx.doi.org/10.7840/kics.2022.47.3.471.

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Cheikh, Imane, Essaid Sabir, Rachid Aouami, Sébastien Roy, and Mohamed Sadik. "Data Freshness and End-to-End Delay in Cross-Layer Two-Tier Linear IoT Networks." Sensors 22, no. 23 (December 3, 2022): 9455. http://dx.doi.org/10.3390/s22239455.

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The operational and technological structures of radio access networks have undergone tremendous changes in recent years. A displacement of priority from capacity–coverage optimization (to ensure data freshness) has emerged. Multiple radio access technology (multi-RAT) is a solution that addresses the exponential growth of traffic demands, providing degrees of freedom in meeting various performance goals, including energy efficiencies in IoT networks. The purpose of the present study was to investigate the possibility of leveraging multi-RAT to reduce each user’s transmission delay while preserving the requisite quality of service (QoS) and maintaining the freshness of the received information via the age of information (AoI) metric. First, we investigated the coordination between a multi-hop network and a cellular network. Each IoT device served as an information source that generated packets (transmitting them toward the base station) and a relay (for packets generated upstream). We created a queuing system that included the network and MAC layers. We propose a framework comprised of various models and tools for forecasting network performances in terms of the end-to-end delay of ongoing flows and AoI. Finally, to highlight the benefits of our framework, we performed comprehensive simulations. In discussing these numerical results, insights regarding various aspects and metrics (parameter tuning, expected QoS, and performance) are made apparent.

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Jiqing Gu, Chao Song, Siqi Liao, Hongwei Li, Ming Liu, and Jie Wu. "Generation rate control with AoI under traffic hole problem in vehicular networks." ITU Journal on Future and Evolving Technologies 3, no. 2 (July 8, 2022): 47–58. http://dx.doi.org/10.52953/difr6805.

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In 6G mobile networks, vehicular networks will significantly benefit from extremely high network throughput and capacity. For Internet of Things (IoT) within a vehicular network, the sensor data as an update is delivered from each sensor source to a nearby gateway, by Vehicle-to-Vehicle (V2V) and Vehicle to Roadside unit (V2R) communications. The mobility of the vehicles is not only affected by the vehicle itself, but also by external means, such as the signal operations of traffic lights. The red light stops the vehicles at the intersection, which will increase the time it takes for updates carried by the vehicle to be delivered. On the other hand, the red light can also increase the opportunities of vehicles moving behind to catch up with the waiting vehicles in forwarding updates. This is termed as the traffic hole problem by the traffic lights in vehicular networks. In this paper, we investigate the influence of traffic lights in vehicular networks using the metric of Age of Information (AoI). We discuss the optimal generation rate at the source by considering the trade-off between AoI and transmission cost. We propose a Total Average Cost aware generation rate Algorithm (TACA) for the generation interval time at the sensor source. Our intensive simulations verify the proposed algorithm and evaluate the influence of the traffic lights on AoI.

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Chiariotti, Federico, Israel Leyva-Mayorga, Čedomir Stefanović, Anders E. Kalør, and Petar Popovski. "Spectrum Slicing for Multiple Access Channels with Heterogeneous Services." Entropy 23, no. 6 (May 28, 2021): 686. http://dx.doi.org/10.3390/e23060686.

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Wireless mobile networks from the fifth generation (5G) and beyond serve as platforms for flexible support of heterogeneous traffic types with diverse performance requirements. In particular, the broadband services aim for the traditional rate optimization, while the time-sensitive services aim for the optimization of latency and reliability, and some novel metrics such as Age of Information (AoI). In such settings, the key question is the one of spectrum slicing: how these services share the same chunk of available spectrum while meeting the heterogeneous requirements. In this work we investigated the two canonical frameworks for spectrum sharing, Orthogonal Multiple Access (OMA) and Non-Orthogonal Multiple Access (NOMA), in a simple, but insightful setup with a single time-slotted shared frequency channel, involving one broadband user, aiming to maximize throughput and using packet-level coding to protect its transmissions from noise and interference, and several intermittent users, aiming to either to improve their latency-reliability performance or to minimize their AoI. We analytically assessed the performances of Time Division Multiple Access (TDMA) and ALOHA-based schemes in both OMA and NOMA frameworks by deriving their Pareto regions and the corresponding optimal values of their parameters. Our results show that NOMA can outperform traditional OMA in latency-reliability oriented systems in most conditions, but OMA performs slightly better in age-oriented systems.

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Chen, Yuchao, Haoyue Tang, Jintao Wang, and Jian Song. "Optimizing Age Penalty in Time-Varying Networks with Markovian and Error-Prone Channel State." Entropy 23, no. 1 (January 10, 2021): 91. http://dx.doi.org/10.3390/e23010091.

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In this paper, we consider a scenario where the base station (BS) collects time-sensitive data from multiple sensors through time-varying and error-prone channels. We characterize the data freshness at the terminal end through a class of monotone increasing functions related to Age of information (AoI). Our goal is to design an optimal policy to minimize the average age penalty of all sensors in infinite horizon under bandwidth and power constraint. By formulating the scheduling problem into a constrained Markov decision process (CMDP), we reveal the threshold structure for the optimal policy and approximate the optimal decision by solving a truncated linear programming (LP). Finally, a bandwidth-truncated policy is proposed to satisfy both power and bandwidth constraint. Through theoretical analysis and numerical simulations, we prove the proposed policy is asymptotic optimal in the large sensor regime.

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Chen, Yuchao, Haoyue Tang, Jintao Wang, and Jian Song. "Optimizing Age Penalty in Time-Varying Networks with Markovian and Error-Prone Channel State." Entropy 23, no. 1 (January 10, 2021): 91. http://dx.doi.org/10.3390/e23010091.

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In this paper, we consider a scenario where the base station (BS) collects time-sensitive data from multiple sensors through time-varying and error-prone channels. We characterize the data freshness at the terminal end through a class of monotone increasing functions related to Age of information (AoI). Our goal is to design an optimal policy to minimize the average age penalty of all sensors in infinite horizon under bandwidth and power constraint. By formulating the scheduling problem into a constrained Markov decision process (CMDP), we reveal the threshold structure for the optimal policy and approximate the optimal decision by solving a truncated linear programming (LP). Finally, a bandwidth-truncated policy is proposed to satisfy both power and bandwidth constraint. Through theoretical analysis and numerical simulations, we prove the proposed policy is asymptotic optimal in the large sensor regime.

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Bu, Fanfeng, Hanjiang Luo, Saisai Ma, Xiang Li, Rukhsana Ruby, and Guangjie Han. "AUV-Aided Optical—Acoustic Hybrid Data Collection Based on Deep Reinforcement Learning." Sensors 23, no. 2 (January 4, 2023): 578. http://dx.doi.org/10.3390/s23020578.

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Autonomous underwater vehicles (AUVs)-assisted mobile data collection in underwater wireless sensor networks (UWSNs) has received significant attention because of their mobility and flexibility. To satisfy the increasing demand of diverse application requirements for underwater data collection, such as time-sensitive data freshness, emergency event security as well as energy efficiency, in this paper, we propose a novel multi-modal AUV-assisted data collection scheme which integrates both acoustic and optical technologies and takes advantage of their complementary strengths in terms of communication distance and data rate. In this scheme, we consider the age of information (AoI) of the data packet, node transmission energy as well as energy consumption of the AUV movement, and we make a trade-off between them to retrieve data in a timely and reliable manner. To optimize these, we leverage a deep reinforcement learning (DRL) approach to find the optimal motion trajectory of AUV by selecting the suitable communication options. In addition to that, we also design an optimal angle steering algorithm for AUV navigation under different communication scenarios to reduce energy consumption further. We conduct extensive simulations to verify the effectiveness of the proposed scheme, and the results show that the proposed scheme can significantly reduce the weighted sum of AoI as well as energy consumption.

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Ju, Zhuoxuan, Parisa Rafiee, and Omur Ozel. "Optimizing Urgency of Information through Resource Constrained Joint Sensing and Transmission." Entropy 24, no. 11 (November 9, 2022): 1624. http://dx.doi.org/10.3390/e24111624.

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Applications requiring services from modern wireless networks, such as those involving remote control and supervision, call for maintaining the timeliness of information flows. Current research and development efforts for 5G, Internet of things, and artificial intelligence technologies will benefit from new notions of timeliness in designing novel sensing, computing, and transmission strategies. The age of information (AoI) metric and a recent related urgency of information (UoI) metric enable promising frameworks in this direction. In this paper, we consider UoI optimization in an interactive point-to-point system when the updating terminal is resource constrained to send updates and receive/sense the feedback of the status information at the receiver. We first propose a new system model that involves Gaussian distributed time increments at the receiving end to design interactive transmission and feedback sensing functions and develop a new notion of UoI suitable for this system. We then formulate the UoI optimization with a new objective function involving a weighted combination of urgency levels at the transmitting and receiving ends. By using a Lyapunov optimization framework, we obtain a decision strategy under energy resource constraints at both transmission and receiving/sensing and show that it can get arbitrarily close to the optimal solution. We numerically study performance comparisons and observe significant improvements with respect to benchmarks.

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Zheng, Huiji, Sicong Yu, Xinyuan Qiu, Xiaolong Cui, and Li Zhu. "“Fed-DRL”: A Timeliness Optimization Method for Dynamic Data Acquisition System Based on Mobile Edge Computing." Mathematical Problems in Engineering 2022 (July 31, 2022): 1–13. http://dx.doi.org/10.1155/2022/5719190.

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Age of Information (AoI) is a metric to describe the timeliness of a system proposed in recent years. It measures the freshness of the latest received data from the perspective of the target node in the system. This work studies a kind of dynamic data acquisition system for urban security that can update and control the situation of urban environmental security by collecting environmental data. The collected data packets need to be uploaded to the cloud center in time for data update, which has high requirements on the timeliness of the system and freshness of data. However, due to the limited computing capacity of mobile terminals and the pressure of bandwidth for data transmission, problems such as high data execution delay and transmission interruption are caused. Emerging mobile edge computing (MEC), a new model of computing that extends cloud computing capabilities to the edge network, promises to solve these problems. This work focuses on the timeliness of the system, as measured by the average AoI across all mobile terminals. First, a timeliness optimization model is defined, and a multi-agent deep reinforcement learning (DRL) algorithm combined with an attention mechanism is proposed to carry out computing offloading and resource allocation through the continuous interaction between agent and environment; then, in order to improve algorithm performance and data security, the federated learning mode is proposed to train agents; finally, the proposed algorithm is compared with other main baseline algorithms based on deep reinforcement learning. The simulation results show that the proposed algorithm not only outperforms other algorithms in optimizing system timeliness, but also improves the stability of training.

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Qin, Zhenquan, Xuan Zhang, Xinwei Zhang, Bingxian Lu, Zhonghao Liu, and Linlin Guo. "The UAV Trajectory Optimization for Data Collection from Time-Constrained IoT Devices: A Hierarchical Deep Q-Network Approach." Applied Sciences 12, no. 5 (February 28, 2022): 2546. http://dx.doi.org/10.3390/app12052546.

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Recently, using unmanned aerial vehicles (UAVs) to collect information from distributed sensors has become one of the hotspots in the Internet of Things (IoT) research. However, previous studies on the UAV-assisted data acquisition systems focused mainly on shortening the acquisition time, reducing the energy consumption, and increasing the amount of collected data, but it lacked the optimization of data freshness. Moreover, we hope that UAVs can perform long-term data collection tasks in dynamic scenarios within a constantly changing age of information (AoI) and within their own power levels. Therefore, we aim to maximize the quality of service (QoS) based on the freshness of data, while considering the endurance of the UAVs. Since our scenario is not an inertial order decision process with uniform time slots, we first transform the optimization problem into a semi-Markov decision process (SMDP) through modeling, and then we propose a hierarchical deep Q-network (DQN)-based path-planning algorithm to learn the optimal strategy. The simulation results show that the algorithm is better than the benchmark algorithm, and the tradeoff between the system QoS and the safe power state can be achieved by adjusting the parameter βe.

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Zhang, Tianci, Shutong Chen, and Zhengchuan Chen. "Internet of Things: The Optimal Generation Rates under Preemption Strategy in a Multi-Source Queuing System." Entropy 23, no. 8 (August 16, 2021): 1055. http://dx.doi.org/10.3390/e23081055.

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With the rapid development and wide application of the Internet of Things (IoT), how to provide timely and fresh information for strategic analysis and decision-making has become a key issue. Recent studies have shown that preemption strategies are of great importance to the improvement of information freshness. In view of this, we focus on the multi-source preemptive queuing model and investigate how to control the generation rate of each source to achieve the optimal overall information freshness. Specifically, we consider two typical preemption strategies: self-preemption strategy and global-preemption strategy. Noting that the urgency requirements of the systems on the data of each source are different, we propose the weighted average age of information (AoI) to characterize the overall information freshness of the system. For the self-preemption strategy, we prove that the optimal generation rate allocation is a convex problem and present an efficient algorithm to find the optimal solution. Additionally, we also derive a closed-form approximate optimal solution under light load cases to meet the demands for rapid deployment. For the global-preemption strategy, we directly derive the closed-form optimal solution of the corresponding problem. By comparing the optimized weighted average AoIs, the performance achieved by the global-preemption system was better than that achieved by the self-preemption system in terms of the overall timeliness. The numerical analysis verified the correctness of the theoretical analysis and that the proposed approximate solution had high accuracy not only under light load cases but also under other cases.

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Amadeo, Marica. "A Literature Review on Caching Transient Contents in Vehicular Named Data Networking." Telecom 2, no. 1 (February 9, 2021): 75–92. http://dx.doi.org/10.3390/telecom2010006.

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Vehicular Named Data Networking (VNDN) is a revolutionary information-centric architecture specifically conceived for vehicular networks and characterized by name-based forwarding and in-network caching. So far, a variety of caching schemes have been proposed for VNDN that work in presence of static Data packets, like traditional Internet contents. However, with the advent of Internet of Things (IoT) and Internet of Vehicles (IoV) applications, large sets of vehicular contents are expected to be transient, i.e., they are characterized by a limited lifetime and become invalid after the latter expires. This is the case of information related to road traffic or parking lot availability, which can change after a few minutes—or even after a few seconds—it has been generated at the source. The transiency of contents may highly influence the network performance, including the gain of in-network caching. Therefore, in this paper, we consider the dissemination of transient contents in vehicular networks and its effects on VNDN caching. By providing a detailed review of related work, we identify the main challenges and objectives when caching transient contents, e.g., to avoid cache inconsistency, to minimize the Age of Information (AoI) and the retrieval latency, and the main strategies to fulfill them. We scan the existing caching and replacement policies specifically designed for transient contents in VNDN and, finally, we outline interesting research perspectives.

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Grant, Frances L., and Robert G. Main. "Curriculum 1984: Meeting the needs of the information age." Journal of the American Society for Information Science 37, no. 1 (January 1986): 12–19. http://dx.doi.org/10.1002/asi.4630370103.

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Karanam, Saraschandra, Herre van Oostendorp, Mylene Sanchiz, Aline Chevalier, Jessie Chin, and Wai-Tat Fu. "Cognitive modeling of age-related differences in information search behavior." Journal of the Association for Information Science and Technology 68, no. 10 (July 18, 2017): 2328–37. http://dx.doi.org/10.1002/asi.23893.

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Lim, Sesil, JongRoul Woo, Jongsu Lee, and Sung-Yoon Huh. "Consumer valuation of personal information in the age of big data." Journal of the Association for Information Science and Technology 69, no. 1 (September 12, 2017): 60–71. http://dx.doi.org/10.1002/asi.23915.

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Gaziel Yablowitz, Michal, and Daphne R. Raban. "Investment decision paths in the information age: The effect of online journalism." Journal of the Association for Information Science and Technology 67, no. 6 (May 5, 2015): 1417–29. http://dx.doi.org/10.1002/asi.23453.

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Foster, Jonathan, and Paul Clough. "Embedded, added, cocreated: Revisiting the value of information in an age of data." Journal of the Association for Information Science and Technology 69, no. 5 (December 8, 2017): 744–48. http://dx.doi.org/10.1002/asi.23987.

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Tenopir, Carol, Kenneth Levine, Suzie Allard, Lisa Christian, Rachel Volentine, Reid Boehm, Frances Nichols, et al. "Trustworthiness and authority of scholarly information in a digital age: Results of an international questionnaire." Journal of the Association for Information Science and Technology 67, no. 10 (September 23, 2015): 2344–61. http://dx.doi.org/10.1002/asi.23598.

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Yao, Xinlin, Cheng Zhang, Zhe Qu, and Bernard C. Y. Tan. "Global village or virtual balkans? evolution and performance of scientific collaboration in the information age." Journal of the Association for Information Science and Technology 71, no. 4 (May 11, 2019): 395–408. http://dx.doi.org/10.1002/asi.24251.

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Belefant-Miller, Helen, and Donald W. King. "A profile of faculty reading and information-use behaviors on the cusp of the electronic age." Journal of the American Society for Information Science and Technology 54, no. 2 (2003): 179–81. http://dx.doi.org/10.1002/asi.10180.

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Baruchson-Arbib, Shifra, and Jenny Bronstein. "Humanists as information users in the digital age: The case of Jewish studies scholars in Israel." Journal of the American Society for Information Science and Technology 58, no. 14 (2007): 2269–79. http://dx.doi.org/10.1002/asi.20699.

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Avis, Emily, Padmaja Sundaram, Rachel Flink-Bochacki, and Johanna Bringley. "Effect of Age on Gynecologic Patients’ Use of Social Media for Women’s Health Information [A84]." Obstetrics & Gynecology 139, no. 1 (May 2022): 25S. http://dx.doi.org/10.1097/01.aog.0000826664.20681.9b.

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Maghari, Ibrahim, Abdul-rahman Abusalim, Pius Ojemolon, Abdul-rahman Abusalim, Hafeez Shaka, and Hisham Laswi. "PSUN119 Obesity As An Independent Factor In Outcome Of SIADH Hospitalizations." Journal of the Endocrine Society 6, Supplement_1 (November 1, 2022): A22—A23. http://dx.doi.org/10.1210/jendso/bvac150.047.

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Abstract Introduction Several comorbidities have been associated with the syndrome of inappropriate anti-diuretic hormone secretion (SIADH). However, not much literature documents an association between SIADH and obesity, and there is a marked paucity of research documenting the impact of obesity on outcomes in patients hospitalized with SIADH. Method We extracted data from the US Nationwide Inpatient Sample (NIS) for 2019. The NIS contains hospital discharge information estimating yearly US hospitalizations. We included hospitalizations with a principal discharge diagnostic code for SIADH using the ICD-10-CM code (E22.2). The study excluded hospitalizations of patients less than 18 years. This cohort was divided based on the secondary diagnosis of obesity. Outcomes included comparing inpatient mortality rates, mean length of hospital stay (LOS), mean hospitalization cost (THC), rates of septic shock, acute myocardial infarction (AMI), acute respiratory failure (ARF), acute renal failure (AKI), acute pulmonary edema (PE) between the subgroups. An adjustment was made for age, sex, race, primary payer, median household income by zip code, Carlson Comorbidity Index (CCI), hospital location, bed-size, and teaching status using multivariate regression analysis. Statistical significance was set at a p-value < 0.05. Results In 2019, a total of 39,110 hospitalizations involved patients with SIADH as the reason for the admission and 7.7% of these admissions had comorbid obesity. A higher proportion of hospitalizations involved females, with more of the obese cohort being females (65.7 vs 61.4%, p=0.034). Patients with obesity comparatively had a lower mean age (67.9±13.1 vs 73±13.3 years, p<0.001), a higher proportion of CCI >2, and a higher proportion of Whites. In patients with SIADH, obesity was associated with no difference in mortality (1.1 vs 1.3%, p=0.589) or THC, but patients with obesity had higher odds of increased LOS (5.6 vs 4.9 days, p=0.007), AKI (20 vs 11.3%, aOR: 1.88, p<0.001), and ARF (11.2 vs 7%, aOR: 1.53, p=0.003). There was no significant difference in CVA, PE, septic shock or AMI odds. Conclusions Comorbid obesity was associated with higher LOS and odds of AKI and ARF, but there was no difference in mortality, THC, CVA, PE, septic shock or AMI compared to SIADH hospitalizations without obesity. Presentation: Sunday, June 12, 2022 12:30 p.m. - 2:30 p.m.

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Haigh, Thomas. "Turing: Pioneer of the Information Age. JackCopeland. Oxford: Oxford University Press, 2013. 224 pp. $17.95 (paperback). (ISBN 9780198719182)." Journal of the Association for Information Science and Technology 67, no. 7 (March 20, 2016): 1787–89. http://dx.doi.org/10.1002/asi.23705.

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Jones, Kyle M. L., Alan Rubel, and Ellen LeClere. "A matter of trust: Higher education institutions as information fiduciaries in an age of educational data mining and learning analytics." Journal of the Association for Information Science and Technology 71, no. 10 (December 19, 2019): 1227–41. http://dx.doi.org/10.1002/asi.24327.

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Journal articles on the topic 'Age-of-information (AoI)'

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