Status Updating Research Articles

OATracker: Object-aware anti-occlusion 3D multiobject tracking for autonomous driving

Efficient and accurate 3D multiobject tracking (MOT) is essential for autonomous driving. However, existing methods still struggle with multiobject occlusion, in which interruptions or even loss of crucial tracked objects is likely. Therefore, a more intelligent object-aware anti-occlusion 3D MOT for autonomous driving, named OATracker, is developed in this paper. First, an updated 3D cascaded detection (3DCD) is adopted as the detection backbone, with incorporation of an updatable component based on the OpenPCDet framework to increase the longevity. Second, a reliable object state-constrained affinity (OSA) metric is designed that adaptively combines 3D geometric and motion metrics to dynamically measure objects’ size and distance in both spatial and temporal dimensions. Third, an object-aware trajectory management (OTM) module is developed for trajectory management and status updating. Specifically, the object identity-aware adaptive tracking life manager (ATLM) allows the tracker to adaptively manage the trajectories of captured objects through a confidence metric for each objects, and the ghost-aware trajectory postoptimizer (GTP) associates the historical and detected motion states, further overcoming id-switch and fragmentation problems. Finally, experiments on the KITTI-Car tracking benchmark and practical autonomous driving car application platform show that the OATracker can achieve competitive and robust tracking performance even in occlusion conditions.

Enhancing information freshness in multi-class mobile edge computing systems using a hybrid discipline

Timely status updating in mobile edge computing (MEC) systems has recently gained the utmost interest in internet of things (IoT) networks, where status updates may need higher computations to be interpreted. Moreover, in real-life situations, the status update streams may also be of different priority classes according to their importance and timeliness constraints. The classical disciplines used for priority service differentiation, preemptive and non-preemptive disciplines, pose a dilemma of information freshness dissatisfaction for the whole priority network. This work proposes a hybrid preemptive/non-preemptive discipline under an M/M/1/2 priority queueing model to regulate the priority-based contention of the status update streams in MEC systems. For this hybrid discipline, a probabilistic discretionary rule for preemption is deployed to govern the server and buffer access independently, introducing distinct probability parameters to control the system performance. The stochastic hybrid system approach is utilized to analyze the average age of information (AoI) along with its higher moments for any number of classes. Then, a numerical study on a three-class network is conducted by evaluating the average AoI performance and the corresponding dispersion. The numerical observations underpin the significance of the hybrid-discipline parameters in ensuring the reliability of the whole priority network. Hence, four different approaches are introduced to demonstrate the setting of these parameters. Under these approaches, some outstanding features are manifested: exploiting the buffering resources efficiently, conserving the aggregate sensing power, and optimizing the whole network satisfaction. For this last feature, a near-optimal low-complex heuristic method is proposed.

Resource Allocation for OFDM-Based Status Update Systems: A Timeliness Perspective

Increasingly more time-sensitive applications emerge in Internet of things (IoT), requiring fresh status updates. Efficient resource allocation is critical for improving the timeliness of information. This paper investigates how to allocate bandwidth and configure the transmission in an orthogonal frequency division multiplexing (OFDM)-based IoT systems for timely status updating. Specifically, a general resource allocation problem is formulated using age of information (AoI) as the timeliness metric. We first consider a static channel case where we propose a fixed time slot length policy, a fixed blocklength policy, an iterative optimization algorithm, and an approximate optimal policy to address the optimal resource allocation and transmission configuration. Then, we extend the study to quasi-static fading channel cases. In particular, sticking to the transmission rate and spectral efficiency, the four policies designated for static channel case are tailored for the quasi-static fading channel case. We show that the iterative algorithms can improve the timeliness of the system significantly. Besides, the approximate optimal policy achieves an AoI performance competitive with the iterative algorithm, while reduces the computation complexity in both channel cases.

Grant Free Age-Optimal Random Access Protocol for Satellite-Based Internet of Things

In satellite-based Internet of Things (S-IoT) system, the timely status updating of terrestrial sensing user equipments (UEs) to satellite could be hampered by the long propagation delay, especially in massive machine type communications (mMTC). To guarantee the information freshness in S-IoT, a new performance indicator called age of information (AoI) is exploited to analyze the average AoI (AAoI) in the overload case of mMTC, and a grant free age-optimal (GFAO) random access protocol is proposed to lower the AAoI. Specifically, the closed-form expression of AAoI is derived by tracing the instantaneous AoI evolution of each UE through Markov analysis. Then, the proposed GFAO random access protocol is proved to achieve a minimum AAoI and a maximum throughput in S-IoT, by adjusting the number of access time slots in each transmission frame in the overload case of mMTC. Extensive simulations are conducted to validate the theoretical analysis, and show that there exists different optimal value of access time slots in system load region from 0.2 to 3, which can minimize AAoI and maximize throughput in the proposed GFAO random access protocol.

When to Preprocess? Keeping Information Fresh for Computing-Enable Internet of Things

Age of information (AoI), a notion that measures the information freshness, is an essential performance measure for time-critical applications in Internet of Things (IoT). With the surge of computing resources at the IoT devices, it is possible to preprocess the information packets that contain the status update before sending them to the destination so as to alleviate the transmission burden. However, the additional time and energy expenditure induced by computing also make the optimal updating a non-trivial problem. In this paper, we consider a time-critical IoT system, where the IoT device is capable of preprocessing the status update before the transmission. Particularly, we aim to jointly design the preprocessing and transmission so that the weighted sum of the average AoI of the destination and the energy consumption of the IoT device is minimized. Due to the heterogeneity in transmission and computation capacities, the durations of distinct actions of the IoT device are non-uniform. Therefore, we formulate the status updating problem as an infinite horizon average cost semi-Markov decision process (SMDP) and then transform it into a discrete-time Markov decision process. We demonstrate that the optimal policy is of threshold type with respect to the AoI. Equipped with this, a structure-aware relative policy iteration algorithm is proposed to obtain the optimal policy of the SMDP. Our analysis shows that preprocessing is more beneficial in regimes of high AoIs, given it can reduce the time required for updates. We further prove the switching structure of the optimal policy in a special scenario, where the status updates are transmitted over a reliable channel, and derive the optimal threshold. Finally, simulation results demonstrate the efficacy of preprocessing and show that the proposed policy outperforms two baseline policies.

Timely Status Updating Over Erasure Channels Using an Energy Harvesting Sensor: Single and Multiple Sources

A status updating system is considered in which data from multiple sources are sampled by an energy harvesting sensor and transmitted to a remote destination through an erasure channel. The goal is to deliver status updates of all sources in a timely manner, such that the cumulative long-term average <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">age-of-information</i> (AoI) is minimized. The AoI for each source is defined as the time elapsed since the generation time of the latest successful status update received at the destination from that source. Transmissions are subject to energy availability, which arrives in units according to a Poisson process, with each energy unit capable of carrying out one transmission from only one source. The sensor is equipped with a unit-sized battery to save the incoming energy. A scheduling policy is designed in order to determine which source is sampled using the available energy. The problem is studied in two main settings: 1) no erasure status feedback and 2) perfect instantaneous feedback. For the case of one source, it is shown that <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">renewal policies</i> are optimal, in which successful status update instances form a renewal process. In the setting without feedback, it is further shown that <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">threshold-based policies</i> are optimal, in which the source is sampled only if the time until a new energy unit arrives exceeds a certain threshold. In the setting with feedback, threshold-greedy policies are investigated, in which the source is sampled according to a threshold-based policy following successful transmissions, and instantaneously whenever energy is available following failed transmissions. The optimal thresholds are found in closed-form in terms of the erasure probability. Such threshold-based policies are then extended for the case of multiple sources, combined with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">round robin</i> scheduling in the setting without feedback, in which sources are sampled in the same repeating order; and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">maximum-age-first</i> scheduling in the setting with feedback, in which sources with maximum AoI are given priority. In both settings, the achieved cumulative long-term average AoI is derived in closed-form in terms of the threshold, the erasure probability and the number of sources.

Private and Fresh Real-Time Status Updating

The freshness and privateness of information in a real-time status updating is mainly investigated in this letter. First, an information freshness and privateness tradeoff is mathematically derived. Then we propose a novel private and communication-efficient framework termed crowded status updating (CSU) which enhances the freshness of information while protecting information privacy. The proposed framework outperforms the unicasting based status updating method by serving multiple clients by multicasting, which results in gaining both higher communication-efficiency and privacy.

Age of Information Minimization for an Energy Harvesting Source With Updating Erasures: Without and With Feedback

Consider an energy harvesting (EH) sensor that continuously monitors a system and sends time-stamped status update to a destination. The sensor harvests energy from nature and uses it to power its updating operations. The destination keeps track of the system status through the successfully received updates. With the recently introduced information freshness metric “Age of Information” (AoI), our objective is to design optimal online status updating policy to minimize the long-term average AoI at the destination, subject to the energy causality constraint at the sensor. Due to the noisy channel between the sensor and the destination, each transmitted update may be erased with a fixed probability, and the AoI at the destination will be reset to zero only when an update is successfully received. We first consider status updating without feedback available to the sensor and show that the Best-effort Uniform updating (BU) policy is optimal in a broadly defined class of online policies. We then investigate status updating with perfect feedback to the sensor and prove similar optimality of the Best-effort Uniform updating with Retransmission (BUR) policy. In order to prove the optimality of the proposed policies, for each case, we first identify a lower bound on the long-term average AoI among a broad class of online policies, and then construct a sequence of virtual policies to approach the lower bound asymptotically. Since those virtual policies are sub-optimal to the original policy, the original policy is thus optimal.

Channel Quality-Based Optimal Status Update for Information Freshness in Internet of Things

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.

Urgency of Information for Context-Aware Timely Status Updates in Remote Control Systems

As 5G and Internet-of-Things (IoT) are deeply integrated into vertical industries such as autonomous driving and industrial robotics, timely status update is crucial for remote monitoring and control. In this regard, Age of Information (AoI) has been proposed to measure the freshness of status updates. However, it is just a metric changing linearly with time and irrelevant of context-awareness. We propose a context-based metric, named as Urgency of Information (UoI), to measure the nonlinear time-varying importance and the non-uniform context-dependence of the status information. This paper first establishes a theoretical framework for UoI characterization and then provides UoI-optimal status updating and user scheduling schemes in both single-terminal and multi-terminal cases. Specifically, an update-index-based scheme is proposed for a single-terminal system, where the terminal always updates and transmits when its update index is larger than a threshold. For the multi-terminal case, the UoI of the proposed scheduling scheme is proven to be upper-bounded and its decentralized implementation by Carrier Sensing Multiple Access with Collision Avoidance (CSMA/CA) is also provided. In the simulations, the proposed updating and scheduling schemes notably outperform the existing ones such as round robin and AoI-optimal schemes in terms of UoI, error-bound violation and control system stability.

Autobiographical Memory, Personality, and Facebook Mementos.

The present study analyzed the relationships between directive, self and social functions of autobiographical memory, personality traits, as defined by the Five Factor model, and the Facebook mementos. We defined Facebook mementos as objective measures of the textual (i.e., Facebook Status Updating) and visual (i.e., Photos uploading) information people record on their Facebook profiles. Questionnaires gathered data from a sample of 193 Italian Facebook users (148 female; 45 male; age M = 22.8, SD = 6.8). Results at path analysis using AMOS showed direct significant positive associations between personality traits related to extraversion, openness, neuroticism, conscientiousness and Facebook mementos. Extraversion and openness were positive precursors of the directive, self and social functions of autobiographical memory, whereas neuroticism predicted directive and self-functions, and conscientiousness was a positive precursor of the directive function of autobiographical memory. As well, indirect significant positive paths among extraversion, neuroticism, openness and the frequency of photos uploaded on Facebook for collecting life events have emerged via the mediation of the self-continuity function of autobiographical memory. In sum, the present study highlights how individual differences in motivations for using autobiographical memory for directive-behavior, self-continuity or social-bonding purposes deeply related with the personal experience of using social media as a repository tool for textual or visual information.

Optimal status updating with a finite-battery energy harvesting source

We consider an energy harvesting source equipped with a finite battery, which needs to send timely status updates to a remote destination. The timeliness of status updates is measured by a non-decreasing penalty function of the age of information (AoI). The problem is to find a policy for generating updates that achieves the lowest possible time-average expected age penalty among all online policies. We prove that one optimal solution of this problem is a monotone threshold policy, which satisfies (i) each new update is sent out only when the age is higher than a threshold and (ii) the threshold is a non-increasing function of the instantaneous battery level. Let τB denote the optimal threshold corresponding to the full battery level B, and p(·) denote the age-penalty function, then we can show that p(τB) is equal to the optimum objective value, i.e., the minimum achievable time-average expected age penalty. These structural properties are used to develop an algorithm to compute the optimal thresholds. Our numerical analysis indicates that the improvement in average age with added battery capacity is largest at small battery sizes; specifically, more than half the total possible reduction in age is attained when battery storage increases from one transmission's worth of energy to two. This encourages further study of status update policies for sensors with small battery storage.

The Age of Information: Real-Time Status Updating by Multiple Sources

We examine multiple independent sources providing status updates to a monitor through simple queues. We formulate an age of information (AoI) timeliness metric and derive a general result for the AoI that is applicable to a wide variety of multiple source service systems. For first-come first-served and two types of last-come first-served systems with Poisson arrivals and exponential service times, we find the region of feasible average status ages for multiple updating sources. We then use these results to characterize how a service facility can be shared among multiple updating sources. A new simplified technique for evaluating the AoI in finite-state continuous-time queuing systems is also derived. Based on stochastic hybrid systems, this method makes AoI evaluation to be comparable in complexity to finding the stationary distribution of a finite-state Markov chain.

Status update: Gratifications derived from Facebook affordances by older adults

Guided by the Uses and Gratifications 2.0 approach, this study examines the role played by three classes of affordances (i.e. modality, agency, and interactivity) in explicating the gratifications derived by older adults on Facebook. Data from a content analysis of Facebook profiles and an online survey with older adults (aged 60 years and older) who have used Facebook for at least 1 year ( N = 202) show that while status updating and posting personal stories are associated with activity and community-building gratifications respectively, profile customization is key for obtaining agency-enhancement gratification, and participating in conversations on comment threads plays an important role in providing interaction gratification. These findings advance our understanding of social networking site (SNS) use among older adults and suggest interface designs that maximize gratifications for older adults.

Condition-based maintenance for complex systems based on current component status and Bayesian updating of component reliability

We propose a new condition-based maintenance policy for complex systems, based on the status (working, defective) of all components within a system, as well as the reliability block diagram of the system. By means of the survival signature, a generalization of the system signature allowing for multiple component types, we obtain a predictive distribution for the system survival time, also known as residual life distribution, based on which of the system’s components currently function or not, and the current age of the functioning components.The time to failure of the components of the system is modeled by a Weibull distribution with a fixed shape parameter. The scale parameter is iteratively updated in a Bayesian fashion using the current (censored and non-censored) component lifetimes. Each component type has a separate Weibull model that may also include test data.The cost-optimal moment of replacement for the system is obtained by minimizing the expected cost rate per unit of time. The unit cost rate is recalculated when components fail or at the end of every (very short) fixed inter-evaluation interval, leading to a dynamic maintenance policy, since the ageing of components and possible failures will change the cost-optimal moment of replacement in the course of time. Via numerical experiments, some insight into the performance of the policy is given.

A simulation model for evaluating facilities' adaptability in the fare collection area of subway stations

According to relative position between ticket office and automatic fare gates, the facility layout of a fare collection area can be classified into three types. The application of these facility layout types are analyzed in the 15 subway hubs and 85 general stations, Beijing. According to the analysis results of facility layout and passenger flow line, fare collection area can be classified into 9 functional subareas. The adjacency degree is defined as the location relationship between adjacent subareas. Secondly, the simulation model is developed with an individual passenger as the object, to update an individual passenger's status. And the moving behavior model of an individual passenger is developed based on the macro pedestrian flow model according to traffic characteristics of many passengers in the field data. In status updating, the average speed of the passengers in different simulation time varied with the density in the subarea. In the case study the facility configurations of the fare collection system in the rail transit hub, DongZhiMen are evaluated with the proposed model for the adaptability of the facility configuration in the fare collection systems. Results show that the provided simulation model is effective and valuable for facility layout optimization and adaptability analysis.

Narcissistic power poster? On the relationship between narcissism and status updating activity on Facebook

The pervasiveness of social networking sites and the popularity of status updates have prompted the question whether excessive online self-presentation is motivated by narcissism. The present studies assessed (1) whether this concern is shared by users of social networking sites, and (2) the actual relationship between narcissism and frequency of status updates using self- and informant reports of narcissism and an observational measure of status updating activity. Results confirmed that users of social networking sites believe that narcissism strongly predicts status updating activity. However, analyses of the actual relationship in a German and US sample yielded null-results. Using the equivalence testing approach allowed us to conclude that the effect of narcissism on status updating activity is not substantial.

Does Posting Facebook Status Updates Increase or Decrease Loneliness? An Online Social Networking Experiment

Online social networking is a pervasive but empirically understudied phenomenon. Strong public opinions on its consequences exist but are backed up by little empirical evidence and almost no causally conclusive, experimental research. The current study tested the psychological effects of posting status updates on Facebook using an experimental design. For 1 week, participants in the experimental condition were asked to post more than they usually do, whereas participants in the control condition received no instructions. Participants added a lab “Research Profile” as a Facebook friend allowing for the objective documentation of protocol compliance, participants’ status updates, and friends’ responses. Results revealed (1) that the experimentally induced increase in status updating activity reduced loneliness, (2) that the decrease in loneliness was due to participants feeling more connected to their friends on a daily basis, and (3) that the effect of posting on loneliness was independent of direct social feedback (i.e., responses) by friends.

From TV to Twitter: How Ambient News Became Ambient Journalism

Scholars have applied the term "ambient" to journalism to describe the omnipresent nature of news in society through the proliferation of one-way media into public spaces. This approach is based on a one-directional model of mass media where the audience is framed as the receptor of communication. However this paper suggests that we need to reassess the meaning of ambient as applied to news and journalism due to the participatory and interactive characteristics of the networked digital media. The Internet has changed the relationship between journalists and audiences from a one-way, asymmetric model of communication to a more participatory and collective system, where citizens have the ability to participate in the news production process. This paper argues that ambient news has evolved into ambient journalism – an awareness system that offers diverse means to collect, communicate, share and display news and information, from both professional and non-professional sources.