As many emerging applications like industrial internet, autonomous driving, and telemedicine works well only over strictly high performance networks, the deterministic networking technology has become a critical supporting infrastructure. In this article, we review the evolution roadway and supporting theories of deterministic networking technology. We characterize the core demands of 6G wireless deterministic networks on four dimensions: the performance dimension, the spatial dimension, the functional dimension, and the management dimension. Despite immense challenges, it is believed that 6G deterministic networks have a prospect future by exploring several key enabling technologies including advanced air interface technologies, innovative network architecture, the comprehensive integration of communication, sensing, computing, and control, as well as intelligent scheduling.

In this article, we consider an Industrial Internet of Things (IIoT) network operating under a carrier sense multiple access with collision avoidance (CSMA/CA) protocol. Latency-sensitive packets generated at multiple stations randomly are transmitted to a destination for decision making. To meet the strict timeliness constraint, the transmissions are carried by finite blocklength (FBL) codes, while the truncated hybrid automatic repeat request (HARQ) scheme is exploited to improve the reliability. For such unsaturated CSMA/CA networks, for the first time, we characterize the timeliness of packets utilized for decision-making via the age upon decisions (AuD) metric which emphasizes the information freshness at decision moments in comparison to age of information (AoI). To explicitly quantify the AuD performance, we develop an equivalent and tractable unsaturated Markov transfer model for the considered network and investigate the transmission probability and collision probability, respectively. Subsequently, the probability density functions of interarrival time and service time of the successfully transmitted packets are derived. We further derive a closed-form expression for the average AuD under a geometric decision process accordingly. Based on these characterizations, we aim at improving average AuD by jointly allocating the blocklength and transmit power. The formulated nonconvex problem is decomposed into subproblems, and we prove its joint convexity across all feasible intervals. Via simulations, we evaluate the performance of the considered network and conclude a series of design guidelines.

Semantic communication aims at conveying semantic features rather than transmitting lossless data. The development of semantic communication is greatly hindered due to the lack of a general mathematical model for semantics, i.e., the absence of a measure of task-oriented source information. To address this problem, we propose a task-oriented concept for source information validity and source compression algorithms. Specifically, we consider semantic communication models in single- and multi-source systems and use the semantic context as well as correlation among sources to reduce redundant transmissions of information. We also study the relationship of code rates between Shannon, distributed, and semantic source coding, detailing the properties of the task and source under equal rates. Simulation results using public datasets demonstrate the validity and feasibility of the proposed semantic source coding algorithm across multiple communication tasks.

The trade-off between security, reliability, and distortion in a direct communication link with an eavesdropper is investigated by adjusting both the transmission power and the transmission rate, which affects the distortion size of the distortion-limited coding. This involves encoding data at a predetermined rate with Channel Side Information (CSI) to ensure successful data recovery within a defined distortion threshold. Using higher transmit power and coding rates effectively minimizes average distortion but increases intercept probability, whereas opting for lower transmit power and coding rates reduces interception probability while amplifying signal distortion. Thus, we investigate the distortion-intercept probability trade-off across feasible transmit powers and transmission intervals. For a Rayleigh fading channel, we derived a closed-form expression for the IP and calculated the maximum power when transmitting with a fixed power such that the intercept probability is below a threshold. We also present a water-filling-based power allocation to minimize the average distortion under some intercept probability requirements. With the proposed method, both numerical and Monte Carlo simulation demonstrate that employing a power control strategy reduces the average distortion and intercept probability to 78% and 50%, respectively, showcasing the effectiveness of the approach.

In this paper, we consider a machine-type communication (MTC) system where the sensor nodes aim to spread their observed updates over the whole network through slotted Aloha based broadcasting and flooding. We investigate the timeliness of the broadcasting process and the rapidity of the flooding process from the perspective of transmitters, which are referred to as the broadcast age of information (bAoI) and the spreading velocity, respectively. Specifically, bAoI quantifies the age of the latest successfully broadcasted packet of each node, and the spreading velocity characterizes the message moving rapidity when the nodes spread their packets over the network. To this end, we develop an analytical transmission model to derive the transmission probability, the collision probability, and the service rate of the nodes. We also propose an analytical traffic model for the network by using the Poisson approximation method. With these two models, we obtain the average bAoI and the spreading velocity over the network in closed-form. Our results show that 1) the total traffic rate p (including the forwarding and original traffic) of an averaged number of n(2r) nodes within the interfering range is upper bounded by n(2r)p

In this paper, we analyze the timeliness of a multi-user system in terms of the age of information (AoI) and the corresponding stability region in which the packet rates of users lead to finite queue lengths. Specifically, we consider a hybrid OFDMA-NOMA system where the users are partitioned into several groups. While users in each group share the same resource block using non-orthogonal multiple access (NOMA), different groups access the fading channel using orthogonal frequency division multiple access (OFDMA). For this system, we consider three decoding schemes at the service terminals: interfering decoding, which treats signals from other users as interference; serial interference cancellation, which removes signals from other users once they have been decoded; and the enhanced SIC strategy, where the receiver attempts to decode for another user if decoding for a previous user fails. We present the average AoI for each of the three decoding schemes in closed form. Under the constraint of the stable region, we find the minimum AoI of each decoding scheme efficiently. The numerical results show that by optionally choosing the decoding scheme and transmission rate, the hybrid OFDMA-NOMA outperforms conventional OFDMA in terms of both system timeliness and stability.

The promptness of decision-making is of paramount importance in coordinate decision-making communication systems. In this paper, we envision a system in which a sender transmits information to a receiver for decision-making. The decision-making process encompasses the extraction of decision-related information followed by subsequent computation. To assess the impact of communication delays, randomness of decision-making and computational time on the immediacy of decisions, we introduce a novel performance metric, namely the age of decision (AoD). Specifically, AoD is defined as the time elapsed since the generation of the update upon which the most recent decision is based. Considering the stochastic nature of decision-making, we analyze the average peak AoD in systems where the arrival and service processes follow general processes or Poisson processes. To facilitate our derivations, we introduce the concept of effective decisions to denote those decisions that can lead to the system’s peak AoD. Simulation results confirm the validity of our derivations and illustrate that appropriately increasing the rate of decision-making can significantly reduce the system’s average peak AoD.

In this paper, we estimate the average age of information (AoI) of the status updating over a wireless channel with an unknown fading model. Different from most related works which take the distributions of the inter-arrival time and transmission time of updates as known information, we approximate the average AoI of the system by using their first and second-order moments. Note that these distributions are often not accessible or known with inevitable errors while their moments are much easier to obtain, e.g., by using counting and statistics. We model the communications over the fading channel with a continuous transmission model and a discrete transmission model, which use the variable-rate scheme and the fixed-rate scheme, respectively. We assume that the arrival of the continuous transmission model is a Bernoulli process and make no assumptions about the arrival process of the discrete transmission model. Based on these information, we present two pairs of tight lower and upper bounds for the AoI of the two models. We show that obtained bounds are the tightest when the inter-arrival time (or transmission time) follows the degenerate distribution and are the loosest when it follows the two-point distribution, which randomly takes value from two possible outcomes. We also show that tighter bounds can be obtained by using higher order moments.

The Internet of Things (IoT) has the capability to support the synchronous transmission of dynamically sensed environmental status information to base stations. To improve transmission timeliness, previous studies have commonly utilized Age of Information (AoI) as a metric for network performance. However, AoI falls short in capturing status synchronicity, as synchronization requires knowledge of updates from both the transmitter and the receiver, which AoI cannot reflect due to its inability to track changes at the transmitter. In this work, we adopt the Age of Synchronization (AoS) as a metric to quantify the time elapsed since the freshest information at the receiver becomes desynchronized. Specifically, we develop a model for an IoT communication network to derive closed-form expressions for the average peak AoS (PAoS) and average AoS, considering discrete geometric and uniformly distributed packet arrivals. Ad-ditionally, the analysis has been carried out for both first-come-first-served (FCFS) and last-come-first-served with preemptive resume (LCFS-PR) service disciplines. Within these results, we prove that network's synchronization performance worsens with longer packet arrival intervals but improves with higher arrival rates. LCFS-PR strategy makes synchronization independent of packet arrival, solely influenced by service rate. Additionally, AoS consistently remains lower than AoI in the same system, with both tending to converge as packet arrival rate rises.

We consider the on-time transmissions of a sequence of packets over a fading channel. Different from traditional in-time communications, we investigate how many packets can be received $\delta$ -on-time, meaning that the packet is received around an expected slot with a deviation no larger than $\delta$ slots. In this framework, we first derive the on-time reception rate of the random transmission scheme when no packet-controlling is used. Our analytical and simulation results show that the on-time reception rate of random transmissions decreases (to zero) with the sequence length. To improve the on-time reception rate, we further propose to schedule the packets by delaying, dropping, or repeating the transmissions. Specifically, we model the packet scheduling problem as a Markov decision process (MDP) and then obtain the optimal scheduling policy using an efficient iterative algorithm. By using the optimal packet scheduling, the on-time reception rate converges to a much larger constant, thus ensuring better on-timeliness. Moreover, we show that the on-time reception rate increases if the target reception interval and/or the deviation tolerance $\delta$ is increased, or the randomness of the fading channel is reduced. By optimally scheduling the packets and choosing these parameters, therefore, wireless channels will be more suitable for the latency-sensitive applications.

In this paper, we consider information transmission over a three-node physical layer security system. Based on the imperfect estimations of the main channel and the eavesdropping channel, we propose reducing the outage probability and interception probability by hindering transmissions in cases where the main channel is too strong or too weak, which is referred to as an SNR-gated transmission control scheme. Specifically, Alice gives up its chance to transmit a packet if the estimated power gain of the main channel is smaller than a certain threshold so that possible outages can be avoided; Alice also becomes silent if the estimated power gain is larger than another threshold so that possible interceptions at Eve can be avoided. We also consider the timeliness of the network in terms of the violation probability of the peak age of information (PAoI). We present the outage probability, interception probability, and PAoI violation probability explicitly; we also investigate the trade-off among these probabilities, considering their weight sum. Our numerical and Monte Carlo results show that by using the SNR-gated transmission control, both the outage probability and the interception probability are reduced.

The data freshness at decision epochs of time-sensitive applications, e.g., auto-driving vehicles and autonomous underwater robots, is jointly affected by the statistics of update process and decision process. This work considers an update-and-decision system with a Poisson-arrival bufferless queue, where updates are delivered and processed for making decisions with exponential or periodic intervals. We use age-upon-decisions (AuD) to characterize timeliness of updates at decision moments, and the missing probability to specify whether updates are useful for decision-making. Our theoretical analyses 1) present the average AuDs and the missing probabilities for bufferless systems with exponential or deterministic decision intervals under different service time distributions; 2) show that for service scheduling, the deterministic service time achieves a lower average AuD and a smaller missing probability than the uniformly distributed and the negative exponentially distributed service time; 3) prove that the average AuD of periodical decision system is larger than and will eventually drop to that of Poisson decision system along with the increase of decision rate; however, the missing probability in periodical decision system is smaller than that of Poisson decision system. The numerical results and simulations verify the correctness of our analyses, and demonstrate that the bufferless systems outperform the systems applying infinite buffer size.

In this paper, we consider a wireless sensor network in which N sensor nodes deliver the observed information of interest to a remote receiver by competing for a sharing channel through the Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) protocol or the slotted ALOHA protocol.For this network, we evaluate the information freshness of the two random multiple access protocols using the age of information (AoI) metric.In order to explicitly express the average AoI of the CSMA/CA based network, we establish an equivalent and tractable transmission model for the network, in which the transmission probabilities and the collision probabilities are assumed to be identical over time and among sensor nodes.For the slotted ALOHA based network, we derive the average AoI by focusing on a randomly chosen reference node.Our theoretical results show that 1) the transmission probability and collision probability of the two networks increase with both the arrival rate and the number of sensor nodes; 2) with the same transmission probability, the average AoI of the CSMA/CA based network is always smaller than that of the slotted ALOHA based network, no matter how the arrival rate and the number of nodes change.Our Monte Carlo simulation results also validate the correctness of our theoretical calculations.

With the rapid development of Internet-of-Things (IoT) technology and machine-type communications, various emerging applications appear in industrial productions and our daily lives. Among these, applications like industrial sensing and controlling, remote surgery, and automatic driving require an extremely low latency and a very small jitter. Delivering information deterministically has become one of the biggest challenges for modern wire-line and wireless communications. In this paper, we present a review of currently available wire-line deterministic networks and discuss the main challenges to build wireless deterministic networks. We also discuss and propose several potential techniques enabling wireless networks to provide deterministic communications. By elaborating the coding/modulation schemes of the physical layer and managing the channel-access/packet-scheduling at the media access control (MAC) layer, it is believed that wireless deterministic communications can be realized in the near future.

In Internet of Things (IoT), the decision timeliness of time-sensitive applications is jointly affected by the statistics of update process and decision process. This work considers an update-and-decision system with a Poisson-arrival bufferless queue, where updates are delivered and processed for making decisions with exponential or periodic intervals. We use age-upon-decisions (AuD) to characterize timeliness of updates at decision moments, and the missing probability to specify whether updates are useful for decision-making. Our theoretical analyses 1) present the average AuDs and the missing probabilities for bufferless systems with exponential or deterministic decision intervals under different service time distributions; 2) show that for service scheduling, the deterministic service time achieves a lower average AuD and a smaller missing probability than the uniformly distributed and the negative exponentially distributed service time; 3) prove that the average AuD of periodical decision system is larger than and will eventually drop to that of Poisson decision system along with the increase of decision rate; however, the missing probability in periodical decision system is smaller than that of S. Chen, T. Z. Chen, and Y. Jia are with the of Microelectronics and Communication Engineering, Chongqing Poisson decision system. The numerical results and simulations verify the correctness of our analyses, and demonstrate that the bufferless systems outperform the systems applying infinite buffer length.

In this article, we consider the timeliness of information transmissions in a three-node industrial wireless sensor network (IWSN) in terms of Age of Information (AoI). In this network, a sensor monitors the ambient environment and transmits the sensed information to a remote monitor directly or through a relay node. In particular, we are interested in how the timeliness of the system is changed by decomposing the long-distance transmission with a relay and by enabling parallel transmissions over the two hops with a packet buffer. To this end, we derive the average AoIs of the transmissions over the direct-link, the relay-links with and without a buffer in a closed form. The obtained results show that the relay-link with a buffer outperforms the other two links, while the relay-link without a buffer outperforms the direct-link only if the relay is properly placed and the sensor–monitor distance is relatively large. On the condition that the average transmission times over the direct-link and the relay-link without a buffer are equal, we further evaluate how fast the average AoI can be reduced by using a relay or a packet buffer, as the packet rate approaches the maximum feasible rate over the links. It is shown that, although the sensor–monitor distance dominates the average AoIs of the links, the gains of using the relay and the buffer do not change much with the distance and are approximately constant.

In traditional recommendation algorithms, the users and/or the items with the same rating scores are equally treated. In real world, however, a user may prefer some items to other items and some users are more loyal to a certain item than other users. In this paper, therefore, we propose a weighted similarity measure by exploiting the difference in user-item relationships. In particular, we refer to the most important item of a user as his core item and the most important user of an item as its core user. We also propose a Core-User-Item Solver (CUIS) to calculate the core users and core items of the system, as well as the weighting coefficients for each user and each item. We prove that the CUIS algorithm converges to the optimal solution efficiently. Based on the weighted similarity measure and the obtained results by CUIS, we also propose three effective recommenders. Through experiments based on real-world data sets, we show that the proposed recommenders outperform corresponding traditional-similarity based recommenders, verify that the proposed weighted similarity can improve the accuracy of the similarity, and then improve the recommendation performance.

Age of information (AoI) has been proposed as a more suitable metric for characterizing the freshness of information than traditional metrics like delay and throughput. However, the calculation of AoI requires complex analysis and strict end-to-end synchronization. Most existential AoI-related works have assumed that the statistical characterizations of the arrival process and the service process are known. In fact, due to the randomness of the sources and the channel noises, these processes are often unavailable in reality. To this end, we propose a method to estimate the average AoI on a point-to-point wireless Rayleigh channel, which uses the available finite order statistical moments of the arrival process. Based on this method, we explicitly present the upper and lower bounds on the average AoI of the system. Our results show that 1) with the increase of the traffic intensity, the absolute error of the estimated average AoI bounds is first increasing and then decreasing, while the average AoI is monotonically increasing; 2) the average AoI can be effectively approximated by using the first two order moment estimation bounds, especially when traffic intensity is small or approaches unity; 3) tighter bounds can be obtained by using more moments.

We consider a wireless network where $N$ nodes compete for a shared channel over the CSMA/CA protocol to deliver observed updates to a common remote monitor. For this network, we rate the information freshness of the CSMA/CA based network using the age of information (AoI). Different from previous work, the network we consider is unsaturated. To theoretically analyze the transmission behavior of the CSMA/CA based network, we, therefore, develop an equivalent and tractable Markov transmission model. Based on this newly developed model, the transmission probability, collision probability and average AoI of the network are obtained. Our numerical results show that as the packet rate and the number of nodes increase, both the transmission probability and collision probability are increasing; the average AoI first decreases and then increases as the packet rate increases and increases with the number of nodes.

In the military field, the current form of warfare is transforming from network-centric warfare to intelligent warfare rapidly. Intelligent command and control networks are becoming the key to solving future intelligent warfare gradually. The current command and control network of military still has shortcomings such as slow interconnection, difficulty in mixing and using, and poor resilience against confrontation. The reason is the lack of theoretical support. And it is difficult to guide the architectural design and protocol improvement of the command and control network. Aiming at these problems, this paper focuses on the theory of intelligent command and control network traffic, and analyzes its basic connotation and research status at home and abroad from three aspects of network traffic characteristics, performance boundaries and changing laws. This paper points out the bottlenecks in the development of the current intelligent network traffic theory, and put forward relevant suggestions.