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Efficient Distributed MAC for Dynamic Demands: Congestion and Age Based Designs
Abstract
Future generation wireless technologies are expected to serve an increasingly dense and dynamic population of users that generate short bundles of information to be transferred over the shared spectrum. This calls for new distributed and low-overhead Multiple-Access-Control (MAC) strategies to serve such dynamic demands with spectral efficiency characteristics. In this work, we address this need by identifying and developing two fundamentally different MAC paradigms: (i) congestion-based paradigm that estimates the congestion level in the system and adapts to it; and (ii) age-based paradigm that prioritizes demands based on their ages. Despite their apparent differences, we develop policies under each paradigm in a generic multi-channel access scenario that are provably throughput-optimal when they employ any asymptotically-efficient channel encoding/decoding mechanism. We also characterize the stability regions of the two designs, and investigate the conditions under which one design outperforms the other. We perform extensive simulations to validate the theoretical claims and investigate the non-asymptotic performances of our designs.
... To measure the freshness of data, the concept of Age of Information (AoI) has been introduced over the last decade (see, for example, [2]- [4]), which is defined concisely as the elapsed time since the generation time of the last received status update. Since the introduction of the AoI metric, numerous related studies emerged in various networking scenarios, including wireless random access networks (e.g., [5], [6]), content distribution networks (e.g., [7], [8]), scheduling (e.g., [9]- [13]), queuing networks (e.g., [14], [15]), and vehicular networks (e.g., [16]). ...
... where y is a column vector of size DL with y = (y 1 1 , · · · , y L 1 , · · · , y 1 D , · · · , y L D ) T as its components; D is an upper bound on the age state in the system which can be set sufficiently large so that the probability of reaching D is vanishing. 6 Qy = 0 is the matrix representation of the following (global balance) equations: ...
... Since there are finitely many states, there exists a stationary distribution π(a) for every a. Let C be the set of all recurrent 6 In practice, moderate level of D is enough so that the dimension of LP won't be large. Also, when there is only age violation related objective and constraints, it's enough to set D = d + 1. See III-C and IV-C for references. ...
We study the optimal scheduling problem where n source nodes attempt to transmit updates over L shared wireless on/off fading channels to optimize their age performance under energy and age-violation tolerance constraints. Specifically, we provide a generic formulation of age-optimization in the form of a constrained Markov Decision Processes (CMDP), and obtain the optimal scheduler as the solution of an associated Linear Programming problem. We investigate the characteristics of the optimal single-user multi-channel scheduler for the important special cases of average-age and violation-rate minimization. This leads to several key insights on the nature of the optimal allocation of the limited energy, where a usual threshold-based policy does not apply and will be useful in guiding scheduler designers. We then investigate the stability region of the optimal scheduler for the multi-user case. We also develop an online scheduler using Lyapunov-drift-minimization methods that do not require the knowledge of channel statistics. Our numerical studies compare the stability region of our online scheduler to the optimal scheduler to reveal that it performs closely with unknown channel statistics.
The Mobile Edge Computing (MEC) paradigm gives impetus to the vigorous advancement of the Internet of Things (IoT), through provisioning low-latency computing services at network edges. The emerging digital twin technique has been explosively growing in the IoT community, which bridges the gap between physical objects and their digital representations in an MEC network, enabling real-time monitoring and analysis, simulations on the dynamics of systems, accurate predictions on behaviours of objects, and optimization on network resource allocation. In this paper, we consider AoI-aware query services in an MEC network empowered by digital twin technology for diverse IoT applications. We aim to maximize the weighted sum of the accumulative freshness of query results measured by the Age of Information (AoI) and the total query service delay of admitted requests. To this end, we first formulate a novel minimization problem that explores nontrivial trade-offs between the two conflicting optimization objectives: the freshness of query results and service delays, and we show the NP-hardness of the problem. Then, we propose an approximation algorithm with a provable approximation ratio for the problem, at the expense of bounded computing capacity violations. We also develop a heuristic for the problem without any capacity violations. We finally evaluate the performance of the proposed algorithms via simulations. The simulation results demonstrate that the proposed algorithms are promising, and outperform the comparison benchmarks.
In this paper, a dynamic access probability adjustment strategy for coded random access schemes based on successive interference cancellation (SIC) is proposed. The developed protocol consists of judiciously tuning the access probability, therefore controlling the number of transmitting users, in order to resolve medium access control (MAC) layer congestion states in high load conditions. The protocol is comprised of two steps: Estimation of the number of transmitting users during the current MAC frame and adjustment of the access probability to the subsequent MAC frame, based on the performed estimation. The estimation algorithm exploits a posteriori information, i.e., available information at the end of the SIC process, in particular it relies on both the frame configuration (residual number of collision slots) and the recovered users configuration (vector of recovered users) to effectively reduce mean-square error (MSE). During the access probability adjustment phase, a target load threshold is employed, tailored to the packet loss rate in the finite frame length case. Simulation results revealed that the developed estimator was able to achieve remarkable performance owing to the information gathered from the SIC procedure. It also illustrated how the proposed dynamic access probability strategy can resolve congestion states efficiently.
In a typical Internet of Things (IoT) application where a central controller collects status updates from multiple terminals, e.g., sensors and monitors, through a wireless multiaccess uplink, an important problem is how to attain timely status updates autonomously. In this paper, the timeliness of the status is measured by the recently proposed age-of-information (AoI) metric; both the theoretical and practical aspects of the problem are investigated: we aim to obtain a scheduling policy with minimum AoI and, meanwhile, still suitable for decentralized implementation on account of signalling exchange overhead. Towards this end, we first consider the set of arrival-independent and renewal (AIR) policies; the optimal policy thereof to minimize the time-average AoI is proved to be a round-robin policy with one-packet (latest packet only and others are dropped) buffers (RR-ONE). The optimality is established based on a generalized Poisson-arrival-see-time-average (PASTA) theorem. It is further proved that RR-ONE is asymptotically optimal among all policies in the massive IoT regime. The AoI steady-state stationary distribution under RR-ONE is also derived. A fully decentralized implementation of RR-ONE is proposed which can accommodate dynamic terminal appearances. In addition, considering scenarios where packets cannot be dropped, the optimal AIR policy thereof is also found with parameters given by the solution to a convex problem.
We consider a wireless broadcast network with a base station sending time-sensitive information to a number of clients through unreliable channels. The Age of Information (AoI), namely the amount of time that elapsed since the most recently delivered packet was generated, captures the freshness of the information. We formulate a discrete-time decision problem to find a transmission scheduling policy that minimizes the expected weighted sum AoI of the clients in the network. We first show that in symmetric networks a Greedy policy, which transmits the packet with highest current age, is optimal. For general networks, we develop three low-complexity scheduling policies: a randomized policy, a Max-Weight policy and a Whittle's Index policy, and derive performance guarantees as a function of the network configuration. To the best of our knowledge, this is the first work to derive performance guarantees for scheduling policies that attempt to minimize AoI in wireless networks with unreliable channels. Numerical results show that both Max-Weight and Whittle's Index policies outperform the other scheduling policies in every configuration simulated, and achieve near optimal performance.
Random access represents possibly the simplest and yet one of the best known approaches for sharing a channel among several users. Since their introduction in the 1970s, random access schemes have been thoroughly studied and small variations of the pioneering Aloha protocol have since then become a key component of many communications standards, ranging from satellite networks to ad hoc and cellular scenarios. A fundamental step forward for this old paradigm has been witnessed in the past few years, with the development of new solutions, mainly based on the principles of successive interference cancellation, which made it possible to embrace constructively collisions among packets rather enduring them as a waste of resources. These new lines of research have rendered the performance of modern random access protocols competitive to that of their coordinated counterparts, paving the road for a multitude of new applications.
This monograph explores the main ideas and design principles that are behind some of such novel schemes, and aims at offering to the reader an introduction to the analytical tools that can be used to model their performance. After reviewing some relevant results for the random access channel, the volume focuses on slotted solutions that combine the approach of diversity Aloha with successive interference cancellation, and discusses their optimisation based on an analogy with the theory of codes on graphs. The potential of modern random access is then further explored considering two families of schemes: the former based on physical layer network coding to resolve collisions among users, and the latter leaning on the concept of receiver diversity. Finally, the opportunities and the challenges encountered by random access solutions recently devised to operate in asynchronous, i.e., unslotted, scenarios are reviewed and discussed
We analyze asynchronous carrier sense multiple access (CSMA) policies for scheduling packet transmissions in multihop wireless networks subject to collisions under primary interference constraints. While the (asymptotic) achievable rate region of CSMA policies for single-hop networks has been well-known, their analysis for general multihop networks has been an open problem due to the complexity of complex interactions among coupled interference constraints. Our work resolves this problem for networks with primary interference constraints by introducing a novel fixed-point formulation that approximates the link service rates of CSMA policies. This formulation allows us to derive an explicit characterization of the achievable rate region of CSMA policies for a limiting regime of large networks with a small sensing period. Our analysis also reveals the rate at which CSMA achievable rate region approaches the asymptotic capacity region of such networks. Moreover, our approach enables the computation of approximate CSMA link transmission attempt probabilities to support any given arrival vector within the achievable rate region. As part of our analysis, we show that both of these approximations become (asymptotically) accurate for large networks with a small sensing period. Our numerical case studies further suggest that these approximations are accurate even for moderately sized networks.
Emerging applications rely on wireless broadcast to disseminate time-critical information. For example, vehicular networks may exchange vehicle position and velocity information to enable safety applications. The number of nodes in one-hop communication range in such networks can be very large, leading to congestion and undesirable levels of packet collisions. Earlier work has examined such broadcasting protocols primarily from a MAC perspective and focused on selective aspects such as packet error rate. In this work, we propose a more comprehensive metric, the average system information age, which captures the requirement of such applications to maintain current state information from all other nearby nodes. We show that information age is minimized at an optimal operating point that lies between the extremes of maximum throughput and minimum delay. Further, while age can be minimized by saturating the MAC and setting the CW size to its throughput-optimal value, the same cannot be achieved without changes in existing hardware. Also, via simulations we show that simple contention window size adaptations like increasing or decreasing the window size are unsuitable for reducing age. This motivates our design of an application-layer broadcast rate adaptation algorithm. It uses local decisions at nodes in the network to adapt their messaging rate to keep the system age to a minimum. Our simulations and experiments with 300 ORBIT nodes show that the algorithm effectively adapts the messaging rates and minimizes the system age.
We present a comprehensive steady-state analysis of
threshold-ALOHA
, a distributed age-aware modification of slotted ALOHA proposed in recent literature. In threshold-ALOHA, each terminal suspends its transmissions until the Age of Information (AoI) of the status update flow it is sending reaches a certain threshold
. Once the age exceeds
, the terminal attempts transmission with constant probability
in each slot, as in standard slotted ALOHA. We analyze the time-average expected AoI attained by this policy, and explore its scaling with network size,
n
. We derive the probability distribution of the number of active users at steady state, and show that as network size increases the policy converges to one that runs slotted ALOHA with fewer sources: on average about one fifth of the users is active at any time. We obtain an expression for steady-state expected AoI and use this to optimize the parameters
and
, resolving the conjectures in previous literature by confirming that the optimal age threshold and transmission probability are
2.2n
and
4.69/n
, respectively. We find that the optimal AoI scales with the network size as
1.4169n
, which is almost half the minimum AoI achievable with slotted ALOHA, while the loss from the maximum throughput of
remains below 1%. We compare the performance of this rudimentary algorithm to that of the SAT policy
[2]
that dynamically adapts its transmission probabilities.
Age of information (AoI) is gaining attention as a valuable performance metric for many IoT systems, in which a large number of devices report time-stamped updates to a central gateway. This is the case, for instance, of remote sensing, monitoring, or tracking, with broad applications in the industrial, vehicular, and environmental domain. In these settings, AoI provides insights that are complementary to those offered by throughput or latency, capturing the ability of the system to maintain an up-to-date view of the status of each transmitting device. From this standpoint, while a good understanding of the metric has been reached for point-to-point links, relatively little attention has been devoted to the impact that link layer solutions employed in IoT systems may have on AoI. In particular, no result is available for
modern random access
protocols, which have recently emerged as promising solutions to support massive machine-type communications. To start addressing this gap we provide in this paper the first study of the AoI of a scheme in this family, namely irregular repetition slotted ALOHA (IRSA). By means of a Markovian analysis, we track the AoI evolution at the gateway, prove that the process is ergodic, and derive a compact closed form expression for its stationary distribution. Leaning on this, we compute exact formulations for the average AoI and the age violation probability. The study reveals non-trivial design trade-offs for IRSA and highlights the key role played by the protocol operating frame size. Moreover, a comparison with the performance of a simpler slotted ALOHA strategy highlights a remarkable potential for modern random access schemes in terms of information freshness.
We consider the problem of scheduling in wireless networks with the aim of maintaining up-to-date and synchronized (also called,
aligned
) information at the receiver across multiple flows. This is in contrast to the more conventional approach of scheduling for optimizing long-term performance metrics such as throughput, fairness, or average delay. Maintaining the age of information at a low and roughly equal level is particularly important for distributed cyber-physical systems, in which the effectiveness of the control decisions depends critically on the freshness and synchrony of information from multiple sources/sensors. In this paper, we first expose the weakness of several popular MaxWeight scheduling solutions that utilize queue-length, delay, and age information as their weights. Then, we develop a novel age-based scheduler that combines age with the interarrival times of incoming packets in its decisions, which yields significant gains in the information freshness at the receiver. We characterize the performance of our strategy through a heavy-traffic analysis that establishes upper and lower bounds on the freshness of system information.
In this paper, an extended version of the CRDSA protocol proposed in and is presented. The enhanced CRDSA protocol, dubbed CRDSA++, extends the original CRDSA concept to more than two replicas (e.g. 4 or 5) and exploits power fluctuations in the received signal to further boost the performance of the CRDSA protocol. The paper provides a wide range of performance and sensitivity analysis with respect to the number of replicas and power unbalance. It is shown that a packet loss ratio (PLR) below 10-4 can be achieved with a normalized throughput in excess of 1 packet per slot. This represents a remarkable performance for an open loop random access (RA) scheme without any kind of access control over a medium shared by a large population of terminals. Finally, the paper also provides a preliminary discussion on the implementation aspects of the CRDSA++ RA scheme, as well as on the integration aspects with a DAMA protocol to support a wider range of service scenarios with improved MAC layer performance. (10 pages)
We consider a multi-user wireless network in which each user has one packet of information to transmit to a central receiver. We study an uncoordinated paradigm where the users send their packet a random number of times according to a probability distribution. Instead of discarding the collided packets, the receiver performs iterative collision resolution. Recently, a few studies have shown that the iterative collision resolution process can be viewed as message-passing decoding on an appropriately defined Tanner graph. Using this equivalence, they used standard techniques to numerically optimize the probability distribution and demonstrated substantial throughput improvement over slotted ALOHA. In this paper, we show that the well-known soliton distribution is an optimal probability distribution and that the resulting throughput efficiency can be arbitrarily close to 1.
We propose a contention-based random-access protocol, designed for wireless networks where the number of users is not a priori known. The protocol operates in rounds divided into equal-duration slots, performing at the same time estimation of the number of users and resolution of their transmissions. The users independently access the wireless link on a slot basis with a predefined probability, resulting in a distribution of user transmissions over slots, based on which the estimation and contention resolution are performed. Specifically, the contention resolution is performed using successive interference cancellation which, coupled with the use of the optimized access probabilities, enables throughputs that are substantially higher than the traditional slotted ALOHA-like protocols. The key feature of the proposed protocol is that the round durations are not a priori set and they are terminated when the estimation/contention-resolution performance reach the satisfactory levels.
This paper describes some examples of the stochastic models found useful in the design and analysis of advanced computer and communication systems. Our major theme might be termed the control of contention. As illustrations of this theme we discuss concurrency control procedures for databases, dynamic channel assignment for cellular radio, and random access schemes for the control of a broadcast channel. We emphasize asymptotic properties of product‐form distributions and we present some new results on the stability of acknowledgement based random access schemes.
Contention resolution diversity slotted ALOHA (CRDSA) is a simple but effective improvement of slotted ALOHA. CRDSA relies on MAC bursts repetition and on interference cancellation (IC), achieving a peak throughput T ≅ 0.55, whereas for slotted ALOHA T ≅ 0.37. In this paper we show that the IC process of CRDSA can be conveniently described by a bipartite graph, establishing a bridge between the IC process and the iterative erasure decoding of graph-based codes. Exploiting this analogy, we show how a high throughput can be achieved by selecting variable burst repetition rates according to given probability distributions, leading to irregular graphs. A framework for the probability distribution optimization is provided. Based on that, we propose a novel scheme, named irregular repetition slotted ALOHA, that can achieve a throughput T ≅ 0.97 for large frames and near to T ≅ 0.8 in practical implementations, resulting in a gain of ~ 45% w.r.t. CRDSA. An analysis of the normalized efficiency is introduced, allowing performance comparisons under the constraint of equal average transmission power. Simulation results, including an IC mechanism described in the paper, substantiate the validity of the analysis and confirm the high efficiency of the proposed approach down to a signal-to-noise ratio as a low as Eb/N0=2 dB.
Multiple access based on orthogonal frequency division multiplexing (OFDM), or OFDMA, enables multiple users to simultaneously access the media by using different subcarriers. This leads to the convenient realization of multi-channel ALOHA, in which each user transmits with a group of subcarriers. In this paper, we first introduce the multi-channel slotted ALOHA algorithm to OFDM, which is called OFDMA-based multi-channel ALOHA (OMC-ALOHA). Since ALOHA is an unstable algorithm, we show OMC-ALOHA is also unstable. To solve this stability problem, we extend the pseudo-Bayesian algorithm to achieve stabilized OMC-ALOHA.
In this paper a new multiple access scheme dubbed contention resolution diversity slotted ALOHA (CRDSA) is introduced and its performance and implementation are thoroughly analyzed. The scheme combines diversity transmission of data bursts with efficient interference cancellation techniques. It is shown that CRDSA largely outperforms the classical lotted ALOHA (SA) technique in terms of throughput under equal packet loss ratio conditions (e.g. 17-fold improvement at packet loss ratio = 2 middot 10-2). CRDSA allows to boost the performance of random access (RA) channels in the return link of interactive satellite networks, making RA very efficient and providing low latency for the transmission of small size sparse packets. Implementation-wise it is shown that the CRDSA technique can be easily integrated in systems equipped with digital burst demodulators.
A dynamic medium access control (MAC) protocol is proposed for a finite-user slotted channel with multipacket reception (MPR). This protocol divides the time axis into transmission periods (TPs) where the ith TP is dedicated to the transmission of the packets generated in the (i-1)th TP. At the beginning of each TP, the state (active or idle) of each user is estimated based on the length of the previous TP and the incoming traffic load. By exploiting the information on the state of users and the channel MPR capability, the number of users who can simultaneously access the channel in the current TP is chosen so that the expected length of this TP is minimized. As a result, the MPR capability is more efficiently utilized by the proposed protocol as compared to, for example, the slotted ALOHA with optimal retransmission probability. Furthermore, the proposed protocol requires little online computation. Its simplicity is comparable to that of slotted ALOHA. It can be applied to random access networks with spread spectrum and/or antenna array.
There has been considerable interest in the idea of cross-layer
design of wireless networks. This is motivated by the need to provide a
greater level of adaptivity to variations of wireless channels. This
article examines one aspect of the interaction between the physical and
medium access control layers. In particular, we consider the impact of
signal processing techniques that enable multipacket reception on the
throughput and design of random access protocols
A transmission control strategy is described for slotted-ALOHA-type broadcast channels with ternary feedback. At each time slot, each station estimates the probability that n stations are ready to transmit a packet for each n , using Bayes' rule and the observed history of collisions, successful transmissions, and holes (empty slots). A station transmits a packet in a probabilistic manner based on these estimates. This strategy is called Bayesian broadcast. An elegant and very practical strategy--pseudo-Bayesian broadcast--is then derived by approximating the probability estimates with a Poisson distribution with mean nu and further simplifying. Each station keeps a copy of nu , transmits a packet with probability 1/nu , and then updates nu in two steps: For collisions, increment nu by (e-2)^{-l}=1.39221 cdots . For successes and holes, decrement nu by 1 . Set nu to max (nu + hat{lambda}, 1) , where hat{lambda} is an estimate of the arrival rate lambda of new packets into the system. Simulation results are presented showing that pseudo-Bayesian broadcast performs well in practice, and methods that can be used to prove that certain versions of pseudo-Bayesian broadcast are stable for lambda < e^{-1} are discussed.
The information theoretic approach and the collision resolution approach to multiaccess channels are reviewed in terms of the underlying communication problems that both are modeling. Some perspective on the strengths and weakness of these approaches is given, and the need of a more combined approach focused on coding and decoding techniques is argued.
We consider a multiaccess channel under the infinite source model and ternary feedback. We consider a recently proposed scheme for the decentralized control of transmissions through the channel, and we prove that it is stable, as long as the rate of generation of new packets is smaller than e-1.
Retransmission policies are presented for the decentralized control of a multiaccess packet-switched broadcast channel. The policies have a simple recursive form yielding a Markov description of the system. Finite average delay is achieved for an infinite-population Poisson arrival model for any rate lambda < e^{-1} . It is proposed that the goal of retransmission policies should be to maintain the traffic intensity at a nearly constant, optimum level. The policies we introduce achieve this goal by nearly decoupling the dynamics of the traffic intensity from the backlog fluctuations. Analysis and simulations show that the policies perform well, even when the channel feedback information is unreliable or incomplete.
FCC adopts rules to facilitate next generation wireless technologies
- Meisch