8 research outputs found
A Unified Sampling and Scheduling Approach for Status Update in Multiaccess Wireless Networks
Information source sampling and update scheduling have been treated
separately in the context of real-time status update for age of information
optimization. In this paper, a unified sampling and scheduling
() approach is proposed, focusing on decentralized updates in
multiaccess wireless networks. To gain some insights, we first analyze an
example consisting of two-state Markov sources, showing that when both
optimized, the unified approach outperforms the separate approach significantly
in terms of status tracking error by capturing the key status variation. We
then generalize to source nodes with random-walk state transitions whose
scaling limit is Wiener processes, the closed-form Whittle's index with
arbitrary status tracking error functions is obtained and indexability
established. Furthermore, a mean-field approach is applied to solve for the
decentralized status update design explicitly. In addition to simulation
results which validate the optimality of the proposed scheme
and its advantage over the separate approach, a use case of dynamic channel
state information (CSI) update is investigated, with CSI generated by a
ray-tracing electromagnetic software.Comment: To appear in INFOCOM 2019, in preperation for an IEEE Journal
submissio
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.Comment: Submitted to IEEE for possible publication
Closed-Form Whittle's Index-Enabled Random Access for Timely Status Update
We consider a star-topology wireless network for status update where a
central node collects status data from a large number of distributed
machine-type terminals that share a wireless medium. The Age of Information
(AoI) minimization scheduling problem is formulated by the restless multi-armed
bandit. A widely-proven near-optimal solution, i.e., the Whittle's index, is
derived in closed-form and the corresponding indexability is established. The
index is then generalized to incorporate stochastic, periodic packet arrivals
and unreliable channels. Inspired by the index scheduling policies which
achieve near-optimal AoI but require heavy signaling overhead, a
contention-based random access scheme, namely Index-Prioritized Random Access
(IPRA), is further proposed. Based on IPRA, terminals that are not urgent to
update, indicated by their indices, are barred access to the wireless medium,
thus improving the access timeliness. A computer-based simulation shows that
IPRA's performance is close to the optimal AoI in this setting and outperforms
standard random access schemes. Also, for applications with hard AoI deadlines,
we provide reliable deadline guarantee analysis. Closed-form achievable AoI
stationary distributions under Bernoulli packet arrivals are derived such that
AoI deadline with high reliability can be ensured by calculating the maximum
number of supportable terminals and allocating system resources proportionally.Comment: 30 pages, 7 figures, submitted to IEEE Transactions on
Communications. arXiv admin note: substantial text overlap with
arXiv:1803.0818
Adaptive Power and Rate Control for Real-time Status Updating over Fading Channels
Age of Information (AoI) has attracted much attention recently due to its
capability of characterizing the freshness of information. To improve
information freshness over fading channels, efficient scheduling methods are
highly desired for wireless transmissions. However, due to the channel
instability and arrival randomness, optimizing AoI is very challenging. In this
paper, we are interested in the AoI-optimal transmissions with rate-adaptive
transmission schemes in a buffer-aware system. More specifically, we utilize a
probabilistic scheduling method to minimize the AoI while satisfying an average
power constraint. By characterizing the probabilistic scheduling policy with a
Constrained Markov Decision Process (CMDP), we formulate a Linear Programming
(LP) problem. Further, a low complexity algorithm is presented to obtain the
optimal scheduling policy, which is proved to belong to a set of
semi-threshold-based policies. Numerical results verify the reduction in
computational complexity and the optimality of semi-threshold-based policy,
which indicates that we can achieve well real-time service with a low
calculating complexity.Comment: Journal versio
Closed-Form Analysis of Non-Linear Age-of-Information in Status Updates with an Energy Harvesting Transmitter
Timely status updates are crucial to enabling applications in massive
Internet of Things (IoT). This paper measures the data-freshness performance of
a status update system with an energy harvesting transmitter, considering the
randomness in information generation, transmission and energy harvesting. The
performance is evaluated by a non-linear function of age of information (AoI)
that is defined as the time elapsed since the generation of the most up-to-date
status information at the receiver. The system is formulated as two queues with
status packet generation and energy arrivals both assumed to be Poisson
processes. With negligible service time, both First-Come-First-Served (FCFS)
and Last-Come-First-Served (LCFS) disciplines for arbitrary buffer and battery
capacities are considered, and a method for calculating the average penalty
with non-linear penalty functions is proposed. The average AoI, the average
penalty under exponential penalty function, and AoI's threshold violation
probability are obtained in closed form. When the service time is assumed to
follow exponential distribution, matrix geometric method is used to obtain the
average peak AoI. The results illustrate that under the FCFS discipline, the
status update frequency needs to be carefully chosen according to the service
rate and energy arrival rate in order to minimize the average penalty.Comment: Accepted by IEEE Transactions on Wireless Communication
Waiting before Serving: A Companion to Packet Management in Status Update Systems
In this paper, we explore the potential of server waiting before packet
transmission in improving the Age of Information (AoI) in status update
systems. We consider a non-preemptive queue with Poisson arrivals and
independent general service distribution and we incorporate waiting before
serving in two packet management schemes: M/GI/1/1 and M/GI/1/. In
M/GI/1/1 scheme, the server waits for a deterministic time immediately after a
packet enters the server. In M/GI/1/ scheme, depending on idle or busy
system state, the server waits for a deterministic time before starting service
of the packet. In both cases, if a potential newer arrival is captured existing
packet is discarded. Different from most existing works, we analyze AoI
evolution by indexing the incoming packets, which is enabled by an alternative
method of partitioning the area under the evolution of instantaneous AoI to
calculate its time average. We obtain expressions for average and average peak
AoI for both queueing disciplines with waiting. Our numerical results
demonstrate that waiting before service can bring significant improvement in
average age, particularly, for heavy-tailed service distributions. This
improvement comes at the expense of an increase in average peak AoI. We
highlight the trade-off between average and average peak AoI generated by
waiting before serving
Scheduling to Minimize Age of Synchronization in Wireless Broadcast Networks with Random Updates
In this work, a wireless broadcast network with a base station (BS) sending
random time-sensitive information updates to multiple users with interference
constraints is considered. The Age of Synchronization (AoS), namely the amount
of time elapsed since the information stored at the network user becomes
desynchronized, is adopted to measure data freshness from the perspective of
network users. Compared with the more widely used metric---the Age of
Information (AoI), AoS accounts for the freshness of the randomly changing
content. The AoS minimization scheduling problem is formulated into a discrete
time Markov decision process and the optimal solution is approximated through
structural finite state policy iteration. An index based heuristic scheduling
policy based on restless multi-arm bandit (RMAB) is provided to further reduce
computational complexity. Simulation results show that the proposed index
policy can achieve compatible performance with the MDP and close to the AoS
lower bound. Moreover, theoretic analysis and simulations reveal the
differences between AoS and AoI. AoI minimization scheduling policy cannot
guarantee a good AoS performance.Comment: accepted and to appear, IEEE Transactions on Wireless Communication
The Age of Information in Networks: Moments, Distributions, and Sampling
A source provides status updates to monitors through a network with state
defined by a continuous-time finite Markov chain. An age of information (AoI)
metric is used to characterize timeliness by the vector of ages tracked by the
monitors. Based on a stochastic hybrid systems (SHS) approach, first order
linear differential equations are derived for the temporal evolution of both
the moments and the moment generating function (MGF) of the age vector
components. It is shown that the existence of a non-negative fixed point for
the first moment is sufficient to guarantee convergence of all higher order
moments as well as a region of convergence for the stationary MGF vector of the
age. The stationary MGF vector is then found for the age on a line network of
preemptive memoryless servers. From this MGF, it is found that the age at a
node is identical in distribution to the sum of independent exponential service
times. This observation is then generalized to linear status sampling networks
in which each node receives samples of the update process at each preceding
node according to a renewal point process. For each node in the line, the age
is shown to be identical in distribution to a sum of independent renewal
process age random variables.Comment: This work was presented in part at the 2018 IEEE Infocom Age of
Information Workshop. This version will be (more or less) the same as what
will appear in the IEEE Transactions on Information Theory. This work was
supported by NSF award 171704