658 research outputs found
Timely Lossless Source Coding for Randomly Arriving Symbols
We consider a real-time streaming source coding system in which an encoder
observes a sequence of randomly arriving symbols from an i.i.d. source, and
feeds binary codewords to a FIFO buffer that outputs one bit per time unit to a
decoder. Each source symbol represents a status update by the source, and the
timeliness of the system is quantified by the age of information (AoI), defined
as the time difference between the present time and the generation time of the
most up-to-date symbol at the output of the decoder. When the FIFO buffer is
allowed to be empty, we propose an optimal prefix-free lossless coding scheme
that minimizes the average peak age based on the analysis of discrete-time
Geo/G/1 queue. For more practical scenarios in which a special codeword is
reserved for indicating an empty buffer, we propose an encoding scheme that
assigns a codeword to the empty buffer state based on an estimate of the buffer
idle time.Comment: IEEE Information Theory Workshop (ITW) 201
Timeliness in Lossless Block Coding
We examine lossless data compression from an average delay perspective. An
encoder receives input symbols one per unit time from an i.i.d. source and
submits binary codewords to a FIFO buffer that transmits bits at a fixed rate
to a receiver/decoder. Each input symbol at the encoder is viewed as a status
update by the source and the system performance is characterized by the status
update age, defined as the number of time units (symbols) the decoder output
lags behind the encoder input. An upper bound on the average status age is
derived from the exponential bound on the probability of error in streaming
source coding with delay. Apart from the influence of the error exponent that
describes the convergence of the error, this upper bound also scales with the
constant multiplier term in the error probability. However, the error exponent
does not lead to an accurate description of the status age for small delay and
small blocklength. An age optimal block coding scheme is proposed based on an
approximation of the average age by converting the streaming source coding
system into a D/G/1 queue. We compare this scheme to the error exponent optimal
coding scheme which uses the method of types. We show that maximizing the error
exponent is not equivalent to minimizing the average status age.Comment: Data Compression Conference (DCC), 201
Optimal Source Codes for Timely Updates
A transmitter observing a sequence of independent and identically distributed
random variables seeks to keep a receiver updated about its latest
observations. The receiver need not be apprised about each symbol seen by the
transmitter, but needs to output a symbol at each time instant . If at time
the receiver outputs the symbol seen by the transmitter at time , the age of information at the receiver at time is . We study
the design of lossless source codes that enable transmission with minimum
average age at the receiver. We show that the asymptotic minimum average age
can be attained up to a constant gap by the Shannon codes for a tilted version
of the original pmf generating the symbols, which can be computed easily by
solving an optimization problem. Furthermore, we exhibit an example with
alphabet \X where Shannon codes for the original pmf incur an asymptotic
average age of a factor O(\sqrt{\log |\X|}) more than that achieved by our
codes. Underlying our prescription for optimal codes is a new variational
formula for integer moments of random variables, which may be of independent
interest. Also, we discuss possible extensions of our formulation to randomized
schemes and to the erasure channel, and include a treatment of the related
problem of source coding for minimum average queuing delay.Comment: Added a missing reference, in IEEE Transactions on Information
Theory, 202
Using Erasure Feedback for Online Timely Updating with an Energy Harvesting Sensor
A real-time status updating system is considered, in which an energy
harvesting sensor is acquiring measurements regarding some physical phenomenon
and sending them to a destination through an erasure channel. The setting is
online, in which energy arrives in units according to a Poisson process with
unit rate, with arrival times being revealed causally over time. Energy is
saved in a unit-sized battery. The sensor is notified by the destination of
whether updates were erased via feedback. Updates need to reach the destination
successfully in a timely fashion, namely, such that the long term average age
of information, defined as the time elapsed since the latest successful update
has reached the destination, is minimized. First, it is shown that the optimal
status update policy has a renewal structure: successful update times should
constitute a renewal process. Then, threshold-greedy policies are investigated:
a new update is transmitted, following a successful one, only if the age of
information grows above a certain threshold; and if it is erased, then all
subsequent update attempts are greedily scheduled whenever energy is available.
The optimal threshold-greedy policy is then analytically derived.Comment: To appear in the 2019 IEEE International Symposium on Information
Theor
Partial Updates: Losing Information for Freshness
We consider an information updating system where a source produces updates as
requested by a transmitter. The transmitter further processes these updates in
order to generate , which have smaller information compared
to the original updates, to be sent to a receiver. We study the problem of
generating partial updates, and finding their corresponding real-valued
codeword lengths, in order to minimize the average age experienced by the
receiver, while maintaining a desired level of mutual information between the
original and partial updates. This problem is NP hard. We relax the problem and
develop an alternating minimization based iterative algorithm that generates a
pmf for the partial updates, and the corresponding age-optimal real-valued
codeword length for each update. We observe that there is a tradeoff between
the attained average age and the mutual information between the original and
partial updates
Benefits of Coding on Age of Information in Broadcast Networks
Age of Information (AoI) is studied in two-user broadcast networks with
feedback, and lower and upper bounds are derived on the expected weighted sum
AoI of the users. In particular, a class of simple coding actions is considered
and within this class, randomized and deterministic policies are devised.
Explicit conditions are found for symmetric dependent channels under which
coded randomized policies strictly outperform the corresponding uncoded
policies. Similar behavior is numerically shown for deterministic policies
Who Should Google Scholar Update More Often?
We consider a resource-constrained updater, such as Google Scholar, which
wishes to update the citation records of a group of researchers, who have
different mean citation rates (and optionally, different importance
coefficients), in such a way to keep the overall citation index as up to date
as possible. The updater is resource-constrained and cannot update citations of
all researchers all the time. In particular, it is subject to a total update
rate constraint that it needs to distribute among individual researchers. We
use a metric similar to the age of information: the long-term average
difference between the actual citation numbers and the citation numbers
according to the latest updates. We show that, in order to minimize this
difference metric, the updater should allocate its total update capacity to
researchers proportional to the of their mean citation rates.
That is, more prolific researchers should be updated more often, but there are
diminishing returns due to the concavity of the square root function. More
generally, our paper addresses the problem of optimal operation of a
resource-constrained sampler that wishes to track multiple independent counting
processes in a way that is as up to date as possible
Selective Encoding Policies for Maximizing Information Freshness
An information source generates independent and identically distributed
status update messages from an observed random phenomenon which takes
distinct values based on a given pmf. These update packets are encoded at the
transmitter node to be sent to a receiver node which wants to track the
observed random variable with as little age as possible. The transmitter node
implements a selective encoding policy such that rather than encoding all
possible realizations, the transmitter node encodes the most probable
realizations. We consider three different policies regarding the remaining
less probable realizations: which
disregards whenever a realization from the remaining values occurs;
which encodes and sends the remaining
realizations with a certain probability to further inform the receiver node at
the expense of longer codewords for the selected realizations; and
which sends a
designated empty symbol when one of the remaining realizations occurs.
For all of these three encoding schemes, we find the average age and determine
the age-optimal real codeword lengths, including the codeword length for the
empty symbol in the case of the latter scheme, such that the average age at the
receiver node is minimized. Through numerical evaluations for arbitrary pmfs,
we show that these selective encoding policies result in a lower average age
than encoding every realization, and find the corresponding age-optimal
values.Comment: Submitted for publication, April 2020. Some text overlap with its
conference version arXiv:2001.0997
Information Freshness in Cache Updating Systems
We consider a cache updating system with a source, a cache and a user. There
are files. The source keeps the freshest version of the files which are
updated with known rates . The cache downloads and keeps the
freshest version of the files from the source with rates . The user gets
updates from the cache with rates . When the user gets an update, it
either gets a fresh update from the cache or the file at the cache becomes
outdated by a file update at the source in which case the user gets an outdated
update. We find an analytical expression for the average freshness of the files
at the user. Next, we generalize our setting to the case where there are
multiple caches in between the source and the user, and find the average
freshness at the user. We provide an alternating maximization based method to
find the update rates for the cache(s), , and for the user, , to
maximize the freshness of the files at the user. We observe that for a given
set of update rates for the user (resp. for the cache), the optimal rate
allocation policy for the cache (resp. for the user) is a ,
where the optimal update rates for rapidly changing files at the source may be
equal to zero. Finally, we consider a system where multiple users are connected
to a single cache and find update rates for the cache and the users to maximize
the total freshness over all users.Comment: Submitted for publicatio
Information Freshness for Timely Detection of Status Changes
In this paper, we aim to establish the connection between Age of Information
(AoI) in network theory, information uncertainty in information theory, and
detection delay in time series analysis. We consider a dynamic system whose
state changes at discrete time points, and a state change won't be detected
until an update generated after the change point is delivered to the
destination for the first time. We introduce an information theoretic metric to
measure the information freshness at the destination, and name it as
generalized Age of Information (GAoI). We show that under any state-independent
online updating policy, if the underlying state of the system evolves according
to a stationary Markov chain, the GAoI is proportional to the AoI. Besides, the
accumulative GAoI and AoI are proportional to the expected accumulative
detection delay of all changes points over a period of time. Thus, any
(G)AoI-optimal state-independent updating policy equivalently minimizes the
corresponding expected change point detection delay, which validates the
fundamental role of (G)AoI in real-time status monitoring. Besides, we also
investigate a Bayesian change point detection scenario where the underlying
state evolution is not stationary. Although AoI is no longer related to
detection delay explicitly, we show that the accumulative GAoI is still an
affine function of the expected detection delay, which indicates the
versatility of GAoI in capturing information freshness in dynamic systems.Comment: 6 pages, 7 figure
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