55 research outputs found
Status Updates Over Unreliable Multiaccess Channels
Applications like environmental sensing, and health and activity sensing, are
supported by networks of devices (nodes) that send periodic packet
transmissions over the wireless channel to a sink node. We look at simple
abstractions that capture the following commonalities of such networks (a) the
nodes send periodically sensed information that is temporal and must be
delivered in a timely manner, (b) they share a multiple access channel and (c)
channels between the nodes and the sink are unreliable (packets may be received
in error) and differ in quality.
We consider scheduled access and slotted ALOHA-like random access. Under
scheduled access, nodes take turns and get feedback on whether a transmitted
packet was received successfully by the sink. During its turn, a node may
transmit more than once to counter channel uncertainty. For slotted ALOHA-like
access, each node attempts transmission in every slot with a certain
probability. For these access mechanisms we derive the age of information
(AoI), which is a timeliness metric, and arrive at conditions that optimize AoI
at the sink. We also analyze the case of symmetric updating, in which updates
from different nodes must have the same AoI. We show that ALOHA-like access,
while simple, leads to AoI that is worse by a factor of about 2e, in comparison
to scheduled access
Minimizing the Age of Information from Sensors with Common Observations
We study the average Age of Information (AoI) in a system where physical
sources produce independent discrete-time updates that are each observed by
several sensors. We devise a model that is simple, but still capable to capture
the main tradeoffs. Two sensor scheduling policies are proposed to minimize the
AoI of the sources; one in which the system parameters are assumed known, and
one in which they are learned. Both policies are able to exploit the common
sensor information to reduce the AoI, resulting in large reductions in AoI
compared to common schedules
Age-Optimal Updates of Multiple Information Flows
In this paper, we study an age of information minimization problem, where
multiple flows of update packets are sent over multiple servers to their
destinations. Two online scheduling policies are proposed. When the packet
generation and arrival times are synchronized across the flows, the proposed
policies are shown to be (near) optimal for minimizing any time-dependent,
symmetric, and non-decreasing penalty function of the ages of the flows over
time in a stochastic ordering sense
Information Freshness Analysis of Slotted ALOHA in Gilbert-Elliot Channels
This letter analyzes a class of information freshness metrics for large IoT
systems in which terminals employ slotted ALOHA to access a common channel.
Considering a Gilbert-Elliot channel model, information freshness is evaluated
through a penalty function that follows a power law of the time elapsed since
the last received update, generalizing the age of information metric. By means
of a signal flow graph analysis of Markov processes, we provide exact closed
form expressions for the average penalty and for the peak penalty violation
probability
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