5,145 research outputs found
On Time Synchronization Issues in Time-Sensitive Networks with Regulators and Nonideal Clocks
Flow reshaping is used in time-sensitive networks (as in the context of IEEE
TSN and IETF Detnet) in order to reduce burstiness inside the network and to
support the computation of guaranteed latency bounds. This is performed using
per-flow regulators (such as the Token Bucket Filter) or interleaved regulators
(as with IEEE TSN Asynchronous Traffic Shaping). Both types of regulators are
beneficial as they cancel the increase of burstiness due to multiplexing inside
the network. It was demonstrated, by using network calculus, that they do not
increase the worst-case latency. However, the properties of regulators were
established assuming that time is perfect in all network nodes. In reality,
nodes use local, imperfect clocks. Time-sensitive networks exist in two
flavours: (1) in non-synchronized networks, local clocks run independently at
every node and their deviations are not controlled and (2) in synchronized
networks, the deviations of local clocks are kept within very small bounds
using for example a synchronization protocol (such as PTP) or a satellite based
geo-positioning system (such as GPS). We revisit the properties of regulators
in both cases. In non-synchronized networks, we show that ignoring the timing
inaccuracies can lead to network instability due to unbounded delay in per-flow
or interleaved regulators. We propose and analyze two methods (rate and burst
cascade, and asynchronous dual arrival-curve method) for avoiding this problem.
In synchronized networks, we show that there is no instability with per-flow
regulators but, surprisingly, interleaved regulators can lead to instability.
To establish these results, we develop a new framework that captures industrial
requirements on clocks in both non-synchronized and synchronized networks, and
we develop a toolbox that extends network calculus to account for clock
imperfections.Comment: ACM SIGMETRICS 2020 Boston, Massachusetts, USA June 8-12, 202
Energy-Efficient Communication over the Unsynchronized Gaussian Diamond Network
Communication networks are often designed and analyzed assuming tight
synchronization among nodes. However, in applications that require
communication in the energy-efficient regime of low signal-to-noise ratios,
establishing tight synchronization among nodes in the network can result in a
significant energy overhead. Motivated by a recent result showing that
near-optimal energy efficiency can be achieved over the AWGN channel without
requiring tight synchronization, we consider the question of whether the
potential gains of cooperative communication can be achieved in the absence of
synchronization. We focus on the symmetric Gaussian diamond network and
establish that cooperative-communication gains are indeed feasible even with
unsynchronized nodes. More precisely, we show that the capacity per unit energy
of the unsynchronized symmetric Gaussian diamond network is within a constant
factor of the capacity per unit energy of the corresponding synchronized
network. To this end, we propose a distributed relaying scheme that does not
require tight synchronization but nevertheless achieves most of the energy
gains of coherent combining.Comment: 20 pages, 4 figures, submitted to IEEE Transactions on Information
Theory, presented at IEEE ISIT 201
Fundamentals of Large Sensor Networks: Connectivity, Capacity, Clocks and Computation
Sensor networks potentially feature large numbers of nodes that can sense
their environment over time, communicate with each other over a wireless
network, and process information. They differ from data networks in that the
network as a whole may be designed for a specific application. We study the
theoretical foundations of such large scale sensor networks, addressing four
fundamental issues- connectivity, capacity, clocks and function computation.
To begin with, a sensor network must be connected so that information can
indeed be exchanged between nodes. The connectivity graph of an ad-hoc network
is modeled as a random graph and the critical range for asymptotic connectivity
is determined, as well as the critical number of neighbors that a node needs to
connect to. Next, given connectivity, we address the issue of how much data can
be transported over the sensor network. We present fundamental bounds on
capacity under several models, as well as architectural implications for how
wireless communication should be organized.
Temporal information is important both for the applications of sensor
networks as well as their operation.We present fundamental bounds on the
synchronizability of clocks in networks, and also present and analyze
algorithms for clock synchronization. Finally we turn to the issue of gathering
relevant information, that sensor networks are designed to do. One needs to
study optimal strategies for in-network aggregation of data, in order to
reliably compute a composite function of sensor measurements, as well as the
complexity of doing so. We address the issue of how such computation can be
performed efficiently in a sensor network and the algorithms for doing so, for
some classes of functions.Comment: 10 pages, 3 figures, Submitted to the Proceedings of the IEE
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