497 research outputs found
An Optimal Medium Access Control with Partial Observations for Sensor Networks
We consider medium access control (MAC) in multihop sensor networks, where only partial information about the shared medium is available to the transmitter. We model our setting as a queuing problem in which the service rate of a queue is a function of a partially observed Markov chain representing the available bandwidth, and in which the arrivals are controlled based on the partial observations so as to keep the system in a desirable mildly unstable regime. The optimal controller for this problem satisfies a separation property: we first compute a probability measure on the state space of the chain, namely the information state, then use this measure as the new state on which the control decisions are based. We give a formal description of the system considered and of its dynamics, we formalize and solve an optimal control problem, and we show numerical simulations to illustrate with concrete examples properties of the optimal control law. We show how the ergodic behavior of our queuing model is characterized by an invariant measure over all possible information states, and we construct that measure. Our results can be specifically applied for designing efficient and stable algorithms for medium access control in multiple-accessed systems, in particular for sensor networks
Network Information Flow with Correlated Sources
In this paper, we consider a network communications problem in which multiple
correlated sources must be delivered to a single data collector node, over a
network of noisy independent point-to-point channels. We prove that perfect
reconstruction of all the sources at the sink is possible if and only if, for
all partitions of the network nodes into two subsets S and S^c such that the
sink is always in S^c, we have that H(U_S|U_{S^c}) < \sum_{i\in S,j\in S^c}
C_{ij}. Our main finding is that in this setup a general source/channel
separation theorem holds, and that Shannon information behaves as a classical
network flow, identical in nature to the flow of water in pipes. At first
glance, it might seem surprising that separation holds in a fairly general
network situation like the one we study. A closer look, however, reveals that
the reason for this is that our model allows only for independent
point-to-point channels between pairs of nodes, and not multiple-access and/or
broadcast channels, for which separation is well known not to hold. This
``information as flow'' view provides an algorithmic interpretation for our
results, among which perhaps the most important one is the optimality of
implementing codes using a layered protocol stack.Comment: Final version, to appear in the IEEE Transactions on Information
Theory -- contains (very) minor changes based on the last round of review
Broadcast Channels with Cooperating Decoders
We consider the problem of communicating over the general discrete memoryless
broadcast channel (BC) with partially cooperating receivers. In our setup,
receivers are able to exchange messages over noiseless conference links of
finite capacities, prior to decoding the messages sent from the transmitter. In
this paper we formulate the general problem of broadcast with cooperation. We
first find the capacity region for the case where the BC is physically
degraded. Then, we give achievability results for the general broadcast
channel, for both the two independent messages case and the single common
message case.Comment: Final version, to appear in the IEEE Transactions on Information
Theory -- contains (very) minor changes based on the last round of review
A Syntactic Model of Mutation and Aliasing
Traditionally, semantic models of imperative languages use an auxiliary
structure which mimics memory. In this way, ownership and other encapsulation
properties need to be reconstructed from the graph structure of such global
memory. We present an alternative "syntactic" model where memory is encoded as
part of the program rather than as a separate resource. This means that
execution can be modelled by just rewriting source code terms, as in semantic
models for functional programs. Formally, this is achieved by the block
construct, introducing local variable declarations, which play the role of
memory when their initializing expressions have been evaluated. In this way, we
obtain a language semantics which directly represents at the syntactic level
constraints on aliasing, allowing simpler reasoning about related properties.
To illustrate this advantage, we consider the issue, widely studied in the
literature, of characterizing an isolated portion of memory, which cannot be
reached through external references. In the syntactic model, closed block
values, called "capsules", provide a simple representation of isolated portions
of memory, and capsules can be safely moved to another location in the memory,
without introducing sharing, by means of "affine' variables. We prove that the
syntactic model can be encoded in the conventional one, hence efficiently
implemented.Comment: In Proceedings DCM 2018 and ITRS 2018 , arXiv:1904.0956
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