13,925 research outputs found
The ContikiMAC Radio Duty Cycling Protocol
Low-power wireless devices must keep their radio
transceivers off as much as possible to reach a low power
consumption, but must wake up often enough to be able to
receive communication from their neighbors. This report
describes the ContikiMAC radio duty cycling mechanism,
the default radio duty cycling mechanism in Contiki 2.5,
which uses a power efficient wake-up mechanism with
a set of timing constraints to allow device to keep their
transceivers off. With ContikiMAC, nodes can participate
in network communication yet keep their radios turned
off for roughly 99% of the time. This report describes the
ContikiMAC mechanism, measures the energy consumption
of individual ContikiMAC operations, and evaluates
the efficiency of the fast sleep and phase-lock optimizations
Bounds on Contention Management in Radio Networks
The local broadcast problem assumes that processes in a wireless network are
provided messages, one by one, that must be delivered to their neighbors. In
this paper, we prove tight bounds for this problem in two well-studied wireless
network models: the classical model, in which links are reliable and collisions
consistent, and the more recent dual graph model, which introduces unreliable
edges. Our results prove that the Decay strategy, commonly used for local
broadcast in the classical setting, is optimal. They also establish a
separation between the two models, proving that the dual graph setting is
strictly harder than the classical setting, with respect to this primitive
Faster Gossiping in Bidirectional Radio Networks with Large Labels
We consider unknown ad-hoc radio networks, when the underlying network is
bidirectional and nodes can have polynomially large labels. For this model, we
present a deterministic protocol for gossiping which takes rounds. This improves upon the previous best result for deterministic
gossiping for this model by [Gasienec, Potapov, Pagourtizis, Deterministic
Gossiping in Radio Networks with Large labels, ESA (2002)], who present a
protocol of round complexity for this problem. This
resolves open problem posed in [Gasienec, Efficient gossiping in radio
networks, SIROCCO (2009)], who cite bridging gap between lower and upper bounds
for this problem as an important objective. We emphasize that a salient feature
of our protocol is its simplicity, especially with respect to the previous best
known protocol for this problem
On Byzantine Broadcast in Loosely Connected Networks
We consider the problem of reliably broadcasting information in a multihop
asynchronous network that is subject to Byzantine failures. Most existing
approaches give conditions for perfect reliable broadcast (all correct nodes
deliver the authentic message and nothing else), but they require a highly
connected network. An approach giving only probabilistic guarantees (correct
nodes deliver the authentic message with high probability) was recently
proposed for loosely connected networks, such as grids and tori. Yet, the
proposed solution requires a specific initialization (that includes global
knowledge) of each node, which may be difficult or impossible to guarantee in
self-organizing networks - for instance, a wireless sensor network, especially
if they are prone to Byzantine failures. In this paper, we propose a new
protocol offering guarantees for loosely connected networks that does not
require such global knowledge dependent initialization. In more details, we
give a methodology to determine whether a set of nodes will always deliver the
authentic message, in any execution. Then, we give conditions for perfect
reliable broadcast in a torus network. Finally, we provide experimental
evaluation for our solution, and determine the number of randomly distributed
Byzantine failures than can be tolerated, for a given correct broadcast
probability.Comment: 1
Cooperative Convex Optimization in Networked Systems: Augmented Lagrangian Algorithms with Directed Gossip Communication
We study distributed optimization in networked systems, where nodes cooperate
to find the optimal quantity of common interest, x=x^\star. The objective
function of the corresponding optimization problem is the sum of private (known
only by a node,) convex, nodes' objectives and each node imposes a private
convex constraint on the allowed values of x. We solve this problem for generic
connected network topologies with asymmetric random link failures with a novel
distributed, decentralized algorithm. We refer to this algorithm as AL-G
(augmented Lagrangian gossiping,) and to its variants as AL-MG (augmented
Lagrangian multi neighbor gossiping) and AL-BG (augmented Lagrangian broadcast
gossiping.) The AL-G algorithm is based on the augmented Lagrangian dual
function. Dual variables are updated by the standard method of multipliers, at
a slow time scale. To update the primal variables, we propose a novel,
Gauss-Seidel type, randomized algorithm, at a fast time scale. AL-G uses
unidirectional gossip communication, only between immediate neighbors in the
network and is resilient to random link failures. For networks with reliable
communication (i.e., no failures,) the simplified, AL-BG (augmented Lagrangian
broadcast gossiping) algorithm reduces communication, computation and data
storage cost. We prove convergence for all proposed algorithms and demonstrate
by simulations the effectiveness on two applications: l_1-regularized logistic
regression for classification and cooperative spectrum sensing for cognitive
radio networks.Comment: 28 pages, journal; revise
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