2,682 research outputs found
Tight Bounds on Information Dissemination in Sparse Mobile Networks
Motivated by the growing interest in mobile systems, we study the dynamics of
information dissemination between agents moving independently on a plane.
Formally, we consider mobile agents performing independent random walks on
an -node grid. At time , each agent is located at a random node of the
grid and one agent has a rumor. The spread of the rumor is governed by a
dynamic communication graph process , where two agents are
connected by an edge in iff their distance at time is within their
transmission radius . Modeling the physical reality that the speed of radio
transmission is much faster than the motion of the agents, we assume that the
rumor can travel throughout a connected component of before the graph is
altered by the motion. We study the broadcast time of the system, which
is the time it takes for all agents to know the rumor. We focus on the sparse
case (below the percolation point ) where, with high
probability, no connected component in has more than a logarithmic number
of agents and the broadcast time is dominated by the time it takes for many
independent random walks to meet each other. Quite surprisingly, we show that
for a system below the percolation point the broadcast time does not depend on
the relation between the mobility speed and the transmission radius. In fact,
we prove that for any , even
when the transmission range is significantly larger than the mobility range in
one step, giving a tight characterization up to logarithmic factors. Our result
complements a recent result of Peres et al. (SODA 2011) who showed that above
the percolation point the broadcast time is polylogarithmic in .Comment: 19 pages; we rewrote Lemma 4, fixing a claim which was not fully
justified in the first version of the draf
Improved Bounds on Information Dissemination by Manhattan Random Waypoint Model
With the popularity of portable wireless devices it is important to model and
predict how information or contagions spread by natural human mobility -- for
understanding the spreading of deadly infectious diseases and for improving
delay tolerant communication schemes. Formally, we model this problem by
considering moving agents, where each agent initially carries a
\emph{distinct} bit of information. When two agents are at the same location or
in close proximity to one another, they share all their information with each
other. We would like to know the time it takes until all bits of information
reach all agents, called the \textit{flood time}, and how it depends on the way
agents move, the size and shape of the network and the number of agents moving
in the network.
We provide rigorous analysis for the \MRWP model (which takes paths with
minimum number of turns), a convenient model used previously to analyze mobile
agents, and find that with high probability the flood time is bounded by
, where agents move on an
grid. In addition to extensive simulations, we use a data set of
taxi trajectories to show that our method can successfully predict flood times
in both experimental settings and the real world.Comment: 10 pages, ACM SIGSPATIAL 2018, Seattle, U
Mobile Conductance in Sparse Networks and Mobility-Connectivity Tradeoff
In this paper, our recently proposed mobile-conductance based analytical
framework is extended to the sparse settings, thus offering a unified tool for
analyzing information spreading in mobile networks. A penalty factor is
identified for information spreading in sparse networks as compared to the
connected scenario, which is then intuitively interpreted and verified by
simulations. With the analytical results obtained, the mobility-connectivity
tradeoff is quantitatively analyzed to determine how much mobility may be
exploited to make up for network connectivity deficiency.Comment: Accepted to ISIT 201
Amorphous Placement and Retrieval of Sensory Data in Sparse Mobile Ad-Hoc Networks
Abstract—Personal communication devices are increasingly being equipped with sensors that are able to passively collect information from their surroundings – information that could be stored in fairly small local caches. We envision a system in which users of such devices use their collective sensing, storage, and communication resources to query the state of (possibly remote) neighborhoods. The goal of such a system is to achieve the highest query success ratio using the least communication overhead (power). We show that the use of Data Centric Storage (DCS), or directed placement, is a viable approach for achieving this goal, but only when the underlying network is well connected. Alternatively, we propose, amorphous placement, in which sensory samples are cached locally and informed exchanges of cached samples is used to diffuse the sensory data throughout the whole network. In handling queries, the local cache is searched first for potential answers. If unsuccessful, the query is forwarded to one or more direct neighbors for answers. This technique leverages node mobility and caching capabilities to avoid the multi-hop communication overhead of directed placement. Using a simplified mobility model, we provide analytical lower and upper bounds on the ability of amorphous placement to achieve uniform field coverage in one and two dimensions. We show that combining informed shuffling of cached samples upon an encounter between two nodes, with the querying of direct neighbors could lead to significant performance improvements. For instance, under realistic mobility models, our simulation experiments show that amorphous placement achieves 10% to 40% better query answering ratio at a 25% to 35% savings in consumed power over directed placement.National Science Foundation (CNS Cybertrust 0524477, CNS NeTS 0520166, CNS ITR 0205294, EIA RI 0202067
Information Spreading in Stationary Markovian Evolving Graphs
Markovian evolving graphs are dynamic-graph models where the links among a
fixed set of nodes change during time according to an arbitrary Markovian rule.
They are extremely general and they can well describe important dynamic-network
scenarios.
We study the speed of information spreading in the "stationary phase" by
analyzing the completion time of the "flooding mechanism". We prove a general
theorem that establishes an upper bound on flooding time in any stationary
Markovian evolving graph in terms of its node-expansion properties.
We apply our theorem in two natural and relevant cases of such dynamic
graphs. "Geometric Markovian evolving graphs" where the Markovian behaviour is
yielded by "n" mobile radio stations, with fixed transmission radius, that
perform independent random walks over a square region of the plane.
"Edge-Markovian evolving graphs" where the probability of existence of any edge
at time "t" depends on the existence (or not) of the same edge at time "t-1".
In both cases, the obtained upper bounds hold "with high probability" and
they are nearly tight. In fact, they turn out to be tight for a large range of
the values of the input parameters. As for geometric Markovian evolving graphs,
our result represents the first analytical upper bound for flooding time on a
class of concrete mobile networks.Comment: 16 page
On the Role of Mobility for Multi-message Gossip
We consider information dissemination in a large -user wireless network in
which users wish to share a unique message with all other users. Each of
the users only has knowledge of its own contents and state information;
this corresponds to a one-sided push-only scenario. The goal is to disseminate
all messages efficiently, hopefully achieving an order-optimal spreading rate
over unicast wireless random networks. First, we show that a random-push
strategy -- where a user sends its own or a received packet at random -- is
order-wise suboptimal in a random geometric graph: specifically,
times slower than optimal spreading. It is known that this
gap can be closed if each user has "full" mobility, since this effectively
creates a complete graph. We instead consider velocity-constrained mobility
where at each time slot the user moves locally using a discrete random walk
with velocity that is much lower than full mobility. We propose a simple
two-stage dissemination strategy that alternates between individual message
flooding ("self promotion") and random gossiping. We prove that this scheme
achieves a close to optimal spreading rate (within only a logarithmic gap) as
long as the velocity is at least . The key
insight is that the mixing property introduced by the partial mobility helps
users to spread in space within a relatively short period compared to the
optimal spreading time, which macroscopically mimics message dissemination over
a complete graph.Comment: accepted to IEEE Transactions on Information Theory, 201
On Space-Time Capacity Limits in Mobile and Delay Tolerant Networks
We investigate the fundamental capacity limits of space-time journeys of
information in mobile and Delay Tolerant Networks (DTNs), where information is
either transmitted or carried by mobile nodes, using store-carry-forward
routing. We define the capacity of a journey (i.e., a path in space and time,
from a source to a destination) as the maximum amount of data that can be
transferred from the source to the destination in the given journey. Combining
a stochastic model (conveying all possible journeys) and an analysis of the
durations of the nodes' encounters, we study the properties of journeys that
maximize the space-time information propagation capacity, in bit-meters per
second. More specifically, we provide theoretical lower and upper bounds on the
information propagation speed, as a function of the journey capacity. In the
particular case of random way-point-like models (i.e., when nodes move for a
distance of the order of the network domain size before changing direction), we
show that, for relatively large journey capacities, the information propagation
speed is of the same order as the mobile node speed. This implies that,
surprisingly, in sparse but large-scale mobile DTNs, the space-time information
propagation capacity in bit-meters per second remains proportional to the
mobile node speed and to the size of the transported data bundles, when the
bundles are relatively large. We also verify that all our analytical bounds are
accurate in several simulation scenarios.Comment: Part of this work will be presented in "On Space-Time Capacity Limits
in Mobile and Delay Tolerant Networks", P. Jacquet, B. Mans and G. Rodolakis,
IEEE Infocom, 201
- …