296 research outputs found
The age of information in gossip networks
We introduce models of gossip based communication networks in which each node
is simultaneously a sensor, a relay and a user of information. We model the
status of ages of information between nodes as a discrete time Markov chain. In
this setting a gossip transmission policy is a decision made at each node
regarding what type of information to relay at any given time (if any). When
transmission policies are based on random decisions, we are able to analyze the
age of information in certain illustrative structured examples either by means
of an explicit analysis, an algorithm or asymptotic approximations. Our key
contribution is presenting this class of models.Comment: 15 pages, 8 figure
Asymptotic behavior of Aldous' gossip process
Aldous [(2007) Preprint] defined a gossip process in which space is a
discrete torus, and the state of the process at time is the set
of individuals who know the information. Information spreads from a site to its
nearest neighbors at rate 1/4 each and at rate to a site chosen
at random from the torus. We will be interested in the case in which
, where the long range transmission significantly accelerates the
time at which everyone knows the information. We prove three results that
precisely describe the spread of information in a slightly simplified model on
the real torus. The time until everyone knows the information is asymptotically
. If is the fraction of the
population who know the information at time and is small
then, for large , the time until reaches is
, where is a
random variable determined by the early spread of the information. The value of
at time is almost a deterministic function
which satisfies an odd looking integro-differential equation. The last
result confirms a heuristic calculation of Aldous.Comment: Published in at http://dx.doi.org/10.1214/10-AAP750 the Annals of
Applied Probability (http://www.imstat.org/aap/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Epidemic Spreading with External Agents
We study epidemic spreading processes in large networks, when the spread is
assisted by a small number of external agents: infection sources with bounded
spreading power, but whose movement is unrestricted vis-\`a-vis the underlying
network topology. For networks which are `spatially constrained', we show that
the spread of infection can be significantly speeded up even by a few such
external agents infecting randomly. Moreover, for general networks, we derive
upper-bounds on the order of the spreading time achieved by certain simple
(random/greedy) external-spreading policies. Conversely, for certain common
classes of networks such as line graphs, grids and random geometric graphs, we
also derive lower bounds on the order of the spreading time over all
(potentially network-state aware and adversarial) external-spreading policies;
these adversarial lower bounds match (up to logarithmic factors) the spreading
time achieved by an external agent with a random spreading policy. This
demonstrates that random, state-oblivious infection-spreading by an external
agent is in fact order-wise optimal for spreading in such spatially constrained
networks
Gossip routing, percolation, and restart in wireless multi-hop networks
Route and service discovery in wireless multi-hop networks applies flooding or
gossip routing to disseminate and gather information. Since packets may get
lost, retransmissions of lost packets are required. In many protocols the
retransmission timeout is fixed in the protocol specification. In this
technical report we demonstrate that optimization of the timeout is required
in order to ensure proper functioning of flooding schemes. Based on an
experimental study, we apply percolation theory and derive analytical models
for computing the optimal restart timeout. To the best of our knowledge, this
is the first comprehensive study of gossip routing, percolation, and restart
in this context
A survey of flooding, gossip routing, and related schemes for wireless multi- hop networks
Flooding is an essential and critical service in computer networks that is
used by many routing protocols to send packets from a source to all nodes in
the network. As the packets are forwarded once by each receiving node, many
copies of the same packet traverse the network which leads to high redundancy
and unnecessary usage of the sparse capacity of the transmission medium.
Gossip routing is a well-known approach to improve the flooding in wireless
multi-hop networks. Each node has a forwarding probability p that is either
statically per-configured or determined by information that is available at
runtime, e.g, the node degree. When a packet is received, the node selects a
random number r. If the number r is below p, the packet is forwarded and
otherwise, in the most simple gossip routing protocol, dropped. With this
approach the redundancy can be reduced while at the same time the reachability
is preserved if the value of the parameter p (and others) is chosen with
consideration of the network topology. This technical report gives an overview
of the relevant publications in the research domain of gossip routing and
gives an insight in the improvements that can be achieved. We discuss the
simulation setups and results of gossip routing protocols as well as further
improved flooding schemes. The three most important metrics in this
application domain are elaborated: reachability, redundancy, and management
overhead. The published studies used simulation environments for their
research and thus the assumptions, models, and parameters of the simulations
are discussed and the feasibility of an application for real world wireless
networks are highlighted. Wireless mesh networks based on IEEE 802.11 are the
focus of this survey but publications about other network types and
technologies are also included. As percolation theory, epidemiological models,
and delay tolerant networks are often referred as foundation, inspiration, or
application of gossip routing in wireless networks, a brief introduction to
each research domain is included and the applicability of the particular
models for the gossip routing is discussed
Trust based attachment
In social systems subject to indirect reciprocity, a positive reputation is
key for increasing one's likelihood of future positive interactions. The flow
of gossip can amplify the impact of a person's actions on their reputation
depending on how widely it spreads across the social network, which leads to a
percolation problem. To quantify this notion, we calculate the expected number
of individuals, the "audience", who find out about a particular interaction.
For a potential donor, a larger audience constitutes higher reputational
stakes, and thus a higher incentive, to perform "good" actions in line with
current social norms. For a receiver, a larger audience therefore increases the
trust that the partner will be cooperative. This idea can be used for an
algorithm that generates social networks, which we call trust based attachment
(TBA). TBA produces graphs that share crucial quantitative properties with
real-world networks, such as high clustering, small-world behavior, and power
law degree distributions. We also show that TBA can be approximated by simple
friend-of-friend routines based on triadic closure, which are known to be
highly effective at generating realistic social network structures. Therefore,
our work provides a new justification for triadic closure in social contexts
based on notions of trust, gossip, and social information spread. These factors
are thus identified as potential significant influences on how humans form
social ties
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