60,921 research outputs found
Swarm-based Intelligent Routing (SIR) - a new approach for efficient routing in content centric delay tolerant networks
This paper introduces Swarm-based Intelligent Routing (SIR), a swarm intelligence based approach used for routing content in content centric Pocket Switched Networks. We first formalize the notion of optimal path in DTN, then introduce a swarm intelligence based routing protocol adapted to content centric DTN that use a publish/subscribe communication paradigm. The protocol works in a fully decentralized way in which nodes do not have any knowledge about the global topology. Nodes, via opportunistic contacts, update utility functions which synthesizes their spatio-temporal proximity from the content subscribers. This individual behavior applied by each node leads to the collective formation of gradient fields between content subscribers and content providers. Therefore, content routing simply sums up to follow the steepest slope along these gradient fields to reach subscribers who are located at the minima of the field. Via real traces analysis and simulation, we demonstrate the existence and relevance of such gradient field and show routing performance improvements when compared to classical routing protocols previously defined for information routing in DTN
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
Impact of spatially constrained sampling of temporal contact networks on the evaluation of the epidemic risk
The ability to directly record human face-to-face interactions increasingly
enables the development of detailed data-driven models for the spread of
directly transmitted infectious diseases at the scale of individuals. Complete
coverage of the contacts occurring in a population is however generally
unattainable, due for instance to limited participation rates or experimental
constraints in spatial coverage. Here, we study the impact of spatially
constrained sampling on our ability to estimate the epidemic risk in a
population using such detailed data-driven models. The epidemic risk is
quantified by the epidemic threshold of the
susceptible-infectious-recovered-susceptible model for the propagation of
communicable diseases, i.e. the critical value of disease transmissibility
above which the disease turns endemic. We verify for both synthetic and
empirical data of human interactions that the use of incomplete data sets due
to spatial sampling leads to the underestimation of the epidemic risk. The bias
is however smaller than the one obtained by uniformly sampling the same
fraction of contacts: it depends nonlinearly on the fraction of contacts that
are recorded and becomes negligible if this fraction is large enough. Moreover,
it depends on the interplay between the timescales of population and spreading
dynamics.Comment: 21 pages, 7 figure
The Dynamics of Vehicular Networks in Urban Environments
Vehicular Ad hoc NETworks (VANETs) have emerged as a platform to support
intelligent inter-vehicle communication and improve traffic safety and
performance. The road-constrained, high mobility of vehicles, their unbounded
power source, and the emergence of roadside wireless infrastructures make
VANETs a challenging research topic. A key to the development of protocols for
inter-vehicle communication and services lies in the knowledge of the
topological characteristics of the VANET communication graph. This paper
explores the dynamics of VANETs in urban environments and investigates the
impact of these findings in the design of VANET routing protocols. Using both
real and realistic mobility traces, we study the networking shape of VANETs
under different transmission and market penetration ranges. Given that a number
of RSUs have to be deployed for disseminating information to vehicles in an
urban area, we also study their impact on vehicular connectivity. Through
extensive simulations we investigate the performance of VANET routing protocols
by exploiting the knowledge of VANET graphs analysis.Comment: Revised our testbed with even more realistic mobility traces. Used
the location of real Wi-Fi hotspots to simulate RSUs in our study. Used a
larger, real mobility trace set, from taxis in Shanghai. Examine the
implications of our findings in the design of VANET routing protocols by
implementing in ns-3 two routing protocols (GPCR & VADD). Updated the
bibliography section with new research work
Yield Effects of Tissue Culture Bananas in Kenya: Accounting for Selection Bias and the Role of Complementary Inputs
We analyze yield effects of tissue culture (TC) banana technology in the Kenyan small farm sector, using recent survey data and an endogenous switching regression approach. TC banana plantlets, which are free from pests and diseases, have been introduced in East Africa since the late-1990s. While field experiments show significant yield advantages over traditional banana suckers, a rigorous assessment of impacts in farmers' fields is still outstanding. A comparison of mean yield levels between TC adopters and non-adopters in our sample shows no significant difference. However, we find a negative selection bias, indicating that farmers with lower than average yields are more likely to adopt TC. Controlling for this bias results in a positive and significant TC net yield gain of 7%. We also find that TC technology is more knowledgeintensive and more responsive to irrigation than traditional bananas. Simulations show that improving access to irrigation could lift TC productivity gains to above 20%. The analytical approach developed and applied here may also be useful for the evaluation of other knowledgeintensive package technologies and innovations in perennial crops. --Biotechnology,adoption,productivity,impact,endogenous switching regression,Kenya
The Strategic Exploitation of Limited Information and Opportunity in Networked Markets
This paper studies the effect of constraining interactions within a market. A model is analysed in which boundedly rational agents trade with and gather information from their neighbours within a trade network. It is demonstrated that a trader’s ability to profit and to identify the equilibrium price is positively correlated with its degree of connectivity within the market. Where traders differ in their number of potential trading partners, well-connected traders are found to benefit from aggressive trading behaviour.Where information propagation is constrained by the topology of the trade network, connectedness affects the nature of the strategies employed
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