Epidemic Models, Algorithms, and Protocols in Wireless Sensor and Ad Hoc Networks

De, P.; Das, Sajal K.

doi:10.1002/9780470396360.ch3

Cited by 21 publications

(7 citation statements)

References 37 publications

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“…Related works [9], [3] have tend to show that these dissemination phenomena present very analogous characteristics indeed. This field has been well studied for years with a particular emphasis on epidemics since either real datasets or simulation tools are available in this domain.…”

Section: Introductionmentioning

confidence: 89%

Simulating human mobility and information diffusion

Collard¹,

Collard

Stattner³

2013

Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining

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Human spatial motions determine geographic social contacts that influence the way an information is spread on a population or a community. As mobility is a transverse dimension to social practices it is important to better understand its role. With the Eternal-Return model we propose, we simulate an artificial world populated by heterogeneous agents who differ in their mobility. We have chosen a multi-agent framework perspective for this simulation. We endow the agents with simple rules on how to move around the space and how to establish proximity-contacts. This allows to distinguish different kinds of mobile agents, from sedentary ones to travelers. To summarize the dynamics induced by mobility over time, we define the mobility-based Social Proximity Network as being the network of all distinct contacts between agents. Its properties give insight in the process of information spreading. We conduct simulations to understand how an information can be broadcast when agent-nodes are in motion.

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Section: Introductionmentioning

confidence: 89%

Simulating human mobility and information diffusion

Collard¹,

Collard

Stattner³

2013

Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining

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“…Information dissemination in the discussed network occurs in an epidemic-based manner [15]. Nodes are infected if they carry the disseminated information and susceptible otherwise.…”

Section: System Model and Epidemic Disseminationmentioning

confidence: 99%

“…[0, 1] for node i at time t. We adopt the Susceptible-Infected-Susceptible (SIS) model [15], according to which an infected node becomes susceptible when cured and may be further infected. The operation of each node at (discrete) time instance t is characterized by two parameters, namely the forwarding probability β i (t) and the AMC mode μ i (t).…”

Section: System Model and Epidemic Disseminationmentioning

confidence: 99%

Epidemic information dissemination controlled by wireless channel awareness

Kontos

Anagnostopoulos

Hadjiefthymiades

et al. 2015

2015 IEEE Symposium on Computers and Communication (ISCC)

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We propose a cross-layer scheme for regulating power consumption in energy-constrained ad hoc wireless networks where information is disseminated in an adaptive epidemic manner. A time-optimized mechanism based on the Optimal Stopping Theory utilizes noise fluctuations to trigger the adaptation of transmission characteristics in a fashion that a perceived net reward is maximized. This results in data delivery being enhanced while energy cost remains modest.Keywords-epidemic information dissemination; adaptive probabilistic information dissemination; wireless sensor networks; optimal stopping theory.

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“…Nodes are infected when carrying the infecting information and susceptible when not. This environment subscribes to the SIS (susceptible-infected-susceptible) model [27]. The setup described above suits sensor data which needs to be disseminated and is of higher value when fresh, such as data from sensors monitoring a common scalar parameter.…”

Section: Epidemic Modelmentioning

confidence: 99%

Adaptive epidemic dissemination as a finite-horizon optimal stopping problem

et al. 2018

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Wireless ad hoc networks are characterized by their limited capabilities and their routine deployment in unfavorable environments. This creates the strong requirement to regulate energy expenditure. We present a scheme to regulate energy cost through optimized transmission scheduling in a noisy epidemic dissemination environment. Building on the intrinsically cross-layer nature of the adaptive epidemic dissemination process, we strive to deliver an optimized mechanism, where energy cost is regulated without compromising the network infection. Improvement of data freshness and applicability in routing are also investigated. Extensive simulations are used to support our proposal.

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Epidemic Models, Algorithms, and Protocols in Wireless Sensor and Ad Hoc Networks

Cited by 21 publications

References 37 publications

Simulating human mobility and information diffusion

Simulating human mobility and information diffusion

Epidemic information dissemination controlled by wireless channel awareness

Adaptive epidemic dissemination as a finite-horizon optimal stopping problem

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