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Description
This report investigates the improvement in the transmission throughput, when fountain codes are used in opportunistic data routing, for a proposed delay tolerant network to connect remote and isolated communities in the Amazon region in Brazil, to the main city of that area. To extend healthcare facilities to the remote and isolated communities, on the banks of river Amazon in Brazil, the network [7] utilizes regularly schedules boats as data mules to carry data from one city to other.
Frequent thunder and rain storms, given state of infrastructure and harsh geographical terrain; all contribute to increase in chances of massages not getting delivered to intended destination. These regions have access to medical facilities only through sporadic visits from medical team from the main city in the region, Belem. The proposed network uses records for routine clinical examinations such as ultrasounds on pregnant women could be sent to the doctors in Belem for evaluation.
However, due to the lack of modern communication infrastructure in these communities and unpredictable boat schedules due to delays and breakdowns, as well as high transmission failures due to the harsh environment in the region, mandate the design of robust delay-tolerant routing algorithms. The work presented here incorporates the unpredictability of the Amazon riverine scenario into the simulation model - accounting for boat mechanical failure in boats leading to delays/breakdowns, possible decrease in transmission speed due to rain and individual packet losses.
Extensive simulation results are presented, to evaluate the proposed approach and to verify that the proposed solution [7] could be used as a viable mode of communication, given the lack of available options in the region. While the simulation results are focused on remote healthcare applications in the Brazilian Amazon, we envision that our approach may also be used for other remote applications, such as distance education, and other similar scenarios.
Frequent thunder and rain storms, given state of infrastructure and harsh geographical terrain; all contribute to increase in chances of massages not getting delivered to intended destination. These regions have access to medical facilities only through sporadic visits from medical team from the main city in the region, Belem. The proposed network uses records for routine clinical examinations such as ultrasounds on pregnant women could be sent to the doctors in Belem for evaluation.
However, due to the lack of modern communication infrastructure in these communities and unpredictable boat schedules due to delays and breakdowns, as well as high transmission failures due to the harsh environment in the region, mandate the design of robust delay-tolerant routing algorithms. The work presented here incorporates the unpredictability of the Amazon riverine scenario into the simulation model - accounting for boat mechanical failure in boats leading to delays/breakdowns, possible decrease in transmission speed due to rain and individual packet losses.
Extensive simulation results are presented, to evaluate the proposed approach and to verify that the proposed solution [7] could be used as a viable mode of communication, given the lack of available options in the region. While the simulation results are focused on remote healthcare applications in the Brazilian Amazon, we envision that our approach may also be used for other remote applications, such as distance education, and other similar scenarios.
ContributorsAgarwal, Rachit (Author) / Richa, Andrea (Thesis advisor) / Dasgupta, Partha (Committee member) / Johnson, Thienne (Committee member) / Arizona State University (Publisher)
Created2015
Description
Imagine that we have a piece of matter that can change its physical properties like its shape, density, conductivity, or color in a programmable fashion based on either user input or autonomous sensing. This is the vision behind what is commonly known as programmable matter. Envisioning systems of nano-sensors devices, programmable matter consists of systems of simple computational elements, called particles, that can establish and release bonds, compute, and can actively move in a self-organized way. In this dissertation the feasibility of solving fundamental problems relevant for programmable matter is investigated. As a model for such self-organizing particle systems (SOPS), the geometric amoebot model is introduced. In this model, particles only have local information and have modest computational power. They achieve locomotion by expanding and contracting, which resembles the behavior of amoeba. Under this model, efficient local-control algorithms for the leader election problem in SOPS are presented. As a central problem for programmable matter, shape formation problems are then studied. The limitations of solving the leader election problem and the shape formation problem on a more general version of the amoebot model are also discussed. The \smart paint" problem is also studied which aims at having the particles self-organize in order to uniformly coat the surface of an object of arbitrary shape and size, forming multiple coating layers if necessary. A Universal Coating algorithm is presented and shown to be asymptotically worst-case optimal both in terms of time with high probability and work. In particular, the algorithm always terminates within a linear number of rounds with high probability. A linear lower bound on the competitive gap between fully local coating algorithms and coating algorithms that rely on global information is presented, which implies that the proposed algorithm is also optimal in a competitive sense. Simulation results show that the competitive ratio of the proposed algorithm may be better than linear in practice. Developed algorithms utilize only local control, require only constant-size memory particles, and are asymptotically optimal in terms of the total number of particle movements needed to reach the desired shape configuration.
ContributorsDerakhshandeh, Zahra (Author) / Richa, Andrea (Thesis advisor) / Sen, Arunabha (Thesis advisor) / Xue, Guoliang (Committee member) / Scheideler, Christian (Committee member) / Arizona State University (Publisher)
Created2017