Network monitoring in multicast networks using network coding

In this paper we show how information contained in robust network codes can be used for passive inference of possible locations of link failures or losses in a network. For distributed randomized network coding, we bound the probability of being able to distinguish among a given set of failure events, and give some experimental results for one and two link failures in randomly generated networks. We also bound the required field size and complexity for designing a robust network code that distinguishes among a given set of failure events

ON A(PE)THEISM: RELIGIOUS DEHUMANIZATION OF ATHEISTS AND OTHER OUTGROUPS

Research on the dark side of religion has recently found evidence that anti-atheist prejudice is embedded in distrust (Gervais et al, 2011). Anti-atheist prejudice though old in its form, has only been systemically researched on over the last couple of years. This study seeks to extend on research in anti-atheist prejudice by examining religious dehumanization of atheists in comparison with other religious outgroups – gays and Muslims. Study 1 utilized a two factor model of dehumanization (Haslam, 2006) to examine dehumanization. Study 2 serves as a conceptual replication and extension using two different measures of dehumanization. Study 1 failed to find support for religious dehumanization while study 2 found partial support

GOD ON TRIAL: ARE OUR MORAL JUDGMENTS DIFFERENT BASED ON WHETHER WE ARE JUDGING GOD OR HUMANS?

Past work in moral psychology has demonstrated that individuals’ judgments of other humans in hypothetical moral scenarios can be influenced by variables such as intentionality, causality and controllability. However, while empirical studies suggest that individuals similarly hold nonhuman agents such as robots morally accountable for their actions to the extent that they are perceived to possess humanlike attributes important for moral judgments, research is scant when God is introduced as a nonhuman agent. On one hand it is proposed that because people anthropomorphize God, our moral intuitions of humans and God tend to show similar effects. In this case, both humans and God should be morally blamed when they are perceived to have engaged in a moral transgression. On the other hand, opinion polls suggest that the public at large generally agrees that belief in God(s) is necessary for one to be moral. By extension, our moral intuitions of God and humans should diverge significantly. Both perspectives offer different predictions about how people morally judge God and humans. This study attempts to test both perspectives by examining whether moral judgments of God show similar patterns to the moral judgments of a human (anthropomorphic perspective) or if judgments are biased toward God even when an immoral deed has occurred (Divine Command perspective). A 2 (Target: human vs God) x 2 (Morality of scenario: moral vs immoral) x 3 (Scenarios: sexual assault vs robbery vs murder) mixed model design was conducted to examine both hypotheses. Exploratory variables (i.e., Morality Founded on Divine Authority (MFDA) scale, religiosity and gender) were also included to test for potential moderation effects. Initial results suggest that people’s moral intuitions of humans and God do diverge, and this effect was moderated only by the MFDA scale. Limitations, implications and possible alternative explanations are discussed

New techniques for geographic routing

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.Includes bibliographical references (p. 141-148).As wireless sensor networks continue to grow in size, we are faced with the prospect of emerging wireless networks with hundreds or thousands of nodes. Geographic routing algorithms are a promising alternative to tradition ad hoc routing algorithms in this new domain for point-to-point routing, but deployments of such algorithms are currently uncommon because of some practical difficulties. This dissertation explores techniques that address two major issues in the deployment of geographic routing algorithms: (i) the costs associated with distributed planarization and (ii) the unavailability of location information. We present and evaluate two new algorithms for geographic routing: Greedy Distributed Spanning Tree Routing (GDSTR) and Greedy Embedding Spring Coordinates (GSpring). Unlike previous geographic routing algorithms which require the planarization of the network connectivity graph, GDSTR switches to routing on a spanning tree instead of a planar graph when packets end up at dead ends during greedy forwarding. To choose a direction on the tree that is most likely to make progress towards the destination, each GDSTR node maintains a summary of the area covered by the subtree below each of its tree neighbors using convex hulls.(cont.) This distributed data structure is called a hull tree. GDSTR not only requires an order of magnitude less bandwidth to maintain these hull trees than CLDP, the only distributed planarization algorithm that is known to work with practical radio networks, it often achieves better routing performance than previous planarization-based geographic routing algorithms. GSpring is a new virtual coordinate assignment algorithm that derives good coordinates for geographic routing when location information is not available. Starting from a set of initial coordinates for a set of elected perimeter nodes, GSpring uses a modified spring relaxation algorithm to incrementally adjust virtual coordinates to increase the convexity of voids in the virtual routing topology. This reduces the probability that packets will end up in dead ends during greedy forwarding, and improves the routing performance of existing geographic routing algorithms. The coordinates derived by GSpring yield comparable routing performance to that for actual physical coordinates and significantly better performance than that for NoGeo, the best existing algorithm for deriving virtual coordinates for geographic routing. Furthermore, GSpring is the first known algorithm that is able to derive coordinates that achieve better geographic routing performance than actual physical coordinates for networks with obstacles.by Ben Wing Lup Leong.Ph.D

Byzantine modification detection in multicast networks using randomized network coding

Distributed randomized network coding, a robust approach to multicasting in distributed network settings, can be extended to provide Byzantine modification detection without the use of cryptographic functions is presented in this paper

Byzantine Modification Detection in Multicast Networks With Random Network Coding

An information-theoretic approach for detecting Byzantine or adversarial modifications in networks employing random linear network coding is described. Each exogenous source packet is augmented with a flexible number of hash symbols that are obtained as a polynomial function of the data symbols. This approach depends only on the adversary not knowing the random coding coefficients of all other packets received by the sink nodes when designing its adversarial packets. We show how the detection probability varies with the overhead (ratio of hash to data symbols), coding field size, and the amount of information unknown to the adversary about the random code

On the utility of network coding in dynamic environments

Many wireless applications, such as ad-hoc networks and sensor networks, require decentralized operation in dynamically varying environments. We consider a distributed randomized network coding approach that enables efficient decentralized operation of multi-source multicast networks. We show that this approach provides substantial benefits over traditional routing methods in dynamically varying environments. We present a set of empirical trials measuring the performance of network coding versus an approximate online Steiner tree routing approach when connections vary dynamically. The results show that network coding achieves superior performance in a significant fraction of our randomly generated network examples. Such dynamic settings represent a substantially broader class of networking problems than previously recognized for which network coding shows promise of significant practical benefits compared to routing

Sand production: A smart control framework for risk mitigation

Due to the current global oil price, the sand production is considered undesirable product and the control of sand production is considered as one of the main concerns of production engineers. It can damage downhole, subsea equipments and surface production facilities, also increasing the risk of catastrophic failure. As a result of that it costs the producers multiple millions of dollars each year. Therefore, there are many different approaches of sand control designed for different reservoir conditions. Selecting an appropriate technique for preventing formation sand production depends on different reservoir parameters. Therefore, choosing the best sand control method is the result of systematic study. In this paper the sand production factors and their effects are presented where the emphasis is given towards the sand prediction to determine the probability of producing sand from the reservoir, followed by the correct prevention implementation of sand control method. The combination of these two is presented as a smart control framework that can be applied for sand production management

New Techniques for Geographic Routing

PhD thesisAs wireless sensor networks continue to grow in size, we are facedwith the prospect of emerging wireless networks with hundreds orthousands of nodes. Geographic routing algorithms are a promisingalternative to tradition ad hoc routing algorithms in this new domainfor point-to-point routing, but deployments of such algorithms arecurrently uncommon because of some practical difficulties.This dissertation explores techniques that address two major issues inthe deployment of geographic routing algorithms: (i) the costsassociated with distributed planarization and (ii) the unavailabilityof location information. We present and evaluate two new algorithmsfor geographic routing: Greedy Distributed Spanning Tree Routing(GDSTR) and Greedy Embedding Spring Coordinates (GSpring).Unlike previous geographic routing algorithms which require theplanarization of the network connectivity graph, GDSTR switches torouting on a spanning tree instead of a planar graph when packets endup at dead ends during greedy forwarding. To choose a direction on thetree that is most likely to make progress towards the destination,each GDSTR node maintains a summary of the area covered by the subtreebelow each of its tree neighbors using convex hulls. This distributeddata structure is called a hull tree. GDSTR not only requires an orderof magnitude less bandwidth to maintain these hull trees than CLDP,the only distributed planarization algorithm that is known to workwith practical radio networks, it often achieves better routingperformance than previous planarization-based geographic routingalgorithms.GSpring is a new virtual coordinate assignment algorithm that derivesgood coordinates for geographic routing when location information isnot available. Starting from a set of initial coordinates for a set ofelected perimeter nodes, GSpring uses a modified spring relaxationalgorithm to incrementally adjust virtual coordinates to increase theconvexity of voids in the virtual routing topology. This reduces theprobability that packets will end up in dead ends during greedyforwarding, and improves the routing performance of existinggeographic routing algorithms.The coordinates derived by GSpring yield comparable routingperformance to that for actual physical coordinates and significantlybetter performance than that for NoGeo, the best existing algorithmfor deriving virtual coordinates for geographic routing. Furthermore,GSpring is the first known algorithm that is able to derivecoordinates that achieve better geographic routing performance thanactual physical coordinates for networks with obstacles

Ecological Transcriptomics of Lake-Type and Riverine Sockeye Salmon (Oncorhynchus nerka)

Background: There are a growing number of genomes sequenced with tentative functions assigned to a largeproportion of the individual genes. Model organisms in laboratory settings form the basis for the assignment ofgene function, and the ecological context of gene function is lacking. This work addresses this shortcoming byinvestigating expressed genes of sockeye salmon (Oncorhynchus nerka) muscle tissue. We compared morphologyand gene expression in natural juvenile sockeye populations related to river and lake habitats. Based on previouslydocumented divergent morphology, feeding strategy, and predation in association with these distinctenvironments, we expect that burst swimming is favored in riverine population and continuous swimming isfavored in lake-type population. In turn we predict that morphology and expressed genes promote burstswimming in riverine sockeye and continuous swimming in lake-type sockeye.Results: We found the riverine sockeye population had deep, robust bodies and lake-type had shallow,streamlined bodies. Gene expression patterns were measured using a 16K microarray, discovering 141 genes withsignificant differential expression. Overall, the identity and function of these genes was consistent with ourhypothesis. In addition, Gene Ontology (GO) enrichment analyses with a larger set of differentially expressed genesfound the “biosynthesis” category enriched for the riverine population and the “metabolism” category enriched forthe lake-type population.Conclusions: This study provides a framework for understanding sockeye life history from a transcriptomicperspective and a starting point for more extensive, targeted studies determining the ecological context of genes