This document proposes incentive mechanisms called Network of Favors (NoF) and its variants to encourage cooperation among selfish peers in a federated cloud computing environment. The baseline NoF approach uses a local credit system to prioritize peers that have provided more resources to others in the past. A Satisfaction-Driven NoF (SD-NoF) maximizes the resources provided to maximize peer satisfaction, while a Fairness-Driven NoF (FD-NoF) regulates the resources provided through a feedback control loop to achieve good fairness levels. Simulation results show FD-NoF can achieve similar satisfaction levels to SD-NoF in high resource contention scenarios, while improving fairness by 44% in low contention scenarios, suggesting
Apresenta巽達o do artigo "Controlando a Conten巽達o de Recursos para Promover Justi巽a em uma Federa巽達o Peer-to-Peer de Nuvens Privadas" no WCGA 2015 - SBRC 2015.
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Cap鱈tulo de livro sobre o X3D publicado em "Tend棚ncias e T辿cnicas em Realidade Virtual e Aumentada" no SVR 2010.
Um pouco sobre SQS e SNS para comunica巽達o entre componentes na AWS, e alguns exemplos simples de utiliza巽達o.
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Este documento apresenta conceitos sobre servi巽os de computa巽達o em nuvem da AWS, incluindo: (1) EC2 para provisionamento de inst但ncias virtuais; (2) ELB para balanceamento de carga entre inst但ncias; (3) Auto Scaling para dimensionamento autom叩tico de inst但ncias; (4) CloudWatch para monitoramento de recursos. O documento descreve caracter鱈sticas e vocabul叩rio desses servi巽os.
A AWS surgiu para resolver os problemas de escalabilidade do site da Amazon. Seus primeiros servi巽os foram SQS, S3 e EC2, permitindo comunica巽達o entre componentes, armazenamento escal叩vel na nuvem e computa巽達o el叩stica por hora. Posteriormente lan巽ou outros servi巽os como RDS, ELB, Auto Scaling e CloudWatch para armazenamento de dados, balanceamento e monitoramento de carga.
Este documento apresenta os principais conceitos da computa巽達o em nuvem, incluindo: (1) os modelos de servi巽o como SaaS, PaaS e IaaS; (2) as cinco caracter鱈sticas essenciais da nuvem como auto-servi巽o sob demanda, amplo acesso, pooling de recursos, elasticidade r叩pida e servi巽o medido; e (3) os quatro modelos de implanta巽達o da nuvem.
Este documento introduz os sistemas distribu鱈dos, definindo-os como um conjunto de computadores independentes que aparecem para os usu叩rios como um 炭nico sistema coerente. Explora as motiva巽探es, caracter鱈sticas e tipos de sistemas distribu鱈dos, incluindo clusters, supercomputadores, grids, sistemas pervasivos e nuvem.
Este documento apresenta uma introdu巽達o ao curso de Sistemas Distribu鱈dos. Ele discute os objetivos do curso, os t坦picos que ser達o abordados, como a avalia巽達o ser叩 realizada e os resultados esperados ao final do curso. Os alunos aprender達o os conceitos fundamentais de sistemas distribu鱈dos e como implantar um sistema escal叩vel na nuvem AWS.
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No ensino de arquitetura de computadores, um dos principais desafios 辿 fazer com que os alunos compreendam com mais facilidade o funcionamento de um processador. Para auxiliar a esta tarefa, s達o utilizadas aplica巽探es que simulam tais arquiteturas. A proposta do presente trabalho 辿 desenvolver uma aplica巽達o, disponibilizada na web, que simule visualmente as instru巽探es de uma arquitetura did叩tica e implement叩vel. poss鱈vel visualizar a simula巽達o de tais instru巽探es com ou sem pipeline, o que facilita a compreens達o das mesmas e do funcionamento de um processador enquanto as executam.
Semin叩rio apresentado na disciplina de Teoria da Computa巽達o. Aborda o processo de tradu巽達o da l鱈ngua portuguesa para a Libras, exemplificando as poss鱈veis aplica巽探es dos assuntos de Teoria da Computa巽達o, como aut担matos.
A Lei de Moore prev棚 o aumento exponencial do n炭mero de transistores nos processadores a cada dois anos, por辿m os desafios da escala de tamanho dos transistores e o aumento do consumo de energia amea巽am essa lei.
A mem坦ria n達o consegue acompanhar o aumento de desempenho dos processadores multicore devido ao "problema da parede da mem坦ria", for巽ando novas abordagens como a hierarquiza巽達o da mem坦ria.
A lei de Amdahl mostra que mesmo com processadores multicore
Este documento discute estilos de intera巽達o para auxiliar o processo fisioter叩pico, como o uso de luvas de dados, biofeedback e realidade virtual. Feedback preciso 辿 essencial para avaliar exerc鱈cios, e diferentes dispositivos como sensores fornecem esse feedback de forma n達o invasiva.
O documento resume conceitos fundamentais de minera巽達o de dados, incluindo: 1) Vis達o geral do processo KDD e das etapas de extra巽達o de informa巽探es dos dados; 2) Tarefas comuns de minera巽達o de dados como classifica巽達o e associa巽達o; 3) T辿cnicas como 叩rvores de decis達o e redes neurais. O documento tamb辿m discute ferramentas como o Weka e aplica巽探es pr叩ticas de minera巽達o de dados.
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2. O simulador permite visualizar instru巽探es sendo executadas de forma passo-a-passo em um processador com e sem pipeline para facilitar a compreens達o.
3. O simulador usa anima巽探es 3D para mostrar o fluxo de informa巽探es durante a execu巽達o de instru巽探es de uma forma intuitiva.
O Laborat坦rio de Tecnologias para o Ensino Virtual e Estat鱈stica (LabTEVE) desenvolve projetos voltados para ensino virtual, realidade virtual e jogos s辿rios, com foco em educa巽達o, sa炭de e engenharia. Seus principais projetos incluem o framework CyberMed para aplica巽探es m辿dicas em RV, o simulador ginecol坦gico SITEG e o Campus Virtual tridimensional.
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Este documento apresenta os principais conceitos da computa巽達o em nuvem, incluindo: (1) os modelos de servi巽o como SaaS, PaaS e IaaS; (2) as cinco caracter鱈sticas essenciais da nuvem como auto-servi巽o sob demanda, amplo acesso, pooling de recursos, elasticidade r叩pida e servi巽o medido; e (3) os quatro modelos de implanta巽達o da nuvem.
Este documento introduz os sistemas distribu鱈dos, definindo-os como um conjunto de computadores independentes que aparecem para os usu叩rios como um 炭nico sistema coerente. Explora as motiva巽探es, caracter鱈sticas e tipos de sistemas distribu鱈dos, incluindo clusters, supercomputadores, grids, sistemas pervasivos e nuvem.
Este documento apresenta uma introdu巽達o ao curso de Sistemas Distribu鱈dos. Ele discute os objetivos do curso, os t坦picos que ser達o abordados, como a avalia巽達o ser叩 realizada e os resultados esperados ao final do curso. Os alunos aprender達o os conceitos fundamentais de sistemas distribu鱈dos e como implantar um sistema escal叩vel na nuvem AWS.
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油
- O documento discute o problema da otimiza巽達o da multiplica巽達o de cadeias de matrizes. Aborda poss鱈veis solu巽探es como programa巽達o din但mica, minimiza巽達o de cache miss e abordagens distribu鱈das com threads e OpenMP. Realiza an叩lise comparativa do desempenho dessas abordagens no problema.
INFORMAO ARQUEOLGICA DE ING: preserva巽達o, acesso e uso a partir de um amb...Eduardo de Lucena Falc達o
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Este documento discute a preserva巽達o do s鱈tio arqueol坦gico Itacoatiaras do Ing叩, localizado em Ing叩, Para鱈ba, atrav辿s da cria巽達o de um ambiente virtual 3D. Uma equipe multidisciplinar coletou informa巽探es sobre o local e as categorizou para compor o ambiente virtual, permitindo a divulga巽達o e acesso remoto ao s鱈tio arqueol坦gico.
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Este documento discute v叩rias abordagens para resolver o problema da multiplica巽達o de cadeias de matrizes de forma otimizada, incluindo: (1) programa巽達o din但mica para encontrar a ordem 坦tima de multiplica巽達o, (2) minimiza巽達o de cache miss ao modificar a ordem de loops, e (3) uso de threads para explorar processadores multicore. O objetivo 辿 analisar esses m辿todos e medir seu impacto no desempenho.
No ensino de arquitetura de computadores, um dos principais desafios 辿 fazer com que os alunos compreendam com mais facilidade o funcionamento de um processador. Para auxiliar a esta tarefa, s達o utilizadas aplica巽探es que simulam tais arquiteturas. A proposta do presente trabalho 辿 desenvolver uma aplica巽達o, disponibilizada na web, que simule visualmente as instru巽探es de uma arquitetura did叩tica e implement叩vel. poss鱈vel visualizar a simula巽達o de tais instru巽探es com ou sem pipeline, o que facilita a compreens達o das mesmas e do funcionamento de um processador enquanto as executam.
Semin叩rio apresentado na disciplina de Teoria da Computa巽達o. Aborda o processo de tradu巽達o da l鱈ngua portuguesa para a Libras, exemplificando as poss鱈veis aplica巽探es dos assuntos de Teoria da Computa巽達o, como aut担matos.
A Lei de Moore prev棚 o aumento exponencial do n炭mero de transistores nos processadores a cada dois anos, por辿m os desafios da escala de tamanho dos transistores e o aumento do consumo de energia amea巽am essa lei.
A mem坦ria n達o consegue acompanhar o aumento de desempenho dos processadores multicore devido ao "problema da parede da mem坦ria", for巽ando novas abordagens como a hierarquiza巽達o da mem坦ria.
A lei de Amdahl mostra que mesmo com processadores multicore
Este documento discute estilos de intera巽達o para auxiliar o processo fisioter叩pico, como o uso de luvas de dados, biofeedback e realidade virtual. Feedback preciso 辿 essencial para avaliar exerc鱈cios, e diferentes dispositivos como sensores fornecem esse feedback de forma n達o invasiva.
O documento resume conceitos fundamentais de minera巽達o de dados, incluindo: 1) Vis達o geral do processo KDD e das etapas de extra巽達o de informa巽探es dos dados; 2) Tarefas comuns de minera巽達o de dados como classifica巽達o e associa巽達o; 3) T辿cnicas como 叩rvores de decis達o e redes neurais. O documento tamb辿m discute ferramentas como o Weka e aplica巽探es pr叩ticas de minera巽達o de dados.
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1. O documento descreve um simulador gr叩fico 3D para ensinar arquitetura de processadores.
2. O simulador permite visualizar instru巽探es sendo executadas de forma passo-a-passo em um processador com e sem pipeline para facilitar a compreens達o.
3. O simulador usa anima巽探es 3D para mostrar o fluxo de informa巽探es durante a execu巽達o de instru巽探es de uma forma intuitiva.
O Laborat坦rio de Tecnologias para o Ensino Virtual e Estat鱈stica (LabTEVE) desenvolve projetos voltados para ensino virtual, realidade virtual e jogos s辿rios, com foco em educa巽達o, sa炭de e engenharia. Seus principais projetos incluem o framework CyberMed para aplica巽探es m辿dicas em RV, o simulador ginecol坦gico SITEG e o Campus Virtual tridimensional.
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In this slide, well discuss on how to modify existing web pages in Odoo 18. Web pages in Odoo 18 can also gather user data through user-friendly forms, encourage interaction through engaging features.
What do students really understand about academic integrity? International Ce...Thomas Lancaster
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How do we find out what students really think and understand about academic integrity? In this presentation, I look at work conducted with my students which goes beyond survey research.
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Computer Network Unit IV - Lecture Notes - Network LayerMurugan146644
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Title:
Lecture Notes - Unit IV - The Network Layer
Description:
Welcome to the comprehensive guide on Computer Network concepts, tailored for final year B.Sc. Computer Science students affiliated with Alagappa University. This document covers fundamental principles and advanced topics in Computer Network. PDF content is prepared from the text book Computer Network by Andrew S. Tenanbaum
Key Topics Covered:
Main Topic : The Network Layer
Sub-Topic : Network Layer Design Issues (Store and forward packet switching , service provided to the transport layer, implementation of connection less service, implementation of connection oriented service, Comparision of virtual circuit and datagram subnet), Routing algorithms (Shortest path routing, Flooding , Distance Vector routing algorithm, Link state routing algorithm , hierarchical routing algorithm, broadcast routing, multicast routing algorithm)
Other Link :
1.Introduction to computer network - /slideshow/lecture-notes-introduction-to-computer-network/274183454
2. Physical Layer - /slideshow/lecture-notes-unit-ii-the-physical-layer/274747125
3. Data Link Layer Part 1 : /slideshow/lecture-notes-unit-iii-the-datalink-layer/275288798
Target Audience:
Final year B.Sc. Computer Science students at Alagappa University seeking a solid foundation in Computer Network principles for academic.
About the Author:
Dr. S. Murugan is Associate Professor at Alagappa Government Arts College, Karaikudi. With 23 years of teaching experience in the field of Computer Science, Dr. S. Murugan has a passion for simplifying complex concepts in Computer Network
Disclaimer:
This document is intended for educational purposes only. The content presented here reflects the authors understanding in the field of Computer Network
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Carbohydrate: Properties, classification Chemical test
Tragacanth
Synonyms
Biological Source
Geographical Source Method of Collection & Preparation Description:
Chemical Constituent Chemical test uses
Adulterant and Substitutes
Acacia
Synonyms
Biological Source
Geographical Source Method of Collection & Preparation Description:
Chemical Constituent Chemical test uses
Adulterant and Substitutes
Agar
Synonyms
Biological Source
Geographical Source Method of Collection & Preparation Description:
Chemical Constituent Chemical test uses
Adulterant and Substitutes
Honey
Synonyms
Biological Source
Geographical Source Method of Collection & Preparation Description:
Chemical Constituent Chemical test uses
Adulterant and Substitutes
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The needs of normal children through the stages of development and parental guidance are crucial aspects of child rearing and overall child development. Understanding these needs and providing appropriate guidance and support is essential for ensuring children grow into healthy, well-adjusted individuals. The following are the needs of children at different developmental stages and how parents can provide effective guidance.
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Dais 2015
1. Incentivising Resource Sharing
in Federated Clouds
Eduardo Falc達o
eduardolfalcao@lsd.ufcg.edu.br
Francisco Brasileiro
Andrey Brito
Jos辿 Luis Vivas
2. Challenge
Promotion of cooperation among selfish
individuals in a decentralized context;
Incentive mechanisms to prevent
collaborative peers from defecting from the
federation;
Peers need to take efficient decisions
To whom should I donate?
How much should I donate?
2
3. Baseline Network of Favors
Network of Favors (NoF)
each peer keeps a local record of the past
interactions with other peers.
Peer Provided
Favors
Consumed
Favors
Credit
D 300 150 150
B 100 55 45
E 30 5 25
C 15 30 0
F 0 200 0
A
{ 3
4. Problem Statement
Whenever there is contention of resources,
the collaborative actors are prioritized;
NoF works fine in these scenarios.
Peer Provided
Favors
Consumed
Favors
Credit
D 300 150 150
B 100 55 45
E 30 5 25
C 15 30 0
F 0 200 0
A
{
requests
+10
+10
+10
+10
+10
free: +20
4
5. Problem Statement
When there isnt contention of resources, some
free riders are able to consume the exceeding
resources.
These resources wont be reciprocated in the future.
Peer Provided
Favors
Consumed
Favors
Credit
D 300 150 150
B 100 55 45
E 30 5 25
C 15 30 0
F 0 200 0
A
{
requests
0
+10
free: +20
0
0
0
5
6. Solution
$$ =
$
=
p
Satisfaction-Driven NoF (SD-NoF)
Context: P2P opportunistic desktop
grids;
Low cost for maintenance and
hosting;
Provides all exceeding
resources to maximize the
satisfaction of the peers.
Fairness-Driven NoF (FD-NoF)
Context: P2P federation of
private cloud providers;
High cost due to purchase,
maintenance, energy, hosting,
etc;
Regulates the amount of
provided resources in order to
guarantee good levels of
fairness
probability of being answered level of reciprocity
6
7. Simulation Model
: number of peers;
: % free riders;
The simulation poceeds in steps;
Collaborators and free riders have the same total
resource capacity (), and the same amount of
demand ( );
SD-NoF provides ;
FD-NoF provides 0, ;
: probability of consuming;
Colaborators [consuming state, provider state];
Free riders [consuming state], critical case, = 1.
factors
7
8. Scenarios
Designed to assess the different scenarios of
contention of resources between
collaborators ():
= 0.5 low resource contention
= 1 moderate resource contention
{2, 4} high resource contention
requested
provided
=
10
20
=
10
10
=
10
5
factors
Constant n=100; f=75%; steps=10000; C=1
Variable and
8
14. Concluding Remarks
FD-NoF shows good evidences that achieves
its goal:
Low resource contention
Satisfaction -4%
Fairness +44%
Moderate and high resource contention: similar
results to SD-NoF.
14
15. Future Work
Improve the Feedback Control Loop;
Validation of the results in a realistic scenario;
Fogbow middleware
http://www.fogbowcloud.org/
EUBrazilCC project: federation of private cloud
providers
http://eubrazilcloudconnect.eu/
15
#3: Once the federation we are dealing is completely decentralized one of the greatest challenges we face is the promotion of cooperation among the participants.
In P2P networks, in a first glance, peers dont know each other and are assumed to be selfish and to have economic incentive to become free riders, which are the non-reciprocators peers.
Therefore, some type of incentive mechanism must exist in order to maximize the benefits of the peers staying in that federation, otherwise, they would leave it.
A federation will provide good results to a peer only if he takes efficient decisions, which includes not donating to free riders.
Thus, our incentive mechanism should help the peer to answer the following questions that they naturally have:
To whom should I donate? (here, the mechanism should point out collaborative partners)
How much should I donate? (once I do not trust anybody, should I donate all my exceeding resources to this unknown peer, or should I increase this ammount gradually?)
#4: Network of Favors (NoF): Ensures the prioritization of favors to colaborators ;
In NoF, each peer keeps a local record of his past interactions with other peers.
For example: peer D provided 300 units of favor to peer A, and condumed 150 units of favor from peer A, which gives him a credit of 150 units of favor with peer A.
A unit of favor could be a measure that involves a processing power (which could be described as a flavour of the instance) multiplied by the time it was lent.
As you can note, this table is ordered by the credit, and whenever peer A has exceeding resources, he will always prioritize the peers in the top of this table.
This is how the NoF reward colaborative peers.
#5: Whenever there is contention of resources the Network of Favors works fine: the collaborative actors are prioritized and granted favors, and the free riders are left with a low degree of success.
Thats what is happening in this case. The peer A has 20 units of free resources, and each peer in the table is requesting 10 units of favor.
A will grant D 10 units, and the last 10 units will be provided to B.
#6: But in scenarios of low contention of resources, the surplus resources of the federation can be consumed by the free riders.
In this new example, only peer F is requesting resources. Note that, for this single case, there is plenty of resources in the federation, and this increases the probability of a free rider grant more favors.
We might note that peer F seems to be a free rider, because he didnt provided any favor to A, he just consumed favors.
In this scenario (low contention of resources) the peer F would grant this favor, and if he really is a free rider, this resource will not be reciprocated to A in the future.
#7: In order to better quantify the performance of the peers in different scenarios of contention of resources, we created these two metrics: satisfaction and fairness.
Satisfaction is measured by the amount of resources consumed over the amount of resources requested, which could be also referred as the probability of being answered when requesting resources.
For example, if a peer requests 10 resources and he is granted these 10 resources, then, he has the best level of satisfaction possible, which is 1.
Fairnes is the amount of consumed resources over the amount of donated resources. It could also be referred as the degree of reciprocity.
For example, if a peer provides 10 resources and consumes only 1 unit of resources, he has a low level of fairness, 0.1.
If he consumed the 10 resources it had provided, then he would have a good level of fairness, 1.
Based on these 2 metrics we took the liberty of renaming the NoF, which was previously proposed to opportunistic desktop grids, to Satisfaction-Driven NoF.
But why?
In this NoF, every peer always provides all of its free resources to try to maximize your own satisfaction.
The idea is that when he provides more resources, higher is the probability of another peer consume them.
Then, the providing peer would increase his credit with the consuming peer, and this would get him to the top of the other peers table.
This would increase the probability of this peer be answered when he need resources.
In this case, this could be done due to the low cost of resources.
But, when we come to a scenario that involves high costs in the business model, like federation of cloud providers, the costs should not be neglected.
Then, in these scenarios, the fairness is the metric to be maximized, since it involves the donation of resources.
Basically, what we propose is that the peers should regulate the amount of provided resources, so that the federation could avoid scenarios of very low contention of resources, which is good for free riders.
#8: Now that we have these 2 metrics, fairness and satisfaction, we want to understand how peers perform in SD-NoF and in our proposed FD-NoF.
Our simulation have the following factors, which are in red.
Each simulation of a p2p network is composed by:
n: the number of peers
f: the amount, in percentage, of free riders
steps: the number of steps
C: the amount of resources each peer has
D: the demand of each peer
PI: the probability of being in consuming state
One simplification that we did is about the time. Here it is not continuous, but discrete.
In our first evaluation, we wanted to know how the set of collaborators perform in relation to free riders. Thus, all collaborators have the same Capacitys and Demands. Further, we eliminate this simplification to better understand how collaborators with higher Demand perform in comparison to another with lower demand.
In the SD-NoF, a collaborator always supplies all of its free resources, in order to try to maximize his Satisfaction.
#9: We designed the scenarios in terms of the contention of resources.
What we want here is to better understand how peers perform in different levels of contention.
In mathematical terms, the contention of resources (kappa) is measured by the amount of requested resources by the set of collaborators in consuming state divided by the amount of resources supplied by the set of collaborators in provider state.
For example, if the consuming collaborators request in total 10 resources.
If there were a set of collaborator that together could donate 20 resources, then we would have a low resource contention scenario. Note that there would be 10 exceeding resources that could be consumed by free riders.
Our proposal is that the set of collaborator could regulate the amount of supplied resources to the federeation and therefore control the level of contention.
Note that this set of collaborators could reduce the total amount of resources supplied from 20 to 10, and so they would have a a moderate contention of resources. Nota that here, there arent surplus resources that the free riders could allocate.
And in a similar way they could increase even more the level of contention, what would give us a scenario of high level of contention.
#10: We advocate that collaborators should be equipped with a control mechanism that enables them to regulate the amount of resources donated, thereby impacting the level of resource contention in the system. This should be done in such a way that high values for fairness are attained without impairing that of satisfaction.
#14: Ao analisarmos K=0.5 e K=1, os casos onde a justi巽a pode ser afetada devido sobra de recursos, podemos ver que os colaboradores apresentaram uma melhoria em ambos os cen叩rios.
Para K=0.5, os colaboradores tiveram ganho absoluto m辿dio de 20% de justi巽a e e ganho relativo de 38%.
Ent達o a pergunta relativa ao trade-off seria: vale a pena trocar 1% de satisfa巽達o por 38% de justi巽a?