1,405 research outputs found
Distributed virtual environment scalability and security
Distributed virtual environments (DVEs) have been an active area of research and engineering for more than 20 years. The most widely deployed DVEs are network games such as Quake, Halo, and World of Warcraft (WoW), with millions of users and billions of dollars in annual revenue. Deployed DVEs remain expensive centralized implementations despite significant research outlining ways to distribute DVE workloads.
This dissertation shows previous DVE research evaluations are inconsistent with deployed DVE needs. Assumptions about avatar movement and proximity - fundamental scale factors - do not match WoW’s workload, and likely the workload of other deployed DVEs. Alternate workload models are explored and preliminary conclusions presented. Using realistic workloads it is shown that a fully decentralized DVE cannot be deployed to today’s consumers, regardless of its overhead.
Residential broadband speeds are improving, and this limitation will eventually disappear. When it does, appropriate security mechanisms will be a fundamental requirement for technology adoption.
A trusted auditing system (“Carbon”) is presented which has good security, scalability, and resource characteristics for decentralized DVEs. When performing exhaustive auditing, Carbon adds 27% network overhead to a decentralized DVE with a WoW-like workload. This resource consumption can be reduced significantly, depending upon the DVE’s risk tolerance.
Finally, the Pairwise Random Protocol (PRP) is described. PRP enables adversaries to fairly resolve probabilistic activities, an ability missing from most decentralized DVE security proposals.
Thus, this dissertations contribution is to address two of the obstacles for deploying research on decentralized DVE architectures. First, lack of evidence that research results apply to existing DVEs. Second, the lack of security systems combining appropriate security guarantees with acceptable overhead
Verifiable Encodings for Secure Homomorphic Analytics
Homomorphic encryption, which enables the execution of arithmetic operations
directly on ciphertexts, is a promising solution for protecting privacy of
cloud-delegated computations on sensitive data. However, the correctness of the
computation result is not ensured. We propose two error detection encodings and
build authenticators that enable practical client-verification of cloud-based
homomorphic computations under different trade-offs and without compromising on
the features of the encryption algorithm. Our authenticators operate on top of
trending ring learning with errors based fully homomorphic encryption schemes
over the integers. We implement our solution in VERITAS, a ready-to-use system
for verification of outsourced computations executed over encrypted data. We
show that contrary to prior work VERITAS supports verification of any
homomorphic operation and we demonstrate its practicality for various
applications, such as ride-hailing, genomic-data analysis, encrypted search,
and machine-learning training and inference.Comment: update authors, typos corrected, scheme update
Causal Consistent Databases
Many consistency criteria have been considered in databases and the causal consistency is one of them. The causal consistency model has gained much attention in recent years because it provides ordering of relative operations. The causal consistency requires that all writes, which are potentially causally related, must be seen in the same order by all processes. The causal consistency is a weaker criteria than the sequential consistency, because there exists an execution, which is causally consistent but not sequentially consistent, however all executions satisfying the sequential consistency are also causally consistent. Furthermore, the causal consistency supports non-blocking operations; i.e. processes may complete read or write operations without waiting for global computation. Therefore, the causal consistency overcomes the primary limit of stronger criteria: communication latency. Additionally, several application semantics are precisely captured by the causal consistency, e.g. collaborative tools. In this paper, we review the state-of-the-art of causal consistent databases, discuss the features, functionalities and applications of the causal consistency model, and systematically compare it with other consistency models. We also discuss the implementation of causal consistency databases and identify limitations of the causal consistency model
Cloud-edge hybrid applications
Many modern applications are designed to provide interactions among users, including multi-
user games, social networks and collaborative tools. Users expect application response time to
be in the order of milliseconds, to foster interaction and interactivity.
The design of these applications typically adopts a client-server model, where all interac-
tions are mediated by a centralized component. This approach introduces availability and fault-
tolerance issues, which can be mitigated by replicating the server component, and even relying on
geo-replicated solutions in cloud computing infrastructures. Even in this case, the client-server
communication model leads to unnecessary latency penalties for geographically close clients and
high operational costs for the application provider.
This dissertation proposes a cloud-edge hybrid model with secure and ecient propagation
and consistency mechanisms. This model combines client-side replication and client-to-client
propagation for providing low latency and minimizing the dependency on the server infras-
tructure, fostering availability and fault tolerance. To realize this model, this works makes the
following key contributions.
First, the cloud-edge hybrid model is materialized by a system design where clients maintain
replicas of the data and synchronize in a peer-to-peer fashion, and servers are used to assist
clients’ operation. We study how to bring most of the application logic to the client-side, us-
ing the centralized service primarily for durability, access control, discovery, and overcoming
internetwork limitations.
Second, we dene protocols for weakly consistent data replication, including a novel CRDT
model (∆-CRDTs). We provide a study on partial replication, exploring the challenges and
fundamental limitations in providing causal consistency, and the diculty in supporting client-
side replicas due to their ephemeral nature.
Third, we study how client misbehaviour can impact the guarantees of causal consistency.
We propose new secure weak consistency models for insecure settings, and algorithms to enforce
such consistency models.
The experimental evaluation of our contributions have shown their specic benets and
limitations compared with the state-of-the-art. In general, the cloud-edge hybrid model leads to
faster application response times, lower client-to-client latency, higher system scalability as fewer clients need to connect to servers at the same time, the possibility to work oine or disconnected
from the server, and reduced server bandwidth usage.
In summary, we propose a hybrid of cloud-and-edge which provides lower user-to-user la-
tency, availability under server disconnections, and improved server scalability – while being
ecient, reliable, and secure.Muitas aplicações modernas são criadas para fornecer interações entre utilizadores, incluindo
jogos multiutilizador, redes sociais e ferramentas colaborativas. Os utilizadores esperam que o
tempo de resposta nas aplicações seja da ordem de milissegundos, promovendo a interação e
interatividade.
A arquitetura dessas aplicações normalmente adota um modelo cliente-servidor, onde todas as
interações são mediadas por um componente centralizado. Essa abordagem apresenta problemas
de disponibilidade e tolerância a falhas, que podem ser mitigadas com replicação no componente
do servidor, até com a utilização de soluções replicadas geogracamente em infraestruturas de
computação na nuvem. Mesmo neste caso, o modelo de comunicação cliente-servidor leva a
penalidades de latência desnecessárias para clientes geogracamente próximos e altos custos
operacionais para o provedor das aplicações.
Esta dissertação propõe um modelo híbrido cloud-edge com mecanismos seguros e ecientes
de propagação e consistência. Esse modelo combina replicação do lado do cliente e propagação
de cliente para cliente para fornecer baixa latência e minimizar a dependência na infraestrutura
do servidor, promovendo a disponibilidade e tolerância a falhas. Para realizar este modelo, este
trabalho faz as seguintes contribuições principais.
Primeiro, o modelo híbrido cloud-edge é materializado por uma arquitetura do sistema em
que os clientes mantêm réplicas dos dados e sincronizam de maneira ponto a ponto e onde os
servidores são usados para auxiliar na operação dos clientes. Estudamos como trazer a maior
parte da lógica das aplicações para o lado do cliente, usando o serviço centralizado principalmente
para durabilidade, controlo de acesso, descoberta e superação das limitações inter-rede.
Em segundo lugar, denimos protocolos para replicação de dados fracamente consistentes,
incluindo um novo modelo de CRDTs (∆-CRDTs). Fornecemos um estudo sobre replicação parcial,
explorando os desaos e limitações fundamentais em fornecer consistência causal e a diculdade
em suportar réplicas do lado do cliente devido à sua natureza efémera.
Terceiro, estudamos como o mau comportamento da parte do cliente pode afetar as garantias
da consistência causal. Propomos novos modelos seguros de consistência fraca para congurações
inseguras e algoritmos para impor tais modelos de consistência.
A avaliação experimental das nossas contribuições mostrou os benefícios e limitações em comparação com o estado da arte. Em geral, o modelo híbrido cloud-edge leva a tempos de resposta
nas aplicações mais rápidos, a uma menor latência de cliente para cliente e à possibilidade de
trabalhar oine ou desconectado do servidor. Adicionalmente, obtemos uma maior escalabilidade
do sistema, visto que menos clientes precisam de estar conectados aos servidores ao mesmo tempo
e devido à redução na utilização da largura de banda no servidor.
Em resumo, propomos um modelo híbrido entre a orla (edge) e a nuvem (cloud) que fornece
menor latência entre utilizadores, disponibilidade durante desconexões do servidor e uma melhor
escalabilidade do servidor – ao mesmo tempo que é eciente, conável e seguro
Eventual Consistent Databases: State of the Art
One of the challenges of cloud programming is to achieve the right balance between the availability and consistency in a distributed database. Cloud computing environments, particularly cloud databases, are rapidly increasing in importance, acceptance and usage in major applications, which need the partition-tolerance and availability for scalability purposes, but sacrifice the consistency side (CAP theorem). In these environments, the data accessed by users is stored in a highly available storage system, thus the use of paradigms such as eventual consistency became more widespread. In this paper, we review the state-of-the-art database systems using eventual consistency from both industry and research. Based on this review, we discuss the advantages and disadvantages of eventual consistency, and identify the future research challenges on the databases using eventual consistency
Transactions and data management in NoSQL cloud databases
NoSQL databases have become the preferred option for storing and processing data in cloud computing as they are capable of providing high data availability, scalability and efficiency. But in order to achieve these attributes, NoSQL databases make certain trade-offs. First, NoSQL databases cannot guarantee strong consistency of data. They only guarantee a weaker consistency which is based on eventual consistency model. Second, NoSQL databases adopt a simple data model which makes it easy for data to be scaled across multiple nodes. Third, NoSQL databases do not support table joins and referential integrity which by implication, means they cannot implement complex queries. The combination of these factors implies that NoSQL databases cannot support transactions. Motivated by these crucial issues this thesis investigates into the transactions and data management in NoSQL databases.
It presents a novel approach that implements transactional support for NoSQL databases in order to ensure stronger data consistency and provide appropriate level of performance. The novelty lies in the design of a Multi-Key transaction model that guarantees the standard properties of transactions in order to ensure stronger consistency and integrity of data. The model is implemented in a novel loosely-coupled architecture that separates the implementation of transactional logic from the underlying data thus ensuring transparency and abstraction in cloud and NoSQL databases. The proposed approach is validated through the development of a prototype system using real MongoDB system. An extended version of the standard Yahoo! Cloud Services Benchmark (YCSB) has been used in order to test and evaluate the proposed approach. Various experiments have been conducted and sets of results have been generated. The results show that the proposed approach meets the research objectives. It maintains stronger consistency of cloud data as well as appropriate level of reliability and performance
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