Building Regular Registers with Rational Malicious Servers and Anonymous Clients

The paper addresses the problem of emulating a regular register in a synchronous distributed system where clients invoking $$\mathsf{read}()$$ and $$\mathsf{write}()$$ operations are anonymous while server processes maintaining the state of the register may be compromised by rational adversaries (i.e., a server might behave as rational malicious Byzantine process). We first model our problem as a Bayesian game between a client and a rational malicious server where the equilibrium depends on the decisions of the malicious server (behave correctly and not be detected by clients vs returning a wrong register value to clients with the risk of being detected and then excluded by the computation). We prove such equilibrium exists and finally we design a protocol implementing the regular register that forces the rational malicious server to behave correctly

A Holistic Approach to Lowering Latency in Geo-distributed Web Applications

User perceived end-to-end latency of web applications have a huge impact on the revenue for many businesses. The end-to-end latency of web applications is impacted by: (i) User to Application server (front-end) latency which includes downloading and parsing web pages, retrieving further objects requested by javascript executions; and (ii) Application and storage server(back-end) latency which includes retrieving meta-data required for an initial rendering, and subsequent content based on user actions. Improving the user-perceived performance of web applications is challenging, given their complex operating environments involving user-facing web servers, content distribution network (CDN) servers, multi-tiered application servers, and storage servers. Further, the application and storage servers are often deployed on multi-tenant cloud platforms that show high performance variability. While many novel approaches like SPDY and geo-replicated datastores have been developed to improve their performance, many of these solutions are specific to certain layers, and may have different impact on user-perceived performance. The primary goal of this thesis is to address the above challenges in a holistic manner, focusing specifically on improving the end-to-end latency of geo-distributed multi-tiered web applications. This thesis makes the following contributions: (i) First, it reduces user-facing latency by helping CDNs identify and map objects that are more critical for page-load latency to the faster CDN cache layers. Through controlled experiments on real-world web pages, we show the potential of our approach to reduce hundreds of milliseconds in latency without affecting overall CDN miss rates. (ii) Next, it reduces back-end latency by optimally adapting the datastore replication policies (including number and location of replicas) to the heterogeneity in workloads. We show the benefits of our replication models using real-world traces of Twitter, Wikipedia and Gowalla on a 8 datacenter Cassandra cluster deployed on EC2. (iii) Finally, it makes multi-tier applications resilient to the inherent performance variability in the cloud through fine-grained request redirection. We highlight the benefits of our approach by deploying three real-world applications on commercial cloud platforms

Performance modelling of replication protocols

PhD ThesisThis thesis is concerned with the performance modelling of data replication protocols. Data replication is used to provide fault tolerance and to improve the performance of a distributed system. Replication not only needs extra storage but also has an extra cost associated with it when performing an update. It is not always clear which algorithm will give best performance in a given scenario, how many copies should be maintained or where these copies should be located to yield the best performance. The consistency requirements also change with application. One has to choose these parameters to maximize reliability and speed and minimize cost. A study showing the effect of change in different parameters on the performance of these protocols would be helpful in making these decisions. With the use of data replication techniques in wide-area systems where hundreds or even thousands of sites may be involved, it has become important to evaluate the performance of the schemes maintaining copies of data. This thesis evaluates the performance of replication protocols that provide differ- ent levels of data consistency ranging from strong to weak consistency. The protocols that try to integrate strong and weak consistency are also examined. Queueing theory techniques are used to evaluate the performance of these protocols. The performance measures of interest are the response times of read and write jobs. These times are evaluated both when replicas are reliable and when they are subject to random breakdowns and repairs.Commonwealth Scholarshi

Fault tolerant software technology for distributed computing system

Issued as Monthly reports [nos. 1-23], Interim technical report, Technical guide books [nos. 1-2], and Final report, Project no. G-36-64

Bringing Order into Things Decentralized and Scalable Ledgering for the Internet-of-Things

The Internet-of-Things (IoT) is simultaneously the largest and the fastest growing distributed system known to date. With the expectation of 50 billion of devices coming online by 2020, far surpassing the size of the human population, problems related to scale, trustability and security are anticipated. Current IoT architectures are inherently flawed as they are centralized on the cloud and explore fragile trust-based relationships over a plethora of loosely integrated devices, leading to IoT platforms being non-robust for every party involved and unable to scale properly in the near future. The need for a new architecture that addresses these concerns is urgent as the IoT is progressively more ubiquitous, pervasive and demanding regarding the integration of devices and processing of data increasingly susceptible to reliability and security issues. In this thesis, we propose a decentralized ledgering solution for the IoT, leveraging a recent concept: blockchains. Rather than replacing the cloud, our solution presents a scalable and fault-tolerant middleware for recording transactions between peers, under verifiable and decentralized trustability assumptions and authentication guarantees for IoT devices, cloud services and users. Following on the emergent trend in modern IoT architectures, we leverage smart hubs as blockchain gateways, aggregating, pre-processing and forwarding small amounts of data and transactions in proximity conditions, that will be verified and processed as transactions in the blockchain. The proposed middleware acts as a secure ledger and establishes private channels between peers, requiring transactions in the blockchain to be signed using threshold signature schemes and grouporiented verification properties. The approach improves the decentralization and robustness characteristics under Byzantine fault-tolerance settings, while preserving the blockchain distributed nature

The Case for Reconfiguration without Consensus: Comparing Algorithms for Atomic Storage

We compare different algorithms for reconfigurable atomic storage in the data-centric model. We present the first experimental evaluation of two recently proposed algorithms for reconfiguration without consensus and compare them to established algorithms for reconfiguration both with and without consensus. Our evaluation reveals that the new algorithms offer a significant improvement in terms of latency and overhead for reconfiguration without consensus. Our evaluation also shows that reconfiguration without consensus, can obtain similar results to that of consensus-based reconfiguration, which relies on a stable leader. Moreover, the new algorithms also substantially reduces the overhead compared to consensus-based reconfiguration without a leader. While our analysis confirms our intuition that batching reconfiguration requests serves to reduce the overhead of reconfigurations, our evaluation also shows that it is equally important to separate reconfigurations from read and write operations. Specifically, we found that using read and write operations to assist in completing concurrent reconfigurations is in fact detrimental to the reconfiguration performance