Fault-tolerant and transactional mobile agent execution

Mobile agents constitute a computing paradigm of a more general nature than the widely used client/server computing paradigm. A mobile agent is essentially a computer program that acts autonomously on behalf of a user and travels through a network of heterogeneous machines. However, the greater flexibility of the mobile agent paradigm compared to the client/server computing paradigm comes at additional costs. These costs include, among others, the additional complexity of developing and managing mobile agent-based applications. This additional complexity comprises such issues as reliability. Before mobile agent technology can appear at the core of tomorrow's business applications, reliability mechanisms for mobile agents must be established. In this context, fault tolerance and transaction support are mechanisms of considerable importance. Various approaches to fault tolerance and transaction support exist. They have different strengths and weaknesses, and address different environments. Because of this variety, it is often difficult for the application programmer to choose the approach best suited to an application. This thesis introduces a classification of current approaches to fault-tolerant and transactional mobile agent execution. The classification, which focuses on algorithmic aspects, aims at structuring the field of fault-tolerant and transactional mobile agent execution and facilitates an understanding of the properties and weaknesses of particular approaches. In a distributed system, any software or hardware component may be subject to failures. A single failing component (e.g., agent or machine) may prevent the agent from proceeding with its execution. Worse yet, the current state of the agent and even its code may be lost. We say that the agent execution is blocked. For the agent owner, i.e., the person or application that has configured the agent, the agent does not return. To achieve fault-tolerance, the agent owner can try to detect the failure of the agent, and upon such an event launch a new agent. However, this requires the ability to correctly detect the crash of the agent, i.e., to distinguish between a failed agent and an agent that is delayed by slow processors or slow communication links. Unfortunately, this cannot be achieved in systems such as the Internet. An agent owner who tries to detect the failure of the agent thus cannot prevent the case in which the agent is mistakenly assumed to have crashed. In this case, launching a new agent leads to multiple executions of the agent, i.e., to the violation of the desired exactly-once property of agent execution. Although this may be acceptable for certain applications (e.g., applications whose operations do not have side-effects), others clearly forbid it. In this context, launching a new agent is a form of replication. In general, replication prevents blocking, but may lead to multiple executions of the agent, i.e., to a violation of the exactly-once execution property. This thesis presents an approach that ensures the exactly-once execution property using a simple principle: the mobile agent execution is modeled as a sequence of agreement problems. This model leads to an approach based on two well-known building blocks: consensus and reliable broadcast. We validate this approach with the implementation of FATOMAS, a Java-based FAult-TOlerant Mobile Agent System, and measure its overhead. Transactional mobile agents execute the mobile agent as a transaction. Assume, for instance, an agent whose task is to buy an airline ticket, book a hotel room, and rent a car at the flight destination. The agent owner naturally wants all three operations to succeed or none at all. Clearly, the rental car at the destination is of no use if no flight to the destination is available. On the other hand, the airline ticket may be useless if no rental car is available. The mobile agent's operations thus need to execute atomically, i.e., either all of them or none at all. Execution atomicity also needs to be ensured in the event of failures of hardware or software components. The approach presented in this thesis is non-blocking. A non-blocking transactional mobile agent execution has the important advantage that it can make progress despite failures. In a blocking transactional mobile agent execution, by contrast, progress is only possible when the failed component has recovered. Until then, the acquired locks generally cannot be freed. As no other transactional mobile agents can acquire the lock, overall system throughput is dramatically reduced. The present approach reuses the work on fault-tolerant mobile agent execution to prevent blocking. We have implemented the proposed approach and present the evaluation results

Partial replication in distributed software transactional memory

Dissertação para obtenção do Grau de Mestre em Engenharia InformáticaDistributed software transactional memory (DSTM) is emerging as an interesting alternative for distributed concurrency control. Usually, DSTM systems resort to data distribution and full replication techniques in order to provide scalability and fault tolerance. Nevertheless, distribution does not provide support for fault tolerance and full replication limits the system’s total storage capacity. In this context, partial data replication rises as an intermediate solution that combines the best of the previous two trying to mitigate their disadvantages. This strategy has been explored by the distributed databases research field, but has been little addressed in the context of transactional memory and, to the best of our knowledge, it has never before been incorporated into a DSTM system for a general-purpose programming language. Thus, we defend the claim that it is possible to combine both full and partial data replication in such systems. Accordingly, we developed a prototype of a DSTM system combining full and partial data replication for Java programs. We built from an existent DSTM framework and extended it with support for partial data replication. With the proposed framework, we implemented a partially replicated DSTM. We evaluated the proposed system using known benchmarks, and the evaluation showcases the existence of scenarios where partial data replication can be advantageous, e.g., in scenarios with small amounts of transactions modifying fully replicated data. The results of this thesis show that we were able to sustain our claim by implementing a prototype that effectively combines full and partial data replication in a DSTM system. The modularity of the presented framework allows the easy implementation of its various components, and it provides a non-intrusive interface to applications.Fundação para a Ciência e Tecnologia - (FCT/MCTES) in the scope of the research project PTDC/EIA-EIA/113613/2009 (Synergy-VM

Data management in cloud environments: NoSQL and NewSQL data stores

: Advances in Web technology and the proliferation of mobile devices and sensors connected to the Internet have resulted in immense processing and storage requirements. Cloud computing has emerged as a paradigm that promises to meet these requirements. This work focuses on the storage aspect of cloud computing, specifically on data management in cloud environments. Traditional relational databases were designed in a different hardware and software era and are facing challenges in meeting the performance and scale requirements of Big Data. NoSQL and NewSQL data stores present themselves as alternatives that can handle huge volume of data. Because of the large number and diversity of existing NoSQL and NewSQL solutions, it is difficult to comprehend the domain and even more challenging to choose an appropriate solution for a specific task. Therefore, this paper reviews NoSQL and NewSQL solutions with the objective of: (1) providing a perspective in the field, (2) providing guidance to practitioners and researchers to choose the appropriate data store, and (3) identifying challenges and opportunities in the field. Specifically, the most prominent solutions are compared focusing on data models, querying, scaling, and security related capabilities. Features driving the ability to scale read requests and write requests, or scaling data storage are investigated, in particular partitioning, replication, consistency, and concurrency control. Furthermore, use cases and scenarios in which NoSQL and NewSQL data stores have been used are discussed and the suitability of various solutions for different sets of applications is examined. Consequently, this study has identified challenges in the field, including the immense diversity and inconsistency of terminologies, limited documentation, sparse comparison and benchmarking criteria, and nonexistence of standardized query languages

A Multiagent System for the Reliable Execution of Automatically Composed Ad-hoc Processes

This article presents an architecture to automatically create ad-hoc processes for complex value-added services and to execute them in a reliable way. The uniqueness of ad-hoc processes is to support users not only in standardized situations like traditional workflows do, but also in unique non-recurring situations. Based on user requirements, a service composition engine generates such ad-hoc processes, which integrate individual services in order to provide the desired functionality. Our infrastructure executes ad-hoc processes by transactional agents in a peer-to-peer style. The process execution is thereby performed under transactional guarantees. Moreover, the service composition engine is used to re-plan in the case of execution failure

Methods to Improve Applicability and Efficiency of Distributed Data-Centric Compute Frameworks

The success of modern applications depends on the insights they collect from their data repositories. Data repositories for such applications currently exceed exabytes and are rapidly increasing in size, as they collect data from varied sources - web applications, mobile phones, sensors and other connected devices. Distributed storage and data-centric compute frameworks have been invented to store and analyze these large datasets. This dissertation focuses on extending the applicability and improving the efficiency of distributed data-centric compute frameworks

Application Aware for Byzantine Fault Tolerance

Driven by the need for higher reliability of many distributed systems, various replication-based fault tolerance technologies have been widely studied. A prominent technology is Byzantine fault tolerance (BFT). BFT can help achieve high availability and trustworthiness by ensuring replica consistency despite the presence of hardware failures and malicious faults on a small portion of the replicas. However, most state-of-the-art BFT algorithms are designed for generic stateful applications that require the total ordering of all incoming requests and the sequential execution of such requests. In this dissertation research, we recognize that a straightforward application of existing BFT algorithms is often inappropriate for many practical systems: (1) not all incoming requests must be executed sequentially according to some total order and doing so would incur unnecessary (and often prohibitively high) runtime overhead and (2) a sequential execution of all incoming requests might violate the application semantics and might result in deadlocks for some applications. In the past four and half years of my dissertation research, I have focused on designing lightweight BFT solutions for a number of Web services applications (including a shopping cart application, an event stream processing application, Web service business activities (WS-BA), and Web service atomic transactions (WS-AT)) by exploiting application semantics. The main research challenge is to identify how to minimize the use of Byzantine agreement steps and enable concurrent execution of requests that are commutable or unrelated. We have shown that the runtime overhead can be significantly reduced by adopting our lightweight solutions. One limitation for our solutions is that it requires intimate knowledge on the application design and implementation, which may be expensive and error-prone to design such BFT solutions on complex applications. Recognizing this limitation, we investigated the use of Conflict-free Replicated Data Types (CRDTs) to

Application Aware for Byzantine Fault Tolerance

Driven by the need for higher reliability of many distributed systems, various replication-based fault tolerance technologies have been widely studied. A prominent technology is Byzantine fault tolerance (BFT). BFT can help achieve high availability and trustworthiness by ensuring replica consistency despite the presence of hardware failures and malicious faults on a small portion of the replicas. However, most state-of-the-art BFT algorithms are designed for generic stateful applications that require the total ordering of all incoming requests and the sequential execution of such requests. In this dissertation research, we recognize that a straightforward application of existing BFT algorithms is often inappropriate for many practical systems: (1) not all incoming requests must be executed sequentially according to some total order and doing so would incur unnecessary (and often prohibitively high) runtime overhead and (2) a sequential execution of all incoming requests might violate the application semantics and might result in deadlocks for some applications. In the past four and half years of my dissertation research, I have focused on designing lightweight BFT solutions for a number of Web services applications (including a shopping cart application, an event stream processing application, Web service business activities (WS-BA), and Web service atomic transactions (WS-AT)) by exploiting application semantics. The main research challenge is to identify how to minimize the use of Byzantine agreement steps and enable concurrent execution of requests that are commutable or unrelated. We have shown that the runtime overhead can be significantly reduced by adopting our lightweight solutions. One limitation for our solutions is that it requires intimate knowledge on the application design and implementation, which may be expensive and error-prone to design such BFT solutions on complex applications. Recognizing this limitation, we investigated the use of Conflict-free Replicated Data Types (CRDTs) to

Byzantine Fault Tolerance for Distributed Systems

The growing reliance on online services imposes a high dependability requirement on the computer systems that provide these services. Byzantine fault tolerance (BFT) is a promising technology to solidify such systems for the much needed high dependability. BFT employs redundant copies of the servers and ensures that a replicated system continues providing correct services despite the attacks on a small portion of the system. In this dissertation research, I developed novel algorithms and mechanisms to control various types of application nondeterminism and to ensure the long-term reliability of BFT systems via a migration-based proactive recovery scheme. I also investigated a new approach to significantly improve the overall system throughput by enabling concurrent processing using Software Transactional Memory (STM). Controlling application nondeterminism is essential to achieve strong replica consistency because the BFT technology is based on state-machine replication, which requires deterministic operation of each replica. Proactive recovery is necessary to ensure that the fundamental assumption of using the BFT technology is not violated over long term, i.e., less than one-third of replicas remain correct. Without proactive recovery, more and more replicas will be compromised under continuously attacks, which would render BFT ineffective. STM based concurrent processing maximized the system throughput by utilizing the power of multi-core CPUs while preserving strong replication consistenc

Byzantine Fault Tolerance for Distributed Systems

The growing reliance on online services imposes a high dependability requirement on the computer systems that provide these services. Byzantine fault tolerance (BFT) is a promising technology to solidify such systems for the much needed high dependability. BFT employs redundant copies of the servers and ensures that a replicated system continues providing correct services despite the attacks on a small portion of the system. In this dissertation research, I developed novel algorithms and mechanisms to control various types of application nondeterminism and to ensure the long-term reliability of BFT systems via a migration-based proactive recovery scheme. I also investigated a new approach to significantly improve the overall system throughput by enabling concurrent processing using Software Transactional Memory (STM). Controlling application nondeterminism is essential to achieve strong replica consistency because the BFT technology is based on state-machine replication, which requires deterministic operation of each replica. Proactive recovery is necessary to ensure that the fundamental assumption of using the BFT technology is not violated over long term, i.e., less than one-third of replicas remain correct. Without proactive recovery, more and more replicas will be compromised under continuously attacks, which would render BFT ineffective. STM based concurrent processing maximized the system throughput by utilizing the power of multi-core CPUs while preserving strong replication consistenc