Attributes of fault-tolerant distributed file systems

Fault tolerance in distributed file systems will be investigated by analyzing recovery techniques and concepts implemented within the following models of distributed systems: pool-processor model and user-server model. The research presented provides an overview of fault tolerance characteristics and mechanisms within current implementations and summarizes future directions for fault tolerant distributed file systems

Building a generalized distributed system model

The key elements in the second year (1991-92) of our project are: (1) implementation of the distributed system prototype; (2) successful passing of the candidacy examination and a PhD proposal acceptance by the funded student; (3) design of storage efficient schemes for replicated distributed systems; and (4) modeling of gracefully degrading reliable computing systems. In the third year of the project (1992-93), we propose to: (1) complete the testing of the prototype; (2) enhance the functionality of the modules by enabling the experimentation with more complex protocols; (3) use the prototype to verify the theoretically predicted performance of locking protocols, etc.; and (4) work on issues related to real-time distributed systems. This should result in efficient protocols for these systems

Space station data system analysis/architecture study. Task 2: Options development, DR-5. Volume 2: Design options

The primary objective of Task 2 is the development of an information base that will support the conduct of trade studies and provide sufficient data to make key design/programmatic decisions. This includes: (1) the establishment of option categories that are most likely to influence Space Station Data System (SSDS) definition; (2) the identification of preferred options in each category; and (3) the characterization of these options with respect to performance attributes, constraints, cost and risk. This volume contains the options development for the design category. This category comprises alternative structures, configurations and techniques that can be used to develop designs that are responsive to the SSDS requirements. The specific areas discussed are software, including data base management and distributed operating systems; system architecture, including fault tolerance and system growth/automation/autonomy and system interfaces; time management; and system security/privacy. Also discussed are space communications and local area networking

Partial Computation in Real-Time Database Systems: A Research Plan

State-of-the-art database management systems are inappropriate for real-time applications due to their lack of speed and predictability of response. To combat these problems, the scheduler needs to be able to take advantage of the vast quantity of semantic and timing information that is typically available in such systems. Furthermore, to improve predictability of response, the system should be capable of providing a partial, but correct, response in a timely manner. We therefore propose to develop a semantics for real-time database systems that incorporates temporal knowledge of data-objects, their validity, and computation using their values. This temporal knowledge should include not just historical information but future knowledge of when to expect values to appear. This semantics will be used to develop a notion of approximate or partial computation, and to develop schedulers appropriate for real-time transactions

Performance assessment of real-time data management on wireless sensor networks

Technological advances in recent years have allowed the maturity of Wireless Sensor Networks (WSNs), which aim at performing environmental monitoring and data collection. This sort of network is composed of hundreds, thousands or probably even millions of tiny smart computers known as wireless sensor nodes, which may be battery powered, equipped with sensors, a radio transceiver, a Central Processing Unit (CPU) and some memory. However due to the small size and the requirements of low-cost nodes, these sensor node resources such as processing power, storage and especially energy are very limited. Once the sensors perform their measurements from the environment, the problem of data storing and querying arises. In fact, the sensors have restricted storage capacity and the on-going interaction between sensors and environment results huge amounts of data. Techniques for data storage and query in WSN can be based on either external storage or local storage. The external storage, called warehousing approach, is a centralized system on which the data gathered by the sensors are periodically sent to a central database server where user queries are processed. The local storage, in the other hand called distributed approach, exploits the capabilities of sensors calculation and the sensors act as local databases. The data is stored in a central database server and in the devices themselves, enabling one to query both. The WSNs are used in a wide variety of applications, which may perform certain operations on collected sensor data. However, for certain applications, such as real-time applications, the sensor data must closely reflect the current state of the targeted environment. However, the environment changes constantly and the data is collected in discreet moments of time. As such, the collected data has a temporal validity, and as time advances, it becomes less accurate, until it does not reflect the state of the environment any longer. Thus, these applications must query and analyze the data in a bounded time in order to make decisions and to react efficiently, such as industrial automation, aviation, sensors network, and so on. In this context, the design of efficient real-time data management solutions is necessary to deal with both time constraints and energy consumption. This thesis studies the real-time data management techniques for WSNs. It particularly it focuses on the study of the challenges in handling real-time data storage and query for WSNs and on the efficient real-time data management solutions for WSNs. First, the main specifications of real-time data management are identified and the available real-time data management solutions for WSNs in the literature are presented. Secondly, in order to provide an energy-efficient real-time data management solution, the techniques used to manage data and queries in WSNs based on the distributed paradigm are deeply studied. In fact, many research works argue that the distributed approach is the most energy-efficient way of managing data and queries in WSNs, instead of performing the warehousing. In addition, this approach can provide quasi real-time query processing because the most current data will be retrieved from the network. Thirdly, based on these two studies and considering the complexity of developing, testing, and debugging this kind of complex system, a model for a simulation framework of the real-time databases management on WSN that uses a distributed approach and its implementation are proposed. This will help to explore various solutions of real-time database techniques on WSNs before deployment for economizing money and time. Moreover, one may improve the proposed model by adding the simulation of protocols or place part of this simulator on another available simulator. For validating the model, a case study considering real-time constraints as well as energy constraints is discussed. Fourth, a new architecture that combines statistical modeling techniques with the distributed approach and a query processing algorithm to optimize the real-time user query processing are proposed. This combination allows performing a query processing algorithm based on admission control that uses the error tolerance and the probabilistic confidence interval as admission parameters. The experiments based on real world data sets as well as synthetic data sets demonstrate that the proposed solution optimizes the real-time query processing to save more energy while meeting low latency.Fundação para a Ciência e Tecnologi

Even bigger data: preparing for the LHC/ATLAS upgrade

The Large Hadron Collider’s (LHC) experiments’ data volume is expected to grow one order of magnitude following the machine operation conditions upgrade in 2013-2014. The challenge to the scientific results of our team is: i) how to deal with a 10-fold increase in the data volume that must be processed for each analysis, while ii) supporting the increase in the complexity of the analysis applications, iii) reduce the turnover time of the results and iv) these issues must be addressed with limited additional resources given Europe’s present political and economic panorama. In this paper we take a position in this challenge and on the research directions to be explored. A systematic analysis of the analysis applications is presented to study optimization opportunities of the application and of the underlying running system. Than a new local system architecture is proposed to increase resource usage efficiency and to provide a gradual upgrade route from current systems.FCT grants SFRH/BPD/63495/2009; SFRH/BPD/47928/2008, by the UT Austin | Portugal FCT grant SFRH/BD/47840/2008; FCT project PEst-OE/EEI/UI0752/2011

Study of fault-tolerant software technology

Presented is an overview of the current state of the art of fault-tolerant software and an analysis of quantitative techniques and models developed to assess its impact. It examines research efforts as well as experience gained from commercial application of these techniques. The paper also addresses the computer architecture and design implications on hardware, operating systems and programming languages (including Ada) of using fault-tolerant software in real-time aerospace applications. It concludes that fault-tolerant software has progressed beyond the pure research state. The paper also finds that, although not perfectly matched, newer architectural and language capabilities provide many of the notations and functions needed to effectively and efficiently implement software fault-tolerance