THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

Data Mining Practical Machine Learning Tools and Techniques

Data replication is a key technology in distributed systems that enables higher availability and performance. This article surveys optimistic replication algorithms. They allow replica contents to diverge in the short term to support concurrent work practices and tolerate failures in low-quality communication links. The importance of such techniques is increasing as collaboration through wide-area and mobile networks becomes popular.Optimistic replication deploys algorithms not seen in traditional “pessimistic” systems. Instead of synchronous replica coordination, an optimistic algorithm propagates changes in the background, discovers conflicts after they happen, and reaches agreement on the final contents incrementally.We explore the solution space for optimistic replication algorithms. This article identifies key challenges facing optimistic replication systems---ordering operations, detecting and resolving conflicts, propagating changes efficiently, and bounding replica divergence---and provides a comprehensive survey of techniques developed for addressing these challenges.

/pdf/optimistic-replication-olzqfvhf6n.pdf

Optimistic replication

In this report (written in Greek) are presented the basics of the hypertext transfer protocol.

Hypertext Transfer Protocol (HTTP)

The security of machine learning in an adversarial setting: A survey

In a Distributed System with N sites, the precise detection of causal relationships between events can only be done with vector clocks of size N. This gives rise to scalability and efficiency problems for logical clocks that can be used to order events accurately. In this paper we propose a class of logical clocks called plausible clocks that can be implemented with a number of components not affected by the size of the system and yet they provide good ordering accuracy. We develop rules to combine plausible clocks to produce more accurate clocks. Several examples of plausible clocks and their combination are presented. Using a simulation model, we evaluate the performance of these clocks. We also present examples of applications where constant size clocks can be used.

Plausible clocks: constant size logical clocks for distributed systems

Ordering and time are two different aspects of consistency of shared objects in a distributed system. One avoids conflicts between operations, the other addresses how quickly the effects of an operation are perceived by the rest of the system. Consistency models such as sequential consistency and causal consistency do not consider the particular time at which an operation is executed to establish a valid order among all the operations of a computation. Timed consistency models require that if a write operation is executed at time t, it must be visible to all nodes by time t +Δ. Timed consistency generalizes several existing consistency criteria and it is well suited for interactive and collaborative applications, where the action of one user must be seen by others in a timely fashion.

Timed consistency for shared distributed objects

Techniques such as replication and caching of objects that implement distributed services lead to consistency problems that must be addressed. We explore new consistency protocols based on the notion of object value lifetimes. By keeping track of the lifetimes of the values stored in shared objects (i.e., the time interval that goes from the writing of a value until the latest time when this value is known to be valid), it is possible to check the mutual consistency of a set of related objects cached at a site. Initially, this technique is presented assuming the presence of physical clocks. Later, these clocks are replaced by vector clocks and then by plausible clocks. Lifetimes based on such clocks result in weaker consistency but do provide more efficient implementations.

Lifetime Based Consistency Protocols for Distributed Objects

Given a distributed system with several shared objects and many processes concurrently updating and reading them, it is convenient that the system achieves convergence on the value of these objects. Such property can be guaranteed depending on the consistency model being employed. Causal Consistency is a weak consistency model that is easy and cheap to implement. However, due to the lack of real-time considerations, this model cannot oer convergence. A solution for overcoming that problem is to include time aspects within the framework of the model. This is the aim of Timed Causal Consistency.

/pdf/convergence-through-a-weak-consistency-model-timed-causal-17wuvrtetz.pdf

Convergence Through a Weak Consistency Model: Timed Causal Consistency

Many application domains have already demonstrated that they can benefit greatly if efficient access can be provided to shared information across widely distributed users. We use the generic term object to describe units of shared information which could include files, web pages or language defined objects. Future applications will require object sharing modes richer than simple browsing. For example, a collaboration system that allows users distributed world-wide (e.g., managers of a multinational company) to interact with each other must manipulate objects that are both read and updated at multiple locations.Several assumptions, which are natural in the context of large scale systems, can be made about scalable object sharing systems. First, such systems will consist of many server nodes that will act as the storehouses for shared objects. These servers will enable access to objects to a much larger number of client nodes. To avoid high latencies and communication costs, servers will store replicated copies of objects frequently accessed by clients in their vicinity. Furthermore, clients will cache objects to reduce access latency and frequency of communication with servers. Both replication at servers and caching at clients result in multiple copies of an object which introduces the problem of maintaining consistency among the copies.Many levels of consistency are possible and the choice of a particular consistency level has implications on the programming as well as performance of a distributed application. Although consistency requirements across copies of a single object are easily seen, such requirements can arise between copies of different but related objects. For example, assume that user 1 writes a memo object ol to produce version o1,1 and later generates its updated version ol,2. User 2 reads ol,2 and writes memo object o2 in response. If user 3 reads memo o2 and wants to read o1 to understand it, it must be provided ol,2 and not o1,1 which could have been cached by it due to a previous read. Thus, consistency requirements exist across copies of ol and o2 even when user 3 accesses them in a read-only mode.We first identify some requirements that must be met by scalable object sharing schemes. We present arguments to demonstrate that existing techniques cannot easily be adapted to meet these requirements. This is followed by an outline of our approach.

Scalable information sharing in large scale distributed systems

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