Non-Uniform Replication

Replication is a key technique in the design of efficient and reliable distributed systems. As information grows, it becomes difficult or even impossible to store all information at every replica. A common approach to deal with this problem is to rely on partial replication, where each replica maintains only a part of the total system information. As a consequence, a remote replica might need to be contacted for computing the reply to some given query, which leads to high latency costs particularly in geo-replicated settings. In this work, we introduce the concept of non- uniform replication, where each replica stores only part of the information, but where all replicas store enough information to answer every query. We apply this concept to eventual consistency and conflict-free replicated data types. We show that this model can address useful problems and present two data types that solve such problems. Our evaluation shows that non-uniform replication is more efficient than traditional replication, using less storage space and network bandwidth

Non-uniform replication for replicated objects

A large number of web applications/services are supported by applications running in cloud computing infrastructures. Many of these application store their data in georeplicated key-value stores, that maintain replicas of the data in several data centers located across the globe. Data management in these settings is challenging, with solutions needing to balance availability and consistency. Solutions that provide high-availability, by allowing operations to execute locally in a single data center, have to cope with a weaker consistency model. In such cases, replicas may be updated concurrently and a mechanism to reconcile divergent replicas is needed. Using the semantics of data types (and operations) helps in providing a solution that meets the requirements of applications, as shown by conflict-free replicated data types. As information grows it becomes difficult or even impossible to store all information at every replica. A common approach to deal with this problem is to rely on partial replication, where each replica maintains only part of the total system information. As a consequence, each partial replica can only reply to a subset of the possible queries. In this thesis, we introduce the concept of non-uniform replication where each replica stores only part of the information, but where all replicas store enough information to answer every query. We apply this concept to eventual consistency and conflict-free replicated data types and propose a set of useful data type designs where replicas synchronize by exchanging operations. Furthermore, we implement support for non-uniform replication in AntidoteDB, a geo-distributed key-value store, and evaluate the space efficiency, bandwidth overhead, and scalability of the solution

Inference of plasmid copy number mean and noise from single cell gene expression data

Plasmids are extra-chromosomal DNA molecules which code for their own replication. We previously reported a setup using genes coding for fluorescent proteins of two colors that allowed us, using a simple model, to extract the plasmid copy number noise in a monoclonal population of bacteria [J. Wong Ng et al., Phys. Rev. E, 81, 011909 (2010)]. Here we present a detailed calculation relating this noise to the measured levels of fluorescence, taking into account all sources of fluorescence fluctuations: the fluctuation of gene expression as in the simple model, but also the growth and division of bacteria, the non-uniform distribution of their ages, the random partition of proteins at divisions and the replication and partition of plasmids and chromosome. We show how using the chromosome as a reference helps extracting the plasmid copy number noise in a self-consistent manner.Comment: 9 pages, 3 figures, 2 table

Multi-disk subsystem organizations for very large databases

This thesis investigates efficient mappings of very large databases with non-uniform access to its data. to a. multi-disk subsystem. Two algorithms are developed to distribute the database across multiple disks, possibly with replication, in order to minimize latency and maximize throughput. These algorithms are compared with respect to the amount of replication overhead incurred to achieve desired throughput. A simulator is developed to simulate these two mapping algorithms and investigate the efficiency of these two mappings

Prion Replication in the Hematopoietic Compartment Is Not Required for Neuroinvasion in Scrapie Mouse Model

Fatal neurodegenerative prion diseases are caused by the transmissible PrPSc prion agent whose initial replication after peripheral inoculation takes place in follicular dendritic cells present in germinal centers of lymphoid organs. However, prion replication also occurs in lymphoid cells. To assess the role of the hematopoietic compartment in neuroinvasion and prion replication, we generated chimeric mice, on a uniform congenic C57/BL6J background, by bone marrow replacement with hematopoietic cells expressing different levels of PrP protein. Nine different types of chimeric mice were inoculated intraperitoneally either with the lymphotropic Rocky Mountain Laboratory (RML) strain or the non lymphotropic ME-7 scrapie strain, at different doses. Here, we clearly demonstrate that overexpression of PrP by the hematopoietic system, or the lack of PrP expression by the bone marrow derived cells, does not change the incubation time period of the disease, even when the mice are infected at limiting doses. We conclude that the hematopoietic compartment is more or less permissive to prion replication, both for RML and ME-7, but does not play a role in neuroinvasion

Replacing P-values with frequentist posterior probabilities of replication:When possible parameter values must have uniform marginal prior probabilities

Possible parameter values in a random sampling model are shown by definition to have uniform base-rate prior probabilities. This allows a frequentist posterior probability distribution to be calculated for such possible parameter values conditional solely on actual study observations. If the likelihood probability distribution of a random selection is modelled with a symmetrical continuous function then the frequentist posterior probability of something equal to or more extreme than the null hypothesis will be equal to the P-value; otherwise the P value would be an approximation. An idealistic probability of replication based on an assumption of perfect study methodological reproducibility can be used as the upper bound of a realistic probability of replication that may be affected by various confounding factors. Bayesian distributions can be combined with these frequentist distributions. The idealistic frequentist posterior probability of replication may be easier than the P-value for non-statisticians to understand and to interpret.Comment: 14 pages, 4 figure