Nearly tight lower and upper bounds on the capacity of generalized Ising channels are presented. For the case where feedback is allowed, a closed-form expression for the capacity is found for channel error probability p ∈ [0, p0], where p0 ≈ 0.398324. A near-capacity-achieving family of encoders is presented for the values p ∈ [0, p0]. Two lower bounds on that capacity for larger values of p are presented, one of which is tight on the interval [p0, 0.5].

Nearly tight lower and upper bounds on the capacity of generalized Ising channels are presented. For the case where feedback is allowed, a closed-form expression for the capacity is found for channel error probability p ∈ [0, p0], where p0≈ 0.398324. Two lower bounds on that capacity for larger values of p are presented.

The configuration of a distributed storage system typically includes, among other parameters, the set of servers and their roles in the replication protocol. Although mechanisms for changing the configuration at runtime exist, it is usually left to system administrators to manually determine the "best" configuration and periodically reconfigure the system, often by trial and error. This paper describes a new workload-driven optimization framework that dynamically determines the optimal configuration at run-time. We focus on optimizing leader and quorum based replication schemes and divide the framework into three optimization tiers, dynamically optimizing different configuration aspects: 1) leader placement, 2) roles of different servers in the replication protocol, and 3) replica locations. We showcase our optimization framework by applying it to a large-scale distributed storage system used internally in Google and demonstrate that most client applications significantly benefit from using our framework, reducing average operation latency by up to 94%.

Improved lower and upper bounds on the size and the rate of grain-correcting codes are presented. The lower bound is Gilbert-Varshamov-like combined with a construction by Gabrys et al., and it improves on the previously best known lower bounds on the asymptotic rate of ⌈τn⌉-grain-correcting codes of length n on the interval [0, 0.0668]. One of the two newly presented upper bounds improves on the best known upper bounds on the asymptotic rate of ⌈τn⌉-grain-correcting codes of length n on the interval τ ∈ (0, 1/8] and meets the lower bound of 1/2 for τ ≥ 1/8. Moreover, in a nonasymptotic regime, both upper bounds improve on the previously best known results on the largest size of t-grain-correcting codes of length n, for certain values of n and t. Constructions of 1-grain-correcting codes based on a partitioning technique are presented for lengths up to 18. Finally, a lower bound of 1/2 log2n on the minimum redundancy of ∞-grain-detecting codes of length n is presented.

New upper bounds on the size and the rate of grain-correcting codes are presented. The new upper bound on the size of t-grain-correcting codes of length n improves on the best known upper bounds for certain values of n and t, whereas the new upper bound on the asymptotic rate of [τn]-grain-correcting codes of length n improves on the previously known upper bounds on the interval τ ∈ (0, ⅛]. A lower bound of 1/2 log2n on the minimum redundancy of ∞-grain-detecting codes of length n is presented.

NoSQL databases were initially designed to provide extreme scalability and availability for Internet applications, often at the expense of data consistency. The recent generation of Web-scale databases fills this gap, by offering transaction support. However, transaction processing implies a significant performance overhead on online applications that only require atomic reads and writes. The state-of-the-art solutions are either static separation of the data accessed by transaction-enabled and native applications, or complete "transactification" of the latter, which are both inadequate.

Bounds on the rates of grain-correcting codes are presented. The lower bounds are Gilbert-Varshamov-like ones, whereas the upper bounds improve on the previously known result by Mazumdar Constructions of t-grain-correcting codes of length n for certain values of n and t are discussed. Finally, an infinite family of codes of rate approaching 1 that can detect an arbitrary number of grain errors is shown to exist.

Many scientists perform extensive computations by executing large bags of similar tasks (BoTs) in mixtures of computational environments, such as grids and clouds. Although the reliability and cost may vary considerably across these environments, no tool exists to assist scientists in the selection of environments that can both fulfill deadlines and fit budgets. To address this situation, we introduce the Expert BoT scheduling framework. Our framework systematically selects from a large search space the Pareto-efficient scheduling strategies, that is, the strategies that deliver the best results for both make span and cost. Expert chooses from them the best strategy according to a general, user-specified utility function. Through simulations and experiments in real production environments, we demonstrate that Expert can substantially reduce both make span and cost in comparison to common scheduling strategies. For bioinformatics BoTs executed in a real mixed grid + cloud environment, we show how the scheduling strategy selected by Expert reduces both make span and cost by 30%-70%, in comparison to commonly-used scheduling strategies.

Consider a channel with an input alphabet that is finite but not necessarily binary. A method for approximating such a channel having a large output alphabet size by a degraded version of it having a smaller output alphabet size is presented and analyzed. The approximation method is used to construct polar codes for both single-user and multiple-access channels with prime input alphabet sizes.

Bounds on the rate of grain-correcting codes are presented. The lower bounds are Gilbert-Varshamov-like ones, whereas the upper bounds improve on the previously known result by Mazumdar et al.. Constructions of t-grain-correcting codes of length n for certain values of n and t are discussed.

A new fixed-rate tiling-based coding scheme is presented for two-dimensional (2-D) constraints. The new scheme is shown to improve on the best known rates of formerly published fixed-rate encoders for certain constraints, such as the “no isolated bits” constraint and several 2-D runlength limited (RLL) constraints. Methods of efficient implementation of the suggested scheme are discussed.

A new variable-rate coding technique is presented for two-dimensional (2-D) constraints. For certain constraints, such as the(0, 2)-runlength-limited (RLL) and(3,¿)-RLL constraints, the technique is shown to improve on previously published lower bounds on the capacity of the constraint.

We present a holistic approach for efficient execution of bags-of-tasks (BOTs) on multiple grids, clusters, and volunteer computing grids virtualized as a single computing platform. The challenge is twofold: to assemble this compound environment and to employ it for execution of a mixture of throughput- and performance-oriented BOTs, with a dozen to millions of tasks each. Our generic mechanism allows per BOT specification of dynamic arbitrary scheduling and replication policies as a function of the system state, BOT execution state, and BOT priority.

A new variable-rate coding technique is presented for two-dimensional constraints. For certain constraints, such as the (0, 2)-RLL, (2, infin)-RLL, and the "no isolated bits" (n.i.b.) constraints, the technique is shown to improve on previously- published lower bounds on the capacity of the constraint.

Grids are becoming a mission-critical component in research and industry. The services they provide are thus required to be highly available, contributing to the vision of the grid as a dependable virtual computer of infinite power. However, building highly available services in grid is particularly difficult due to the unique characteristics of the grid environment. We believe that high availability functionality should itself be provided as a service, which can be used by transparently decorating, but not changing, the original services, thus making them highly available. In this work we highlight the major challenges and describe our initial experience in building such a generic high availability service in the context of the Condor system