to reduce synchronization overhead, we extended Hoard — a state of the art memory allocator with the ability to allocate thread-local storage. Experimental results using the tool show runtime saving of up to 44 % for a set of memory management benchmarks. To allow transparent usage of thread-local storage

Farsite is a secure, scalable file system that logically functions as a centralized file server but is physically distributed among a set of untrusted computers. Farsite provides file availability and reliability through randomized replicated storage; it ensures the secrecy of file contents

The design of a provably correct local storage subsystem that integrates local reliability and concurrency control is analysed. The description of the reliability and concurrency control strate-gies, as well as the correctness proof, is divided into successive layers of abstraction.. The relia

. It can be used to support a wide range of peer-to-peer applications like global data storage, global data sharing, and naming. An insert operation in Pastry stores an object at a user-defined number of diverse nodes within the Pastry network. A lookup operation reliably retrieves a copy of the requested

the Internet. It can be used to support a variety of peer-to-peer applications, including global data storage, data sharing, group communication and naming. Each node in the Pastry network has a unique identifier (nodeId). When presented with a message and a key, a Pastry node efficiently routes the message

in the system can store, cache, or control any block of data. Our approach uses this location independence, in combination with fast local area networks, to provide better performance and scalability than traditional file systems. Further, because any machine in the system can assume the responsibilities of a

Abstract We introduce a new problem inspired by energy pricing schemes in which a client is billed for peak usage. At each timeslot the system meets an energy demand through a combination of a new request, an unreliable amount of free source energy (e.g. solar or wind power), and previously received energy. The added piece of infrastructure is the battery, which can store surplus energy for future use, and is initially assumed to be perfectly efficient or lossless. In a feasible solution, each demand must be supplied on time, through a combination of newly requested energy, energy withdrawn from the battery, and free source. The goal is to minimize the maximum request. In the online version of this problem, the algorithm must determine each request without knowledge of future demands or free source availability, with the goal of maximizing the amount by which the peak is reduced. We give efficient optimal algorithms for the offline problem, with and without a bounded battery. We also show how to find the optimal offline battery size, given the requirement that the final battery level equals the initial battery level. Finally, we give efficient H n -competitive algorithms assuming the peak effective demand is revealed in advance, and provide matching lower bounds. Later, we consider the setting of lossy batteries, which lose to conversion inefficiency a constant fraction of any amount charged (e.g. 33%). We efficiently adapt our algorithms to this setting, maintaining optimality for offline and (we conjecture) maintaining competitiveness for online. We give factor-revealing LPs, which provide some quasi-empirical evidence for competitiveness. Finally, we evaluate these and other, heuristic algorithms on real and synthetic data.

present in real-world programs, and describe how to effectively capture and exploit it in order to perform load value prediction. Temporal and spatial locality are attributes of storage locations, and describe the future likelihood of references to those locations or their close neighbors. In a similar

of the critical needs of HPC applications is an efficient, scalable and persistent storage. Unfortunately, storage options proposed by cloud providers are not standardized and typically use a different access model. In this context, the local disks on the compute nodes can be used to save large data sets

are to be used: Overly restrictive rules might deny the potential of data sharing, while a lack of control could easily lead to Orwellian surveillance scenarios. This paper presents FragDB, a storage concept based on localized access control, where data storage and retrieval are bound to a specific place, rather