Enabling distributed key-value stores with low latency-impact snapshot support

Current distributed key-value stores generally provide greater scalability at the expense of weaker consistency and isolation. However, additional isolation support is becoming increasingly important in the environments in which these stores are deployed, where different kinds of applications with different needs are executed, from transactional workloads to data analytics. While fully-fledged ACID support may not be feasible, it is still possible to take advantage of the design of these data stores, which often include the notion of multiversion concurrency control, to enable them with additional features at a much lower performance cost and maintaining its scalability and availability. In this paper we explore the effects that additional consistency guarantees and isolation capabilities may have on a state of the art key-value store: Apache Cassandra. We propose and implement a new multiversioned isolation level that provides stronger guarantees without compromising Cassandra's scalability and availability. As shown in our experiments, our version of Cassandra allows Snapshot Isolation-like transactions, preserving the overall performance and scalability of the system.This work is partially supported by the Ministry of Science and Technology of Spain and the European Union’s FEDER funds (TIN2007-60625, TIN2012-34557), by the Generalitat de Catalunya (2009-SGR-980), by the BSC-CNS Severo Ochoa program (SEV-2011-00067), by the HiPEAC European Network of Excellence (IST- 004408, FP7-ICT-217068, FP7-ICT-287759), and by IBM through the 2008 and 2010 IBM Faculty Award program.Peer ReviewedPostprint (author’s final draft

Providing Location Abstract Information in a Ubiquitous Computing Environment

To take full advantage of the promise of ubiquitous computing requires the use of location information, yet peo-ple should have control over who may know their where-abouts. We present an architecture that achieves these goals for an interesting set of applications. Personal in-formation is managed by User Agents, and a partially decentralized Location Query Service is used to facili-tate location-based operations. This architecture gives users primary control over their location information, at the cost of making more expensive certain queries, such as those wherein location and identity closely interact. We also discuss various extensions to our architecture that offer users additional trade-offs between privacy and efficiency. Finally, we report some measurements of the unextended system in operation, focusing on how well the system is actually able to track people. Our sys-tem uses two kinds of location information, which turn out to provide partial and complementary coverage.

Gossip-based Resource Management for Cloud Environments

We address the problem of resource management for a large-scale cloud environment that hosts sites. Our contribution centers around outlining a distributed middleware architecture and presenting one of its key elements, a gossip protocol that meets our design goals: fairness of resource allocation with respect to hosted sites, efficient adaptation to load changes and scalability in terms of both the number of machines and sites. We formalize the resource allocation problem as that of dynamically maximizing the cloud utility under CPU and memory constraints. While we can show that an optimal solution without considering memory constraints is straightforward (but not useful), we provide an efficient heuristic solution for the complete problem instead. We evaluate the protocol through simulation and find its performance to be well-aligned with our design goals.“© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”QC 2012012

A Gossip Protocol for Dynamic Resource Management in Large Cloud Environments

We address the problem of dynamic resource management for a large-scale cloud environment. Our contribution includes outlining a distributed middleware architecture and presenting one of its key elements: a gossip protocol that (1) ensures fair resource allocation among sites/applications, (2) dynamically adapts the allocation to load changes and (3) scales both in the number of physical machines and sites/applications. We formalize the resource allocation problem as that of dynamically maximizing the cloud utility under CPU and memory constraints. We first present a protocol that computes an optimalsolution without considering memory constraints and prove correctness and convergence properties. Then, we extend that protocol to provide an efficient heuristic solution for the complete problem, which includes minimizing the cost for adapting an allocation. The protocol continuously executes on dynamic, local input and does not require global synchronization, as other proposed gossip protocols do. We evaluate the heuristic protocol through simulation and find its performance to be well-aligned with our design goals.© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.QC 20120611</p

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Since many Internet applications employ a multitier architecture, in this article, we focus on the problem of analytically modeling the behavior of such applications. We present a model based on a network of queues where the queues represent different tiers of the application. Our model is sufficiently general to capture (i) the behavior of tiers with significantly different performance characteristics and (ii) application idiosyncrasies such as session-based workloads, tier replication, load imbalances across replicas, and caching at intermediate tiers. We validate our model using real multitier applications running on a Linux server cluster. Our experiments indicate that our model faithfully captures the performance of these applications for a number of workloads and configurations. Furthermore, our model successfully handles a comprehensive range of resource utilization—from 0 to near saturation for the CPU—for two separate tiers. For a variety of scenarios, including those with caching at one of the application tiers, the average response times predicted by our model were within the 95 % confidence intervals of the observed average response times. Our experiments also demonstrate the utility of the model for dynamic capacity provisioning, performance prediction, bottleneck identification, and session policing. In one scenario, where the request arrival rate increased from less than 1500 to nearly 4200 requests/minute, a dynamic provisionin

First-Class Data-type Representation is SchemeXerox

In most programming language implementations, the compiler has detailed knowledge of the representations of and operations on primitive data types and data-type constructors. In SchemeXerox, this knowledge is almost entirely external to the compiler, in ordinary, procedural user code. The primitive representations and operations are embodied in first-class &quot;representation types&quot; that are constructed and implemented in an abstract and high-level fashion. Despite this abstractness, a few generally-useful optimizing transformations are sufficient to allow the SchemeXerox compiler to generate efficient code for the primitive operations, essentially as good as could be achieved using more contorted, traditional techniques. 1 Introduction and Motivation Typically, the compiler for a given programming language embodies detailed knowledge of the syntax and semantics of that language&apos;s data-type specifications. This knowledge includes, for example, algorithms for bit-level layout of data-type..