OpenRaiser/Intern-Atlas huggingface dataset:
Software Verification for Weak Memory via Program Transformation
Venue: arXiv cs.LO 2012
Year: 2012

Despite multiprocessors implementing weak memory models, verification methods often assume Sequential Consistency (SC), thus may miss bugs due to weak memory. We propose a sound transformation of the program to verify, enabling SC tools to perform verification w.r.t. weak memory. We present experiments for a broad variety of models (from x86/TSO to Power/ARM) and a vast range of verification tools, quantify the additional cost of the transformation and highlight the cases when we can drastically reduce it. Our benchmarks include work-queue management code from PostgreSQL.
Capacity Results for Two Classes of Three-Way Channels
Venue: arXiv cs.IT 2012
Year: 2012

This paper considers the three-way channel, consisting of three nodes, where each node broadcasts a message to the two other nodes. The capacity of the finite-field three-way channel is derived, and is shown to be achievable using a non-cooperative scheme without feedback. The same scheme is also shown to achieve the equal-rate capacity (when all nodes transmit at the same rate) of the sender-symmetrical (each node receives the same SNR from the other two nodes) phase-fading AWGN channel. In the light that the non-cooperative scheme is not optimal in general, a cooperative feedback scheme that utilizes relaying and network coding is proposed and is shown to achieve the equal-rate capacity of the reciprocal (each pair of nodes has the same forward and backward SNR) phase-fading AWGN three-way channel.
Streaming Codes for Channels with Burst and Isolated Erasures
Venue: arXiv cs.IT 2012
Year: 2012

We study low-delay error correction codes for streaming recovery over a class of packet-erasure channels that introduce both burst-erasures and isolated erasures. We propose a simple, yet effective class of codes whose parameters can be tuned to obtain a tradeoff between the capability to correct burst and isolated erasures. Our construction generalizes previously proposed low-delay codes which are effective only against burst erasures. We establish an information theoretic upper bound on the capability of any code to simultaneously correct burst and isolated erasures and show that our proposed constructions meet the upper bound in some special cases. We discuss the operational significance of column-distance and column-span metrics and establish that the rate 1/2 codes discovered by Martinian and Sundberg [IT Trans.\, 2004] through a computer search indeed attain the optimal column-distance and column-span tradeoff. Numerical simulations over a Gilbert-Elliott channel model and a Fritchman model show significant performance gains over previously proposed low-delay codes and random linear codes for certain range of channel parameters.
Spatial Queries with Two kNN Predicates
Venue: arXiv cs.DB 2012
Year: 2012

The widespread use of location-aware devices has led to countless location-based services in which a user query can be arbitrarily complex, i.e., one that embeds multiple spatial selection and join predicates. Amongst these predicates, the k-Nearest-Neighbor (kNN) predicate stands as one of the most important and widely used predicates. Unlike related research, this paper goes beyond the optimization of queries with single kNN predicates, and shows how queries with two kNN predicates can be optimized. In particular, the paper addresses the optimization of queries with: (i) two kNN-select predicates, (ii) two kNN-join predicates, and (iii) one kNN-join predicate and one kNN-select predicate. For each type of queries, conceptually correct query evaluation plans (QEPs) and new algorithms that optimize the query execution time are presented. Experimental results demonstrate that the proposed algorithms outperform the conceptually correct QEPs by orders of magnitude.
Labeling Workflow Views with Fine-Grained Dependencies
Venue: arXiv cs.DB 2012
Year: 2012

This paper considers the problem of efficiently answering reachability queries over views of provenance graphs, derived from executions of workflows that may include recursion. Such views include composite modules and model fine-grained dependencies between module inputs and outputs. A novel view-adaptive dynamic labeling scheme is developed for efficient query evaluation, in which view specifications are labeled statically (i.e. as they are created) and data items are labeled dynamically as they are produced during a workflow execution. Although the combination of fine-grained dependencies and recursive workflows entail, in general, long (linear-size) data labels, we show that for a large natural class of workflows and views, labels are compact (logarithmic-size) and reachability queries can be evaluated in constant time. Experimental results demonstrate the benefit of this approach over the state-of-the-art technique when applied for labeling multiple views.
Opening the Black Boxes in Data Flow Optimization
Venue: arXiv cs.DB 2012
Year: 2012

Many systems for big data analytics employ a data flow abstraction to define parallel data processing tasks. In this setting, custom operations expressed as user-defined functions are very common. We address the problem of performing data flow optimization at this level of abstraction, where the semantics of operators are not known. Traditionally, query optimization is applied to queries with known algebraic semantics. In this work, we find that a handful of properties, rather than a full algebraic specification, suffice to establish reordering conditions for data processing operators. We show that these properties can be accurately estimated for black box operators by statically analyzing the general-purpose code of their user-defined functions. We design and implement an optimizer for parallel data flows that does not assume knowledge of semantics or algebraic properties of operators. Our evaluation confirms that the optimizer can apply common rewritings such as selection reordering, bushy join-order enumeration, and limited forms of aggregation push-down, hence yielding similar rewriting power as modern relational DBMS optimizers. Moreover, it can optimize the operator order of non-relational data flows, a unique feature among today's systems.
Spinning Fast Iterative Data Flows
Venue: arXiv cs.DB 2012
Year: 2012

Parallel dataflow systems are a central part of most analytic pipelines for big data. The iterative nature of many analysis and machine learning algorithms, however, is still a challenge for current systems. While certain types of bulk iterative algorithms are supported by novel dataflow frameworks, these systems cannot exploit computational dependencies present in many algorithms, such as graph algorithms. As a result, these algorithms are inefficiently executed and have led to specialized systems based on other paradigms, such as message passing or shared memory. We propose a method to integrate incremental iterations, a form of workset iterations, with parallel dataflows. After showing how to integrate bulk iterations into a dataflow system and its optimizer, we present an extension to the programming model for incremental iterations. The extension alleviates for the lack of mutable state in dataflows and allows for exploiting the sparse computational dependencies inherent in many iterative algorithms. The evaluation of a prototypical implementation shows that those aspects lead to up to two orders of magnitude speedup in algorithm runtime, when exploited. In our experiments, the improved dataflow system is highly competitive with specialized systems while maintaining a transparent and unified dataflow abstraction.
K-Reach: Who is in Your Small World
Venue: arXiv cs.DB 2012
Year: 2012

We study the problem of answering k-hop reachability queries in a directed graph, i.e., whether there exists a directed path of length k, from a source query vertex to a target query vertex in the input graph. The problem of k-hop reachability is a general problem of the classic reachability (where k=infinity). Existing indexes for processing classic reachability queries, as well as for processing shortest path queries, are not applicable or not efficient for processing k-hop reachability queries. We propose an index for processing k-hop reachability queries, which is simple in design and efficient to construct. Our experimental results on a wide range of real datasets show that our index is more efficient than the state-of-the-art indexes even for processing classic reachability queries, for which these indexes are primarily designed. We also show that our index is efficient in answering k-hop reachability queries.
Personalization in Geographic information systems: A survey
Venue: arXiv cs.IR 2012
Year: 2012

Geographic Information Systems (GIS) are widely used in different domains of applications, such as maritime navigation, museums visits and route planning, as well as ecological, demographical and economical applications. Nowadays, organizations need sophisticated and adapted GIS-based Decision Support System (DSS) to get quick access to relevant information and to analyze data with respect to geographic information, represented not only as spatial objects, but also as maps. Several research works on GIS personalization was proposed: Face the great challenge of developing both the theory and practice to provide personalization GIS visualization systems. This paper aims to provide a comprehensive review of literature on presented GIS personalization approaches. A benchmarking study of GIS personalization methods is proposed. Several evaluation criteria are used to identify the existence of trends as well as potential needs for further investigations.
Spatial and Spatio-Temporal Multidimensional Data Modelling: A Survey
Venue: arXiv cs.DB 2012
Year: 2012

Data warehouse store and provide access to large volume of historical data supporting the strategic decisions of organisations. Data warehouse is based on a multidimensional model which allow to express user's needs for supporting the decision making process. Since it is estimated that 80% of data used for decision making has a spatial or location component [1, 2], spatial data have been widely integrated in Data Warehouses and in OLAP systems. Extending a multidimensional data model by the inclusion of spatial data provides a concise and organised spatial datawarehouse representation. This paper aims to provide a comprehensive review of litterature on developed and suggested spatial and spatio-temporel multidimensional models. A benchmarking study of the proposed models is presented. Several evaluation criterias are used to identify the existence of trends as well as potential needs for further investigations.
The Complexity of MaxMin Length Triangulation
Venue: arXiv cs.CG 2012
Year: 2012

In 1991, Edelsbrunner and Tan gave an O(n^2) algorithm for finding the MinMax Length triangulation of a set of points in the plane. In this paper we resolve one of the open problems stated in that paper, by showing that finding a MaxMin Length triangulation is an NP-complete problem. The proof implies that (unless P=NP), there is no polynomial-time approximation algorithm that can approximate the problem within any polynomial factor.
Automatic Partitioning of Database Applications
Venue: arXiv cs.DB 2012
Year: 2012

Database-backed applications are nearly ubiquitous in our daily lives. Applications that make many small accesses to the database create two challenges for developers: increased latency and wasted resources from numerous network round trips. A well-known technique to improve transactional database application performance is to convert part of the application into stored procedures that are executed on the database server. Unfortunately, this conversion is often difficult. In this paper we describe Pyxis, a system that takes database-backed applications and automatically partitions their code into two pieces, one of which is executed on the application server and the other on the database server. Pyxis profiles the application and server loads, statically analyzes the code's dependencies, and produces a partitioning that minimizes the number of control transfers as well as the amount of data sent during each transfer. Our experiments using TPC-C and TPC-W show that Pyxis is able to generate partitions with up to 3x reduction in latency and 1.7x improvement in throughput when compared to a traditional non-partitioned implementation and has comparable performance to that of a custom stored procedure implementation.
Who Tags What? An Analysis Framework
Venue: arXiv cs.DB 2012
Year: 2012

The rise of Web 2.0 is signaled by sites such as Flickr, del.icio.us, and YouTube, and social tagging is essential to their success. A typical tagging action involves three components, user, item (e.g., photos in Flickr), and tags (i.e., words or phrases). Analyzing how tags are assigned by certain users to certain items has important implications in helping users search for desired information. In this paper, we explore common analysis tasks and propose a dual mining framework for social tagging behavior mining. This framework is centered around two opposing measures, similarity and diversity, being applied to one or more tagging components, and therefore enables a wide range of analysis scenarios such as characterizing similar users tagging diverse items with similar tags, or diverse users tagging similar items with diverse tags, etc. By adopting different concrete measures for similarity and diversity in the framework, we show that a wide range of concrete analysis problems can be defined and they are NP-Complete in general. We design efficient algorithms for solving many of those problems and demonstrate, through comprehensive experiments over real data, that our algorithms significantly out-perform the exact brute-force approach without compromising analysis result quality.
A Generic Framework for Efficient and Effective Subsequence Retrieval
Venue: arXiv cs.DB 2012
Year: 2012

This paper proposes a general framework for matching similar subsequences in both time series and string databases. The matching results are pairs of query subsequences and database subsequences. The framework finds all possible pairs of similar subsequences if the distance measure satisfies the "consistency" property, which is a property introduced in this paper. We show that most popular distance functions, such as the Euclidean distance, DTW, ERP, the Frechet distance for time series, and the Hamming distance and Levenshtein distance for strings, are all "consistent". We also propose a generic index structure for metric spaces named "reference net". The reference net occupies O(n) space, where n is the size of the dataset and is optimized to work well with our framework. The experiments demonstrate the ability of our method to improve retrieval performance when combined with diverse distance measures. The experiments also illustrate that the reference net scales well in terms of space overhead and query time.
Flash-based Extended Cache for Higher Throughput and Faster Recovery
Venue: arXiv cs.DB 2012
Year: 2012

Considering the current price gap between disk and flash memory drives, for applications dealing with large scale data, it will be economically more sensible to use flash memory drives to supplement disk drives rather than to replace them. This paper presents FaCE, which is a new low-overhead caching strategy that uses flash memory as an extension to the DRAM buffer. FaCE aims at improving the transaction throughput as well as shortening the recovery time from a system failure. To achieve the goals, we propose two novel algorithms for flash cache management, namely, Multi-Version FIFO replacement and Group Second Chance. One striking result from FaCE is that using a small flash memory drive as a caching device could deliver even higher throughput than using a large flash memory drive to store the entire database tables. This was possible due to flash write optimization as well as disk access reduction obtained by the FaCE caching methods. In addition, FaCE takes advantage of the non-volatility of flash memory to fully support database recovery by extending the scope of a persistent database to include the data pages stored in the flash cache. We have implemented FaCE in the PostgreSQL open source database server and demonstrated its effectiveness for TPC-C benchmarks.
An Economic Analysis of User-Privacy Options in Ad-Supported Services
Venue: arXiv cs.GT 2012
Year: 2012

We analyze the value to e-commerce website operators of offering privacy options to users, e.g., of allowing users to opt out of ad targeting. In particular, we assume that site operators have some control over the cost that a privacy option imposes on users and ask when it is to their advantage to make such costs low. We consider both the case of a single site and the case of multiple sites that compete both for users who value privacy highly and for users who value it less. One of our main results in the case of a single site is that, under normally distributed utilities, if a privacy-sensitive user is worth at least $\sqrt{2} - 1$ times as much to advertisers as a privacy-insensitive user, the site operator should strive to make the cost of a privacy option as low as possible. In the case of multiple sites, we show how a Prisoner's-Dilemma situation can arise: In the equilibrium in which both sites are obliged to offer a privacy option at minimal cost, both sites obtain lower revenue than they would if they colluded and neither offered a privacy option.
Optimization hardness as transient chaos in an analog approach to constraint satisfaction
Venue: arXiv cs.CC 2012
Year: 2012

Boolean satisfiability [1] (k-SAT) is one of the most studied optimization problems, as an efficient (that is, polynomial-time) solution to k-SAT (for $k\geq 3$) implies efficient solutions to a large number of hard optimization problems [2,3]. Here we propose a mapping of k-SAT into a deterministic continuous-time dynamical system with a unique correspondence between its attractors and the k-SAT solution clusters. We show that beyond a constraint density threshold, the analog trajectories become transiently chaotic [4-7], and the boundaries between the basins of attraction [8] of the solution clusters become fractal [7-9], signaling the appearance of optimization hardness [10]. Analytical arguments and simulations indicate that the system always finds solutions for satisfiable formulae even in the frozen regimes of random 3-SAT [11] and of locked occupation problems [12] (considered among the hardest algorithmic benchmarks); a property partly due to the system's hyperbolic [4,13] character. The system finds solutions in polynomial continuous-time, however, at the expense of exponential fluctuations in its energy function.
Fast Monotone Summation over Disjoint Sets
Venue: arXiv cs.DS 2012
Year: 2012

We study the problem of computing an ensemble of multiple sums where the summands in each sum are indexed by subsets of size $p$ of an $n$-element ground set. More precisely, the task is to compute, for each subset of size $q$ of the ground set, the sum over the values of all subsets of size $p$ that are disjoint from the subset of size $q$. We present an arithmetic circuit that, without subtraction, solves the problem using $O((n^p+n^q)\log n)$ arithmetic gates, all monotone; for constant $p$, $q$ this is within the factor $\log n$ of the optimal. The circuit design is based on viewing the summation as a "set nucleation" task and using a tree-projection approach to implement the nucleation. Applications include improved algorithms for counting heaviest $k$-paths in a weighted graph, computing permanents of rectangular matrices, and dynamic feature selection in machine learning.
Simulation Study For Performance Comparison in Hierarchical Network With CHG Approach in MANET
Venue: arXiv cs.NI 2012
Year: 2012

The implementation of MANET for commercial purposes is not an easy task. Unlike other wireless technologies such as cellular networks, MANET face more difficult problems concerning management functions, routing and scalability . As a solution to these complications, clustering schemes are proposed for MANET in order to organize the network topology in a hierarchical manner. Many clustering techniques have been developed. Clustering is a method which aggregates nodes into groups. These groups are contained by the network and they are known as clusters. By Increasing network capacity and reducing the routing overhead through clustering brings more efficiency and effectiveness to scalability in relation to node numbers and the necessity for high mobility. The manager node in clustering has responsibility for many functions such as cluster maintenance, routing table updates, and the discovery of new routes within the network. The other node named as gateway node communicate to the other cluster. In this paper we remove the cluster head (CH) and given a new approach in which cluster head and gateway will be same and that node is known as cluster head gateway (CHG), in which all the responsibilities of cluster head and gateway will be perform by the Cluster head gateway(CHG) itself. By applying this approach we reduce of overheads and improve the over all performance of the network while throughput will be same in both condition with the help of Exata simulation.
Economics of Electric Vehicle Charging: A Game Theoretic Approach
Venue: arXiv cs.GT 2012
Year: 2012

In this paper, the problem of grid-to-vehicle energy exchange between a smart grid and plug-in electric vehicle groups (PEVGs) is studied using a noncooperative Stackelberg game. In this game, on the one hand, the smart grid that acts as a leader, needs to decide on its price so as to optimize its revenue while ensuring the PEVGs' participation. On the other hand, the PEVGs, which act as followers, need to decide on their charging strategies so as to optimize a tradeoff between the benefit from battery charging and the associated cost. Using variational inequalities, it is shown that the proposed game possesses a socially optimal Stackelberg equilibrium in which the grid optimizes its price while the PEVGs choose their equilibrium strategies. A distributed algorithm that enables the PEVGs and the smart grid to reach this equilibrium is proposed and assessed by extensive simulations. Further, the model is extended to a time-varying case that can incorporate and handle slowly varying environments.
Comparative Evaluation of Data Stream Indexing Models
Venue: arXiv cs.DB 2012
Year: 2012

In recent years, the management and processing of data streams has become a topic of active research in several fields of computer science such as, distributed systems, database systems, and data mining. A data stream can be thought of as a transient, continuously increasing sequence of data. In data streams' applications, because of online monitoring, answering to the user's queries should be time and space efficient. In this paper, we consider the special requirements of indexing to determine the performance of different techniques in data stream processing environments. Stream indexing has main differences with approaches in traditional databases. Also, we compare data stream indexing models analytically that can provide a suitable method for stream indexing.