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Parallel and Distributed Systems, IEEE Transactions on

Issue 6 • Date June 2012

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Displaying Results 1 - 24 of 24
  • [Front cover]

    Publication Year: 2012 , Page(s): c1
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  • [Inside front cover]

    Publication Year: 2012 , Page(s): c2
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  • A Correlated Resource Model of Internet End Hosts

    Publication Year: 2012 , Page(s): 977 - 984
    Cited by:  Papers (2)
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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1301 KB) |  | HTML iconHTML  

    Understanding and modeling resources of Internet end hosts are essential for the design of desktop software and Internet-distributed applications. In this paper, we develop a correlated resource model of Internet end hosts based on real-trace data taken from several volunteer computing projects, including SETI@home. This data cover a five-year period with statistics for 6.7 million hosts. Our resource model is based on statistical analysis of host computational power, memory, and storage as well as how these resources change over time and the correlations among them. We find that resources with few discrete values (core count, memory) are well modeled by approximations governing the change of relative resource quantities over time. Resources with a continuous range of values are well modeled by correlated log-normal distributions (cache, processor speed, and available disk space). We validate and show the utility of the model by applying it to a resource allocation problem for Internet-distributed applications, and compare it to other models. We also make our trace data and tool for automatically generating realistic Internet end hosts publicly available. View full abstract»

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  • A Network Coding Equivalent Content Distribution Scheme for Efficient Peer-to-Peer Interactive VoD Streaming

    Publication Year: 2012 , Page(s): 985 - 994
    Cited by:  Papers (4)
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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1290 KB)  

    Although random access operations are desirable for on-demand video streaming in peer-to-peer systems, they are difficult to efficiently achieve due to the asynchronous interactive behaviors of users and the dynamic nature of peers. In this paper, we propose a network coding equivalent content distribution (NCECD) scheme to efficiently handle interactive video-on-demand (VoD) operations in peer-to-peer systems. In NCECD, videos are divided into segments that are then further divided into blocks. These blocks are encoded into independent blocks that are distributed to different peers for local storage. With NCECD, a new client only needs to connect to a sufficient number of parent peers to be able to view the whole video and rarely needs to find new parents when performing random access operations. In most existing methods, a new client must search for parent peers containing specific segments; however, NCECD uses the properties of network coding to cache equivalent content in peers, so that one can pick any parent without additional searches. Experimental results show that the proposed scheme achieves low startup and jump searching delays and requires fewer server resources. In addition, we present the analysis of system parameters to achieve reasonable block loss rates for the proposed scheme. View full abstract»

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  • A Secure Erasure Code-Based Cloud Storage System with Secure Data Forwarding

    Publication Year: 2012 , Page(s): 995 - 1003
    Cited by:  Papers (19)
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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (700 KB) |  | HTML iconHTML  

    A cloud storage system, consisting of a collection of storage servers, provides long-term storage services over the Internet. Storing data in a third party's cloud system causes serious concern over data confidentiality. General encryption schemes protect data confidentiality, but also limit the functionality of the storage system because a few operations are supported over encrypted data. Constructing a secure storage system that supports multiple functions is challenging when the storage system is distributed and has no central authority. We propose a threshold proxy re-encryption scheme and integrate it with a decentralized erasure code such that a secure distributed storage system is formulated. The distributed storage system not only supports secure and robust data storage and retrieval, but also lets a user forward his data in the storage servers to another user without retrieving the data back. The main technical contribution is that the proxy re-encryption scheme supports encoding operations over encrypted messages as well as forwarding operations over encoded and encrypted messages. Our method fully integrates encrypting, encoding, and forwarding. We analyze and suggest suitable parameters for the number of copies of a message dispatched to storage servers and the number of storage servers queried by a key server. These parameters allow more flexible adjustment between the number of storage servers and robustness. View full abstract»

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  • Adaptive Approximate Data Collection for Wireless Sensor Networks

    Publication Year: 2012 , Page(s): 1004 - 1016
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1616 KB) |  | HTML iconHTML  

    Data collection is a fundamental task in wireless sensor networks. In many applications of wireless sensor networks, approximate data collection is a wise choice due to the constraints in communication bandwidth and energy budget. In this paper, we focus on efficient approximate data collection with prespecified error bounds in wireless sensor networks. The key idea of our data collection approach ADC (Approximate Data Collection) is to divide a sensor network into clusters, discover local data correlations on each cluster head, and perform global approximate data collection on the sink node according to model parameters uploaded by cluster heads. Specifically, we propose a local estimation model to approximate the readings of sensor nodes in subsets, and prove rated error-bounds of data collection using this model. In the process of model-based data collection, we formulate the problem of selecting the minimum subset of sensor nodes into a minimum dominating set problem which is known to be NP-hard, and propose a greedy heuristic algorithm to find an approximate solution. We further propose a monitoring algorithm to adaptively adjust the composition of node subsets according to changes of sensor readings. Our trace-driven simulations demonstrate that ADC remarkably reduces communication cost of data collection with guaranteed error bounds. View full abstract»

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  • An Online Data Access Prediction and Optimization Approach for Distributed Systems

    Publication Year: 2012 , Page(s): 1017 - 1029
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4844 KB) |  | HTML iconHTML  

    Current scientific applications have been producing large amounts of data. The processing, handling and analysis of such data require large-scale computing infrastructures such as clusters and grids. In this area, studies aim at improving the performance of data-intensive applications by optimizing data accesses. In order to achieve this goal, distributed storage systems have been considering techniques of data replication, migration, distribution, and access parallelism. However, the main drawback of those studies is that they do not take into account application behavior to perform data access optimization. This limitation motivated this paper which applies strategies to support the online prediction of application behavior in order to optimize data access operations on distributed systems, without requiring any information on past executions. In order to accomplish such a goal, this approach organizes application behaviors as time series and, then, analyzes and classifies those series according to their properties. By knowing properties, the approach selects modeling techniques to represent series and perform predictions, which are, later on, used to optimize data access operations. This new approach was implemented and evaluated using the OptorSim simulator, sponsored by the LHC-CERN project and widely employed by the scientific community. Experiments confirm this new approach reduces application execution time in about 50 percent, specially when handling large amounts of data. View full abstract»

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  • CLOSER: A Collaborative Locality-Aware Overlay SERvice

    Publication Year: 2012 , Page(s): 1030 - 1037
    Cited by:  Papers (2)
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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (504 KB) |  | HTML iconHTML  

    Current Peer-to-Peer (P2P) file sharing systems make use of a considerable percentage of Internet Service Providers (ISPs) bandwidth. This paper presents the Collaborative Locality-aware Overlay SERvice (CLOSER), an architecture that aims at lessening the usage of expensive international links by exploiting traffic locality (i.e., a resource is downloaded from the inside of the ISP whenever possible). The paper proves the effectiveness of CLOSER by analysis and simulation, also comparing this architecture with existing solutions for traffic locality in P2P systems. While savings on international links can be attractive for ISPs, it is necessary to offer some features that can be of interest for users to favor a wide adoption of the application. For this reason, CLOSER also introduces a privacy module that may arouse the users' interest and encourage them to switch to the new architecture. View full abstract»

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  • Codesign of NoC and Cache Organization for Reducing Access Latency in Chip Multiprocessors

    Publication Year: 2012 , Page(s): 1038 - 1046
    Cited by:  Papers (2)
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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (594 KB) |  | HTML iconHTML  

    Reducing data access latency is vital to achieving performance improvements in computing. For chip multiprocessors (CMPs), data access latency depends on the organization of the memory hierarchy, the on-chip interconnect, and the running workload. Several network-on-chip (NoC) designs exploit communication locality to reduce communication latency by configuring special fast paths or circuits on which communication is faster than the rest of the NoC. However, communication patterns are directly affected by the cache organization and many cache organizations are designed in isolation of the underlying NoC or assume a simple NoC design, thus possibly missing optimization opportunities. In this work, we take a codesign approach of the NoC and cache organization. First, we propose a hybrid circuit/packet-switched NoC that exploits communication locality through periodic configuration of the most beneficial circuits. Second, we design a Unique Private (UP) caching scheme targeting the class of interconnects which exploit communication locality to improve communication latency. The Unique Private cache stores the data that are mostly accessed by each processor core in the core's locally accessible cache bank, while leveraging dedicated high-speed circuits in the interconnect to provide remote cores with fast access to shared data. Simulations of a suite of scientific and commercial workloads show that our proposed design achieves a speedup of 15.2 and 14 percent on a 16-core and a 64-core CMP, respectively, over the state-of-the-art NoC-Cache codesigned system that also exploits communication locality in multithreaded applications. View full abstract»

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  • Comparison-Based System-Level Fault Diagnosis: A Neural Network Approach

    Publication Year: 2012 , Page(s): 1047 - 1059
    Cited by:  Papers (4)
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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1170 KB) |  | HTML iconHTML  

    We consider the fault identification problem, also known as the system-level self-diagnosis, in multiprocessor and multicomputer systems using the comparison approach. In this diagnosis model, a set of tasks is assigned to pairs of nodes and their outcomes are compared by neighboring nodes. Given that comparisons are performed by the nodes themselves, faulty nodes can incorrectly claim that fault-free nodes are faulty or that faulty ones are fault-free. The collections of all agreements and disagreements, i.e., the comparison outcomes, among the nodes are used to identify the set of permanently faulty nodes. Since the introduction of the comparison model, significant progress has been made in both theory and practice associated with the original model and its offshoots. Nevertheless, the problem of efficiently identifying the set of faulty nodes when not all the comparison outcomes are available to the diagnosis algorithm at the beginning of the diagnosis phase, i.e., partial syndromes, remains an outstanding research issue. In this paper, we introduce a novel diagnosis approach using neural networks to solve this fault identification problem using partial syndromes. Results from a thorough simulation study demonstrate the effectiveness of the neural-network-based self-diagnosis algorithm for randomly generated diagnosable systems of different sizes and under various fault scenarios. We have then conducted extensive simulations using partial syndromes and nondiagnosable systems. Simulations showed that the neural-network-based diagnosis approach provided good results making it a viable addition or alternative to existing diagnosis algorithms. View full abstract»

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  • Detecting Concurrency Bugs from the Perspectives of Synchronization Intentions

    Publication Year: 2012 , Page(s): 1060 - 1072
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    Concurrency bugs are among the most difficult to detect and diagnose of all software bugs. This paper combats concurrency bugs from the perspective of programmers' synchronization intentions. We first study the root causes of 74 real-world concurrency bugs to understand what types of synchronization assumptions are violated in real world. This study reveals two classes of synchronization intentions that are common, frequently violated, and understudied-single-variable atomicity intention and multivariable correlation intention. Following this study, two bug detection tools, AVIO and MUVI, are proposed to automatically infer these two types of synchronization intentions and detect related bugs. Specifically, AVIO automatically extracts access interleaving invariants and detects a variety of atomicity-violations during production runs. It can work both with and without special hardware support in our implementation. MUVI automatically infers multivariable correlations through static analysis and detects multivariable concurrency bugs. Our evaluation with real-world large multithreaded applications shows that AVIO can detect more atomicity-violation bugs with 15 times fewer false positives on average than previous solutions. Besides, AVIO-H incurs negligible (0.4-0.5 percent) overhead. MUVI successfully extracts 6,449 access correlations from Linux, Mozilla, MySQL, and PostgreSQL with high (83 percent) accuracy. Race detectors extended by MUVI can correctly identify the root causes of real-world multivariable concurrency bugs in our experiments. They also report four new multivariable concurrency bugs that have never been reported before. View full abstract»

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  • Discriminating DDoS Attacks from Flash Crowds Using Flow Correlation Coefficient

    Publication Year: 2012 , Page(s): 1073 - 1080
    Cited by:  Papers (9)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (678 KB) |  | HTML iconHTML  

    Distributed Denial of Service (DDoS) attack is a critical threat to the Internet, and botnets are usually the engines behind them. Sophisticated botmasters attempt to disable detectors by mimicking the traffic patterns of flash crowds. This poses a critical challenge to those who defend against DDoS attacks. In our deep study of the size and organization of current botnets, we found that the current attack flows are usually more similar to each other compared to the flows of flash crowds. Based on this, we proposed a discrimination algorithm using the flow correlation coefficient as a similarity metric among suspicious flows. We formulated the problem, and presented theoretical proofs for the feasibility of the proposed discrimination method in theory. Our extensive experiments confirmed the theoretical analysis and demonstrated the effectiveness of the proposed method in practice. View full abstract»

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  • Embedding Cycles and Paths in Product Networks and Their Applications to Multiprocessor Systems

    Publication Year: 2012 , Page(s): 1081 - 1089
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    In this paper, we consider two embedding problems in Cartesian product networks: one is the pancycle problem, which involves embedding cycles of various lengths in the given product network; and the other is the panconnectivity problem, which involves embedding paths of various lengths between any pair of distinct nodes in the given product network. We then apply our technical lemmas and theorems to derive new topological properties of two multiprocessor systems, namely, generalized hypercubes and nearest neighbor mesh hypercubes. View full abstract»

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  • Energy-Efficient Capture of Stochastic Events under Periodic Network Coverage and Coordinated Sleep

    Publication Year: 2012 , Page(s): 1090 - 1102
    Cited by:  Papers (9)
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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1418 KB) |  | HTML iconHTML  

    We consider a high density of sensors randomly placed in a geographical area for event monitoring. The monitoring regions of the sensors may have significant overlap, and a subset of the sensors can be turned off to conserve energy, thereby increasing the lifetime of the monitoring network. Prior work in this area does not consider the event dynamics. In this paper, we show that knowledge about the event dynamics can be exploited for significant energy savings, by putting the sensors on a periodic on/off schedule. We discuss energy-aware optimization of the periodic schedule for the cases of an synchronous and a asynchronous network. To reduce the overhead of global synchronization, we further consider a spectrum of regionally synchronous networks where the size of the synchronization region is specifiable. Under the periodic scheduling, coordinated sleep by the sensors can be applied orthogonally to minimize the redundancy of coverage and further improve the energy efficiency. We consider the interactions between the periodic scheduling and coordinated sleep. We show that the asynchronous network exceeds any regionally synchronous network in the coverage intensity, thereby increasing the effectiveness of the event capture, though the opportunities for coordinated sleep decreases as the synchronization region gets smaller. When the sensor density is high, the asynchronous network with coordinated sleep can achieve extremely good event capture performance while being highly energy efficient. View full abstract»

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  • Footprint: Detecting Sybil Attacks in Urban Vehicular Networks

    Publication Year: 2012 , Page(s): 1103 - 1114
    Cited by:  Papers (5)
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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (684 KB) |  | HTML iconHTML  

    In urban vehicular networks, where privacy, especially the location privacy of anonymous vehicles is highly concerned, anonymous verification of vehicles is indispensable. Consequently, an attacker who succeeds in forging multiple hostile identifies can easily launch a Sybil attack, gaining a disproportionately large influence. In this paper, we propose a novel Sybil attack detection mechanism, Footprint, using the trajectories of vehicles for identification while still preserving their location privacy. More specifically, when a vehicle approaches a road-side unit (RSU), it actively demands an authorized message from the RSU as the proof of the appearance time at this RSU. We design a location-hidden authorized message generation scheme for two objectives: first, RSU signatures on messages are signer ambiguous so that the RSU location information is concealed from the resulted authorized message; second, two authorized messages signed by the same RSU within the same given period of time (temporarily linkable) are recognizable so that they can be used for identification. With the temporal limitation on the linkability of two authorized messages, authorized messages used for long-term identification are prohibited. With this scheme, vehicles can generate a location-hidden trajectory for location-privacy-preserved identification by collecting a consecutive series of authorized messages. Utilizing social relationship among trajectories according to the similarity definition of two trajectories, Footprint can recognize and therefore dismiss “communities” of Sybil trajectories. Rigorous security analysis and extensive trace-driven simulations demonstrate the efficacy of Footprint. View full abstract»

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  • k-Pancyclicity of k-ary n-Cube Networks under the Conditional Fault Model

    Publication Year: 2012 , Page(s): 1115 - 1120
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    The k-ary n-cube is one of the most popular interconnection networks for parallel and distributed systems. We prove that a k-ary n-cube with at most in 5 faulty edges but where every vertex is incident with at least two healthy edges is k-pancyclic and bipancyclic for n ≥ 3 and odd k ≥ 3. View full abstract»

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  • On Multicopy Opportunistic Forwarding Protocols in Nondeterministic Delay Tolerant Networks

    Publication Year: 2012 , Page(s): 1121 - 1128
    Cited by:  Papers (3)
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    Delay Tolerant Networks (DTNs) are characterized by nondeterministic mobility and connectivity. Message routing in DTNs usually employs a multicopy forwarding scheme. To avoid the cost associated with flooding, much effort has been focused on opportunistic forwarding, which aims to reduce the cost of forwarding while retaining high routing performance by forwarding messages only to nodes that have high delivery probabilities. This paper presents two multicopy forwarding protocols, called optimal opportunistic forwarding (OOF) and OOF-, which maximize the expected delivery rate and minimize the expected delay, respectively, while requiring that the number of forwardings per message does not exceed a certain threshold. Our contributions in this paper are summarized as follows: We apply the optimal stopping rule in the multicopy opportunistic forwarding protocol. Specifically, we propose two optimal opportunistic forwarding metrics to maximize delivery probability and minimize delay, respectively, with a fixed number of copies and within a given time-to-live. We implement and evaluate OOF and OOF- as well as several other representative forwarding protocols, i.e., Epidemic, Spray-and-wait, MaxProp* and Delegation. We perform trace-driven simulations using both real and synthetic traces. Simulation results show that, in the traces where nodes have regular intermeeting times, the delivery rates of OOF and OOF- can be 30 percent greater than the compared routing protocols. View full abstract»

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  • Optimal Construction of All Shortest Node-Disjoint Paths in Hypercubes with Applications

    Publication Year: 2012 , Page(s): 1129 - 1134
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    Routing functions had been shown effective in constructing node-disjoint paths in hypercube-like networks. In this paper, by the aid of routing functions, m node-disjoint shortest paths from one source node to other m (not necessarily distinct) destination nodes are constructed in an n-dimensional hypercube, provided the existence of such node-disjoint shortest paths which can be verified in O(mn1.5) time, where m ≤ n. The construction procedure has worst case time complexity O(mn), which is optimal and hence improves previous results. By taking advantages of the construction procedure, m node-disjoint paths from one source node to other m (not necessarily distinct) destination nodes in an n-dimensional hypercube such that their total length is minimized can be constructed in O(mn1.5 + m3n) time, which is more efficient than the previous result of O(m2n2.5 + mn3) time. Besides, their maximal length is also minimized in the worst case. View full abstract»

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  • Optimizing Techniques for Parallel Digital Logic Simulation

    Publication Year: 2012 , Page(s): 1135 - 1146
    Cited by:  Papers (3)
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    A major part of the design process for Integrated Circuits (IC) is the process of circuit verification, in which the correctness of a circuit's design is evaluated. Discrete event simulation is a central tool in this effort. As proscribed by Moore's law, the number of transistors which can be placed on an IC doubles every 18 months. As a result, simulation has become the major bottleneck in the circuit design process. To alleviate this difficulty, it is possible to make use of parallel (or distributed) circuit simulation. In this paper, we make use of a parallel gate-level simulator which we developed and which is based upon Time Warp. Gate-level simulations exhibit two characteristics which can easily result in either instability or severely degraded simulation performance. Because of the low computational granularity of a gate-level simulation and because the computational load varies throughout the course of the simulation, the performance of Time Warp can be either severely degraded or be unstable. Restraining the optimism of Time Warp via a bounded window and utilizing dynamic load balancing are approaches to deal with these difficulties. In this paper, we make use of learning techniques from artificial intelligence (multiagent Q-learning, simulated annealing) to develop a combined bounded window and dynamic load balancing algorithm for parallel digital logic simulation. We evaluated the performance of these algorithms on open source Sparc and Leon designs and on two Viterbi decoder designs. We observed up to 60 percent improvement in simulation time of one of the decoders using this approach. View full abstract»

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  • Optimizing Information Credibility in Social Swarming Applications

    Publication Year: 2012 , Page(s): 1147 - 1158
    Cited by:  Papers (6)
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    With the advent of smartphone technology, it has become possible to conceive of entirely new classes of applications. Social swarming, in which users armed with smartphones are directed by a central director to report on events in the physical world, has several real-world applications: search and rescue, coordinated fire-fighting, and the DARPA balloon hunt challenge. In this paper, we focus on the following problem: how does the director optimize the selection of reporters to deliver credible corroborating information about an event. We first propose a model, based on common notions of believability, about the credibility of information. We then cast the problem posed above as a discrete optimization problem, prove hardness results, introduce optimal centralized solutions, and design an approximate solution amenable to decentralized implementation whose performance is about 20 percent off, on average, from the optimal (on real-world data sets derived from Google News) while being three orders of magnitude more computationally efficient. More interesting, a time-averaged version of the problem is amenable to a novel stochastic utility optimization formulation, and can be solved optimally, while in some cases yielding decentralized solutions. To our knowledge, we are the first to propose and explore the problem of extracting credible information from a network of smartphones. View full abstract»

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  • Precise, Scalable, and Online Request Tracing for Multitier Services of Black Boxes

    Publication Year: 2012 , Page(s): 1159 - 1167
    Cited by:  Papers (4)
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    As more and more multitier services are developed from commercial off-the-shelf components or heterogeneous middleware without source code available, both developers and administrators need a request tracing tool to (1) exactly know how a user request of interest travels through services of black boxes and (2) obtain macrolevel user request behaviors of services without manually analyzing massive logs. This need is further exacerbated by IT system “agility,” which mandates the tracing tool to provide online performance data since offline approaches cannot reflect system changes in real time. Moreover, considering the large scale of deployed services, a pragmatic tracing approach should be scalable in terms of the cost in collecting and analyzing logs. In this paper, we introduce a precise, scalable, and online request tracing tool for multitier services of black boxes. Our contributions are threefold. First, we propose a precise request tracing algorithm for multitier services of black boxes, which only uses application-independent knowledge. Second, we present a microlevel abstraction, component activity graph, to represent causal paths of each request. On the basis of this abstraction, we use dominated causal path patterns to represent repeatedly executed causal paths that account for significant fractions, and we further present a derived performance metric of causal path patterns, latency percentages of components, to enable debugging performance-in-the-large. Third, we develop two mechanisms, tracing on demand and sampling, to significantly increase the system scalability. We implement a prototype of the proposed system, called PreciseTracer, and release it as open source code. In comparison with WAP5-a black-box tracing approach, PreciseTracer achieves higher tracing accuracy and faster response time. Our experimental results also show that PreciseTracer has low overhead, and still achieves high tracing accuracy even if an aggressive sampling - olicy is adopted, indicating that PreciseTracer is a promising tracing tool for large-scale production systems. View full abstract»

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  • Call for Papers: Special Issue on Trust, Security, and Privacy in Parallel and Distributed Systems

    Publication Year: 2012 , Page(s): 1168
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    Freely Available from IEEE
  • [Inside back cover]

    Publication Year: 2012 , Page(s): c3
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    Freely Available from IEEE
  • [Back cover]

    Publication Year: 2012 , Page(s): c4
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    Freely Available from IEEE

Aims & Scope

IEEE Transactions on Parallel and Distributed Systems (TPDS) is published monthly. It publishes a range of papers, comments on previously published papers, and survey articles that deal with the parallel and distributed systems research areas of current importance to our readers.

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Meet Our Editors

Editor-in-Chief
David Bader
College of Computing
Georgia Institute of Technology