http://www.computer.org/tpds IEEE Transactions on Parallel and Distributed Systems (TPDS) is published monthly. The goal of TPDS is to publish a range of papers, comments on previously published papers, and survey articles that deal with the research areas of current importance to our readers. Current areas of particular interest include, but are not limited to the following: a) architectures: design, analysis, and implementation of multiple-processor systems (including multi-processors, multicomputers, and networks); impact of VLSI on system design; interprocessor communications; b) software: parallel languages and compilers; scheduling and task partitioning; databases, operating systems, and programming environments for multiple-processor systems; c) algorithms and applications: models of computation; analysis and design of parallel/distributed algorithms; application studies resulting in better multiple-processor systems; d) other issues: performance measurements, evaluation, modeling and simulation of multiple-processor systems; real-time, reliability and fault-tolerance issues; conversion of software from sequential-to-parallel forms. en-us Wed, 4 Jan 2012 11:00:01 GMT http://csdl.computer.org/common/images/logos/tpds.gif List of recently published journal articles http://www.computer.org/tpds http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.310 Nowadays there is urgent demand for wireless sensor network applications. In these applications, usually a base station is responsible for monitoring the entire network and collecting information. If emergency happens, it will propagate such information to all other nodes. However, quite often the message source is not a fixed node, since there may be base stations in charge of different regions or events. Therefore, how to propagate information efficiently when message sources vary from time to time is a challenging issue. None of conventional broadcast algorithms can deal with this case efficiently, since the change of message source incurs a huge implementation cost of re-building a broadcast tree. To deal with this difficult problem, we make endeavor in studying multiple source broadcast, in which targeted algorithms should be source-independent to serve the practical need. In this paper, we formulate the Minimum-Latency Multi-Source Broadcast problem. We propose a novel solution using a fixed shared backbone, which is independent of the message sources and can be used repeatedly to reduce the broadcast latency. To the best of our knowledge, our work is deemed the first attempt to design such a multi-source broadcast algorithm with a derived theoretical latency upper-bound. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.310 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.308 In this work, we present a survey of the different parallel programming models and tools available today with special consideration to their suitability for high performance computing. Thus, we review the shared and distributed memory approaches, as well as the current heterogeneous parallel programming model. In addition, we analyze how the partitioned global address space (PGAS) and hybrid parallel programming models are used to combine the advantages of shared and distributed memory systems. The work is completed by considering languages with specific parallel support and the distributed programming paradigm. In all cases, we present characteristics, strengths and weaknesses. The study shows that the availability of multicore CPUs has given new impulse to the shared memory parallel programming approach. In addition, we find that hybrid parallel programming is the current way of harnessing the capabilities of computer clusters with multicore nodes. On the other hand, heterogeneous programming is found to be an increasingly popular paradigm, as a consequence of the availability of multicore CPUs+GPUs systems. The use of open industry standards like OpenMP, MPI or OpenCL, as opposed to proprietary solutions, seems to be the way to uniformize and extend the use of parallel programming models. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.308 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.303 Recently, utility Grids have emerged as a new model of service provisioning in heterogeneous distributed systems. In this model, users negotiate with service providers on their required Quality of Service and on the corresponding price to reach a Service Level Agreement. One of the most challenging problems in utility Grids is workflow scheduling, i.e., the problem of satisfying the QoS of the users as well as minimizing the cost of workflow execution. In this paper, we propose a new QoS-based workflow scheduling algorithm based on a novel concept called Partial Critical Paths (PCP), that tries to minimize the cost of workflow execution while meeting a user-defined deadline. The PCP algorithm has two phases: in the deadline distribution phase it recursively assigns sub-deadlines to the tasks on the partial critical paths ending at previously assigned tasks, and in the planning phase it assigns the cheapest service to each task while meeting its sub-deadline. The simulation results show that the performance of the PCP algorithm is very promising. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.303 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.297 Over the past decades, caching has become the key technology used for bridging the performance gap across memory hierarchies via temporal or spatial localities. Applications that involve heavy I/O activities, which are common in the cloud, probably benefit the most from caching. The use of local volatile memory as cache might be a natural alternative, but many well known restrictions, such as capacity and the utilization of host machines, hinder its effective use. In addition to technical challenges, providing cache services in clouds encounters a major practical issue of pricing. As a result, the current cloud platforms lack appropriate caching models or services. In this paper, we present a cache service model for the cloud, called cache as a service (CaaS), which resolves many technical and practical issues. Specifically, we investigate the feasibility of providing CaaS with the proof of concept elastic cache system (using dedicated remote memory servers) built and validated on the actual system; and practical benefits of CaaS for both users and providers (i.e., performance and profit, respectively) are thoroughly studied with a novel pricing scheme. Our CaaS model helps to leverage the cloud economy greatly in that (1) the extra user cost for I/O performance gain is minimal if ever exists, and (2) the provider's profit increases due to improvements in server consolidation resulting from that performance gain. Through extensive experiments with eight resource allocation strategies we demonstrate that our CaaS model can be a promising cost-efficient solution for both users and providers. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.297 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.295 P2P-Video-on-Demand (P2P-VoD) is a popular Internet service which aims to provide a scalable and high quality service to users. At the same time, content providers of P2P-VoD services also need to make sure that the service is operated with a manageable operating cost. Given the volume-based charging model by ISPs, P2P-VoD content providers would like to reduce peers' access to the content server so as to reduce the operating cost. In this paper, we address an important open problem: what is the "{\em optimal replication ratio}" in a P2P-VoD system such that peers will receive service from each other and at the same time, reduce the access to the content server? We address two fundamental issues: (a) what is the optimal replication ratio of a movie if we know its popularity, and (b) how to achieve these optimal ratios in a distributed and dynamic fashion. We first formally show how movie popularities can impact server's workload, and formulate the video replication as an optimization problem. We show that the conventional wisdom of using the proportional replication strategy is "{\em sub-optimal}", and expand the design space to both "{\em passive replacement policy}" and "{\em active push policy}" to achieve the optimal replication ratios. We consider practical implementation issues, evaluate the performance of P2P-VoD systems and show how to greatly reduce server's workload and improve streaming quality via our distributed algorithms. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.295 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.289 This paper presents an empirical study on the performance of mobile High Speed Packet Access (a 3.5G cellular standard usually abbreviated as HSPA) networks in Hong Kong via extensive field tests. Our study, from the viewpoint of end users, covers virtually all possible mobile scenarios in urban areas, including subways, trains, off-shore ferries and city buses. We have confirmed that mobility has largely negative impacts on the performance of HSPA networks, as fast-changing wireless environment causes serious service deterioration or even interruption. Meanwhile our field experiment results have shown unexpected new findings and thereby exposed new features of the mobile HSPA networks, which contradict commonly held views. We surprisingly find out that mobility can improve fairness of bandwidth sharing among users and traffic flows. Also the triggering and final results of handoffs in mobile HSPA networks are unpredictable and often inappropriate, thus calling for fast reacting fallover mechanisms. Moreover, we find that throughput performance does not monotonically decrease with increased mobility level. We have conducted in-depth research to furnish detailed analysis and explanations to what we have observed. We conclude that mobility is a double-edged sword for HSPA networks. To the best of our knowledge, this is the first public report on a large scale empirical study on the performance of commercial mobile HSPA networks. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.289 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.282 Cloud computing economically enables the paradigm of data service outsourcing. However, for protecting data privacy, sensitive cloud data has to be encrypted before outsourcing to the commercial public cloud, which makes effective data utilization service a very challenging task. Although traditional searchable encryption techniques allow users to securely search over encrypted data through keywords, they support only boolean search and are not yet sufficient to meet the effective data utilization need that is inherently demanded by large number of users and huge amount of data files in cloud. In this paper, we define and solve the problem of secure ranked keyword search over encrypted cloud data. Ranked search greatly enhances system usability by enabling search result relevance ranking instead of sending undifferentiated results and further ensures the file retrieval accuracy. Specifically, we explore the statistical measure approach, i.e. relevance score, from information retrieval to build a secure searchable index, and develop a one-to-many order-preserving mapping technique to properly protect those sensitive score information. The resulting design is able to facilitate efficient server-side ranking without losing keyword privacy. Thorough analysis shows that our proposed solution enjoys "as-strong-as-possible"; security guarantee compared to previous searchable encryption schemes, while correctly realizing the goal of ranked keyword search. Extensive experimental results demonstrate the efficiency of the proposed solution. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.282 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.280 Delay Tolerant Networks (DTNs) are characterized by nondeterministic mobility and connectivity. Message routing in DTNs usually employs a multi-copy 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 mini- mize 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 multi-copy 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 inter-meeting times, the delivery rates of OOF and OOF- can be 30% greater than the compared routing protocols. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.280 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.278 Evidence propagation is a major step in exact inference, a key problem in exploring probabilistic graphical models. In this paper, we propose a novel approach for parallelizing evidence propagation in junction trees on clusters. Our proposed method explores structural parallelism in a given junction tree. We decompose a junction tree into a set of subtrees, each consisting of one or multiple leaf-root paths in the junction tree. In evidence propagation, we first perform evidence collection in these subtrees concurrently. Then, the partially updated subtrees exchange data for junction tree merging, so that all the cliques in the junction tree can be fully updated for evidence collection. Finally, evidence distribution is performed in all the subtrees to complete evidence propagation. Since merging subtrees requires communication across processors, we propose a technique called bitmap partitioning to explore the tradeoff between bandwidth utilization efficiency and the overhead due to the startup latency of message passing. We implemented the proposed method using message passing interface (MPI) on a state-of-the-art Myrinet cluster consisting of 128 processors. Compared with a baseline method, our technique results in improved scalability. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.278 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.275 Interconnection networks with adaptive routing are susceptible to deadlock, which could lead to performance degradation or system failure. Detecting deadlocks at run-time is challenging because of their highly distributed characteristics. In this paper, we present a deadlock detection method that utilizes run-time transitive closure (TC) computation to discover the existence of deadlock-equivalence sets, which imply loops of requests in networks-on-chip (NoC). This detection scheme guarantees the discovery of all true-deadlocks without false alarms in contrast with state-of-the-art approximation and heuristic approaches. A distributed TC-network architecture, which couples with the NoC infrastructure, is also presented to realize the detection mechanism efficiently. Detailed hardware realization architectures and schematics are also discussed. Our results based on a cycle-accurate simulator demonstrate the effectiveness of the proposed method. It drastically outperforms timing-based deadlock detection mechanisms by eliminating false detections and, thus, reducing energy wastage in retransmission for various traffic scenarios including real-world application. We found that timing based methods may produce two orders of magnitude more deadlock alarms than the TC-network method. Moreover, the implementations presented in this paper demonstrate that the hardware overhead of TC-networks is insignificant. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.275 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.265 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 pre-specified 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. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.265 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.256 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 on-line 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, latter 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%, specially when handling large amounts of data. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.256 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.190 Most standard cluster interconnect technologies are flexible with respect to network topology. This has spawned a substantial amount of research on topology agnostic routing algo- rithms, which make no assumption about the network structure, thus providing the flexibility needed to route on irregular net- works. Actually, such an irregularity should be often interpreted as minor modifications of some regular interconnection pattern, such as those induced by faults. In fact, topology agnostic routing algorithms are also becoming increasingly useful for networks on-chip (NoC), where faults may make the preferred 2D mesh topology irregular. Existing topology agnostic routing algorithms were developed for varying purposes, giving them different and not always comparable properties. Details are scattered among many papers, each with distinct conditions, making comparison difficult. This paper presents a comprehensive overview of the known topology agnostic routing algorithms. We classify these algorithms by their most important properties, and evaluate them consis- tently. This provides significant insight into the algorithms and their appropriateness for different on and off chip environments. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.190 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.180 As sensor nodes are energy constrained, one challenge in wireless sensor networks (WSNs) is to guarantee information coverage and maximize network lifetime. In this paper, we leverage prediction to solve the problem by exploiting temporal-spatial correlations between sensory data. The basic idea lies in that a sensor node can be turned off safely when its sensory information can be inferred through some prediction methods, like Bayesian inference. We adopt the concept of entropy in information theory to evaluate the information uncertainty about the region of interest (RoI). We formulate the problem as a minimum weight submodular set cover problem, which is known to be NP hard. To address this problem, an efficient centralized algorithm, truncated greedy algorithm (TGA), is proposed. We prove theoretically the performance guarantee of TGA in terms of the ratio of aggregate weight obtained by TGA to that by the optimal algorithm. Due to the decentralization nature of WSNs, we proceed to design a distributed version of TGA, DTGA, which can obtain the same solution as TGA. The implementation issues such as network connectivity and communication cost are extensively discussed. We perform real data experiments as well as simulations to demonstrate the advantage of DTGA over existing algorithms and the impacts of different parameters associated with data correlations on the network lifetime. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.180 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.312 In this work, for a wireless sensor network (WSN) of $n$ randomly placed sensors with node density $\lambda \in [1,n]$, we study the tradeoffs between the \emph{aggregation throughput} and \emph{gathering efficiency}. The gathering efficiency refers to the ratio of the number of the sensors whose data have been gathered to the total number of sensors. Specifically, we design two efficient aggregation schemes, called \textit{single-hop-length} (SLH) scheme and \textit{multiple-hop-length} (MLH) scheme. By novelly integrating these two schemes, we theoretically prove that our protocol achieves the optimal tradeoffs, and derive the optimal aggregation throughput depending on a given threshold value (lower bound) on gathering efficiency. Particularly, we show that under the MLH scheme, for a practically important set of symmetric functions called \emph{divisible perfectly compressible} (DPC) functions, including the mean, max, or various kinds of indicator functions, \etc, the data from $\Theta(n)$ sensors can be aggregated to the sink at the throughput of a constant order $\Theta(1)$, implying that, our MLH scheme is indeed scalable. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.312 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.309 Virtual appliances store the required information to instantiate a functional virtual machine on Infrastructure as a Service (IaaS) cloud systems. Large appliance size obstructs IaaS systems to deliver dynamic and scalable infrastructures according to their promise. To overcome this issue, this article offers a novel technique for virtual appliance developers to publish appliances for the dynamic environments of IaaS systems. Our solution achieves faster virtual machine instantiation by reducing the appliance size while maintaining its key functionality. The new virtual appliance optimization algorithm identifies the removable parts of the appliance. Then, it applies active fault injection to remove the identified parts. Afterwards, our solution assesses the functionality of the reduced virtual appliance by applying the - appliance developer provided - validation algorithms. We also introduce a technique to parallelize the fault injection and validation phases of the algorithm. Finally, the prototype implementation of the algorithm is discussed to demonstrate the efficiency of the proposed algorithm through the optimization of two well-known virtual appliances. Results show that the algorithm significantly decreased virtual machine instantiation time and increased dynamism in IaaS systems. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.309 http://opac.ieeecomputersociety.org/opac?year=2012&volume=23&issue=02&acronym=tpds IEEE Transactions on Parallel and Distributed Systems http://www.computer.org/portal/site/tpds/ http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.307 Activity monitoring, a crucial task in many applications, is often conducted expensively using video cameras. Effectively monitoring a large field by analyzing images from multiple cameras remains a challenging issue. Other approaches generally require the tracking objects to attach special devices, which are infeasible in many scenarios. To address the issue, we propose to use RF tag arrays for activity monitoring, where data mining techniques play a critical role. The RFID technology provides an economically attractive solution due to the low cost of RF tags and readers. Another novelty of this design is that the tracking objects do not need to be equipped with any RF transmitters or receivers. By developing a practical fault-tolerant method, we offset the noise of RF tag data and mine frequent trajectory patterns as models of regular activities. Our empirical study using real RFID systems and data sets verifies the feasibility and the effectiveness of this design. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.307 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.306 We present a novel framework, CloudView, for storage, processing and analysis of massive machine maintenance data, collected from a large number of sensors embedded in industrial machines, in a cloud computing environment. This paper describes the architecture, design, and implementation of CloudView, and how the proposed framework leverages the parallel computing capability of a computing cloud based on a large-scale distributed batch processing infrastructure that is built of commodity hardware. A case-based reasoning (CBR) approach is adopted for machine fault prediction, where the past cases of failure from a large number of machines are collected in a cloud. A case-base of past cases of failure is created using the global information obtained from a large number of machines. CloudView facilitates organization of sensor data and creation of case-base with global information. Experimental measurements show that fault predictions can be done in real-time (on a timescale of seconds) at the local nodes and massive machine data analysis for case-base creation and updating can be done on a timescale of minutes in the cloud. Our approach, in addition to being the first reported use of the cloud architecture for maintenance data storage, processing and analysis, also evaluates several possible cloud-based architectures that leverage the advantages of the parallel computing capabilities of the cloud to make local decisions with global information efficiently, while avoiding potential data bottlenecks that can occur in getting the maintenance data in and out of the cloud. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.306 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.305 Wireless Sensor Network (WSN) is key for various applications involving long-term and low-cost monitoring and actuating. In these applications, sensor nodes use batteries as the sole energy source. Therefore, energy efficiency becomes critical. We observe that many WSN applications require redundant sensor nodes to achieve fault tolerance and Quality of Service (QoS) of the sensing. However, the same redundancy may not be necessary for multi-hop communication because of the light traffic load and the stable wireless links. In this paper, we present a novel sleep-scheduling technique called Virtual Backbone Scheduling (VBS). VBS is designed for WSNs has redundant sensor nodes. VBS forms multiple overlapped backbones which work alternatively to prolong the network lifetime. In VBS, traffic is only forwarded by backbone sensor nodes, and the rest of the sensor nodes turn off their radios to save energy. The rotation of multiple backbones makes sure that the energy consumption of all sensor nodes is balanced, which fully utilizes the energy and achieves a longer network lifetime than the existing techniques. The scheduling problem of VBS is formulated as the Maximum Lifetime Backbone Scheduling (MLBS) problem. Since the MLBS problem is NP-hard, we propose approximation algorithms based on the Schedule Transition Graph (STG) and Virtual Scheduling Graph (VSG). We also present an Iterative Local Replacement (ILR) scheme as a distributed implementation. Theoretical analyses and simulation studies verify that VBS is superior to the existing techniques. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.305 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.304 Traditional software-based barrier implementations for shared memory parallel machines tend to produce hot-spots in terms of memory and network contention as the number of processors increases. This could limit their applicability to future many-core CMPs in which possibly several dozens of cores would need to be synchronized efficiently. In this work, we develop GBarrier, a hardware-based barrier mechanism especially aimed at providing efficient barriers in future many-core CMPs. Our proposal deploys a dedicated G-line-based network to allow for fast and efficient signaling of barrier arrival and departure. Since GBarrier does not have any influence on the memory system, we avoid all coherence activity and barrier-related network traffic that traditional approaches introduce and that restrict scalability. Through detailed simulations of a 32-core CMP, we compare GBarrier against one of the most efficient software-based barrier implementations for a set of kernels and scientific applications. Evaluation results show average reductions of 54% and 21% in execution time, 53% and 18% in network traffic, and also 76% and 31% in the energy-delay2 product metric for the full CMP when the kernels and scientific applications, respectively, are considered. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.304 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.302 In wireless sensor networks, adversaries can make use of traffic information to locate the monitored objects, e.g., to hunt endangered animals or kill soldiers. In this paper, we first define a hotspot phenomenon that causes an obvious inconsistency in the network traffic pattern due to a large volume of packets originating from a small area. Second, we develop a realistic adversary model, assuming that the adver-sary can monitor the network traffic in multiple areas, rather than the entire network or only one area. Using this model, we introduce a novel attack called Hotspot-Locating where the adversary uses traffic analysis techniques to locate hotspots. Finally, we propose a cloud-based scheme for efficiently pro-tecting source nodes' location privacy against Hotspot-Locating attack by creating a cloud with an irregular shape of fake traffic, to counteract the inconsistency in the traffic pat-tern and camouflage the source node in the nodes forming the cloud. To reduce the energy cost, clouds are active only during data transmission and the intersection of clouds creates a larger merged cloud, to reduce the number of fake packets and also boost privacy preservation. Simulation and analyti-cal results demonstrate that our scheme can provide stronger privacy protection than routing-based schemes and requires much less energy than global-adversary-based schemes. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.302 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.301 Memoryless online routing (MOR) algorithms are suitable for the applications only using local information to find paths, and Delaunay triangulations are the class of geometric graphs widely proposed as network topologies. Motivated by these two facts, this paper reports a variety of new MOR algorithms that work for Delaunay triangulations, thus greatly enriching the family of such algorithms. This paper also evaluates and compares these new algorithms with three existing MOR algorithms. The experimental results shed light on their performance in terms of both Euclidean and link metrics, and also reveal certain properties of Delaunay triangulations. Finally, this paper poses three open problems, with their importance explained. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.301 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.300 The automation of today's large-scale industrial systems relies on the operation of distributed controller devices that perform local computations and exchange information via communication networks. The subject of this paper is the The automation of today';s large-scale industrial systems relies on the operation of distributed controller devices, that perform local computations and exchange information via communication networks. The subject of this paper is the development of a family of shared-medium industrial communication protocols, that support the transmission of real-time (RT) and non-real-time (nRT) data among distributed controller devices. Different from existing protocols, we suggest to incorporate information, that is available from the control application in the protocol definition. As a result, our protocols dynamically change the bandwidth allocation on the shared medium, according to the instantaneous communication requirements, while ensuring hard RT guarantees. Following the recent developments in industrial automation, our protocols can be realized as software layers on top of low-cost conventional Ethernet. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.300 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.299 The owner and users of a sensor network may be different, which necessitates privacy-preserving access control. On the one hand, the network owner need enforce strict access control so that the sensed data are only accessible to users willing to pay. On the other hand, users wish to protect their respective data access patterns whose disclosure may be used against their interests. This paper presents DP²AC, a Distributed Privacy-Preserving Access Control scheme for sensor networks, which is the first work of its kind. Users in DP²AC purchase tokens from the network owner whereby to query data from sensor nodes which will reply only after validating the tokens. The use of blind signatures in token generation ensures that tokens are publicly verifiable yet unlinkable to user identities, so privacy-preserving access control is achieved. A central component in DP²AC is to prevent malicious users from reusing tokens, for which we propose a suite of distributed token reuse detection (DTRD) schemes without involving the base station. These schemes share the essential idea that a sensor node checks with some other nodes (called witnesses) whether a token has been used, but they differ in how the witnesses are chosen. We thoroughly compare their performance with regard to TRD capability, communication overhead, storage overhead, and attack resilience. The efficacy and efficiency of DP²AC are confirmed by detailed performance evaluations. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.299 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.298 Design patterns for parallel computing attempt to make the field accessible to non-experts by generalizing the common techniques experts use to develop parallel software. Existing parallel patterns have tremendous descriptive power, but it is often unclear to non-experts how to choose a pattern based on the specific performance goals of a given application. This paper addresses the need for a pattern selection methodology by presenting four patterns and an accompanying decision framework for choosing from these patterns given an application's throughput and latency goals. The patterns are based on recognizing that one can partition an application's data or instructions and that these partitionings can be done in time or space, hence we refer to them as spatiotemporal partitioning strategies. This paper introduces a taxonomy that describes each of the resulting four partitioning strategies and presents a three-step methodology for selecting one or more given a throughput and latency goal. Several case studies are presented to illustrate the use of this methodology. These case studies cover several simple examples, as well as more complicated applications including a radar processing application and an H.264 video encoder. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.298 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.296 In this paper, we address the problem of balancing the network traffic load in a geographic hash table. Existing approaches allow balancing network load by changing the geo-routing protocol used to forward queries in the ght. However, this comes at the expense of considerably complicating the routing process. In this paper, we demonstrate that it is possible to balance network traffic load in a geographic hash table without changing the underlying geo-routing protocol. Instead of changing the (near) straight-line geo-routing protocol used to send a query from the node issuing the query (the source) to the node managing the queried key (the destination), we propose to "reverse engineer" the hash function used to store data in the network, implementing a sort of "load-aware" assignment of key ranges to wireless sensor nodes. This innovative methodology is instantiated into two specific approaches: an analytical one, in which the destination density function yielding quasi-perfect load balancing is analytically characterized under uniformity assumptions for what concerns location of nodes and query sources; and an iterative, heuristic approach that can be used whenever these uniformity assumptions are not fulfilled. In order to prove practicality of our load balancing methodology, we have performed extensive simulations resembling realistic wireless sensor network deployments showing the effectiveness of the two proposed approaches in considerably improving load balancing and extending network lifetime. Simulation results also show that our proposed technique achieves better load balancing than an existing approach based on modifying geo-routing. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.296 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.294 Recently, distributed data storage has gained increasing popularity for reliable access to data through redundancy spread over unreliable nodes in wireless sensor networks (WSNs). However, without any protection to guaran¬tee the data integrity and availability, the reliable data storage can not be achieved since sensor nodes are prone to various failures, and attackers may compromise sensor nodes to pollute or destroy the stored data. Therefore, how to design a robust sensor data storage scheme to efficiently guaran-tee the data integrity and availability becomes a critical issue for distributed storage networks. In this paper, we propose a distributed fault/intrusion-tolerant data storage scheme based on network coding and homomorphic fingerprinting in volatile WSNs environments. For high data availability, the proposed scheme uses network coding to encode the original data and distribute encoded fragments with original data pieces. With secure, compact, and efficient homomorphic fingerprinting, our scheme can fast locate incorrect fragments and then initialize data maintenance. Extensive theoretical analysis and simulative results demonstrate the efficacy and efficiency of the proposed scheme. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.294 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.293 Cooperative communication (CC) exploits space diversity through allowing multiple nodes cooperatively relay signals to the receiver so that the combined signal at the receiver can be correctly decoded. Since CC can reduce the transmission power and extend the transmission coverage, it has been considered in topology control protocols [1,2]. However, prior research on topology control with CC only focuses on maintaining the network connectivity, minimizing the transmission power of each node, whereas ignores the energy-efficiency of paths in constructed topologies. This may cause inefficient routes and hurt the overall network performance in cooperative ad hoc networks. In this paper, to address this problem, we introduce a new topology control problem: energy-efficient topology control problem with cooperative communication, and propose two topology control algorithms to build cooperative energy spanners in which the energy efficiency of individual paths are guaranteed. Both proposed algorithms can be performed in distributed and localized fashion while maintaining the globally efficient paths. Simulation results confirm the nice performance of all proposed algorithms. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.293 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.292 The Web Service Atomic Transactions (WS-AT) specification makes it possible for businesses to engage in standard distributed transaction processing on the Internet using Web Services technology. For such business applications, trustworthy coordination of WS-AT is crucial. In this paper, we explain how to render WS-AT coordination trustworthy by applying Byzantine fault tolerance (BFT) techniques. More specifically, we show how to protect the core services described in the WS-AT specification, namely, the Activation service, the Registration service, the Completion service, and the Coordinator service, against Byzantine faults. The main contribution of this work is that BFT techniques are not applied naively, which would be prohibitively expensive. Rather, the semantics of the various services in the WS-AT specification are exploited to minimize the use of Byzantine agreement. We have incorporated our BFT protocols and mechanisms into an open-source framework that implements the WS-AT specification. The resulting BFT framework for WS-AT is useful for business applications that are based on WS-AT and that require a high degree of dependability, security and trust. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.292 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.288 We show that the 2a×a rectangular twisted torus introduced by Cámara et al ("Twisted torus topologies for enhanced interconnection networks," IEEE Trans. Parallel Dist. Syst., vol. 21, no. 12, pp. 1765-1778, Dec. 2010) is edge decomposable into two Hamiltonian cycles. In the process, the 2a×a×a prismatic twisted torus is edge decomposable into three Hamiltonian cycles, and the 2a×a×a prismatic doubly twisted torus admits two edge-disjoint Hamiltonian cycles. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.288 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.287 Some of today's TM systems implement the two- phase-locking (2PL) algorithm which aborts transactions every time a conflict occurs. 2PL is a simple algorithm that provides fast transactional operations. However, it limits concurrency in benchmarks with high contention because it increases the rate of aborts. We propose the use of a more relaxed concurrency control algorithm to provide better concurrency. This algorithm is based on the conflict-serializability (CS) model. Unlike 2PL, it allows some transactions to commit successfully even when they make conflicting accesses. We implement this algorithm in a STM system and evaluate its performance on 16 cores using standard benchmarks. Our evaluation shows that the algorithm improves the performance of applications with long transactions and high abort rates. Throughput is improved by up to 2.99 times despite the overheads of testing for CS at run-time. These improvements come with little additional implementation complexity and re- quire no changes to the transactional programming model. We also propose an adaptive approach that switches between 2PL and CS to mitigate the overhead in applications that have low abort rates. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.287 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.286 The performance of data collection in Wireless Sensor Networks (WSNs) can be measured by network capacity. However, few existing works dedicatedly consider the Continuous Data Collection (CDC) capacity for WSNs under the protocol interference model. In this paper, we propose a multi-path scheduling algorithm for SDC in single-radio multi-channel WSNs and derive its network capacity which is a tighter lower bound compared with the previously best result [10]. We also propose a novel CDC method for dual-radio multi-channel WSNs. It significantly speeds up the data collection process, and achieves a capacity of $\frac{nW}{12M\left\lceil (3.63\rho^2 + c_3 \rho + c_4)/H \right\rceil}$ when $\Delta_e\le 12$ or $\frac{nW}{M\Delta_e\left\lceil (3.63\rho^2 + c_3 \rho + c_4)/H \right\rceil}$ when $\Delta_e >12$, where $n$ is the number of the sensors, $M$ is a constant value and usually $M \ll n$, $\Delta _e$ is the maximum number of the leaf nodes having a same parent in the data collection tree, $W$ is the channel bandwidth, $H$ is the number of available orthogonal channels, $\rho$ is the ratio of the interference radius over the transmission radius, $c_3 = \frac{8\pi}{\sqrt 3} + \pi + 2$, and $c_4 = \frac{8\pi}{\sqrt 3} + 2\pi + 6$. Extensive simulation results indicate that the proposed algorithms improve network capacity significantly compared with existing works. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.286 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.285 Average service time, quality-of-service and service reliability associated with heterogeneous parallel and distributed-computing systems (DCSs) are analytically characterized in a realistic setting for which tangible, stochastic communication delays are present with non-exponential distributions. The departure from the traditionally assumed exponential distributions for event times, such as task-execution times, communication arrival times and load-transfer delays, gives rise to a non-Markovian dynamical problem for which a novel age-dependent, renewal-based distributed queuing model is developed. Numerical examples offered by the model shed light on the operational and system settings for which the Markovian setting, resulting from employing an exponential-distribution assumption on the event times, yields inaccurate predictions. A key benefit of the model is that it offers a rigorous framework for devising optimal dynamic task-reallocation policies systematically in heterogeneous DCSs by optimally selecting the fraction of the excess loads that need to be exchanged among the servers, thereby controlling the degree of cooperative processing in a DCSs. Key results on performance prediction and optimization of DCSs are validated using Monte-Carlo simulation as well as experiments on a distributed-computing testbed. The scalability, in the number of servers, of the age-dependent model is studied and a linearly scalable analytical approximation is derived. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.285 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.284 This work introduces the Distributed Network Reachability (DNR) algorithm, a distributed system-level diagnosis algorithm that allows every node of a partitionable arbitrary topology network to determine which portions of the network are reachable and unreachable. DNR is the first distributed diagnosis algorithm that works in the presence of network partitions and healings caused by dynamic fault and repair events. Both crash and timing faults are assumed, and a faulty node is indistinguishable of a network partition. Every link is alternately tested by one of its adjacent nodes at subsequent testing intervals. Upon the detection of a new event, the new diagnostic information is disseminated to reachable nodes. New events can occur before the dissemination completes. Any time a new event is detected or informed, a working node may compute the network reachability using local diagnostic information. The bounded correctness of DNR is proved, including the bounded diagnostic latency, bounded start-up and accuracy. Simulation results are presented for several random and regular topologies, showing the performance of the algorithm under highly dynamic fault situations. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.284 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.283 Peer-to-peer (P2P) live video streaming systems have recently received substantial attention, with commercial deployment gaining increased popularity in the Internet. It is evident from our practical experiences with real-world systems that, it is not uncommon for hundreds of thousands of users to choose to join a program in the first few minutes of a live broadcast. Such a severe flash crowd phenomenon in live streaming poses significant challenges in the system design. In this paper, for the first time, we develop a mathematical model to: (1) capture the fundamental relationship between time and scale in P2P live streaming systems under a flash crowd, and (2) explore the design principle of population control to alleviate the impact of the flash crowd. We carry out rigorous analysis that brings forth an in-depth understanding on effects of the gossip protocol and peer dynamics. In particular, we demonstrate that there exists an upper bound on the system scale with respect to a time constraint. By trading peer startup delays in the initial stage of a flash crowd for system scale, we design a simple and flexible population control framework that can alleviate the flash crowd without the requirement of otherwise costly server deployment. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.283 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.281 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% off on average from the optimal (on real-world datasets derived from Google News) while being 3 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. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.281 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.279 Data access latency, a limiting factor in the performance of chip multiprocessors, grows significantly with the number of cores in non-uniform cache architectures with distributed cache banks. To mitigate this effect, we use a compiler-based approach to leverage data access locality to choose an optimized data placement and efficiently configure the on- chip network. The proposed experimental compiler framework employs novel compilation techniques to discover and represent multi-threaded memory access patterns (MMAPs). At run time, symbolic MMAPs are resolved and used by a partitioning algorithm to choose a partition of allocated memory blocks among the forked threads in the analyzed application. This partition is used to enforce data ownership by associating the data with the core that executes the thread owning the data. Based on the partition, the communication pattern of the application can be extracted. We demonstrate how this information can be used in an experimental architecture to accelerate applications. In particular, our compiler assisted data-partitioning approach shows a 20% speedup over shared caching and 5% speedup over the closest runtime approximation, first touch. By leveraging the communication pattern we can achieve a comparable performance to a system that uses a complex centralized network configuration system at runtime. Thus, our final system saves significant runtime complexity and achieves an 5.1% additional speedup through the addition of the reconfigurable network. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.279 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.277 Consider a wireless multi-hop network where nodes are randomly distributed in a given area following a homogeneous Poisson process. The hop count statistics, viz the probabilities related to the number of hops between two nodes, are important for performance analysis of the multi-hop networks. In this paper, we provide analytical results on the probability that two nodes separated by a known Euclidean distance are k hops apart in networks subject to both shadowing and small-scale fading. Some interesting results are derived which have generic significance. For example, it is shown that the locations of nodes three or more hops away provide little information in determining the relationship of a node with other nodes in the network. This observation is useful for the design of distributed routing, localization and network security algorithms. As an illustration of the application of our results, we derive the effective energy consumption per successfully transmitted packet in end-to-end packet transmissions. We show that there exists an optimum transmission range which minimizes the effective energy consumption. The results provide useful guidelines on the design of a randomly deployed network in a more realistic radio environment. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.277 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.274 Surveillance is a critical problem for harbor protection, border control or the security of commercial facilities. The effective protection of vast near-coast sea surfaces and busy harbor areas from intrusions of unauthorized marine vessels, such as pirates smugglers or, illegal fishermen is particularly challenging. In this paper, we present an innovative solution for ship intrusion detection. Equipped with three-axis accelerometer sensors, we deploy an experimental wireless sensor network on the sea's surface to detect ships. Using signal processing techniques and cooperative signal processing, we can detect any passing ships by distinguishing the ship-generated waves from the ocean waves. We design a three-tier intrusion detection system with which we propose to exploit spatial and temporal correlations of an intrusion to increase detection reliability. We conduct evaluations with real data collected in our initial experiments, and provide quantitative analysis of the detection system, such as the successful detection ratio, detection latency, and an estimation of an intruding vessel's velocity. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.274 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.267 In mobile-beacon assisted sensor localization, beacon mobility scheduling aims to determine best beacon trajectory so that each sensor receives sufficient beacon signals with minimum delay. We propose a novel DeteRministic dynamic bEAcon Mobility Scheduling (DREAMS) algorithm, without requiring any prior knowledge of the sensory field. In this algorithm, beacon trajectory is defined as the track of depth-first traversal (DFT) of the network graph, thus deterministic. The mobile beacon performs DFT dynamically, under the instruction of nearby sensors on the fly. It moves from sensor to sensor in an intelligent heuristic manner according to RSS (Received Signal Strength) based distance measurements. We prove that DREAMS guarantees full localization (every sensor is localized) when the measurements are noise-free and derive the upper bound of robot total moving distance in this case. Then we suggest to apply node elimination and topology control (Local Minimum Spanning Tree) to shorten beacon tour and reduce delay. Further, we extend DREAMS to multi-beacon scenarios. Beacons with different coordinate systems compete for localizing sensors. Loser beacons agree on winner beacon’s coordinate system, and become cooperative in subsequent localization. All sensors are finally localized in a commonly agreed coordinate system. Through simulation we show that DREAMS guarantees full localization even with noisy distance measurements. We evaluate its performance on localization delay and communication overhead in comparison with a previously proposed static path based scheduling method. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.267 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.264 Wireless sensor networks may be deployed in many applications to detect and track events of interest. Events can be either point events with an exact location and constant shape, or region events which cover a large area and have dynamic shapes. While both types of events have received attention, no event detection and tracking protocol in existing wireless sensor network research is able to identify and track region events with dynamic identities, which arise when events are created or destroyed through splitting and merging. In this paper, we propose DRAGON, an event detection and tracking protocol which is able to handle all types of events including region events with dynamic identities. DRAGON employs two physics metaphors: event center of mass, to give an approximate location to the event; and node momentum, to guide the detection of event merges and splits. Both detailed theoretical analysis and extensive performance studies of DRAGON's properties demonstrate that DRAGON's execution is distributed among the sensor nodes, has low latency, is energy efficient, is able to run on a wide array of physical deployments, and has performance which scales well with event size, speed, and count. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.264 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.263 In 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 and time. 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 areis 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. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.263 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.262 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 amongst 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. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.262 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.261 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(mn^1.5) 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(mn^1.5+m^3n) time, which is more efficient than the previous result of O(m^2n^2.5+mn^3) time. Besides, their maximal length is also minimized in the worst case. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.261 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.260 Wireless sensor networks (WSNs) have been widely used in many areas for critical infrastructure monitoring and information collection. While confidentiality of the message can be ensured through content encryption, it is much more difficult to adequately address source-location privacy (SLP). For WSNs, SLP service is further complicated by the nature that the sensor nodes generally consist of low-cost and low-power radio devices and computationally intensive cryptographic algorithms (such as public-key cryptosystems), and large scale broadcasting-based protocols may not be suitable. In this paper, we first propose criteria to quantitatively measure source-location information leakage in routing-based SLP protection schemes for WSNs. Through this model, we identify vulnerabilities of some well-known SLP protection schemes. We then propose a scheme to provide source-location privacy through routing to a randomly selected intermediate node (RSIN) and a network mixing ring (NMR). Our security analysis, based on the proposed criteria, shows that the proposed scheme can provide excellent SLP. Our comprehensive simulation results demonstrate that the proposed scheme is very efficient and can achieve a high message delivery ratio. We believe it can be used in many practical applications. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.260 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.259 In this paper, we propose a systematic approach to designing and deploying a RFID Assisted Navigation System (RFID-ANS) for VANETs. RFID-ANS consists of passive tags deployed on roads to provide navigation information while the RFID readers attached to the center of the vehicle bumper query the tag when passing by to obtain the data for navigation guidance. We analyze the design criteria of RFID-ANS and present the design of the RFID reader in detail to support vehicles at high speeds. We also jointly consider the scheduling of the read attempts and the deployment of RFID tags based on the navigation requirements to support seamless navigations. The estimation of the vehicle position and its accuracy are also investigated. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.259 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.258 The paper presents a programming language, DSystemJ, for dynamic distributed Globally Asynchronous Locally Synchronous (GALS) systems, its formal model of computation, formal syntax and semantics, its compilation and implementation. The language is aimed at dynamic distributed systems, which use socket based communication protocols for communicating between components. DSystemJ allows the creation and control at runtime of asynchronous processes called clock-domains, their mobility on a distributed execution platform, as well as the runtime reconfiguration of the system’s functionality and topology. As DSystemJ is based on a GALS model of computation and has a formal semantics, it offers very safe mechanisms for implementation of distributed systems, as well as potential for their formal verification. The details and principles of its compilation, as well as its required runtime support are described. The runtime support is implemented in the SystemJ GALS language that can be considered as a static subset of DSystemJ. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.258 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.257 As more and more multi-tier 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 macro-level 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 on-line performance data. In this paper, our contributions are three-fold. First, we propose a precise request tracing algorithm for multi-tier services of black boxes, which only uses application-independent knowledge. Second, we present a micro-level 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. 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. 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 policy is adopted, indicating that PreciseTracer is a promising tracing tool for large-scale production systems. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.257 http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.255 Out-of-order retirement of instructions has been shown to be an effective technique to increase the number of in-flight instructions. This form of runtime scheduling can reduce pipeline stalls caused by head-of-line blocking effects in the reorder buffer (ROB). Expanding the width of the instruction window can be highly beneficial to multiprocessors that implement a strict memory model, especially when both loads and stores encounter long latencies due to cache misses, and whose stalls must be overlapped with instruction execution to overcome the memory latencies. Based on the Validation Buffer (VB) architecture (a previously proposed out-of-order retirement, checkpoint-free architecture for single processors), this paper proposes a cost-effective, scalable, out-of-order retirement multiprocessor, capable of enforcing sequential consistency without impacting the design of the memory hierarchy or interconnect. Our simulation results indicate that utilizing a VB can speed up both relaxed and sequentially consistent in-order retirement in future multiprocessor systems by between 3% and 20%, depending on the ROB size. http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.255