Developing parallel applications on heterogeneous processors is facing the challenges of 'memory wall',due to limited capacity of local storage,limited bandwidth and long latency for memory access. Aiming at t...
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Developing parallel applications on heterogeneous processors is facing the challenges of 'memory wall',due to limited capacity of local storage,limited bandwidth and long latency for memory access. Aiming at this problem,a parallelization approach was proposed with six memory optimization schemes for CG,four schemes of them aiming at all kinds of sparse matrix-vector multiplication (SPMV) operation. Conducted on IBM QS20,the parallelization approach can reach up to 21 and 133 times speedups with size A and B,respectively,compared with single power processor element. Finally,the conclusion is drawn that the peak bandwidth of memory access on Cell BE can be obtained in SPMV,simple computation is more efficient on heterogeneous processors and loop-unrolling can hide local storage access latency while executing scalar operation on SIMD cores.
Spectrum trading is the promising method to improve spectrum efficiency from the perspective of economics. In this paper we propose a queueing-theory based spectrum trading model, where the primary user plays the serv...
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Spectrum trading is the promising method to improve spectrum efficiency from the perspective of economics. In this paper we propose a queueing-theory based spectrum trading model, where the primary user plays the server role providing spectrum to the secondary user who acts as the customer. The most significant challenge is how to optimize the spectrum trading model considering the server uncertainty which includes service state, service time, service area, service content and service price. We design a STACP queueing model according to the server attributes, so that the secondary user can choose the right queue quickly and reasonably according to its demand. Moreover, we further analyze the optimizing strategies for STACP model which can maximize the profit of the primary user and minimize the service cost of the secondary user. The simulation results demonstrate the analysis results.
A common way to construct a fault model is injecting the fault into the system and observing the subsequent symptoms, e. g. event logs. However, fault features would vary during the propagation period, and present dif...
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A common way to construct a fault model is injecting the fault into the system and observing the subsequent symptoms, e. g. event logs. However, fault features would vary during the propagation period, and present different symptoms at different stage of the fault propagation process. The exiting detection window based feature extraction methods can only identify the early symptoms of a fault, but fail to detect the latter symptoms and cause false alarms. To solve the problem, we present a fault feature extraction method, called Companion State Tracer (CSTracer), which consists of 3 integrated steps: (1) pre-process logs to remove the unrelated logs;(2) construct a general identifier for the early symptoms of a fault;(3) construct a finite state machine model for the fault to trace the latter symptoms. CSTracer can persistently monitor a fault after the fault has been identified. We have justified the effectiveness of CSTracer in an enterprise cloud system. Compared with the existing, the results show that CSTracer has a better detection accuracy.
Nowadays, more and more scientific applications are moving to cloud computing. The optimal deployment of scientific applications is critical for providing good services to users. Scientific applications are usually to...
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Nowadays, more and more scientific applications are moving to cloud computing. The optimal deployment of scientific applications is critical for providing good services to users. Scientific applications are usually topology-aware applications. Therefore, considering the topology of a scientific application during the development will benefit the performance of the application. However, it is challenging to automatically discover and make use of the communication pattern of a scientific application while deploying the application on cloud. To attack this challenge, in this paper, we propose a framework to discover the communication topology of a scientific application by pre-execution and multi-scale graph clustering, based on which the deployment can be optimized. Comprehensive experiments are conducted by employing a well-known MPI benchmark and comparing the performance of our method with those of other methods. The experimental results show the effectiveness of our topology-aware deployment method.
In the relay-trading mode of wireless cognitive radio networks the secondary user (SU) can achieve a promised spectrum access opportunity by relaying for the primary user (PU). How to utilize the exchanged resource ef...
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In the relay-trading mode of wireless cognitive radio networks the secondary user (SU) can achieve a promised spectrum access opportunity by relaying for the primary user (PU). How to utilize the exchanged resource efficiently and fairly is an interesting and practical problem. In this paper we proposed a cooperative spectrum sharing strategy (RT-CSS) for the relay-trading mode from the fairness view. The cooperative SUs are gathered in a cooperative sharing group (CSG), and contribution metric (CM) is proposed to measure each CSG member's contribution to CSG as well as benefit from CSG. The adjustment of CM can guarantee the fairness and efficiency of spectrum sharing. The numerical simulation shows that RT-CSS can achieve better performance than the sense-uncooperative mode.
The availability of computers and communication networks allows us to gather and analyse data on a far larger scale than previously. At present, it is believed that statistics is a suitable method to analyse networks ...
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The availability of computers and communication networks allows us to gather and analyse data on a far larger scale than previously. At present, it is believed that statistics is a suitable method to analyse networks with millions, or more, of vertices. The MATLAB language, with its mass of statistical functions, is a good choice to rapidly realize an algorithm prototype of complex networks. The performance of the MATLAB codes can be further improved by using graphic processor units (GPU). This paper presents the strategies and performance of the GPU implementation of a complex networks package, and the Jacket toolbox of MATLAB is used. Compared with some commercially available CPU implementations, GPU can achieve a speedup of, on average, 11.3x. The experimental result proves that the GPU platform combined with the MATLAB language is a good combination for complex network research.
Many real-world networks are found to be scale-free. However, graph partition technology, as a technology capable of parallel computing, performs poorly when scale-free graphs are provided. The reason for this is that...
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Many real-world networks are found to be scale-free. However, graph partition technology, as a technology capable of parallel computing, performs poorly when scale-free graphs are provided. The reason for this is that traditional partitioning algorithms are designed for random networks and regular networks, rather than for scale-free networks. Multilevel graph-partitioning algorithms are currently considered to be the state of the art and are used extensively. In this paper, we analyse the reasons why traditional multilevel graph-partitioning algorithms perform poorly and present a new multilevel graph-partitioning paradigm, top down partitioning, which derives its name from the comparison with the traditional bottom-up partitioning. A new multilevel partitioning algorithm, named betweenness-based partitioning algorithm, is also presented as an implementation of top-down partitioning paradigm. An experimental evaluation of seven different real-world scale-free networks shows that the betweenness-based partitioning algorithm significantly outperforms the existing state-of-the-art approaches.
Jamming attack can severely affect the performance of Wireless sensor networks (WSNs) due to the broadcast nature of wireless medium. In order to localize the source of the attacker, we in this paper propose a jammer ...
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Jamming attack can severely affect the performance of Wireless sensor networks (WSNs) due to the broadcast nature of wireless medium. In order to localize the source of the attacker, we in this paper propose a jammer localization algorithm named as Minimum-circlecovering based localization (MCCL). Comparing with the existing solutions that rely on the wireless propagation parameters, MCCL only depends on the location information of sensor nodes at the border of the jammed region. MCCL uses the plane geometry knowledge, especially the minimum circle covering technique, to form an approximate jammed region, and hence the center of the jammed region is treated as the estimated position of the jammer. Simulation results showed that MCCL is able to achieve higher accuracy than other existing solutions in terms of jammer's transmission range and sensitivity to nodes' density.
Human itineraries are often initiated by some general intentions and will be optimized after considering all kinds of constraints and available information. This paper proposes a category-based itinerary recommendatio...
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Human itineraries are often initiated by some general intentions and will be optimized after considering all kinds of constraints and available information. This paper proposes a category-based itinerary recommendation framework to help the user transfer from intentions to itinerary planning, which join physical trajectories and information of location based social networks. The main contributions are: (1) Build the category based activity scheduling model;(2) Design and implement the category tree based POI (point or interest) query strategy and algorithm;(3) Propose the Voronoi graph based GPS trajectory analysis method to build traffic information networks;(4) Combine social networks with traffic information networks to implement category based recommendation by ant colony algorithm. The study conducts experiments on datasets from FourSquare and GeoLife project. A test on satisfaction of recommended items is also performed. Results show that the satisfaction reaches 80% in average.
There is an increasing need to build scalable distributed systems over the Internet infrastructure. However the development of distributed scalable applications suffers from lack of a wide accepted virtual computing e...
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There is an increasing need to build scalable distributed systems over the Internet infrastructure. However the development of distributed scalable applications suffers from lack of a wide accepted virtual computing environment. Users have to take great efforts on the management and sharing of the involved resources over Internet, whose characteristics are intrinsic growth, autonomy and diversity. To deal with this challenge, Internet-based Virtual Computing Environment (iVCE) is proposed and developed to serve as a platform for distributed scalable applications over the open infrastructure, whose kernel mechanisms are on-demand aggregation and autonomic collaboration of resources. In this paper, we present a programming language for iVCE named Owlet. Owlet conforms with the conceptual model of iVCE, and exposes the iVCE to application developers. As an interaction language based on peer-to-peer content-based publish/subscribe scheme, Owlet abstracts the Internet as an environment for the roles to interact, and uses roles to build a relatively stable view of resources for the on-demand resource aggregation. It provides language constructs to use 1) distributed event driven rules to describe interaction protocols among different roles, 2) conversations to correlate events and rules into a common context, and 3) resource pooling to do fault tolerance and load balancing among networked nodes. We have implemented an Owlet compiler and its runtime environment according to the architecture of iVCE, and built several Owlet applications, including a peer-to-peer file sharing application. Experimental results show that, with iVCE, the separation of resource aggregation logic and business logic significantly eases the process of building scalable distributed applications.
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