Force directed approach is one of the most widely used methods in graph drawing research. However, the running time is increased intolerablely along with the enlargement of the graph size, which restricts the algorith...
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Force directed approach is one of the most widely used methods in graph drawing research. However, the running time is increased intolerablely along with the enlargement of the graph size, which restricts the algorithm's practicability. By the aid of GPU (graphics processing unit) computing platform, we can speed-up the graph layout with low cost, but the existing GPU implementation mainly employees an “one-by-one” style to update the vertex' coordination per iteration, which has a lower convergent rate than the “batch” style which is instead used commonly in traditional CPU implementation. As a result, the aesthetics of graph layout would be decreased if the total running time is restricted. It is hard to achieve both a high speedup factor of GPU over CPU and a high convergent rate in existing GPU computing implementation. In order to solve this problem partially, this paper presents two new strategies to implement the large-scale graph layout on CPU+GPU heteromerous platform to accelerate the force directed layout for graph drawing problem. The numerical computation results show that our GPU implementation can dramatically improve the performance of force-direct layout and is 20 times on a NVIDIA GeForce 9800 GT GPU at 1.44 GHz faster than the one on single-CPU core of Intel Pentium 4 PC at 3.0 GHz for the graph layout with moderate size (typically 1000 vertices).
As the wide application of multi-core processor architecture in the domain of high performance computing, fault tolerance for shared memory parallel programs becomes a hot spot of research. For years, checkpointing ha...
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Existing routing protocols for Wireless Mesh Networks (WMNs) are generally optimized with statistical link measures, while not addressing on the intrinsic uncertainty of wireless links. We show evidence that, with the...
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ISBN:
(纸本)9781424459889
Existing routing protocols for Wireless Mesh Networks (WMNs) are generally optimized with statistical link measures, while not addressing on the intrinsic uncertainty of wireless links. We show evidence that, with the transient link uncertainties at PHY and MAC layers, a pseudo-deterministic routing protocol that relies on average or historic statistics can hardly explore the full potentials of a multi-hop wireless mesh. We study optimal WMN routing using probing-based online anypath forwarding, with explicit consideration of transient link uncertainties. We show the underlying connection between WMN routing and the classic Canadian Traveller Problem (CTP) [1]. Inspired by a stochastic recoverable version of CTP (SRCTP), we develop a practical SRCTP-based online routing algorithm under link uncertainties. We study how dynamic next hop selection can be done with low cost, and derive a systematic selection order for minimizing transmission delay. We conduct simulation studies to verify the effectiveness of the SRCTP algorithms under diverse network configurations. In particular, compared to deterministic routing, reduction of end-to-end delay (51:15∼73:02%) and improvement on packet delivery ratio (99:76%) are observed.
Event-driven programming has been a relatively hot topic in distributed systems development. Having worked on these systems for years, we now believe that it is not the best choice. Besides the well-known "stack ...
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In order to improve the efficiency of the communication networks, we used the Kruskal algorithm and the Prim algorithm through algorithm comparison and analysis methods of data structure. A dynamic framework for the c...
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In this paper, we introduce a generic model to deal with the event matching problem of content-based publish/ subscribe systems over structured P2P overlays. In this model, we claim that there are three methods (event...
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Many applications demand distributing data with different contents efficiently in the network environment with unreliable links and a high node churn. Existing approaches mostly focus on optimizing either efficiency o...
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Many applications demand distributing data with different contents efficiently in the network environment with unreliable links and a high node churn. Existing approaches mostly focus on optimizing either efficiency or robustness of data distribution, and fail to ensure both of them simultaneously. In this paper, we propose Semantic Cast - a content-based data distribution approach over self-organizing semantic overlay networks. Semantic Cast maintains a self-organizing semantic overlay based on view exchange (called Crowd). In Crowd, each node seeks neighbors with more similar interests by periodically exchanging its neighbor list (called view) with a chosen neighbor. Through these nodes' self-organizing behavior, various interest communities emerge in the overlay. For data distribution over Crowd, Semantic Cast adopts random walk to route data between interest communities, and adopts flooding to disseminate data inside the interested communities. The experimental results show that compared to existing approaches, Semantic Cast can support efficient content-based data distribution in the unreliable and highly dynamic network environment.
Building distributed applications is difficult mostly because of concurrency management. Existing approaches primarily include events and threads. Researchers and developers have been debating for decades to prove whi...
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ISBN:
(纸本)9781424477548;9781424477555
Building distributed applications is difficult mostly because of concurrency management. Existing approaches primarily include events and threads. Researchers and developers have been debating for decades to prove which is superior. Although the conclusion is far from obvious, this long debate clearly shows that neither of them is perfect. One of the problems is that they are both complex and error-prone. Both events and threads need the programmers to explicitly manage concurrency, and we believe it is just the source of difficulties. In this paper, we propose a novel approach-automatic concurrency management by the runtime system. It dynamically analyzes the programs to discover potential concurrency opportunities; and it dynamically schedules the communication and the computation tasks, resulting in automatic concurrent execution. This approach is inspired by the instruction scheduling technologies used in modern microprocessors, which dynamically exploits instruction-level parallelism. However, hardware scheduling algorithms do not fit software in many aspects, thus we have to design a new scheme completely from scratch. automatic concurrency management is a runtime technique with no modification to the language, compiler or byte code, so it is good at backward compatibility. It is essentially a dynamic optimization for networking programs.
The efficiency of communication is a key factor to the performance of networking applications, and concurrent communication is an important approach to the efficiency of communication. However, many concurrency opport...
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The efficiency of communication is a key factor to the performance of networking applications, and concurrent communication is an important approach to the efficiency of communication. However, many concurrency opportunities are very difficult to exploit because they depend on some undeterministic conditions. If these conditions are highly predictable, speculative execution can be a very effective approach to cope with the uncertainties. Existing researches on speculation seldom target at networking systems, and none of them can handle the event-driven model that is very popular in such systems. In this paper, we propose Nexus, a novel speculation scheme that supports event-driven networking applications. Nexus analyzes the dependence relationship of events, and performs speculation according to the duality of events and threads. Evaluation on a prototype implementation of nexus shows that this approach can significantly reduces the time needed to complete an event-driven program.
Reputation systems provide a promising way to build trust relationships between users in distributed cooperation systems, such as file sharing, streaming, distributed computing and social network, through which a user...
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