Social coding paradigm is reshaping the distributed soft- ware development with a surprising speed in recent years. Github, a remarkable social coding community, attracts a huge number of developers in a short time. V...
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ISBN:
(纸本)9781450332248
Social coding paradigm is reshaping the distributed soft- ware development with a surprising speed in recent years. Github, a remarkable social coding community, attracts a huge number of developers in a short time. Various kinds of social networks are formed based on social activities among developers. Why this new paradigm can achieve such a great success in attracting external developers, and how they are connected in such a massive community, are interesting questions for revealing power of social coding paradigm. In this paper, we firstly compare the growth curves of project and user in GitHub with three traditional open source software communities to explore differences of their growth modes. We find an explosive growth of the users in GitHub and introduce the Diffusion of Innovation theory to illustrate intrinsic sociological basis of this phenomenon. Secondly, we construct follow-networks according to the follow behaviors among developers in GitHub. Finally, we present four typical social behavior patterns by mining follow-networks containing independence-pattern, group-pattern, star-pattern and hub-pattern. This study can provide several instructions of crowd collaboration to newcomers. According to the typical behavior patterns, the community manager could design corresponding assistive tools for developers. Copyright 2014 ACM.
The performance of an ad-hoc network is greatly limited by collisions due to hidden terminals. In this paper, we propose a receiver tracking contention (RTC) scheme, which achieves high throughput by allowing the rece...
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ISBN:
(纸本)9781479982172
The performance of an ad-hoc network is greatly limited by collisions due to hidden terminals. In this paper, we propose a receiver tracking contention (RTC) scheme, which achieves high throughput by allowing the receivers to assist for channel contention. In RTC, link is the basic unit for channel access contention. Specifically, transmitter is used to contend for the channel and receiver is used to announce the potential collision. Based on INT message coding scheme, transmitter and its corresponding receiver can be well coordinated. In such mechanism, hidden terminals are avoided and exposed terminals are encouraged to transmit simultaneously. Based on OFDM modulation, RTC packets several subcarriers as subcontention unit and operates channel contention over multiple subcontention units. Furthermore, each subcontention unit maintains a transmission set, where collision-free links are allowed to merged into the transmission set In this case, the transmission set of subcontention unit can be aggregated after each contention period. When the subcontention unit i is the smallest index of non-empty subcontention unit, the transmission set of unit i will win the channel contention and transmitters of unit i will start to transmit in the following data transmission period. Analysis and simulation results show that RTC achieves a notable throughput gain over Back2f as high as 190% through simulation.
In China, the expressway isn’t free. When a vehicle exits, the exit toll station needs to calculate the toll according to the vehicle trajectory obtained by sending a trajectory query task to the trajectory center re...
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Partitioning links rather than nodes is effective in overlapping community detection (OCD) on complex networks. However, it consumes high CPU and memory overheads because the volume of links is huge especially when th...
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ISBN:
(纸本)9781479986989
Partitioning links rather than nodes is effective in overlapping community detection (OCD) on complex networks. However, it consumes high CPU and memory overheads because the volume of links is huge especially when the network is rather complex. In this paper, we proposes a symmetric non-negative matrix factorization (SNMF) based link partition method called SNMF-Link to overcome this deficiency. In particular, SNMF-Link represents data in a lower-dimensional space spanned by the node-link incidence matrix. By solving a lighter SNMF problem, SNMF-Link learns the clustering indicators of each links. Since traditional multiplicative update rule (MUR) based optimization algorithm for SNMF suffers from slow convergence, we applied the augmented Lagrangian method (ALM) to efficiently optimize SNMF. Experimental results show that SNMF-Link is much more efficient than the representative clustering algorithms without reducing the OCD performance.
Asynchrony based overlapping of computation and communication is commonly used in MPI applications. However, this overlapping introduces synchronization errors frequently in asynchronous MPI programming. In this paper...
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The growing interest in wireless mobile network techniques has resulted in many routing protocol proposals. The unpredictable motion and the unreliable behavior of mobile nodes is one of the key issues in wireless mob...
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In this paper, we present a novel stochastic analyzing model for e2e virtualized cloud services using hierarchical Quasi-Birth Death structures (QBDs). We divide the overall virtualized cloud services into three sub-h...
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This paper proposes an array receiving scheme for ultra-wideband (UWB) OFDM signals in WSN networks. The major feature of the proposed scheme is recovering the UWB OFDM signal by frequency stitching. Firstly, the UWB ...
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Non-negative matrix factorization (NMF) is a powerful dimension reduction method and has been widely used in many pattern recognition and computer vision problems. However, conventional NMF methods are neither robust ...
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ISBN:
(纸本)9781479919611
Non-negative matrix factorization (NMF) is a powerful dimension reduction method and has been widely used in many pattern recognition and computer vision problems. However, conventional NMF methods are neither robust enough as their loss functions are sensitive to outliers, nor discriminative because they completely ignore labels in a dataset. In this paper, we proposed a correntropy supervised NMF (CSNMF) to simultaneously overcome aforementioned deficiencies. In particular, CSNMF maximizes the correntropy between the data matrix and its reconstruction in low-dimensional space to inhibit outliers during learning the subspace, and narrows the minimizes the distances between coefficients of any two samples with the same class labels to enhance the subsequent classification performance. To solve CSNMF, we developed a multiplicative update rules and theoretically proved its convergence. Experimental results on popular face image datasets verify the effectiveness of CSNMF comparing with NMF, its supervised variants, and its robustified variants.
Resource allocation for multi-user across multiple data centers is an important problem in cloud computing environments. Many geographically-distributed users may request virtualized resources simultaneously. And the ...
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