8970759
Linux kernels as complex networks: A novel method to study evolution
In recent years, many graphs have turned out to be complex networks. This paper presents a novel method to study Linux kernel evolution — using complex networks to understand how Linux kernel modules evolve over time. After studying the node degree distribution and average path length of the call graphs corresponding to the kernel modules of 223 different versions (V1.1.0 to V2.4.35), we found that the call graphs of the file system and drivers module are scale-free small-world complex networks. In addition, both of the file system and drivers module exhibit very strong preferential attachment tendency. Finally, we proposed a generic method that could be used to find major structural changes that occur during the evolution of software systems.
14387828
Escape analysis for synchronization removal
In this paper we introduce our escape analysis framework for Java, which is a kind of flow-insensitive, inter-procedural, and context-sensitive data flow analysis. And we present an efficient static intra-procedural algorithm for inferring the set of types that can occur at runtime for each object. With intra-procedural type information, virtual method resolution, callee-stub inline, exception analysis, and thread allocation site analysis are implemented. Virtual method resolution and callee-stub inline effectively reduce the call graph and SCC (strongly connected components). In exception analysis, we present a more precise analysis algorithm, especially in the inter-procedural exception in SCC.Our escape analysis can be applied to the whole Java program and Java libraries to identify unnecessary synchronization in Java and remove them. We have developed an implementation on Intel's Open Runtime Platform. For our benchmarks, 7.3% to 99% (with an average of 54%) of synchronization operations are eliminated.
45075264
Multi-path GEM for Routing in Wireless Sensor Networks
Wireless sensor networks are expected to be used in many different applications such as disaster relief and environmental control. Efficient routing protocols need to be thoroughly studied before wireless sensor networks are widely deployed. GEM is an ingenious routing algorithm that is based on the idea of graph embedding. Using a well designed virtual coordinate system, GEM provides a remarkably simple route selection mechanism. However, GEM does not survive edge failures well. In this paper, we propose R-GEM and S-GEM that use the idea of GEM and improve its reliability performance significantly. Both of them outperform GEM in all of the experimental scenarios. Specifically, in the case that 2% of all edges in the network fail to transfer packets, when only disjoint pairs are taken into consideration, GEM leads to a path error rate of 10% while R-GEM and S-GEM only result in a path error rate of 2%.
9419059
TLDFS: A Distributed File System based on the Layered Structure
This paper presents a novel distributed file system TLDFS, which consists of two layers. One is the block device layer, which makes the distributed file system manage the consistency of data easily by choosing an appropriate granularity of lock. We implement the distributed interfaces and the new data organization at the block level, which is different from most distributed file systems. The other is the file system layer that consists of three parts: interconnecting module, locking module and distributed file system module. Our prototype system proves the feasibility of the two-layered structure and the experiments show several advantages of TLDFS.
2945869
Feature Subset Selection for Multi-class SVM Based Image Classification
Multi-class image classification can benefit much from feature subset selection. This paper extends an error bound of binary SVMs to a feature subset selection criterion for the multi-class SVMs. By minimizing this criterion, the scale factors assigned to each feature in a kernel function are optimized to identify the important features. This minimization problem can be efficiently solved by gradient-based search techniques, even if hundreds of features are involved. Also, considering that image classification is often a small sample problem, the regularization issue is investigated for this criterion, showing its robustness in this situation. Experimental study on multiple benchmark image data sets demonstrates the effectiveness of the proposed approach.
117675
Analysis of Deskew Signaling Via Adaptive Timing
This paper presents an adaptive timing method for analysis of deskew signaling in high-performance integrated systems. The proposed approach models the practical deskew schemes as an adaptive system to study the performance limit of deskew signaling. We investigate the statistical properties of optimal deskew, which can be considered as the theoretical limit of deskew signaling. This approach also allows us to study the related energy efficiency issues in deskew schemes. We determine the bound on energy efficiency subject to the performance constraint on deskew signaling. Simulation results show that the performance of practical deskew schemes in a 90-nm process is 23.2% away from the optimal deskew scheme, and the gap of energy efficiency is 51% above the bound.
2723209
An energy-efficient skew compensation technique for high-speed skew-sensitive signaling
Presented in this paper is an energy-efficient skew compensation technique referred to as the resistance-based distributed clock deskew (RDSK) technique. In comparison with the existing clock deskew techniques, the proposed RDSK technique achieves significant power reduction while maintaining effective in skew management. Furthermore, the proposed RDSK provides a better scalability for future technology scaling. Simulation results of an on-chip interconnect communication system with distributed receivers designed in a 0.10 /spl mu/m CMOS process demonstrate 20%-51% power reduction over the existing techniques. The proposed RDSK is an essential element of our adaptive timing framework where circuit performance can be adjusted adaptively in response to time-varying disturbances and uncertainties.
7977463
LiveBT: Providing Video-on-Demand Streaming Service over BitTorrent Systems
BitTorrent (BT) is one of the most popular Peer-to- Peer (P2P) protocols for delivering media files in the Internet today. Although BT is quite efficient for sharing and downloading files by using P2P swarming technique, the users have to download almost the whole media file before playing it. This is determined by the Rarest-Block-Download-First strategy of standard BT implementations, which is designed for fast delivery of files in the systems but not for streaming application. In this paper, we present LiveBT, a new protocol which supports video-on- demand streaming service and is totally compatible to the current BitTorrent protocol. LiveBT enables users to play hot movies shared in the BT systems smoothly just after 2-3 minutes of buffering time. We also develop the prototype of LiveBT and test the performance through the real BT download tasks of media files. By comparing our prototype with some popular BT clients claiming to support view-as- download service such as Bitcomet, we find that LiveBT spends a much shorter buffering time to play and achieves quite smooth playback performance.
14334349
Learning Cascaded Reduced-Set SVMs Using Linear Programming
This paper proposes a simple and efficient detection framework that uses reduced-set kernels. We first describe our approach which reduces the number of kernels. A convex optimization method is used for calculating the reduced sets. Following this, we propose a method that optimally designs the cascade. Our experimental results indicate that our method minimizes complexity regarding the number of kernels in the cascaded structure while preserving the low error rates. Our algorithm generates the optimal weight of kernels for each cascade stage. This proposed algorithm achieves high detection-rates at low computational cost.