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Currently, with the booming growth of cloud computing, workloads from broad ranges of functions and demands are crammed into a single physical machine. They lay considerable stress on the need of evolution of the operating system underneath, especially the memory subsystem. Even enhancing large pages with main memory compression is not intuitively straightforward due to rigid rules imposed by the state-of-the-art manager Buddy System from the beginning of the design. To relieve the aforementioned problems and provide broader design space for system designers, we propose Zweilous, a clean slate physical memory management framework. It is self-contained, highly decoupled, and thus can co-exist with the vanilla memory manager. Separate self-contained metadata/functions guarantee a flexible extension with little modification to current frameworks. To show it is easy to add enhanced functions that accelerate the evolution of the memory management subsystem, we implement Hzmem, a new large page memory manager redesign enhanced with the function of main memory compression. Our method achieves competitive performance compared with native and virtualized large page support, effective memory size increased and fewer impacts on other parts of the operating system. [ABSTRACT FROM AUTHOR]

A large amount of valuable information resides in a decentralized attributed social graph, where each user locally maintains a limited view of the graph. However, there exists a conflicting requirement between publishing an attributed social graph and protecting the privacy of sensitive information contained in each user’s local data. In this paper, we aim to collect and generate attributed social graphs in a decentralized manner while providing local differential privacy (LDP) for the collected data. Existing LDP-based synthetic graph generation methods either fail to preserve important graph properties (such as modularity and clustering coefficient) due to excessive noise injection or are unable to process attribute data, thus limiting their adoption and applicability. To overcome these weaknesses, we propose AsgLDP, a novel technique to generate privacy-preserving attributed graph data while satisfying LDP. AsgLDP preserves various graph properties through carefully designing the injected noise and estimating the joint distribution of attribute data. There are two key steps in AsgLDP: 1) collecting and generating graph data while satisfying LDP, and 2) optimizing the privacy-utility tradeoff of the generated data while preserving general graph properties such as the degree distribution, community structure and attribute distribution. Through theoretical analysis as well as experiments over 6 real-world datasets, we demonstrate the effectiveness of AsgLDP in preserving general graph properties such as degree distribution, community structure and attributed community search, while rigorously satisfying LDP. We also show that AsgLDP achieves a superior balance between utility and privacy as compared to the state-of-the-art approaches. [ABSTRACT FROM AUTHOR]

Point set filtering, which aims at reconstructing noise-free point sets from their corresponding noisy inputs, is a fundamental problem in 3D geometry processing. The main challenge of point set filtering is to preserve geometric features of the underlying geometry while at the same time removing the noise. State-of-the-art point set filtering methods still struggle with this issue: some are not designed to recover sharp features, and others cannot well preserve geometric features, especially fine-scale features. In this paper, we propose a novel approach for robust feature-preserving point set filtering, inspired by the Gaussian Mixture Model (GMM). Taking a noisy point set and its filtered normals as input, our method can robustly reconstruct a high-quality point set which is both noise-free and feature-preserving. Various experiments show that our approach can soundly outperform the selected state-of-the-art methods, in terms of both filtering quality and reconstruction accuracy. [ABSTRACT FROM AUTHOR]

With the advantages of low latency, high performance, and low power consumption, solid state drives (SSDs) have been widely deployed as the cache layer between memory and back-end low-speed storage devices to narrow the performance gap between CPU and storage system. However, in virtualization environment, the high integration of virtual machines can introduce a lot of duplicate data blocks in the cache device. Existing cache architectures and replacement algorithms rarely take this situation into consideration. This greatly limits the efficient use of the cache device. For this case, we proposed a duplication-aware SSD-based cache architecture. In this architecture, duplicate data blocks can be significantly reduced, and the utilization efficiency of the cache device will be notably improved. Furthermore, to reduce the cache replacement overhead, we also proposed an improved adaptive replacement cache (ARC)-based replacement strategy, which we named D-ARC. Experiment results show that, in some situations, our cache architecture can improve the cache hit ratio by five times, reduce the average I/O latency by 63%, and eliminate SDD writes by 81%. Compared with the ARC-based replacement strategy, D-ARC can provide a performance improvement by about 16% if the configuration is set appropriately. [ABSTRACT FROM PUBLISHER]

As we enter the era of many-core, providing the shared memory abstraction through cache coherence has become progressively difficult. The standard directory-based coherence does not scale well with increasing core count. Timestamp-based hardware coherence protocols introduced recently offer an attractive alternative solution. This paper proposes a timestamp-based coherence protocol, called TC-Release++ , that efficiently supports cache coherence in large-scale systems. Our approach is inspired by TC-Weak, a recently proposed timestamp-based coherence protocol targeting GPU architectures. We first design TC-Release in an attempt to straightforwardly port TC-Weak to general-purpose many-cores. But re-purposing TC-Weak for general-purpose many-core architectures is challenging due to significant differences both in architecture and the programming model. Indeed the performance of TC-Release turns out to be worse than conventional directory protocols. We overcome the limitations and overheads of TC-Release by exploiting simple hardware support to eliminate frequent memory stalls, and an optimized lifetime prediction mechanism to improve cache performance. The resulting optimized coherence protocol TC-Release++ is highly scalable (storage scales logarithmically with core count) and shows better performance (3.0 percent) and comparable network traffic (within 1.3 percent) relative to the baseline MESI directory protocol. We use Murphi to formally verify that TC-Release ++ is error-free and imposes small verification cost. [ABSTRACT FROM PUBLISHER]

Vehicular ad-hoc networks (VANETs) have drawn much attention of researchers. The vehicles in VANETs frequently join and leave the networks, and therefore restructure the network dynamically and automatically. Forwarded messages in vehicular ad-hoc networks are primarily multimedia data, including structured data, plain text, sound, and video, which require access control with efficient privacy preservation. Ciphertext-policy attribute-based encryption (CP-ABE) is adopted to meet the requirements. However, solutions based on traditional CP-ABE suffer from challenges of the limited computational resources on-board units equipped in the vehicles, especially for the complex policies of encryption and decryption. In this paper, we propose a CP-ABE delegation scheme, which allows road side units (RSUs) to perform most of the computation, for the purpose of improving the decryption efficiency of the vehicles. By using decision tree to jointly optimize multiple factors, such as the distance from RSU, the communication and computational cost, the CP-ABE delegation scheme is adaptively activated based on the estimation of various vehicles decryption overhead. Experimental results thoroughly demonstrate that our scheme is effective and efficient for multimedia data forwarding in vehicular ad-hoc networks with privacy preservation. [ABSTRACT FROM PUBLISHER]

Virtualization technology enables multiple virtual machines (VMs) to share a single physical server. Commercial servers increasingly use the nonuniform memory access (NUMA) architecture due to its scalable memory performance. However, multiple VMs running on a NUMA physical server will cause performance overheads such as remote memory access latency and shared microarchitectural resource contention, which makes the VM performance less efficient and stable. These performance overheads are mainly caused by memory traffic from data-intensive workloads. In this paper, we propose a traffic-aware VM optimization (TAVO) scheme on NUMA systems. Based on the performance monitoring of the data traffic and CPU/memory resource usages in the system, TAVO addresses VM memory access locality and shared resource contention problems via automatic VM initial placement and NUMA-aware VM online scheduling. Our experimental results show that TAVO improves VM performance in terms of benchmark runtime by up to 22.6% compared with the default KVM CFS scheduler. TAVO also achieves a much stable performance with benchmark's average runtime variation under 3%. [ABSTRACT FROM PUBLISHER]

Cu(In, Ga)Se2 solar cells are the representative of high efficient thin-film solar cell with energy conversion efficiency of over 22%. However, nowadays, top electrodes of solar cells gradually become the performance limitation for optimized devices. The Al-doped ZnO thin film is widely used as a transparent top electrode in Cu(In, Ga)Se2, but there are still some techniques and electrical property issues. In this letter, we establish a ZnO/Ag/ZnO:Al multilayer top electrode, composed of ZnO nanorod arrays, Ag nanoparticles, and ZnO:Al thin films. Such multilayer top electrode was applied on Cu(In, Ga)Se2 thin-film solar cells and the devices yield a higher efficiency from 6.79% to 8.52%. Importantly, we also propose that the enhanced electronic carrier concentration in such ZnO/Ag/ZnO:Al top electrode aids the performance of solar cells. Therefore, well-designed ZnO-based top electrodes offer the opportunity to remove the bottleneck of improving the solar cell efficiency. [ABSTRACT FROM PUBLISHER]

In recent years researchers have made noticeable progresses in mesh denoising, that is, recovering high-quality 3D models from meshes corrupted with noise (raw or synthetic). Nevertheless, these state of the art approaches still fall short for robustly handling various noisy 3D models. The main technical challenge of robust mesh denoising is to remove noise while maximally preserving geometric features. In particular, this issue becomes more difficult for models with considerable amount of noise. In this paper we present a novel scheme for robust feature-preserving mesh denoising. Given a noisy mesh input, our method first estimates an initial mesh, then performs feature detection, identification and connection, and finally, iteratively updates vertex positions based on the constructed feature edges. Through many experiments, we show that our approach can robustly and effectively denoise various input mesh models with synthetic noise or raw scanned noise. The qualitative and quantitative comparisons between our method and the selected state of the art methods also show that our approach can noticeably outperform them in terms of both quality and robustness. [ABSTRACT FROM PUBLISHER]

Mobile virtualization has emerged fairly recently and is considered a valuable way to mitigate security risks on Android devices. However, major challenges in mobile virtualization include runtime, hardware, resource overhead, and compatibility. In this paper, we propose a lightweight Android virtualization solution named Condroid , which is based on container technology. Condroid utilizes resource isolation based on namespaces feature and resource control based on cgroups feature. By leveraging them, Condroid can host multiple independent Android virtual machines on a single kernel to support mutilple Android containers. Furthermore, our implementation presents both a system service sharing mechanism to reduce memory utilization and a filesystem sharing mechanism to reduce storage usage. The evaluation results on Google Nexus 5 demonstrate that Condroid is feasible in terms of runtime, hardware resource overhead, and compatibility. Therefore, we find that Condroid has a higher performance than other virtualization solutions. [ABSTRACT FROM AUTHOR]

This article discusses the use of digital heritage in preserving and presenting natural and cultural heritage by preservation specialists and computer scientists. The author describes how animations, computer games, and virtual reality (VR) were applied to China's Jing-Hang Grand Canal (Da Yunhe in Chinese). The techniques in building the virtual canal are presented as well as some screenshots of the virtual grand canal itself.