Henk J. Sips

The bittorrent p2p file-sharing system: measurements and analysis

Of the many P2P file-sharing prototypes in existence, BitTorrent is one of the few that has managed to attract millions of users. BitTorrent relies on other (global) components for file search, employs a moderator system to ensure the integrity of file data, and uses a bartering technique for downloading in order to prevent users from freeriding. In this paper we present a measurement study of BitTorrent in which we focus on four issues, viz. availability, integrity, flashcrowd handling, and download performance. The purpose of this paper is to aid in the understanding of a real P2P system that apparently has the right mechanisms to attract a large user community, to provide measurement data that may be useful in modeling P2P systems, and to identify design issues in such systems.

TRIBLER: a social-based peer-to-peer system

Most current peer‐to‐peer (P2P) file‐sharing systems treat their users as anonymous, unrelated entities, and completely disregard any social relationships between them. However, social phenomena such as friendship and the existence of communities of users with similar tastes or interests may well be exploited in such systems in order to increase their usability and performance. In this paper we present a novel social‐based P2P file‐sharing paradigm that exploits social phenomena by maintaining social networks and using these in content discovery, content recommendation, and downloading. Based on this paradigms main concepts such as taste buddies and friends, we have designed and implemented the TRIBLER P2P file‐sharing system as a set of extensions to BitTorrent. We present and discuss the design of TRIBLER, and we show evidence that TRIBLER enables fast content discovery and recommendation at a low additional overhead, and a significant improvement in download performance. Copyright

Dynamic voltage scaling on a low-power microprocessor

Power consumption is the limiting factor for the functionality of future wearable devices. Since interactive applications like wireless information access generate bursts of activities, it is important to match the performance of the wearable device accordingly. This paper describes a system with a microprocessor whose speed can be varied (frequency scaling) as well as its supply voltage. Voltage scaling is important for reducing power consumption to very low values when operating at low speeds. Measurements show that the energy per instruction at minimal speed is 1/5 of the energy required at full speed. The frequency and voltage can be scaled dynamically from user space in only 140 μs. This allows power-aware applications to quickly adjust the performance level of the processor whenever the workload changes. Experiments with an H.263 video benchmark show that the power-aware decoder outperforms a static fixed-frequency policy as well as a dynamic interval-based scheduler.

A Comprehensive Performance Comparison of CUDA and OpenCL

This paper presents a comprehensive performance comparison between CUDA and OpenCL. We have selected 16 benchmarks ranging from synthetic applications to real-world ones. We make an extensive analysis of the performance gaps taking into account programming models, ptimization strategies, architectural details, and underlying compilers. Our results show that, for most applications, CUDA performs at most 30\% better than OpenCL. We also show that this difference is due to unfair comparisons: in fact, OpenCL can achieve similar performance to CUDA under a fair comparison. Therefore, we define a fair comparison of the two types of applications, providing guidelines for more potential analyses. We also investigate OpenCLs portability by running the benchmarks on other prevailing platforms with minor modifications. Overall, we conclude that OpenCLs portability does not fundamentally affect its performance, and OpenCL can be a good alternative to CUDA.

Give-to-Get : free-riding resilient video-on-demand in P2P systems

Centralised solutions for Video-on-Demand (VoD) services, which stream pre-recorded video content to multiple clients who start watching at the moments of their own choosing, are not scalable because of the high bandwidth requirements of the central video servers. Peer-to-peer (P2P) techniques which let the clients distribute the video content among themselves, can be used to alleviate this problem. However, such techniques may introduce the problem of free-riding, with some peers in the P2P network not forwarding the video content to others if there is no incentive to do so. When the P2P network contains too many free-riders, an increasing number of the well-behaving peers may not achieve high enough download speeds to maintain an acceptable service. In this paper we propose Give-to-Get, a P2P VoD algorithm which discourages free-riding by letting peers favour uploading to other peers who have proven to be good uploaders. As a consequence, free-riders are only tolerated as long as there is spare capacity in the system. Our simulations show that even if 20% of the peers are free-riders, Give-to-Get continues to provide good performance to the well-behaving peers. In particular, they show that Give-to-Get performs very well for short videos, which dominate the current VoD traffic on the Internet.

The distributed ASCI Supercomputer project

The Distributed ASCI Supercomputer (DAS) is a homogeneous wide-area distributed system consisting of four cluster computers at different locations. DAS has been used for research on communication software, parallel languages and programming systems, schedulers, parallel applications, and distributed applications. The paper gives a preview of the most interesting research results obtained so far in the DAS project.

Hybrid rate control for IEEE 802.11

Streaming multimedia content in real-time over a wireless link is a challenging task because of the rapid fluctuations in link conditions that can occur due to movement, interference, and so on. The popular IEEE 802.11 standard includes low-level tuning parameters like the transmission rate. Standard device drivers for todays wireless products are based on gathering statistics, and consequently, adapt rather slowly to changes in conditions. To meet the strict latency requirements of streaming applications, we designed and implemented an advanced control algorithm that uses signal-strength (SNR) information to achieve fast responses. Since SNR readings are quite noisy we do not use that information to directly control the rate setting, but rather as a safeguard limiting the range of feasible settings to choose from. We report on real-time experiments involving two laptops equipped with IEEE 802.11a wireless interface cards. The results show that using SNR information greatly enhances responsiveness in comparison to statistics-based rate controllers.

Euro-Par 2009 Parallel Processing

Abstracts Invited Talks.- Multicore Programming Challenges.- Ibis: A Programming System for Real-World Distributed Computing.- What Is in a Namespace?.- Topic 1: Support Tools and Environments.- Atune-IL: An Instrumentation Language for Auto-tuning Parallel Applications.- Assigning Blame: Mapping Performance to High Level Parallel Programming Abstractions.- A Holistic Approach towards Automated Performance Analysis and Tuning.- Pattern Matching and I/O Replay for POSIX I/O in Parallel Programs.- An Extensible I/O Performance Analysis Framework for Distributed Environments.- Grouping MPI Processes for Partial Checkpoint and Co-migration.- Process Mapping for MPI Collective Communications.- Topic 2: Performance Prediction and Evaluation.- Stochastic Analysis of Hierarchical Publish/Subscribe Systems.- Characterizing and Understanding the Bandwidth Behavior of Workloads on Multi-core Processors.- Hybrid Techniques for Fast Multicore Simulation.- PSINS: An Open Source Event Tracer and Execution Simulator for MPI Applications.- A Methodology to Characterize Critical Section Bottlenecks in DSM Multiprocessors.- Topic 3: Scheduling and Load Balancing.- Dynamic Load Balancing of Matrix-Vector Multiplications on Roadrunner Compute Nodes.- A Unified Framework for Load Distribution and Fault-Tolerance of Application Servers.- On the Feasibility of Dynamically Scheduling DAG Applications on Shared Heterogeneous Systems.- Steady-State for Batches of Identical Task Trees.- A Buffer Space Optimal Solution for Re-establishing the Packet Order in a MPSoC Network Processor.- Using Multicast Transfers in the Replica Migration Problem: Formulation and Scheduling Heuristics.- A New Genetic Algorithm for Scheduling for Large Communication Delays.- Comparison of Access Policies for Replica Placement in Tree Networks.- Scheduling Recurrent Precedence-Constrained Task Graphs on a Symmetric Shared-Memory Multiprocessor.- Energy-Aware Scheduling of Flow Applications on Master-Worker Platforms.- Topic 4: High Performance Architectures and Compilers.- Last Bank: Dealing with Address Reuse in Non-Uniform Cache Architecture for CMPs.- Paired ROBs: A Cost-Effective Reorder Buffer Sharing Strategy for SMT Processors.- REPAS: Reliable Execution for Parallel ApplicationS in Tiled-CMPs.- Impact of Quad-Core Cray XT4 System and Software Stack on Scientific Computation.- Topic 5: Parallel and Distributed Databases.- Unifying Memory and Database Transactions.- A DHT Key-Value Storage System with Carrier Grade Performance.- Selective Replicated Declustering for Arbitrary Queries.- Topic 6: Grid, Cluster, and Cloud Computing.- POGGI: Puzzle-Based Online Games on Grid Infrastructures.- Enabling High Data Throughput in Desktop Grids through Decentralized Data and Metadata Management: The BlobSeer Approach.- MapReduce Programming Model for .NET-Based Cloud Computing.- The Architecture of the XtreemOS Grid Checkpointing Service.- Scalable Transactions for Web Applications in the Cloud.- Provider-Independent Use of the Cloud.- MPI Applications on Grids: A Topology Aware Approach.- Topic 7: Peer-to-Peer Computing.- A Least-Resistance Path in Reasoning about Unstructured Overlay Networks.- SiMPSON: Efficient Similarity Search in Metric Spaces over P2P Structured Overlay Networks.- Uniform Sampling for Directed P2P Networks.- Adaptive Peer Sampling with Newscast.- Exploring the Feasibility of Reputation Models for Improving P2P Routing under Churn.- Selfish Neighbor Selection in Peer-to-Peer Backup and Storage Applications.- Zero-Day Reconciliation of BitTorrent Users with Their ISPs.- Surfing Peer-to-Peer IPTV: Distributed Channel Switching.- Topic 8: Distributed Systems and Algorithms.- Distributed Individual-Based Simulation.- A Self-stabilizing K-Clustering Algorithm Using an Arbitrary Metric.- Active Optimistic Message Logging for Reliable Execution of MPI Applications.- Topic 9: Parallel and Distributed Programming.- A Parallel Numerical Library for UPC.- A Multilevel Parallelization Framework for High-Order Stencil Computations.- Using OpenMP vs. Threading Building Blocks for Medical Imaging on Multi-cores.- Parallel Skeletons for Variable-Length Lists in SkeTo Skeleton Library.- Stkm on Sca: A Unified Framework with Components, Workflows and Algorithmic Skeletons.- Grid-Enabling SPMD Applications through Hierarchical Partitioning and a Component-Based Runtime.- Reducing Rollbacks of Transactional Memory Using Ordered Shared Locks.- Topic 10: Parallel Numerical Algorithms.- Wavelet-Based Adaptive Solvers on Multi-core Architectures for the Simulation of Complex Systems.- Localized Parallel Algorithm for Bubble Coalescence in Free Surface Lattice-Boltzmann Method.- Fast Implicit Simulation of Oscillatory Flow in Human Abdominal Bifurcation Using a Schur Complement Preconditioner.- A Parallel Rigid Body Dynamics Algorithm.- Optimized Stencil Computation Using In-Place Calculation on Modern Multicore Systems.- Parallel Implementation of Runge-Kutta Integrators with Low Storage Requirements.- PSPIKE: A Parallel Hybrid Sparse Linear System Solver.- Out-of-Core Computation of the QR Factorization on Multi-core Processors.- Adaptive Parallel Householder Bidiagonalization.- Topic 11: Multicore and Manycore Programming.- Tile Percolation: An OpenMP Tile Aware Parallelization Technique for the Cyclops-64 Multicore Processor.- An Extension of the StarSs Programming Model for Platforms with Multiple GPUs.- StarPU: A Unified Platform for Task Scheduling on Heterogeneous Multicore Architectures.- XJava: Exploiting Parallelism with Object-Oriented Stream Programming.- JCUDA: A Programmer-Friendly Interface for Accelerating Java Programs with CUDA.- Fast and Efficient Synchronization and Communication Collective Primitives for Dual Cell-Based Blades.- Searching for Concurrent Design Patterns in Video Games.- Parallelization of a Video Segmentation Algorithm on CUDA-Enabled Graphics Processing Units.- A Parallel Point Matching Algorithm for Landmark Based Image Registration Using Multicore Platform.- High Performance Matrix Multiplication on Many Cores.- Parallel Lattice Basis Reduction Using a Multi-threaded Schnorr-Euchner LLL Algorithm.- Efficient Parallel Implementation of Evolutionary Algorithms on GPGPU Cards.- Topic 12: Theory and Algorithms for Parallel Computation.- Implementing Parallel Google Map-Reduce in Eden.- A Lower Bound for Oblivious Dimensional Routing.- Topic 13: High-Performance Networks.- A Case Study of Communication Optimizations on 3D Mesh Interconnects.- Implementing a Change Assimilation Mechanism for Source Routing Interconnects.- Dependability Analysis of a Fault-Tolerant Network Reconfiguring Strategy.- RecTOR: A New and Efficient Method for Dynamic Network Reconfiguration.- NIC-Assisted Cache-Efficient Receive Stack for Message Passing over Ethernet.- A Multipath Fault-Tolerant Routing Method for High-Speed Interconnection Networks.- Hardware Implementation Study of the SCFQ-CA and DRR-CA Scheduling Algorithms.- Topic 14: Mobile and Ubiquitous Computing.- Optimal and Near-Optimal Energy-Efficient Broadcasting in Wireless Networks.

Optimized video streaming over 802.11 by cross-layer signaling

Seamless video streaming over wireless links imposes strong demands on video codecs and the underlying network. It is not sufficient that only the video codec or only the radio adapts to changes in the wireless link quality; efforts should be applied in both layers, and - if possible - synchronized. Also, the disturbing effect of possible background traffic over the same shared medium has to be taken into account. In this article we present a communication architecture for video streaming over 802.11 that is capable of adapting to changes in the link quality and sharing of the wireless channel in various use scenarios. Experimental results show that substantial improvements in the quality of the video can be obtained by applying link adaptation and cross-layer signaling techniques.

Automatic IEEE 802.11 rate control for streaming applications

Summary Streaming multimedia content in real-time over a wireless link is a challenging task because of the rapid fluctuations in link conditions that can occur due to movement, interference, and so on. The popular IEEE 802.11 standard includes low-level tuning parameters like the transmission rate. Standard device drivers for today’s wireless products are based on gathering statistics and consequently, adapt rather slowly to changes in conditions. To meet the strict latency requirements of streaming applications, we designed and implemented an advanced hybrid control algorithm that uses signal-strength (SNR) information to achieve fast responses. Since SNR readings are quite noisy, we do not use that information to directly control the rate setting, but rather as a safeguard limiting the range of feasible settings to choose from. We report on real-time experiments involving two laptops equipped with IEEE 802.11a wireless interface cards. The results show that using SNR information greatly enhances responsiveness in comparison to statistics-based rate controllers. Finally, we will present the results of an experiment with real-time video streaming to a moving laptop in an office-like environment. Our hybrid control algorithm effectively prevented many packet losses, thereby achieving a much higher video quality than the statistics-based algorithm. Copyright # 2005 John Wiley & Sons, Ltd.