Fast Packet Processing on High Performance Architectures

The rapid growth of Internet and the fast emergence of new network applications have brought great challenges and complex issues in deploying high-speed and QoS guaranteed IP network. For this reason packet classication and network intrusion detection have assumed a key role in modern communication networks in order to provide Qos and security. In this thesis we describe a number of the most advanced solutions to these tasks. We introduce NetFPGA and Network Processors as reference platforms both for the design and the implementation of the solutions and algorithms described in this thesis. The rise in links capacity reduces the time available to network devices for packet processing. For this reason, we show different solutions which, either by heuristic and randomization or by smart construction of state machine, allow IP lookup, packet classification and deep packet inspection to be fast in real devices based on high speed platforms such as NetFPGA or Network Processors

Network Processors and Next Generation Networks: Design, Applications, and Perspectives

Network Processors (NPs) are hardware platforms born as appealing solutions for packet processing devices in networking applications. Nowadays, a plethora of solutions exists, with no agreement on a common architecture. Each vendor has proposed its specific solution and no official standard still exists. The common features of all proposals are a hierarchy of processors, with a general purpose processor and several units specialized for packet processing, a series of memory devices with different sizes and latencies, a low-level programmability. The target is a platform for networking applications with low time to market and high time in market, thanks to a high flexibility and a programmability simpler than that of ASICs, for example. After about ten years since the "birth" of network processors, this research activity wants to make an analytical balance of their development and usage. Many authoritative opinions suggest that NPs have been "outdated" by multicore or manycore systems, which provide general purpose environments and some specialized cores. The main reasons of these negative opinions are the hard programmability of NPs, which often requires the knowledge of private microcode, or the excessive architectural limits, such as reduced memories and minimal instruction store. Our research shows that Network Processors can be appealing for different applications in networking area, and many interesting solutions can be obtained, which present very high performance, outscoring current solutions. However, the issues of hard programming and remarkable limits exist, and they could be alleviated only by providing almost a comprehensive programming environment and a proper design in terms of processing and memory resources. More e cient solutions can be surely provided, but the experience of network processors has produced an important legacy in developing packet processing engines. In this work, we have realized many devices for networking purposes based on NP platform, in order to understand the complexity of programming, the flexibility of design, the complexity of tasks that can be implemented, the maximum depth of packet processing, the performance of such devices, the real usefulness of NPs in network devices. All these features have been accurately analyzed and will be illustrated in this thesis. Many remarkable results have been obtained, which confirm the Network Processors as appealing solutions for network devices. Moreover, the research on NPs have lead us to analyze and solve more general issues, related for instance to multiprocessor systems or to processors with no big available memory. In particular, the latter issue lead us to design many interesting data structures for set representation and membership query, which are based on randomized techniques and allow for big memory savings

Model-Based High-Dimensional Pose Estimation with Application to Hand Tracking

This thesis presents novel techniques for computer vision based full-DOF human hand motion estimation. Our main contributions are: A robust skin color estimation approach; A novel resolution-independent and memory efficient representation of hand pose silhouettes, which allows us to compute area-based similarity measures in near-constant time; A set of new segmentation-based similarity measures; A new class of similarity measures that work for nearly arbitrary input modalities; A novel edge-based similarity measure that avoids any problematic thresholding or discretizations and can be computed very efficiently in Fourier space; A template hierarchy to minimize the number of similarity computations needed for finding the most likely hand pose observed; And finally, a novel image space search method, which we naturally combine with our hierarchy. Consequently, matching can efficiently be formulated as a simultaneous template tree traversal and function maximization

Incremental Non-Greedy Clustering at Scale

Clustering is the task of organizing data into meaningful groups. Modern clustering applications such as entity resolution put several demands on clustering algorithms: (1) scalability to massive numbers of points as well as clusters, (2) incremental additions of data, (3) support for any user-specified similarity functions. Hierarchical clusterings are often desired as they represent multiple alternative flat clusterings (e.g., at different granularity levels). These tree-structured clusterings provide for both fine-grained clusters as well as uncertainty in the presence of newly arriving data. Previous work on hierarchical clustering does not fully address all three of the aforementioned desiderata. Work on incremental hierarchical clustering often makes greedy, irrevocable clustering decisions that are regretted in the presence of future data. Work on scalable hierarchical clustering does not support incremental additions or deletions. These methods often make requirements on the similarity functions used and/or empirically tend to over merge clusters, which can lead to inaccurate clusterings. In this thesis, we present incremental and scalable methods for hierarchical clustering to empirically satisfy the above desiderata. Our work aims to represent uncertainty and meaningful alternative clusterings, to efficiently reconsider past decisions in the incremental case, and to use parallelism to scale to massive datasets. Our method, Grinch, handles incrementally arriving data in a non-greedy fashion, by reconsidering past decisions using tree structure re-arrangements (e.g., rotations and grafts) invoked in accordance with the user’s specified similarity function. To achieve scalability to massive datasets, our method, SCC, builds a hierarchical clusterings in a level-wise bottom-up manner. Certain clustering decisions are made independently in parallel within each level, and a global similarity threshold schedule prevents greedy over-merging. We show how SCC can be combined with the tree-structure re-arrangements in Grinch to form a mini-batch algorithm achieving both scalable and incremental performance. Lastly, we generalize our hierarchical clustering approaches to DAG-structured ones, which can better represent uncertainty in clustering by representing overlapping clusters. We introduce an efficient bottom-up method for DAG-structured clustering, Llama. For each of the proposed methods, we provide both a theoretical and empirical analysis. Empirically, our methods achieve state-of-the-art results on clustering benchmarks in both the batch and the incremental settings, including multiple point improvements in dendrogram purity and scalability to billions of points

"The authority of the steam" : power dynamics of digital production in the Bitcoin blockchain

This thesis offers a critical investigation of the Bitcoin currency and the operation of its technical structure, i.e. blockchain technology. The main objective of the research is to identify and describe the specific power dynamics performed by and through this digital phenomenon. “Power dynamics” are framed in this work largely in terms of authority and sovereignty. To structure an exploration of such dynamics, the narrative is overarched by four different notions of “utopia” —as paradox, ideal, no-place, and imagined governance— that address the following main questions always underpinned by the general inquiry on power: What is the Bitcoin Blockchain? Where is it located? How are power relations performed in it? And how are power relations modified in relation with previous institutional systems? The thesis addresses distinct notions of authority in Bitcoin through the observation of its historical, spatial, and organizational characteristics. It maps the techno-political emergence of the blockchain system, the geographical distribution of Bitcoin’s infrastructural network, and the strategies for governance involved in its development as software. Based on the observation of these settings, this thesis argues that Bitcoin posits a restructuration of power dynamics through the automation of code, in particular, through its process of production. In order to develop this restructuration, the power dynamics of the Bitcoin blockchain are weighted against authority models of the state’s institutions. The thesis builds upon existing political theories of Empire (Hardt and Negri), protocol (Galloway), and the Stack (Bratton) to develop a critical account of Bitcoin’s power dynamics. The work sits in between the disciplines of Media Theory, Software Studies, Political Theory, and Digital Methods, and makes use of qualitative and quantitative methods to empirically support the former argument

Hurricane Shoes And Other Stories

Hurricane Shoes and Other Stories is a collection of short stories that center on evolving and devolving relationships. The characters in these stories form tentative bonds with people in their lives while other relationships slip away. In Hurricane Shoes, Katrina attempts to reinvent herself by ending an affair. Katrina\u27s pregnancy and her mother\u27s cancer pull the two women closer. Da\u27s Violets is about Cheryl\u27s changing relationship with her father. Just as he moves on from the wife who left him for her podiatrist, the wife returns with hopes to reconcile. These stories catch characters in moments when they must make difficult choices and endure the uncertainties and ambiguities of relationships. In Lady Luck, Laurel is a cocaine addict and alcoholic on the verge of finalizing a divorce. She propositions a young man named River to exchange sex for money. River turns the table, and offers Laurel a deal where she\u27ll have all the money and drugs she wants, as long as she helps him transport cocaine. Bridges is a coming of age story in which Linda and Kristin have a close call with a train, and Linda matures as she realizes love has limits. The catalyst for changing relationships is sometimes an exchange between characters. In Special Son, Mark\u27s father is dying of cancer. The father asks his son to take special care of his mother, and Mark needs his father to finally acknowledge Mark\u27s sexuality. In Swim or Sink, Doreen befriends her campground neighbor, Michael McBride. McBride has been living at the campground since he left his cheating wife, and he offers Doreen insight when she discovers her husband\u27s infidelity. Together the stories function as a mosaic--each very different, but a complement to the others in forming a larger portrayal of relationships

Big Data Processing with Peer-To-Peer Architectures

Ph.DDOCTOR OF PHILOSOPH

ON THE RUN, October 19, 1978

Issue No.8 Super Coach by Blaine NewnhamBill Dellinger claims he has been as close to being fired as a coach can he. But his potential fate never worried him, because Dellinger has the faith. House House Harriers by Bill BranyanOver the river and through the woods, the Hash House Harriers pursue one another in the name of sport and good time. But they sometimes harry others in the process. Happy Anniversary by Ray HoslerFor 10 years, Los Angeles runner Mark Covert has not missed a day of running. Happy anniversary, Mark. O.J. Is OK by Bob MoriartyO.J. Simpson is better than ever, thanks to a summer of running that helped him return to football form after a knee injury.https://openprairie.sdstate.edu/on_the_run/1006/thumbnail.jp