Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Made available in DSpace on 2015-03-05T13:58:26Z (GMT). No. of bitstreams: 0 Previous issue date: 13 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Apesar de ser uma das principais aplicações da Internet na atualidade, o compartilhamento de arquivos P2P tem sido fortemente prejudicado por ataques de poluição de conteúdo. Esta dissertação propõe e analisa uma classe de métodos de contenção de poluição cujo princípio básico é a limitação do número instantâneo de downloads de acordo com a reputação de versões. Inicialmente, o método é proposto e avaliado em termos de um ambiente idealizado, mostrando sua eficiência na contenção de poluição e baixa sobrecarga induzida quando o título não é poluído. A seguir, valendo-se de modelos clássicos para projeto de redes P2P, são propostos e comparados métodos de contenção distribuída / Despite currently one of the main Internet applications, P2P file sharing has been hampered by content pollution attacks. This work proposes and analyzes a class of contention methods to reduce the dissemination of polluted content whose basic principle is to limit the amount of instantaneous downloads according to its reputation. The method is firstly proposed and evaluated in terms of an idealized environment. The evaluation shows the eficiency of the contention method and the low overhead induced when the content is not polluted. Then, inspired by classic P2P designs, we propose and compare distributed contention methods

Current heterogeneous CPU-GPU architectures integrate general purpose CPUs and highly thread-level parallelized GPUs (Graphic Processing Units) in the same die. This dissertation focuses on improving the energy efficiency and performance for the heterogeneous CPU-GPU system. Leakage energy has become an increasingly large fraction of total energy consumption, making it important to reduce leakage energy for improving the overall energy efficiency. Cache occupies a large on-chip area, which are good targets for leakage energy reduction. For the CPU cache, we study how to reduce the cache leakage energy efficiently in a hybrid SPM (Scratch-Pad Memory) and cache architecture. For the GPU cache, the access pattern of GPU cache is different from the CPU, which usually has little locality and high miss rate. In addition, GPU can hide memory latency more effectively due to multi-threading. Because of the above reasons, we find it is possible to place the cache lines of the GPU data caches into the low power mode more aggressively than traditional leakage management for CPU caches, which can reduce more leakage energy without significant performance degradation. The contention in shared resources between CPU and GPU, such as the last level cache (LLC), interconnection network and DRAM, may degrade both CPU and GPU performance. We propose a simple yet effective method based on probability to control the LLC replacement policy for reducing the CPU’s inter-core conflict misses caused by GPU without significantly impacting GPU performance. In addition, we develop two strategies to combine the probability based method for the LLC and an existing technique called virtual channel partition (VCP) for the interconnection network to further improve the CPU performance. For a specific graph application of Breadth first search (BFS), which is a basis for graph search and a core building block for many higher-level graph analysis applications, it is a typical example of parallel computation that is inefficient on GPU architectures. In a graph, a small portion of nodes may have a large number of neighbors, which leads to irregular tasks on GPUs. These irregularities limit the parallelism of BFS executing on GPUs. Unlike the previous works focusing on fine-grained task management to address the irregularity, we propose Virtual-BFS (VBFS) to virtually change the graph itself. By adding virtual vertices, the high-degree nodes in the graph are divided into groups that have an equal number of neighbors, which increases the parallelism such that more GPU threads can work concurrently. This approach ensures correctness and can significantly improve both the performance and energy efficiency on GPUs.

Recognizing that over the past decade transnational environmental activism focusing on climate change has radicalized in public tactics and discourse, this project employs a mechanism-process approach to analyze and explain processes of tactical and discursive radicalization within the global climate justice movement(s) over time. As global activists within this movement construct and pursue public, as well as covert, campaigns directed at states, international institutions, corporations, the media and society at large, it asks why, how and to what effect specific sectors of the broader movement have radicalized from the period 2006-2010. Utilizing longitudinal quantitative protest event and political claims analysis and ethnographic field work and participant action research, it aims to provide a descriptive and comparative account of tactical and discursive variations at international climate change protests situated within the context of a broader cycle of transnational global justice contention.

The emerging widespread use of real-time multimedia applications over wireless networks makes the support of Quality of Service (QoS) a key problem. In this paper, we focus on QoS support mechanisms for IEEE 802.11 Wireless ad-hoc networks. First, we review the IEEE 802.11 standard and other enhanced MAC schemes that have been proposed to support QoS for 802.11 ad hoc networks. Then we propose a new priority MAC scheme which uses the different initial contention window instead of CWmin in IEEE 802.11 MAC to reduce the collision rate, then reduces the average delay and increases the throughput.

This work studies the allocation of bandwidth resources in wireless ad hoc networks. The highest-density clustering algorithm is presented to promote reuse of the spatial channel and a new slot allocation algorithm is proposed to achieve conflict-free scheduling for transmissions. Since the location-dependent contention is an important characteristic of ad hoc networks, in this paper we consider this feature of ad hoc networks to present a new cluster formation algorithm, by increasing the number of simultaneous links to enhance spatial channel reuse. Furthermore, because each cluster has its own scheduler and schedulers operate independently of each other, the transmissions may conflict among the clusters. In this paper, we classify the flows by the locations of their endpoints to prevent this problem. Finally, the proposed mechanism is implemented by simulation and the results reveal that the conflicts can be efficiently avoided without global information and the network throughput is improved without violating fairness.

In this thesis, a feedback-based contention avoidance technique based on weighted Dijkstra algorithm is proposed to address the contention avoidance problem for Optical Burst Switching networks. Optical Burst Switching (OBS) has been proposed as a promising technique to support high-bandwidth, bursty data traffic in the next-generation optical Internet. Nevertheless, there are still some challenging issues that need to be solved to achieve an effective implementation of OBS. Contention problem occurs when two or more bursts are destined for the same wavelength. To solve this problem, various reactive contention resolution methods have been proposed in the literature. However, many of them are very vulnerable to network load and may suffer severe loss in case of heavy traffic. By proactively controlling the overall traffic, network is able to update itself in case of high congestion and by means of this method / contention avoidance can be achieved efficiently. The performance analysis of the proposed algorithm is presented through network simulation results provided by OMNET++ simulation environment. The simulation results show that the proposed contention avoidance technique significantly reduces the burst loss probability as compared to networks without any contention avoidance techniques.

Robot and sensor networks are needed for safety, security, and rescue applicationssuch as port security and reconnaissance during a disaster. These applications rely on realtimetransmission of images, which generally saturate the available wireless networkinfrastructure. Knowledge-based Compression is a strategy for reducing the video frametransmission rate between robots or sensors and remote operators. Because images mayneed to be archived as evidence and/or distributed to multiple applications with differentpost processing needs, lossy compression schemes, such as MPEG, H.26x, etc., are notacceptable. This work proposes a lossless video server system consisting of three classesof filters (redundancy, task, and priority) which use different levels of knowledge (localsensed environment, human factors associated with a local task, and relative globalpriority of a task) at the application layer of the network. It demonstrates the redundancyand task filters for realistic robot search scenarios. The redundancy filter is shown toreduce the overall transmission bandwidth by 24.07% to 33.42%, and when combinedwith the task filter, reduces overall transmission bandwidth by 59.08% to 67.83%. Byitself, the task filter has the capability to reduce transmission bandwidth by 32.95% to33.78%. While Knowledge-based Compression generally does not reach the same levels ofreduction as MPEG, there are instances where the system outperforms MPEG encoding.

Political contention has entered a new age. Over the past three years unprecedented large-scale movements have challenged states across the globe, and social media has been an important component in their development and articulation. With the advent of social media sites, such as Facebook and Twitter, ordinary people have the technological ability to instantaneously transcend space, time and resources (Aouraugh and Alexander 2011; Castells 2012; Earl and Kimport 2009, 2011; Eltantawy, Nahed and Wiest 2011; Gerbaudo 2012; Hands 2011; Holmes 2012; Mason 2012). Are we currently living in a historical moment where a new repertoire of contention is emerging? If so, how is social media changing the way we collectively contest for our interests? The theoretical framework I propose in this paper advances and elaborates a social geographic approach in the framing of political contention that emphasizes the importance of the spatiality and temporality created by the hashtag (#) in the development and articulation of today's social movements. In addition to secondary sources about the protests in Brazil (#VemPraRua), I draw on participant observations to analyze a new modular form of protest I call the "hashtag movement." I claim that the hashtag (#) creates a new space/time (Massey 1992, 2007; Soja 1996) that fundamentally shifts the process of nation-ness (Anderson 2006) and marks a new phase in the mediazation of modern culture (Thompson 1991); two fundamental shifts that I argue are comparable to the structural and cultural shifts that formed the modern repertoire of contention (Anderson 2006; Della Porta and Diani 1999; McAdam 1999; McAdam, Tarrow and Tilly 2001; Sewell 1990, 1996; Swidler 1986; Tarrow 1993, 1994; Tilly 1986, 1995a, 1995b; Young 2002). / text

Hate crime laws in both Canada and the United States purport to promote equality using the language of antidiscrimination law. National criminal codes in both countries authorize enhanced punishment for crimes motivated by “sexual orientation” but not “gender identity” or “gender expression.” Cities and states in the United States have also adopted hate crime laws, some of which denounce both homophobic and trans-phobic crimes. Hate crime penalty enhancement laws have been applied by courts in both Canada and the United States to establish a growing jurisprudence. In both countries, moreover, other hate crime laws contribute to official legal knowledge by regulating hate speech, hate crime statistics, and conduct equivalent to hate crimes in schools, workplaces, and elsewhere. Yet, despite the proliferation of hate crime laws and jurisprudence, governmental officials do not control all legal knowledge about hate crimes. Sociological “others” attend criminal sentencing proceedings and provide support to hate crime victims during prosecutions, but they also frame their own unofficial inquiries and announce their own classification decisions for hate-related events. In both Canada and the United States, nongovernmental groups contend both inside and outside official governmental channels to establish legal knowledge about homophobic and trans-phobic hate crimes. In two comparable Canadian and American cities, similar groups monitor and classify homophobic and trans-phobic attacks using a variety of information practices. Interviews with representatives of these groups reveal a relationship between the practices of each group and hate crime laws at each site. The results support one principal conclusion. The availability of local legislative power and a local mechanism for public review are key determinants of the sites and styles of nongovernmental contention about hate crimes. Where police gather and publish official hate crime statistics, the official classification system serves as both a site for mobilization, and a constraint on the styles of contention used by nongovernmental groups. Where police do not gather or publish hate crime statistics, nongovernmental groups are deprived of the resource represented by a local site for social contention, but their styles of contention are liberated from the subtle influences of an official hate crime classification system.