CacheCash: A Cryptocurrency-based Decentralized Content Delivery Network

Online content delivery has witnessed dramatic growth recently with traffic consuming over half of today’s Internet bandwidth. This escalating demand has motivated content publishers to move outside the traditional solutions of infrastructure-based content delivery networks (CDNs). Instead, many are employing peer-to-peer data transfers to reduce the service cost and avoid bandwidth over-provision to handle peak demands. Unfortunately, the open access work model of this paradigm, which allows anyone to join, introduces several design challenges related to security, efficiency, and peer availability. In this dissertation, we introduce CacheCash, a cryptocurrency-based decentralized content distribution network designed to address these challenges. CacheCash bypasses the centralized approach of CDN companies for one in which end users organically set up new caches in exchange for cryptocurrency tokens. Thus, it enables publishers to hire caches on an as-needed basis, without constraining these parties with long-term business commitments. To address the challenges encountered as the system evolved, we propose a number of protocols and techniques that represent basic building blocks of CacheCash’s design. First, motivated by the observation that conventional security assessment tools do not suit cryptocurrency-based systems, we propose ABC, a threat modeling framework capable of identifying attacker collusion and the new threat vectors that cryptocurrencies introduce. Second, we propose CAPnet, a defense mechanism against cache accounting attacks (i.e., a client pretends to be served allowing a colluding cache to collect rewards without doing any work). CAPnet features a bandwidth expenditure puzzle that clients must solve over the content before caches are given credit, which bounds the effectiveness of this collusion case. Third, to make it feasible to reward caches per data chunk served, we introduce MicroCash, a decentralized probabilistic micropayment scheme that reduces the overhead of processing these small payments. MicroCash implements several novel ideas that make micropayments more suitable for delay-sensitive applications, such as online content delivery. CacheCash combines the previous techniques to produce a novel service-payment exchange protocol that secures the content distribution process. This protocol utilizes gradual content disclosure and partial payment collection to encourage the honest collaborative work between participants. We present a detailed game theoretic analysis showing how to exploit rational financial incentives to address several security threats. This is in addition to various performance optimization mechanisms that promote system efficiency and scalability. Lastly, we evaluate system performance and show that modest machines can serve/retrieve content at a high bitrate with minimal overhead

Market-Based Resourse Management for Many-Core Systems

101 σ.Αντικείμενο της διπλωματικής αποτελεί η μελέτη και η ανάπτυξη μιας κλιμακώσιμης και κατανεμημένης πλατφόρμας (framework) διαχείρισης πόρων σε χρόνο εκτέλεσης για συστήματα πολλαπλών πυρήνων. Σε αυτήν την πλατφόρμα η διαχείριση πόρων είναι βασισμένη σε μοντέλα, τα οποία είναι εμπνευσμένα από την οικονομία. Παρουσιάζεται ένας διαχειριστής πόρων, ο οποίος προσφέρει ένα περιβάλλον διαχείρισης πόρων και εφαρμογών καθ ́ όλη τη διάρκεια ζωής τους, στο οποίο η κατανομή και δρομολόγηση των εφαρμογών στους πόρους πραγματοποιείται με αλγόριθμους βασισμένους σε κανόνες αγοράς. Η αποδοτικότητα κάθε μοντέλου αξιολογείται βάσει της πτώσης της αξιοπιστίας των πόρων (μετρική MTTF-Mean Time To Failure).The purpose of this diploma thesis is the design and development of a scalable and distributed run-time resource management framework for Many-core systems. In this framework, resource management is based on economy-inspired models. The presented resource management framework offers an environment that manages both application tasks and resources at run-time, matches and distributes application tasks across resources with algorithms which are based on market principles. The efficiency of each model is evaluated with respect to resource reliability degradation (metric MTTF-Mean Time to Failure).Θεμιστοκλής Γ. Μελισσάρη

Performance Characterization of Multi-threaded Graph Processing Applications on Intel Many-Integrated-Core Architecture

Intel Xeon Phi many-integrated-core (MIC) architectures usher in a new era of terascale integration. Among emerging killer applications, parallel graph processing has been a critical technique to analyze connected data. In this paper, we empirically evaluate various computing platforms including an Intel Xeon E5 CPU, a Nvidia Geforce GTX1070 GPU and an Xeon Phi 7210 processor codenamed Knights Landing (KNL) in the domain of parallel graph processing. We show that the KNL gains encouraging performance when processing graphs, so that it can become a promising solution to accelerating multi-threaded graph applications. We further characterize the impact of KNL architectural enhancements on the performance of a state-of-the art graph framework.We have four key observations: 1 Different graph applications require distinctive numbers of threads to reach the peak performance. For the same application, various datasets need even different numbers of threads to achieve the best performance. 2 Only a few graph applications benefit from the high bandwidth MCDRAM, while others favor the low latency DDR4 DRAM. 3 Vector processing units executing AVX512 SIMD instructions on KNLs are underutilized when running the state-of-the-art graph framework. 4 The sub-NUMA cache clustering mode offering the lowest local memory access latency hurts the performance of graph benchmarks that are lack of NUMA awareness. At last, We suggest future works including system auto-tuning tools and graph framework optimizations to fully exploit the potential of KNL for parallel graph processing.Comment: published as L. Jiang, L. Chen and J. Qiu, "Performance Characterization of Multi-threaded Graph Processing Applications on Many-Integrated-Core Architecture," 2018 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), Belfast, United Kingdom, 2018, pp. 199-20

The Parthenon, November 9, 2011

The Parthenon, Marshall University’s student newspaper, is published by students Monday through Friday during the regular semester and weekly Thursday during the summer. The editorial staff is responsible for the news and the editorial content

Web Content Delivery Optimization

Milliseconds matters, when they’re counted. If we consider the life of the universe into one single year, then on 31 December at 11:59:59.5 PM, “speed” was transportation’s concern, and now after 500 milliseconds it is web’s, and no one knows whose concern it would be in coming milliseconds, but at this very moment; this thesis proposes an optimization method, mainly for content delivery on slow connections. The method utilizes a proxy as a middle box to fetch the content; requested by a client, from a single or multiple web servers, and bundles all of the fetched image content types that fits into the bundling policy; inside a JavaScript file in Base64 format. This optimization method reduces the number of HTTP requests between the client and multiple web servers as a result of its proposed bundling solution, and at the same time optimizes the HTTP compression efficiency as a result of its proposed method of aggregative textual content compression. Page loading time results of the test web pages; which were specially designed and developed to capture the optimum benefits of the proposed method; proved up to 81% faster page loading time for all connection types. However, other tests in non-optimal situations such as webpages which use “Lazy Loading” techniques, showed just 35% to 50% benefits, that is only achievable on 2G and 3G connections (0.2 Mbps – 15 Mbps downlink) and not faster connections