2,849 research outputs found
Arithmetic on a Distributed-Memory Quantum Multicomputer
We evaluate the performance of quantum arithmetic algorithms run on a
distributed quantum computer (a quantum multicomputer). We vary the node
capacity and I/O capabilities, and the network topology. The tradeoff of
choosing between gates executed remotely, through ``teleported gates'' on
entangled pairs of qubits (telegate), versus exchanging the relevant qubits via
quantum teleportation, then executing the algorithm using local gates
(teledata), is examined. We show that the teledata approach performs better,
and that carry-ripple adders perform well when the teleportation block is
decomposed so that the key quantum operations can be parallelized. A node size
of only a few logical qubits performs adequately provided that the nodes have
two transceiver qubits. A linear network topology performs acceptably for a
broad range of system sizes and performance parameters. We therefore recommend
pursuing small, high-I/O bandwidth nodes and a simple network. Such a machine
will run Shor's algorithm for factoring large numbers efficiently.Comment: 24 pages, 10 figures, ACM transactions format. Extended version of
Int. Symp. on Comp. Architecture (ISCA) paper; v2, correct one circuit error,
numerous small changes for clarity, add reference
Optimizing on-demand resource deployment for peer-assisted content delivery (PhD thesis)
Increasingly, content delivery solutions leverage client resources in exchange for service in a peer-to-peer (P2P) fashion. Such peer-assisted service paradigms promise significant infrastructure cost reduction, but suffer from the unpredictability associated with client resources, which is often exhibited as an imbalance between the contribution and consumption of resources by clients. This imbalance hinders the ability to guarantee a minimum service fidelity of these services to the clients. In this thesis, we propose a novel architectural service model that enables the establishment of higher fidelity services through (1) coordinating the content delivery to optimally utilize the available resources, and (2) leasing the least additional cloud resources, available through special nodes (angels) that join the service on-demand, and only if needed, to complement the scarce resources available through clients. While the proposed service model can be deployed in many settings, this thesis focuses on peer-assisted content delivery applications, in which the scarce resource is typically the uplink capacity of clients. We target three applications that require the delivery of fresh as opposed to stale content. The first application is bulk-synchronous transfer, in which the goal of the system is to minimize the maximum distribution time -- the time it takes to deliver the content to all clients in a group. The second application is live streaming, in which the goal of the system is to maintain a given streaming quality. The third application is Tor, the anonymous onion routing network, in which the goal of the system is to boost performance (increase throughput and reduce latency) throughout the network, and especially for bandwidth-intensive applications. For each of the above applications, we develop mathematical models that optimally allocate the already available resources. They also optimally allocate additional on-demand resource to achieve a certain level of service. Our analytical models and efficient constructions depend on some simplifying, yet impractical, assumptions. Thus, inspired by our models and constructions, we develop practical techniques that we incorporate into prototypical peer-assisted angel-enabled cloud services. We evaluate those techniques through simulation and/or implementation.
(Major Advisor: Azer Bestavros
OnionBots: Subverting Privacy Infrastructure for Cyber Attacks
Over the last decade botnets survived by adopting a sequence of increasingly
sophisticated strategies to evade detection and take overs, and to monetize
their infrastructure. At the same time, the success of privacy infrastructures
such as Tor opened the door to illegal activities, including botnets,
ransomware, and a marketplace for drugs and contraband. We contend that the
next waves of botnets will extensively subvert privacy infrastructure and
cryptographic mechanisms. In this work we propose to preemptively investigate
the design and mitigation of such botnets. We first, introduce OnionBots, what
we believe will be the next generation of resilient, stealthy botnets.
OnionBots use privacy infrastructures for cyber attacks by completely
decoupling their operation from the infected host IP address and by carrying
traffic that does not leak information about its source, destination, and
nature. Such bots live symbiotically within the privacy infrastructures to
evade detection, measurement, scale estimation, observation, and in general all
IP-based current mitigation techniques. Furthermore, we show that with an
adequate self-healing network maintenance scheme, that is simple to implement,
OnionBots achieve a low diameter and a low degree and are robust to
partitioning under node deletions. We developed a mitigation technique, called
SOAP, that neutralizes the nodes of the basic OnionBots. We also outline and
discuss a set of techniques that can enable subsequent waves of Super
OnionBots. In light of the potential of such botnets, we believe that the
research community should proactively develop detection and mitigation methods
to thwart OnionBots, potentially making adjustments to privacy infrastructure.Comment: 12 pages, 8 figure
Optimizing on-demand resource deployment for peer-assisted content delivery
Increasingly, content delivery solutions leverage client resources in exchange for services in a pee-to-peer (P2P) fashion. Such peer-assisted service paradigm promises significant infrastructure cost
reduction, but suffers from the unpredictability associated with client resources, which is often exhibited as an imbalance between the contribution and consumption of resources by clients. This imbalance hinders the ability to guarantee a minimum service fidelity of these services to clients especially for real-time applications where content can not be cached. In this thesis, we propose a
novel architectural service model that enables the establishment of higher fidelity services through (1) coordinating the content delivery to efficiently utilize the available resources, and (2) leasing the least additional cloud resources, available through special nodes (angels) that join the service on-demand, and only if needed, to complement the scarce resources available through clients.
While the proposed service model can be deployed in many settings, this thesis focuses on peer-assisted content delivery applications, in which the scarce resource is typically the upstream
capacity of clients. We target three applications that require the delivery of real-time as opposed to stale content. The first application is bulk-synchronous transfer, in which the goal of the system is
to minimize the maximum distribution time - the time it takes to deliver the content to all clients in a group. The second application is live video streaming, in which the goal of the system is to maintain
a given streaming quality. The third application is Tor, the anonymous onion routing network, in which the goal of the system is to boost performance (increase throughput and reduce latency)
throughout the network, and especially for clients running bandwidth-intensive applications.
For each of the above applications, we develop analytical models that efficiently allocate the already available resources. They also efficiently allocate additional on-demand resource to achieve
a certain level of service. Our analytical models and efficient constructions depend on some simplifying, yet impractical, assumptions. Thus, inspired by our models and constructions, we develop practical techniques that we incorporate into prototypical peer-assisted angel-enabled cloud services.
We evaluate these techniques through simulation and/or implementation
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