14,731 research outputs found
Implementation and Deployment of a Distributed Network Topology Discovery Algorithm
In the past few years, the network measurement community has been interested
in the problem of internet topology discovery using a large number (hundreds or
thousands) of measurement monitors. The standard way to obtain information
about the internet topology is to use the traceroute tool from a small number
of monitors. Recent papers have made the case that increasing the number of
monitors will give a more accurate view of the topology. However, scaling up
the number of monitors is not a trivial process. Duplication of effort close to
the monitors wastes time by reexploring well-known parts of the network, and
close to destinations might appear to be a distributed denial-of-service (DDoS)
attack as the probes converge from a set of sources towards a given
destination. In prior work, authors of this report proposed Doubletree, an
algorithm for cooperative topology discovery, that reduces the load on the
network, i.e., router IP interfaces and end-hosts, while discovering almost as
many nodes and links as standard approaches based on traceroute. This report
presents our open-source and freely downloadable implementation of Doubletree
in a tool we call traceroute@home. We describe the deployment and validation of
traceroute@home on the PlanetLab testbed and we report on the lessons learned
from this experience. We discuss how traceroute@home can be developed further
and discuss ideas for future improvements
Distributed coordination of self-organizing mechanisms in communication networks
The fast development of the Self-Organizing Network (SON) technology in
mobile networks renders the problem of coordinating SON functionalities
operating simultaneously critical. SON functionalities can be viewed as control
loops that may need to be coordinated to guarantee conflict free operation, to
enforce stability of the network and to achieve performance gain. This paper
proposes a distributed solution for coordinating SON functionalities. It uses
Rosen's concave games framework in conjunction with convex optimization. The
SON functionalities are modeled as linear Ordinary Differential Equation
(ODE)s. The stability of the system is first evaluated using a basic control
theory approach. The coordination solution consists in finding a linear map
(called coordination matrix) that stabilizes the system of SON functionalities.
It is proven that the solution remains valid in a noisy environment using
Stochastic Approximation. A practical example involving three different SON
functionalities deployed in Base Stations (BSs) of a Long Term Evolution (LTE)
network demonstrates the usefulness of the proposed method.Comment: submitted to IEEE TCNS. arXiv admin note: substantial text overlap
with arXiv:1209.123
Spoiled Onions: Exposing Malicious Tor Exit Relays
Several hundred Tor exit relays together push more than 1 GiB/s of network
traffic. However, it is easy for exit relays to snoop and tamper with
anonymised network traffic and as all relays are run by independent volunteers,
not all of them are innocuous.
In this paper, we seek to expose malicious exit relays and document their
actions. First, we monitored the Tor network after developing a fast and
modular exit relay scanner. We implemented several scanning modules for
detecting common attacks and used them to probe all exit relays over a period
of four months. We discovered numerous malicious exit relays engaging in
different attacks. To reduce the attack surface users are exposed to, we
further discuss the design and implementation of a browser extension patch
which fetches and compares suspicious X.509 certificates over independent Tor
circuits.
Our work makes it possible to continuously monitor Tor exit relays. We are
able to detect and thwart many man-in-the-middle attacks which makes the
network safer for its users. All our code is available under a free license
Measurement-Based Monitoring and Control in Power Systems with High Renewable Penetrations
Power systems are experiencing rapid changes in their generation mixes because of the increasing integration of inverter-based resources (IBRs) and the retirement of traditional generations. This opens opportunities for a cleaner energy outlook but also poses challenges to the safe operation of the power networks. Enhanced monitoring and control based on the increasingly available measurements are essential in assisting stable operation and effective planning for these evolving systems.
First, awareness of the evolving dynamic characteristics is quintessential for secure operation and corrective planning. A quantified monitoring study that keeps track of the inertial response and primary frequency response is conducted on the Eastern Interconnection (EI) for the past decade with field data. Whereas the inertia declined by at least 10%, the primary frequency response experienced an unexpected increase. The findings unveiled in the trending analysis also led to an improved event MW size estimation method, as well as discussions about regional dynamics.
Experiencing a faster and deeper renewable integration, the Continental Europe Synchronous Area (CESA) system has been threatened by more frequent occurrences of inter-area oscillations during light-load high-renewable periods. A measurement-based oscillation damping control scheme is proposed for CESA with reduced reliance on system models. The design, implementation, and hardware-in-the-loop (HIL) testing of the controller are discussed in detail.
Despite the challenges, the increasing presence of IBRs also brings opportunities for fast and efficient controls. Together with synchronized measurement, IBRs have the potential to flexibly complement traditional frequency and voltage control schemes for improved frequency and voltage recovery. The design, implementation, and HIL testing of the measurement-based frequency and voltage control for the New York State Grid are presented.
In addition to the transmission level development, IBRs deployed in distribution networks can also be valuable assets in emergency islanding situations if controlled properly. A power management module is proposed to take advantage of measurements and automatically control the electric boundaries of islanded microgrids for maximized power utilization and improved frequency regulation. The module is designed to be adaptive to arbitrary non-meshed topologies with multiple source locations for increased flexibility, expedited deployment, and reduced cost
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
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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