21 research outputs found
Incentive-driven QoS in peer-to-peer overlays
A well known problem in peer-to-peer overlays is that no single entity has control over the software,
hardware and configuration of peers. Thus, each peer can selfishly adapt its behaviour to maximise its
benefit from the overlay. This thesis is concerned with the modelling and design of incentive mechanisms
for QoS-overlays: resource allocation protocols that provide strategic peers with participation incentives,
while at the same time optimising the performance of the peer-to-peer distribution overlay.
The contributions of this thesis are as follows. First, we present PledgeRoute, a novel contribution
accounting system that can be used, along with a set of reciprocity policies, as an incentive mechanism
to encourage peers to contribute resources even when users are not actively consuming overlay services.
This mechanism uses a decentralised credit network, is resilient to sybil attacks, and allows peers to
achieve time and space deferred contribution reciprocity. Then, we present a novel, QoS-aware resource
allocation model based on Vickrey auctions that uses PledgeRoute as a substrate. It acts as an incentive
mechanism by providing efficient overlay construction, while at the same time allocating increasing
service quality to those peers that contribute more to the network. The model is then applied to lagsensitive
chunk swarming, and some of its properties are explored for different peer delay distributions.
When considering QoS overlays deployed over the best-effort Internet, the quality received by a
client cannot be adjudicated completely to either its serving peer or the intervening network between
them. By drawing parallels between this situation and well-known hidden action situations in microeconomics,
we propose a novel scheme to ensure adherence to advertised QoS levels. We then apply
it to delay-sensitive chunk distribution overlays and present the optimal contract payments required,
along with a method for QoS contract enforcement through reciprocative strategies. We also present a
probabilistic model for application-layer delay as a function of the prevailing network conditions.
Finally, we address the incentives of managed overlays, and the prediction of their behaviour. We
propose two novel models of multihoming managed overlay incentives in which overlays can freely
allocate their traffic flows between different ISPs. One is obtained by optimising an overlay utility
function with desired properties, while the other is designed for data-driven least-squares fitting of the
cross elasticity of demand. This last model is then used to solve for ISP profit maximisation
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
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
Innovations in the Internetâs Architecture that Challenge the Status Quo
The current debate over broadband policy has largely overlooked a number of changes to the architecture of the Internet that have caused the price paid by and quality of service received by traffic traveling across the Internet to vary widely. Topological innovations, such as private peering, multihoming, secondary peering, server farms, and content delivery networks, have caused the Internetâs traditionally hierarchical architecture to be replaced by one that is more heterogeneous. Moreover, network providers have begun to employ an increasingly varied array of business arrangements. Some of these innovations are responses to the growing importance of peer-to-peer technologies. Others, such as paid peering and partial transit, are driven by the growing dominance of advertising-based business models as well as the insights provided by the economics of two-sided markets. At times interpreted as network providersâ attempts to promote their self interest at the expense of the public, these changes often reflect network providersâ attempts to reduce cost, manage congestion, and maintain quality of service. As such, they have the potential to yield substantial benefits both to individual consumers and to society as a whole
Private and censorship-resistant communication over public networks
Societyâs increasing reliance on digital communication networks is creating unprecedented opportunities for wholesale
surveillance and censorship. This thesis investigates the use of public networks such as the Internet to build
robust, private communication systems that can resist monitoring and attacks by powerful adversaries such as national
governments.
We sketch the design of a censorship-resistant communication system based on peer-to-peer Internet overlays in which
the participants only communicate directly with people they know and trust. This âfriend-to-friendâ approach protects
the participantsâ privacy, but it also presents two significant challenges. The first is that, as with any peer-to-peer
overlay, the users of the system must collectively provide the resources necessary for its operation; some users might
prefer to use the system without contributing resources equal to those they consume, and if many users do so, the
system may not be able to survive.
To address this challenge we present a new game theoretic model of the problem of encouraging cooperation between
selfish actors under conditions of scarcity, and develop a strategy for the game that provides rational incentives for
cooperation under a wide range of conditions.
The second challenge is that the structure of a friend-to-friend overlay may reveal the usersâ social relationships to
an adversary monitoring the underlying network. To conceal their sensitive relationships from the adversary, the
users must be able to communicate indirectly across the overlay in a way that resists monitoring and attacks by other
participants.
We address this second challenge by developing two new routing protocols that robustly deliver messages across
networks with unknown topologies, without revealing the identities of the communication endpoints to intermediate
nodes or vice versa. The protocols make use of a novel unforgeable acknowledgement mechanism that proves that a
message has been delivered without identifying the source or destination of the message or the path by which it was
delivered. One of the routing protocols is shown to be robust to attacks by malicious participants, while the other
provides rational incentives for selfish participants to cooperate in forwarding messages
Networks, complexity and internet regulation: scale-free law
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