Throughput Optimal Routing in Overlay Networks

Maximum throughput requires path diversity enabled by bifurcating traffic at different network nodes. In this work, we consider a network where traffic bifurcation is allowed only at a subset of nodes called \emph{routers}, while the rest nodes (called \emph{forwarders}) cannot bifurcate traffic and hence only forward packets on specified paths. This implements an overlay network of routers where each overlay link corresponds to a path in the physical network. We study dynamic routing implemented at the overlay. We develop a queue-based policy, which is shown to be maximally stable (throughput optimal) for a restricted class of network scenarios where overlay links do not correspond to overlapping physical paths. Simulation results show that our policy yields better delay over dynamic policies that allow bifurcation at all nodes, such as the backpressure policy. Additionally, we provide a heuristic extension of our proposed overlay routing scheme for the unrestricted class of networks

Improvements to the Secure Construction and Utilization of Greedy Embeddings in Friend-to-Friend Overlays

Routing based on greedy network embeddings enables efficient and privacy-preserving routing in overlays where connectivity is restricted to mutually trusted nodes. In previous works, we proposed security enhancements to the embedding and routing procedures to protect against denial-of-service attacks by malicious overlay participants. In this work, we propose an improved timeout scheme to reduce the stabilization overhead of secure tree maintenance in response to node failures and malicious behavior. Furthermore, we present an attack-resistant packet replication scheme that leverages alternative paths discovered during routing

The Scope of Supreme Court Review in Obscenity Cases

Performance of many P2P systems depends on the ability  to construct a ran- dom overlay network among the nodes. Current state-of-the-art techniques for constructing random overlays have an implicit  requirement that any two nodes in the system should always be able to communicate and establish a link be- tween them.  However, this is not the case in some of the environments where distributed systems are required to be deployed,  e.g, Decentralized Online So- cial Networks, Wireless networks, or networks with limited connectivity because of NATs/firewalls,  etc. In such restricted networks, every node is able to com- municate with only a predefined set of nodes and thus, the existing solutions for constructing random overlays are not applicable.In this thesis we propose a gossip based peer sampling service capable of running on top of such restricted networks and producing an on-the-fly random overlay.  The service provides ev- ery participating node with a set of uniform random nodes from the network, as well as efficient routing paths for reaching those nodes via the restricted net- work. We perform extensive experiments on four real-world networks and show that  the resulting overlays rapidly converge to random overlays. The results also exhibit that the constructed random overlays have self healing behaviour under churn and catastrophic failures

End-to-end QoE optimization through overlay network deployment

In this paper an overlay network for end-to-end QoE management is presented. The goal of this infrastructure is QoE optimization by routing around failures in the IP network and optimizing the bandwidth usage on the last mile to the client. The overlay network consists of components that are located both in the core and at the edge of the network. A number of overlay servers perform end-to-end QoS monitoring and maintain an overlay topology, allowing them to route around link failures and congestion. Overlay access components situated at the edge of the network are responsible for determining whether packets are sent to the overlay network, while proxy components manage the bandwidth on the last mile. This paper gives a detailed overview of the end-to-end architecture together with representative experimental results which comprehensively demonstrate the overlay network's ability to optimize the QoE

NextBestOnce: Achieving Polylog Routing despite Non-greedy Embeddings

Social Overlays suffer from high message delivery delays due to insufficient routing strategies. Limiting connections to device pairs that are owned by individuals with a mutual trust relationship in real life, they form topologies restricted to a subgraph of the social network of their users. While centralized, highly successful social networking services entail a complete privacy loss of their users, Social Overlays at higher performance represent an ideal private and censorship-resistant communication substrate for the same purpose. Routing in such restricted topologies is facilitated by embedding the social graph into a metric space. Decentralized routing algorithms have up to date mainly been analyzed under the assumption of a perfect lattice structure. However, currently deployed embedding algorithms for privacy-preserving Social Overlays cannot achieve a sufficiently accurate embedding and hence conventional routing algorithms fail. Developing Social Overlays with acceptable performance hence requires better models and enhanced algorithms, which guarantee convergence in the presence of local optima with regard to the distance to the target. We suggest a model for Social Overlays that includes inaccurate embeddings and arbitrary degree distributions. We further propose NextBestOnce, a routing algorithm that can achieve polylog routing length despite local optima. We provide analytical bounds on the performance of NextBestOnce assuming a scale-free degree distribution, and furthermore show that its performance can be improved by more than a constant factor when including Neighbor-of-Neighbor information in the routing decisions.Comment: 23 pages, 2 figure