We propose a new architecture for efficient network monitoring and measurements in a traditional IP network. This new architecture enables establishment of multiple paths (tunnels) between source-destination pairs without having to modify the underlying routing protocol(s). Based on the proposed architecture we propose a measurement-based multipath routing algorithm derived from simultaneous perturbation stochastic approximation. The proposed algorithm does not assume that the gradient of analytical cost function is known to the algorithm, but rather relies on noisy estimates from measurements. Using the analytical model presented in the paper we prove the convergence of the algorithm to the optimal solution. Simulation results are presented to demonstrate the advantages of the proposed algorithm under a variety of network scenarios. A comparative study with an existing optimal routing algorithm, MATE, is also provided.

This paper presents an overlay architecture where service providers deploy a set of service nodes (called MSNs) in the network to efficiently implement media-streaming applications. These MSNs are organized into an overlay and act as application-layer multicast forwarding entities for a set of clients. We present a decentralized scheme that organizes the MSNs into an appropriate overlay structure that is particularly beneficial for real-time applications. We formulate our optimization criterion as a "degree-constrained minimum average-latency problem" which is known to be NP-hard. A key feature of this formulation is that it gives a dynamic priority to different MSNs based on the size of its service set. Our proposed approach iteratively modifies the overlay tree using localized transformations to adapt with changing distribution of MSNs, clients, as well as network conditions. We show that a centralized greedy approach to this problem does not perform quite as well, while our distributed iterative scheme efficiently converges to near-optimal solutions.

We consider the problem of finding nearby application peers over the Internet. We define a new peer-finding scheme (called Tiers) that scales to large application peer groups. Tiers creates a hierarchy of the peers, which allows an efficient and scalable solution to this problem. The scheme can be implemented entirely in the application-layer and does not require the deployment of either any additional measurement services, or well-known reference landmarks in the network. We present detailed evaluation of Tiers and compare it to one previously proposed scheme called Beaconing. Through analysis and detailed simulations on 10,000 node Internet-like topologies we show that Tiers achieves comparable or better performance with a significant reduction in control overheads for groups of size 32 or more.

We describe a new scalable application-layer multicast protocol, specifically designed for low-bandwidth, data streaming applications with large receiver sets. Our scheme is based upon a hierarchical clustering of the application-layer multicast peers and can support a number of different data delivery trees with desirable properties.We present extensive simulations of both our protocol and the Narada application-layer multicast protocol over Internet-like topologies. Our results show that for groups of size 32 or more, our protocol has lower link stress (by about 25%), improved or similar end-to-end latencies and similar failure recovery properties. More importantly, it is able to achieve these results by using orders of magnitude lower control traffic.Finally, we present results from our wide-area testbed in which we experimented with 32-100 member groups distributed over 8 different sites. In our experiments, average group members established and maintained low-latency paths and incurred a maximum packet loss rate of less than 1% as members randomly joined and left the multicast group. The average control overhead during our experiments was less than 1 Kbps for groups of size 100.

We consider the problem of finding nearby application-peers (close friends) over the Internet. We focus on unicast-only solutions and introduce a new scheme -Beaconing-for finding peers that are near. Our scheme uses distance measurement points (called beacons) and can be implemented entirely in the application-layer without investing in large infrastructure changes. We present an extensive evaluation of Beaconing and compare it to existing schemes including Expanding Ring searches and Triangulation. Our experiments show that 3-8 beacons are sufficient to provide efficient peer-location service on 10 000 node Internet-like topologies. Further, our results are 2-5 times more accurate than existing techniques. We also present results from an implementation of Beaconing over a non-trivial wide-area testbed. In our experiments, Beaconing is able to efficiently (< 3 K Bytes and < 50 packets on average), quickly (< 1 second on average), and accurately (< 20 ms error on average) find nearby peers on the Internet.