Araneola: A scalable reliable multicast system for dynamic environments

We present Araneola ∗ , a scalable reliable applicationlevel multicast system for highly dynamic wide-area environments. Araneola supports multi-point to multi-point reliable communication in a fully distributed manner while incurring constant load on each node. For a tunable parameter k ≥ 3, Araneola constructs and dynamically maintains an overlay structure in which each node’s degree is either k or k + 1, and roughly 90 % of the nodes have degree k. Empirical evaluation shows that Araneola’s overlay structure achieves three important mathematical properties of k-regular random graphs (i.e., random graphs in which each node has exactly k neighbors) with N nodes: (i) its diameter grows logarithmically with N; (ii) it is generally kconnected; and (iii) it remains highly connected following random removal of linear-size subsets of edges or nodes. The overlay is constructed at a very low cost: each join, leave, or failure is handled locally, and entails the sending of only about 3k messages in total. Given this overlay, Araneola disseminates multicast messages by gossiping over the overlay’s links. We show that compared to a standard gossip-based multicast protocol, Araneola achieves substantial improvements in load, reliability, and latency. Finally, we present an extension to Araneola in which the basic overlay is enhanced with additional links chosen according to geographic proximity and available bandwidth. We show that this approach reduces the number of physical hops messages traverse without hurting the overlay’s robustness. 1

Octopus: A Fault-Tolerant and Efficient Ad-hoc Routing Protocol

Mobile ad-hoc networks (MANETs) are failure-prone environments; it is common for mobile wireless nodes to intermittently disconnect from the network, e.g., due to signal blockage. This paper focuses on withstanding such failures in large MANETs: we present Octopus, a fault-tolerant and efficient position-based routing protocol. Fault-tolerance is achieved by employing redundancy, i.e., storing the location of each node at many other nodes, and by keeping frequently refreshed soft state. At the same time, Octopus achieves a low location update overhead by employing a novel aggregation technique, whereby a single packet updates the location of many nodes at many other nodes. Octopus is highly scalable: for a fixed node density, the number of location update packets sent does not grow with the network size. And when the density increases, the overhead drops. Thorough empirical evaluation using the ns2 simulator with up to 675 mobile nodes shows that Octopus achieves excellent fault-tolerance at a modest overhead: when all nodes intermittently disconnect and reconnect, Octopus achieves the same high reliability as when all nodes are constantly up

Constructing Scalable Overlays for Pub-Sub with Many Topics Problems, Algorithms, and Evaluation

We investigate the problem of designing a scalable overlay network to support decentralized topic-based pub/sub communication. We introduce a new optimization problem, called Minimum Topic-Connected Overlay (Min-TCO), that captures the tradeoff between the scalability of the overlay (in terms of the nodes ’ fanout) and the message forwarding overhead incurred by the communicating parties. Roughly, the Min-TCO problem is as follows: Given a collection of nodes and their subscriptions, connect the nodes using the minimum possible number of edges so that for each topic t, a message published on t could reach all the nodes interested in t by being forwarded by only the nodes interested in t. We show that the decision version of Min-TCO is NPcomplete, and present a polynomial algorithm that approximate

Octopus: A fault-tolerant and efficient ad-hoc routing protocol

Mobile ad-hoc networks (MANETs) are failure-prone environments; it is common for mobile wireless nodes to intermittently disconnect from the network, e.g., due to signal blockage. This paper focuses on withstanding such failures in large MANETs: we present Octopus, a fault-tolerant and efficient positionbased routing protocol. Fault-tolerance is achieved by employing redundancy, i.e., storing the location of each node at many other nodes, and by keeping frequently refreshed soft state. At the same time, Octopus achieves a low location update overhead by employing a novel aggregation technique, whereby a single packet updates the location of many nodes at many other nodes. Octopus is highly scalable: for a fixed node density, the number of location update packets sent does not grow with the network size. And when the density increases, the overhead drops. Thorough empirical evaluation using the ns2 simulator with up to 675 mobile nodes shows that Octopus achieves excellent fault-tolerance at a modest overhead: when all nodes intermittently disconnect and reconnect, Octopus achieves the same high reliability as when all nodes are constantly up