We consider an unreliable wireless sensor gridnetwork with n nodes placed in a square of unit area. We are interested in the coverage of the region and the connectivity of the network. We first show that the necessary and sufficient conditions for the random grid network to cover the unit square region as well as ensure that the active nodes are connected are of the form p(n)r ,wherer(n) is the transmission radius of each node and p(n) is the probability that a node is "active" (not failed). This result indicates that, when n is large, even if each node is highly unreliable and the transmission power is small, we can still maintain connectivity with coverage.

Gossip-based protocols for group communication have attractive scalability and reliability properties. The probabilistic gossip schemes studied so far typically assume that each group member has full knowledge of the global membership and chooses gossip targets uniformly at random. The requirement of global knowledge impairs their applicability to very large-scale groups. In this paper, we present SCAMP (Scalable Membership protocol), a novel peer-to-peer membership protocol which operates in a fully decentralized manner and provides each member with a partial view of the group membership. Our protocol is self-organizing in the sense that the size of partial views naturally converges to the value required to support a gossip algorithm reliably. This value is a function of the group size, but is achieved without any node knowing the group size. We propose additional mechanisms to achieve balanced view sizes even with highly unbalanced subscription patterns. We present the design, theoretical analysis, and a detailed evaluation of the basic protocol and its refinements. Simulation results show that the reliability guarantees provided by SCAMP are comparable to previous schemes based on global knowledge. The scale of the experiments attests to the scalability of the protocol.

The growth of the Internet raises new challenges for the design of distributed systems and applications. In the context of group communication protocols, gossip-based schemes have attracted interest as they are scalable, easy to deploy, and resilient to network and process failures. However, traditional gossip-based protocols have two major drawbacks: 1) They rely on each peer having knowledge of the global membership and 2) being oblivious to the network topology, they can impose a high load on network links when applied to wide-area settings. In this paper, we provide a theoretical analysis of gossip-based protocols which relates their reliability to key system parameters (system size, failure rates, and number of gossip targets). The results provide guidelines for the design of practical protocols. In particular, they show how reliability can be maintained while alleviating drawback 1) by providing each peer with only a small subset of the total membership information and drawback 2) by organizing members into a hierarchical structure that reflects their proximity according to some network-related metric. We validate the analytical results by simulations and verify that the hierarchical gossip protocol considerably reduces the load on the network compared to the original, nonhierarchical protocol.

In this paper, we argue that a broad range of large-scale network services would benefit from a scalable mechanism for delivering state about a random subset of global participants. Key to this approach is ensuring that membership in the subset changes periodically and with uniform representation over all participants. Random subsets could help overcome inherent scaling limitations to services that maintain global state and perform global network probing. It could further improve the routing performance of peer-to-peer distributed hash tables by locating topologically-close nodes. This paper presents the design, implementation, and evaluation of RanSub, a scalable protocol for delivering such state.

Epidemic-style (gossip-based) techniques have recently emerged as a scalable class of protocols for peer-to-peer reliable multicast dissemination in large process groups. These protocols provide probabilistic guarantees on reliability and scalability. However, existing implementations of epidemic-style dissemination are reputed to suffer from two major drawbacks: a) (Network Overhead) when deployed on a WAN-wide or VPN-wide scale they cause a large number of packets to transit across the boundaries of network domains (eg., LANs, subnets, ASs), causing an overload on core network elements such as bridges, routers, and links, and b) (Lack of Adaptivity) they impose the same load on process group members and the network regardless of the failure characteristics of the underlying network. In this paper, we report on the first comprehensive set of solutions to these problems. The solution includes two protocols: a) a Hierarchical Gossiping protocol, and b) an Adaptive multicast Dissemination Framework that can be used with any gossiping primitive. Our solution organizes nodes in a hierarchy which re ects the network topology and guarantees low trac across domain boundaries in the network. In the interests of space, this paper focuses on the Hierarchical Gossiping protocol in detail through mathematical and simulation analysis that evaluate the improvement over a traditional gossiping protocol. We present an overview of the working and properties of the Adaptive Dissemination protocol.

We consider the problem of a user querying for information over a sensor network, where the user does not have prior knowledge of the location of the information. We consider three information query strategies: (i) a Source-only search, where the source (user) tries to locate the destination by initiating query which propagates as a continuous time random walk (Brownian motion); (ii) a Source and Receiver Driven “Sticky ” Search, where both the source and the destination send a query or an advertisement, and these leave a “sticky ” trail to aid in locating the destination; and (iii) where the destination information is spatially cached (i.e., repeated over space), and the source tries to locate any one of the caches. After a random interval of time with average t, if the information is not located, the query times-out, and the search is unsuccessful. For a source-only search, we show that the probability that a query is unsuccessful decays as (log(t)) −1. When both the source and the destination send queries or advertisements, we show that the probability that a query is unsuccessful decays as t −5/8. Further, faster polynomial decay rates can be achieved by using a finite number of queries or advertisements. Finally, when a spatially periodic cache is employed, we show that the probability that a query is unsuccessful

Abstract. The newscast model is a general approach for communication in large agent-based distributed systems. The two basic services— membership management and information dissemination—are implemented by the same epidemic-style protocol. In this paper we present the newscast model and report on experiments using a Java implementation. The experiments involve communication in a large, wide-area cluster computer. By analysis of the outcome of the experiments we demonstrate that the system indeed shows the scalability and dependability properties predicted by our previous theoretical and simulation results. 1

This paper describes and evaluates Fireflies, a scalable protocol for supporting intrusion-tolerant network overlays. While such a protocol cannot distinguish Byzantine nodes from correct nodes in general, Fireflies provides correct nodes with a reasonably current view of which nodes are live, as well as a pseudo-random mesh for communication. The amount of data sent by correct nodes grows linearly with the aggregate rate of failures and recoveries, even if provoked by Byzantine nodes. The set of correct nodes form a connected submesh; correct nodes cannot be eclipsed by Byzantine nodes. Fireflies is deployed and evaluated on PlanetLab. 1.

This paper presents RaWMS, a novel lightweight random membership service for ad hoc networks. The service provides each node with a partial uniformly chosen view of network nodes. Such a membership service is useful, e.g., in data dissemination algorithms, lookup and discovery services, peer sampling services, and complete membership construction. The design of RaWMS is based on a novel reverse random walk (RW) sampling technique. The paper includes a formal analysis of both the reverse RW sampling technique and RaWMS and verifies it through a detailed simulation study. In addition, RaWMS is compared both analytically and by simulations with a number of other known methods such as flooding and gossip-based techniques.

Gossip, or epidemic, protocols have emerged as a powerful strategy to implement highly scalable and resilient reliable broadcast primitives. Due to scalability reasons, each participant in a gossip protocol maintains a partial view of the system. The reliability of the gossip protocol depends upon some critical properties of these views, such as degree distribution and clustering coefficient. Several algorithms have been proposed to maintain partial views for gossip protocols. In this paper, we show that under a high number of faults, these algorithms take a long time to restore the desirable view properties. To address this problem, we present HyParView, a new membership protocol to support gossip-based broadcast that ensures high levels of reliability even in the presence of high rates of node failure. The HyParView protocol is based on a novel approach that relies in the use of two distinct partial views, which are maintained with different goals by different strategies. 1