Motivated by applications to wireless sensor, peer-to-peer, and ad hoc networks, we propose a distributed algorithm called broadcast based multi-gossiping algorithm (BMGA), which is designed for exchanging information and computing in an arbitrarily connected network of nodes. Unlike traditional randomized gossip algorithms, push-sum mechanism based BMGA preserves the sums and weights, and admi...

Randomized gossip (RG) based distributed averaging has been popular for wireless sensor networks (WSNs) in multiple areas. With RG, randomly two adjacent nodes are selected to communicate and exchange information iteratively until consensus is reached. One way to improve the convergence speed of RG is to use greedy gossip with eavesdropping (GGE). Instead of randomly selecting two nodes, GGE se...

Workplace gossip is a ubiquitous phenomenon around the world: research on organizations in both the United States and Western Europe suggests that over 90% of the workforce engages in at least some gossip activity on the job (Gosser et al., 2012). Organizational literature has paid little attention to gossip and, perhaps because of its complexity, management research surrounding gossip is scant...

Gossip is informal talking about colleagues. Taking a social network perspective, we argue that group boundaries and social status in the informal workplace network determine who the objects of positive and negative gossip are. Gossip networks were collected among 36 employees in a public child care organization, and analyzed using exponential random graph modeling (ERGM). As hypothesized, both...

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 pres...

of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science GOSSIP-BASED FAILURE DETECTION AND CONSENSUS FOR TERASCALE COMPUTING By Rajagopal Subramaniyan May 2003 Chair: Alan D. George Department: Electrical and Computer Engineering One promising avenue of research on failure detection for large systems ...

In the context of Web 2.0, the users become massive producers of diverse data that can be stored in a large variety of systems. The fact that the users’ data spaces are distributed in many different systems makes data sharing difficult. In this context of large scale distribution of users and data, a general solution to data sharing is offered by distributed search and recommendation. In partic...

In our DACE project [6], diverging requirements expressed through QoS are mainly explored by a variety of different delivery semantics implemented through different dissemination algorithms ranging from “classic” Reliable Broadcast [18], to new and original algorithms, like the broadcast algorithm we introduce in [7], and which ensures reliable delivery of events despite network failures. While...

in this paper we describe, in the case of short messages, an efficient gossiping algorithm for 3-dimensional torus networks (wrap-around or toroidal meshes) that uses synchronous circuitswitched routing. The algorithm is based on a recursive decomposition of a torus. The algorithm requires an optimal number of rounds and a quasi-optimal number of intermediate switch settings to gossip in an 7i ...

Gossip is a well-known protocol which was proposed to implement broadcast service with a high reliability in an arbitrarily connected network of sensor nodes. The probabilistic techniques employed in gossip have been used to address many challenges which are caused by flooding in wireless sensor networks (WSNs). However, very little work has yet been done on real-time wireless sensor networks w...