2,337 research outputs found
Gossip Algorithms for Distributed Signal Processing
Gossip algorithms are attractive for in-network processing in sensor networks
because they do not require any specialized routing, there is no bottleneck or
single point of failure, and they are robust to unreliable wireless network
conditions. Recently, there has been a surge of activity in the computer
science, control, signal processing, and information theory communities,
developing faster and more robust gossip algorithms and deriving theoretical
performance guarantees. This article presents an overview of recent work in the
area. We describe convergence rate results, which are related to the number of
transmitted messages and thus the amount of energy consumed in the network for
gossiping. We discuss issues related to gossiping over wireless links,
including the effects of quantization and noise, and we illustrate the use of
gossip algorithms for canonical signal processing tasks including distributed
estimation, source localization, and compression.Comment: Submitted to Proceedings of the IEEE, 29 page
INDIGO: An In Situ Distributed Gossip Framework for Sensor Networks
AbstractâWith the onset of Cyber-Physical Systems (CPS), distributed algorithms on Wireless Sensor Networks(WSNs) have been receiving renewed attention. The distributed consensus problem is a well studied problem having a myriad of applications which can be accomplished using asynchronous distributed gossip algorithms on Wireless Sensor Networks(WSN). However, a practical realization of gossip algorithms for WSNs is found lacking in the current state of the art. In this paper, we propose the design, development and analysis of a novel in-situ distributed gossip framework called INDIGO. A key aspect of INDIGO is its ability to execute on a generic system platform as well as on a hardware oriented testbed platform in a seamless manner allowing easy portability of existing algorithms. We evaluate the performance of INDIGO with respect to the distributed consensus problem as well as the distributed optimization problem. We also present a data driven analysis of the effect, certain operating parameters like sleep time and wait time have on the performance of the framework and empirically attempt to determine a sweet spot. The results obtained from various experiments on INDIGO validate its efficacy, reliability and robustness and demonstrate its utility as a framework for the evaluation and implementation of asynchronous distributed algorithms
Pheromone-based In-Network Processing for wireless sensor network monitoring systems
Monitoring spatio-temporal continuous fields using wireless sensor networks (WSNs) has emerged as a novel solution. An efficient data-driven routing mechanism for sensor querying and information gathering in large-scale WSNs is a challenging problem. In particular, we consider the case of how to query the sensor network information with the minimum energy cost in scenarios where a small subset of sensor nodes has relevant readings. In order to deal with this problem, we propose a Pheromone-based In-Network Processing (PhINP) mechanism. The proposal takes advantages of both a pheromone-based iterative strategy to direct queries towards nodes with relevant information and query- and response-based in-network filtering to reduce the number of active nodes. Additionally, we apply reinforcement learning to improve the performance. The main contribution of this work is the proposal of a simple and efficient mechanism for information discovery and gathering. It can reduce the messages exchanged in the network, by allowing some error, in order to maximize the network lifetime. We demonstrate by extensive simulations that using PhINP mechanism the query dissemination cost can be reduced by approximately 60% over flooding, with an error below 1%, applying the same in-network filtering strategy.Fil: Riva, Guillermo Gaston. Universidad Nacional de CĂłrdoba. Facultad de Ciencias Exactas, FĂsicas y Naturales; Argentina. Universidad TecnolĂłgica Nacional; Argentina. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas. Centro CientĂfico TecnolĂłgico Conicet - CĂłrdoba; ArgentinaFil: Finochietto, Jorge Manuel. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas. Centro CientĂfico TecnolĂłgico Conicet - CĂłrdoba. Instituto de Estudios Avanzados en IngenierĂa y TecnologĂa. Universidad Nacional de CĂłrdoba. Facultad de Ciencias Exactas FĂsicas y Naturales. Instituto de Estudios Avanzados en IngenierĂa y TecnologĂa; Argentin
Geographic Gossip: Efficient Averaging for Sensor Networks
Gossip algorithms for distributed computation are attractive due to their
simplicity, distributed nature, and robustness in noisy and uncertain
environments. However, using standard gossip algorithms can lead to a
significant waste in energy by repeatedly recirculating redundant information.
For realistic sensor network model topologies like grids and random geometric
graphs, the inefficiency of gossip schemes is related to the slow mixing times
of random walks on the communication graph. We propose and analyze an
alternative gossiping scheme that exploits geographic information. By utilizing
geographic routing combined with a simple resampling method, we demonstrate
substantial gains over previously proposed gossip protocols. For regular graphs
such as the ring or grid, our algorithm improves standard gossip by factors of
and respectively. For the more challenging case of random
geometric graphs, our algorithm computes the true average to accuracy
using radio
transmissions, which yields a factor improvement over
standard gossip algorithms. We illustrate these theoretical results with
experimental comparisons between our algorithm and standard methods as applied
to various classes of random fields.Comment: To appear, IEEE Transactions on Signal Processin
Greedy Gossip with Eavesdropping
This paper presents greedy gossip with eavesdropping (GGE), a novel
randomized gossip algorithm for distributed computation of the average
consensus problem. In gossip algorithms, nodes in the network randomly
communicate with their neighbors and exchange information iteratively. The
algorithms are simple and decentralized, making them attractive for wireless
network applications. In general, gossip algorithms are robust to unreliable
wireless conditions and time varying network topologies. In this paper we
introduce GGE and demonstrate that greedy updates lead to rapid convergence. We
do not require nodes to have any location information. Instead, greedy updates
are made possible by exploiting the broadcast nature of wireless
communications. During the operation of GGE, when a node decides to gossip,
instead of choosing one of its neighbors at random, it makes a greedy
selection, choosing the node which has the value most different from its own.
In order to make this selection, nodes need to know their neighbors' values.
Therefore, we assume that all transmissions are wireless broadcasts and nodes
keep track of their neighbors' values by eavesdropping on their communications.
We show that the convergence of GGE is guaranteed for connected network
topologies. We also study the rates of convergence and illustrate, through
theoretical bounds and numerical simulations, that GGE consistently outperforms
randomized gossip and performs comparably to geographic gossip on
moderate-sized random geometric graph topologies.Comment: 25 pages, 7 figure
GCP: Gossip-based Code Propagation for Large-scale Mobile Wireless Sensor Networks
Wireless sensor networks (WSN) have recently received an increasing interest.
They are now expected to be deployed for long periods of time, thus requiring
software updates. Updating the software code automatically on a huge number of
sensors is a tremendous task, as ''by hand'' updates can obviously not be
considered, especially when all participating sensors are embedded on mobile
entities. In this paper, we investigate an approach to automatically update
software in mobile sensor-based application when no localization mechanism is
available. We leverage the peer-to-peer cooperation paradigm to achieve a good
trade-off between reliability and scalability of code propagation. More
specifically, we present the design and evaluation of GCP ({\emph Gossip-based
Code Propagation}), a distributed software update algorithm for mobile wireless
sensor networks. GCP relies on two different mechanisms (piggy-backing and
forwarding control) to improve significantly the load balance without
sacrificing on the propagation speed. We compare GCP against traditional
dissemination approaches. Simulation results based on both synthetic and
realistic workloads show that GCP achieves a good convergence speed while
balancing the load evenly between sensors
Gossip along the way: order-optimal consensus through randomized path averaging
Gossip algorithms have recently received significant attention, mainly because they constitute simple and robust algorithms for distributed information processing over networks. However for many topologies that are realistic for wireless ad-hoc and sensor networks (like grids and random geometric graphs), the standard nearest-neighbor gossip converges very slowly. A recently proposed algorithm called geographic gossip improves gossip efficiency by a factor for random geometric graphs, by exploiting geographic information of node locations. In this paper we prove that a variation of geographic gossip that averages along routed paths, improves efficiency by an additional factor and is order optimal for grids and random geometric graphs. Our analysis provides some general techniques and can be used to provide bounds on the performance of randomized message passing algorithms operating over various graph topologies
A Chemistry-Inspired Framework for Achieving Consensus in Wireless Sensor Networks
The aim of this paper is to show how simple interaction mechanisms, inspired
by chemical systems, can provide the basic tools to design and analyze a
mathematical model for achieving consensus in wireless sensor networks,
characterized by balanced directed graphs. The convergence and stability of the
model are first proven by using new mathematical tools, which are borrowed
directly from chemical theory, and then validated by means of simulation
results, for different network topologies and number of sensors. The underlying
chemical theory is also used to derive simple interaction rules that may
account for practical issues, such as the estimation of the number of neighbors
and the robustness against perturbations. Finally, the proposed chemical
solution is validated under real-world conditions by means of a four-node
hardware implementation where the exchange of information among nodes takes
place in a distributed manner (with no need for any admission control and
synchronism procedure), simply relying on the transmission of a pulse whose
rate is proportional to the state of each sensor.Comment: 12 pages, 10 figures, submitted to IEEE Sensors Journa
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