A comparison of epidemic algorithms in wireless sensor networks

Cataloged from PDF version of article.We consider the problem of reliable data dissemination in the context of wireless sensor networks. For some application scenarios, reliable data dissemination to all nodes is necessary for propagating code updates, queries, and other sensitive information in wireless sensor networks. Epidemic algorithms are a natural approach for reliable distribution of information in such ad hoc, decentralized, and dynamic environments. In this paper we show the applicability of epidemic algorithms in the context of wireless sensor environments, and provide a comparative performance analysis of the three variants of epidemic algorithms in terms of message delivery rate, average message latency, and messaging overhead on the network. © 2006 Elsevier B.V. All rights reserved

A comparison of epidemic algorithms in wireless sensor networks

We consider the problem of reliable data dissemination in the context of wireless sensor networks. For some application scenarios, reliable data dissemination to all nodes is necessary for propagating code updates, queries, and other sensitive information in wireless sensor networks. Epidemic algorithms are a natural approach for reliable distribution of information in such ad hoc, decentralized, and dynamic environments. In this paper we show the applicability of epidemic algorithms in the context of wireless sensor environments, and provide a comparative performance analysis of the three variants of epidemic algorithms in terms of message delivery rate, average message latency, and messaging overhead on the network. © 2006 Elsevier B.V. All rights reserved

Fuzzy tuned gossip algorithms in mobile ad hoc networks

“This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder." “Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.” DOI: 10.1109/MED.2009.5164552Mobile ad hoc networks (MANET) are modeled as agents that form communities without infrastructure, for a random period of time and with usually cooperative behavior. The nodes of MANET often carry information to disseminate. The dynamics of information delivery, mostly referred as average consensus, is a common problem in these networks. The gossip protocols are designed to implement this task. The standard algorithms that are used in these protocols exploit the network describing matrix, aka Laplacian, and exchange information to all node neighbors. In static networks the problem can be considered as an output feedback problem but in the case of MANET the problem is getting complicated due to the continuous change of network topology. In this paper the fuzzy reasoning approach is proposed to tune and leverage the gossip protocol. Illustrative simulations are included to demonstrate the application of the method and to present comparative results in various cases

Analysis of Push-type Epidemic Data Dissemination in Fully Connected Networks

Consider a fully connected network of nodes, some of which have a piece of data to be disseminated to the whole network. We analyze the following push-type epidemic algorithm: in each push round, every node that has the data, i.e., every infected node, randomly chooses $c \in {\mathbb Z}_+$ other nodes in the network and transmits, i.e., pushes, the data to them. We write this round as a random walk whose each step corresponds to a random selection of one of the infected nodes; this gives recursive formulas for the distribution and the moments of the number of newly infected nodes in a push round. We use the formula for the distribution to compute the expected number of rounds so that a given percentage of the network is infected and continue a numerical comparison of the push algorithm and the pull algorithm (where the susceptible nodes randomly choose peers) initiated in an earlier work. We then derive the fluid and diffusion limits of the random walk as the network size goes to $\infty$ and deduce a number of properties of the push algorithm: 1) the number of newly infected nodes in a push round, and the number of random selections needed so that a given percent of the network is infected, are both asymptotically normal 2) for large networks, starting with a nonzero proportion of infected nodes, a pull round infects slightly more nodes on average 3) the number of rounds until a given proportion $\lambda$ of the network is infected converges to a constant for almost all $\lambda \in (0,1)$. Numerical examples for theoretical results are provided.Comment: 28 pages, 5 figure

A lightweight distributed super peer election algorithm for unstructured dynamic P2P systems

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e de ComputadoresNowadays with the current growth of information exchange, and the increasing mobility of devices, it becomes essential to use technology to monitor this development. For that P2P networks are used, the exchange of information between agencies is facilitated, these now being applied in mobile networks, including MANETs, where they have special features such as the fact that they are semi-centralized, where it takes peers more ability to make a greater role in the network. But those peer with more capacity, which are used in the optimization of various parameters of these systems, such as optimization\to research, are difficult to identify due to the fact that the network does not have a fixed topology, be constantly changing, (we like to go online and offline, to change position, etc.) and not to allow the exchange of large messages. To this end, this thesis proposes a distributed election algorithm of us greater capacity among several possible goals, enhance research in the network. This includes distinguishing characteristics, such as election without global knowledge network, minimal exchange of messages, distributed decision made without dependence on us and the possibility of influencing the election outcome as the special needs of the network

A Game-Theoretic Approach for Elastic Distributed Data Stream Processing

Distributed data stream processing applications are structured as graphs of interconnected modules able to ingest high-speed data and to transform them in order to generate results of interest. Elasticity is one of the most appealing features of stream processing applications. It makes it possible to scale up/down the allocated computing resources on demand in response to fluctuations of the workload. On clouds, this represents a necessary feature to keep the operating cost at affordable levels while accommodating user-defined QoS requirements. In this article, we study this problem from a game-theoretic perspective. The control logic driving elasticity is distributed among local control agents capable of choosing the right amount of resources to use by each module. In a first step, we model the problem as a noncooperative game in which agents pursue their self-interest. We identify the Nash equilibria and we design a distributed procedure to reach the best equilibrium in the Pareto sense. As a second step, we extend the noncooperative formulation with a decentralized incentive-based mechanism in order to promote cooperation by moving the agreement point closer to the system optimum. Simulations confirm the results of our theoretical analysis and the quality of our strategies