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Distributed algorithm

About: Distributed algorithm is a research topic. Over the lifetime, 20416 publications have been published within this topic receiving 548109 citations.


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Journal ArticleDOI
TL;DR: This approach is the first of its kind for solving the on-line cooperative observation problem and implementing it on a physical robot team and proposes that the CMOMMT problem makes an excellent domain for studying multi-robot learning in inherently cooperative tasks.
Abstract: An important issue that arises in the automation of many security, surveillance, and reconnaissance tasks is that of observing the movements of targets navigating in a bounded area of interest. A key research issue in these problems is that of sensor placement—determining where sensors should be located to maintain the targets in view. In complex applications involving limited-range sensors, the use of multiple sensors dynamically moving over time is required. In this paper, we investigate the use of a cooperative team of autonomous sensor-based robots for the observation of multiple moving targets. In other research, analytical techniques have been developed for solving this problem in complex geometrical environments. However, these previous approaches are very computationally expensive—at least exponential in the number of robots—and cannot be implemented on robots operating in real-time. Thus, this paper reports on our studies of a simpler problem involving uncluttered environments—those with either no obstacles or with randomly distributed simple convex obstacles. We focus primarily on developing the on-line distributed control strategies that allow the robot team to attempt to minimize the total time in which targets escape observation by some robot team member in the area of interest. This paper first formalizes the problem (which we term CMOMMT for i>Cooperative Multi-Robot Observation of Multiple Moving Targets) and discusses related work. We then present a distributed heuristic approach (which we call A-CMOMMT) for solving the CMOMMT problem that uses weighted local force vector control. We analyze the effectiveness of the resulting weighted force vector approach by comparing it to three other approaches. We present the results of our experiments in both simulation and on physical robots that demonstrate the superiority of the A-CMOMMT approach for situations in which the ratio of targets to robots is greater than 1/2. Finally, we conclude by proposing that the CMOMMT problem makes an excellent domain for studying multi-robot learning in inherently cooperative tasks. This approach is the first of its kind for solving the on-line cooperative observation problem and implementing it on a physical robot team.

273 citations

Proceedings ArticleDOI
19 Sep 1999
TL;DR: A distributed algorithm is presented that partitions the nodes of a fully mobile network (multi-hop network) into clusters, thus giving the network a hierarchical organization and is proven to be adaptive to changes in the network topology due to nodes' mobility and to nodes addition/removal.
Abstract: A distributed algorithm is presented that partitions the nodes of a fully mobile network (multi-hop network) into clusters, thus giving the network a hierarchical organization. The algorithm is proven to be adaptive to changes in the network topology due to nodes' mobility and to nodes addition/removal. A new weight-based mechanism is introduced for the efficient cluster formation/maintenance that allows the cluster organization to be configured for specific applications and adaptive to changes in the network status, not available in previous solutions. Specifically, new and flexible criteria are defined that allow the choice of the nodes that coordinate the clustering process based on mobility parameters and/or their current status. Simulation results are provided that demonstrate up to an 85% reduction on the communication overhead associated with the cluster maintenance with respect to techniques used in clustering algorithms previously proposed.

272 citations

Journal ArticleDOI
TL;DR: This article shows that SeRLoc is robust against known attacks on a WSNs such as the wormhole attack, the Sybil attack, and compromise of network entities and analytically compute the probability of success for each attack.
Abstract: Many distributed monitoring applications of Wireless Sensor Networks (WSNs) require the location information of a sensor node. In this article, we address the problem of enabling nodes of Wireless Sensor Networks to determine their location in an untrusted environment, known as the secure localization problem. We propose a novel range-independent localization algorithm called SeRLoc that is well suited to a resource constrained environment such as a WSN. SeRLoc is a distributed algorithm based on a two-tier network architecture that allows sensors to passively determine their location without interacting with other sensors. We show that SeRLoc is robust against known attacks on a WSNs such as the wormhole attack, the Sybil attack, and compromise of network entities and analytically compute the probability of success for each attack. We also compare the performance of SeRLoc with state-of-the-art range-independent localization schemes and show that SeRLoc has better performance.

272 citations

Proceedings ArticleDOI
16 Jun 2008
TL;DR: This paper proposes an optimal buffer management policy based on global knowledge about the network that outperforms existing ones in terms of both average delivery rate and delivery delay and introduces a distributed algorithm that uses statistical learning to approximate the global knowledge required by the the optimal algorithm, in practice.
Abstract: Delay Tolerant Networks are wireless networks where disconnections may occur frequently due to propagation phenomena, node mobility, and power outages. Propagation delays may also be long due to the operational environment (e.g. deep space, underwater). In order to achieve data delivery in such challenging networking environments, researchers have proposed the use of store-carry-and-forward protocols: there, a node may store a message in its buffer and carry it along for long periods of time, until an appropriate forwarding opportunity arises. Additionally, multiple message replicas are often propagated to increase delivery probability. This combination of long-term storage and replication imposes a high storage overhead on untethered nodes (e.g. handhelds). Thus, efficient buffer management policies are necessary to decide which messages should be discarded, when node buffers are operated close to their capacity. In this paper, we propose efficient buffer management policies for delay tolerant networks. We show that traditional buffer management policies like drop-tail or drop-front fail to consider all relevant information in this context and are, thus, sub-optimal. Using the theory of encounter-based message dissemination, we propose an optimal buffer management policy based on global knowledge about the network. Our policy can be tuned either to minimize the average delivery delay or to maximize the average delivery rate. Finally, we introduce a distributed algorithm that uses statistical learning to approximate the global knowledge required by the the optimal algorithm, in practice. Using simulations based on a synthetic mobility model and real mobility traces, we show that our buffer management policy based on statistical learning successfully approximates the performance of the optimal policy in all considered scenarios. At the same time, our policy outperforms existing ones in terms of both average delivery rate and delivery delay.

271 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202381
2022135
2021583
2020759
2019876
2018845