4,376 research outputs found
Energy Efficient Ant Colony Algorithms for Data Aggregation in Wireless Sensor Networks
In this paper, a family of ant colony algorithms called DAACA for data
aggregation has been presented which contains three phases: the initialization,
packet transmission and operations on pheromones. After initialization, each
node estimates the remaining energy and the amount of pheromones to compute the
probabilities used for dynamically selecting the next hop. After certain rounds
of transmissions, the pheromones adjustment is performed periodically, which
combines the advantages of both global and local pheromones adjustment for
evaporating or depositing pheromones. Four different pheromones adjustment
strategies are designed to achieve the global optimal network lifetime, namely
Basic-DAACA, ES-DAACA, MM-DAACA and ACS-DAACA. Compared with some other data
aggregation algorithms, DAACA shows higher superiority on average degree of
nodes, energy efficiency, prolonging the network lifetime, computation
complexity and success ratio of one hop transmission. At last we analyze the
characteristic of DAACA in the aspects of robustness, fault tolerance and
scalability.Comment: To appear in Journal of Computer and System Science
GraphStream: A Tool for bridging the gap between Complex Systems and Dynamic Graphs
The notion of complex systems is common to many domains, from Biology to
Economy, Computer Science, Physics, etc. Often, these systems are made of sets
of entities moving in an evolving environment. One of their major
characteristics is the emergence of some global properties stemmed from local
interactions between the entities themselves and between the entities and the
environment. The structure of these systems as sets of interacting entities
leads researchers to model them as graphs. However, their understanding
requires most often to consider the dynamics of their evolution. It is indeed
not relevant to study some properties out of any temporal consideration. Thus,
dynamic graphs seem to be a very suitable model for investigating the emergence
and the conservation of some properties. GraphStream is a Java-based library
whose main purpose is to help researchers and developers in their daily tasks
of dynamic problem modeling and of classical graph management tasks: creation,
processing, display, etc. It may also be used, and is indeed already used, for
teaching purpose. GraphStream relies on an event-based engine allowing several
event sources. Events may be included in the core of the application, read from
a file or received from an event handler
A cluster based communication architecture for distributed applications in mobile ad hoc networks
Thesis (Master)--Izmir Institute of Technology, Computer Engineering, Izmir, 2006Includes bibliographical references (leaves: 63-69)Text in English; Abstract: Turkish and Englishx, 85 leavesIn this thesis, we aim to design and implement three protocols on a hierarchical architecture to solve the balanced clustering, backbone formation and distributed mutual exclusion problems for mobile ad hoc network(MANET)s. Our ¯rst goal is to cluster the MANET into balanced partitions. Clustering is a widely used approach to ease implemen-tation of various problems such as routing and resource management in MANETs. We propose the Merging Clustering Algorithm(MCA) for clustering in MANETs that merges clusters to form higher level of clusters by increasing their levels. Secondly, we aim to con-struct a directed ring topology across clusterheads which were selected by MCA. Lastly, we implement the distributed mutual exclusion algorithm based on Ricart-Agrawala algo-rithm for MANETs(Mobile RA). Each cluster is represented by a coordinator node on the ring which implements distributed mutual exclusion algorithm on behalf of any member in the cluster it represents. We show the operations of the algorithms, analyze their time and message complexities and provide results in the simulation environment of ns2
Resilient Wireless Sensor Networks Using Topology Control: A Review
Wireless sensor networks (WSNs) may be deployed in failure-prone environments, and WSNs nodes easily fail due to unreliable wireless connections, malicious attacks and resource-constrained features. Nevertheless, if WSNs can tolerate at most losing k − 1 nodes while the rest of nodes remain connected, the network is called k − connected. k is one of the most important indicators for WSNs’ self-healing capability. Following a WSN design flow, this paper surveys resilience issues from the topology control and multi-path routing point of view. This paper provides a discussion on transmission and failure models, which have an important impact on research results. Afterwards, this paper reviews theoretical results and representative topology control approaches to guarantee WSNs to be k − connected at three different network deployment stages: pre-deployment, post-deployment and re-deployment. Multi-path routing protocols are discussed, and many NP-complete or NP-hard problems regarding topology control are identified. The challenging open issues are discussed at the end. This paper can serve as a guideline to design resilient WSNs
Decentralized Connectivity-Preserving Deployment of Large-Scale Robot Swarms
We present a decentralized and scalable approach for deployment of a robot
swarm. Our approach tackles scenarios in which the swarm must reach multiple
spatially distributed targets, and enforce the constraint that the robot
network cannot be split. The basic idea behind our work is to construct a
logical tree topology over the physical network formed by the robots. The
logical tree acts as a backbone used by robots to enforce connectivity
constraints. We study and compare two algorithms to form the logical tree:
outwards and inwards. These algorithms differ in the order in which the robots
join the tree: the outwards algorithm starts at the tree root and grows towards
the targets, while the inwards algorithm proceeds in the opposite manner. Both
algorithms perform periodic reconfiguration, to prevent suboptimal topologies
from halting the growth of the tree. Our contributions are (i) The formulation
of the two algorithms; (ii) A comparison of the algorithms in extensive
physics-based simulations; (iii) A validation of our findings through
real-robot experiments.Comment: 8 pages, 8 figures, submitted to IROS 201
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