3,916 research outputs found
Performance evaluation of WMN-GA for different mutation and crossover rates considering number of covered users parameter
Node placement problems have been long investigated in the optimization field due to numerous applications in location science and classification. Facility location problems are showing their usefulness to communication networks, and more especially from Wireless Mesh Networks (WMNs) field. Recently, such problems are showing their usefulness to communication networks, where facilities could be servers or routers offering connectivity services to clients. In this paper, we deal with the effect of mutation and crossover operators in GA for node placement problem. We evaluate the performance of the proposed system using different selection operators and different distributions of router nodes considering number of covered users parameter. The simulation results show that for Linear and Exponential ranking methods, the system has a good performance for all rates of crossover and mutation.Peer ReviewedPostprint (published version
A simulated annealing algorithm for router nodes placement problem in Wireless Mesh Networks
Mesh router nodes placement is a central problem in Wireless Mesh Networks (WMNs). An efficient placement of mesh router nodes is indispensable for achieving network performance in terms of both network connectivity and user coverage. Unfortunately the problem is computationally hard to solve to optimality even for small deployment areas and a small number of mesh router nodes. As WMNs are becoming an important networking infrastructure for providing cost-efficient broadband wireless connectivity, researchers are paying attention to the resolution of the mesh router placement problem through heuristic approaches in order to achieve near optimal, yet high quality solutions in reasonable time. In this work we propose and evaluate a simulated annealing (SA) approach to placement of mesh router nodes in WMNs. The optimization model uses two maximization objectives, namely, the size of the giant component in the network and user coverage. Both objectives are important to deployment of WMNs; the former is crucial to achieve network connectivity while the later is an indicator of the QoS in WMNs. The SA approach distinguishes for its simplicity yet its policy of neighborhood exploration allows to reach promising areas of the solution space where quality solutions could be found. We have experimentally evaluated the SA algorithm through a benchmark of generated instances, varying from small to large size, and capturing different characteristics of WMNs such as topological placements of mesh clients. The experimental results showed the efficiency of the annealing approach for the placement of mesh router nodes in WMNs.Peer ReviewedPostprint (author's final draft
Effects of population size for location-aware node placement in WMNs: evaluation by a genetic algorithm--based approach
Wireless mesh networks (WMNs) are cost-efficient networks that have the potential to serve as an infrastructure for advanced location-based services. Location service is a desired feature for WMNs to support location-oriented applications. WMNs are also interesting infrastructures for supporting ubiquitous multimedia Internet access for mobile or fixed mesh clients. In order to efficiently support such services and offering QoS, the optimized placement of mesh router nodes is very important. Indeed, such optimized mesh placement can support location service managed in the mesh and keep the rate of location updates low...Peer ReviewedPostprint (author's final draft
Solving mesh router nodes placement problem in Wireless Mesh Networks by Tabu Search algorithm
Wireless Mesh Networks (WMNs) are an important networking paradigm that offer cost effective Internet connectivity. The performance and operability of WMNs depend, among other factors, on the placement of network nodes in the area. Among the most important objectives in designing a WMN is the formation of a mesh backbone to achieve high user coverage. Given a number of router nodes to deploy, a deployment area and positions of client nodes in the area, an optimization problem can be formulated aiming to find the placement of router nodes so as to maximize network connectivity and user coverage. This optimization problem belongs to facility location problems, which are computationally hard to solve to optimality. In this paper we present the implementation and evaluation of Tabu Search (TS) for the problem of mesh router node placement in WMNs. The experimental evaluation showed the efficiency of TS in solving a benchmark of instances.Peer ReviewedPostprint (author's final draft
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Multimedia delivery in the future internet
The term “Networked Media” implies that all kinds of media including text, image, 3D graphics, audio
and video are produced, distributed, shared, managed and consumed on-line through various networks,
like the Internet, Fiber, WiFi, WiMAX, GPRS, 3G and so on, in a convergent manner [1]. This white
paper is the contribution of the Media Delivery Platform (MDP) cluster and aims to cover the Networked
challenges of the Networked Media in the transition to the Future of the Internet.
Internet has evolved and changed the way we work and live. End users of the Internet have been confronted
with a bewildering range of media, services and applications and of technological innovations concerning
media formats, wireless networks, terminal types and capabilities. And there is little evidence that the pace
of this innovation is slowing. Today, over one billion of users access the Internet on regular basis, more
than 100 million users have downloaded at least one (multi)media file and over 47 millions of them do so
regularly, searching in more than 160 Exabytes1 of content. In the near future these numbers are expected
to exponentially rise. It is expected that the Internet content will be increased by at least a factor of 6, rising
to more than 990 Exabytes before 2012, fuelled mainly by the users themselves. Moreover, it is envisaged
that in a near- to mid-term future, the Internet will provide the means to share and distribute (new)
multimedia content and services with superior quality and striking flexibility, in a trusted and personalized
way, improving citizens’ quality of life, working conditions, edutainment and safety.
In this evolving environment, new transport protocols, new multimedia encoding schemes, cross-layer inthe
network adaptation, machine-to-machine communication (including RFIDs), rich 3D content as well as
community networks and the use of peer-to-peer (P2P) overlays are expected to generate new models of
interaction and cooperation, and be able to support enhanced perceived quality-of-experience (PQoE) and
innovative applications “on the move”, like virtual collaboration environments, personalised services/
media, virtual sport groups, on-line gaming, edutainment. In this context, the interaction with content
combined with interactive/multimedia search capabilities across distributed repositories, opportunistic P2P
networks and the dynamic adaptation to the characteristics of diverse mobile terminals are expected to
contribute towards such a vision.
Based on work that has taken place in a number of EC co-funded projects, in Framework Program 6 (FP6)
and Framework Program 7 (FP7), a group of experts and technology visionaries have voluntarily
contributed in this white paper aiming to describe the status, the state-of-the art, the challenges and the way
ahead in the area of Content Aware media delivery platforms
An annealing approach to router nodes placement problem in wireless mesh networks
Mesh router nodes placement is a central problem to Wireless Mesh Networks (WMNs). An efficient placement of mesh router nodes is indispensable for achieving network performance in terms of both network connectivity and user coverage. Unfortunately the problem is computationally hard to solve to optimality even for small deployment areas and a small number of mesh router nodes. As WMNs are becoming an important networking infrastructure for providing cost-efficient broadband wireless connectivity, researchers are paying attention to the resolution of the mesh router placement problem through heuristic approaches in order to achieve near optimal, yet high quality solutions in reasonable time. In this work we propose and evaluate a Simulated Annealing (SA) approach to placement of mesh router nodes in WMNs. The optimization model uses two maximization objectives, namely, the size of the giant component in the network and user coverage. Both objectives are important to deployment of WMNs; the former is crucial to achieve network connectivity while the later is an indicator of the QoS in WMNs. The SA approach distinguishes for its simplicity yet its policy of neighborhood exploration allows to reach promising areas of the solution space where quality solutions could be found. We have experimentally evaluated the SA algorithm through a benchmark of generated instances, varying from small to large size, and capturing different characteristics of WMNs such as topological placements of mesh clients. The experimental results showed the efficiency of the annealing approach for the placement of mesh router nodes in WMNs.Peer ReviewedPostprint (published version
Genetic algorithms for efficient placement of router nodes in wireless mesh networks
In Wireless Mesh Networks (WMNs) the meshing architecture, consisting of a grid of mesh routers, provides connectivity services to different mesh client nodes. The good performance and operability of WMNs largely depends on placement of mesh routers nodes in the geographical area to achieve network connectivity and stability. Thus, finding optimal or near-optimal mesh router nodes placement is crucial to such networks. In this work we propose and evaluate Genetic Algorithms (GAs) for near-optimally solving the problem. In our approach we seek a two-fold optimization, namely, the maximization of the size of the giant component in the network and that of user coverage. The size of the giant component is considered here as a criteria for measuring network connectivity. GAs explore the solution space by means of a population of individuals, which are evaluated, selected, crossed and mutated to reproduce new individuals of better quality. The fitness of individuals is measured with respect to network connectivity and user coverage being the former a primary objective and the later a secondary one. Several genetic operators have been considered in implementing GAs in order to find the configuration that works best for the problem. We have experimentally evaluated the proposed GAs using a benchmark of generated instances varying from small to large size. In order to evaluate the quality of achieved solutions for different possible client distributions, instances have been generated using different distributions of mesh clients (Uniform, Normal, Exponential and Weibull). The experimental results showed the efficiency of the GAs for computing high quality solutions of mesh router nodes placement in WMNs.Peer ReviewedPostprint (published version
PHALANX: Expendable Projectile Sensor Networks for Planetary Exploration
Technologies enabling long-term, wide-ranging measurement in hard-to-reach areas are a critical need for planetary science inquiry. Phenomena of interest include flows or variations in volatiles, gas composition or concentration, particulate density, or even simply temperature. Improved measurement of these processes enables understanding of exotic geologies and distributions or correlating indicators of trapped water or biological activity. However, such data is often needed in unsafe areas such as caves, lava tubes, or steep ravines not easily reached by current spacecraft and planetary robots. To address this capability gap, we have developed miniaturized, expendable sensors which can be ballistically lobbed from a robotic rover or static lander - or even dropped during a flyover. These projectiles can perform sensing during flight and after anchoring to terrain features. By augmenting exploration systems with these sensors, we can extend situational awareness, perform long-duration monitoring, and reduce utilization of primary mobility resources, all of which are crucial in surface missions. We call the integrated payload that includes a cold gas launcher, smart projectiles, planning software, network discovery, and science sensing: PHALANX. In this paper, we introduce the mission architecture for PHALANX and describe an exploration concept that pairs projectile sensors with a rover mothership. Science use cases explored include reconnaissance using ballistic cameras, volatiles detection, and building timelapse maps of temperature and illumination conditions. Strategies to autonomously coordinate constellations of deployed sensors to self-discover and localize with peer ranging (i.e. a local GPS) are summarized, thus providing communications infrastructure beyond-line-of-sight (BLOS) of the rover. Capabilities were demonstrated through both simulation and physical testing with a terrestrial prototype. The approach to developing a terrestrial prototype is discussed, including design of the launching mechanism, projectile optimization, micro-electronics fabrication, and sensor selection. Results from early testing and characterization of commercial-off-the-shelf (COTS) components are reported. Nodes were subjected to successful burn-in tests over 48 hours at full logging duty cycle. Integrated field tests were conducted in the Roverscape, a half-acre planetary analog environment at NASA Ames, where we tested up to 10 sensor nodes simultaneously coordinating with an exploration rover. Ranging accuracy has been demonstrated to be within +/-10cm over 20m using commodity radios when compared to high-resolution laser scanner ground truthing. Evolution of the design, including progressive miniaturization of the electronics and iterated modifications of the enclosure housing for streamlining and optimized radio performance are described. Finally, lessons learned to date, gaps toward eventual flight mission implementation, and continuing future development plans are discussed
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