18,949 research outputs found
Optimisation of Mobile Communication Networks - OMCO NET
The mini conference âOptimisation of Mobile Communication Networksâ focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University.
The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing
Distributed Detection over Random Networks: Large Deviations Performance Analysis
We study the large deviations performance, i.e., the exponential decay rate
of the error probability, of distributed detection algorithms over random
networks. At each time step each sensor: 1) averages its decision variable
with the neighbors' decision variables; and 2) accounts on-the-fly for its new
observation. We show that distributed detection exhibits a "phase change"
behavior. When the rate of network information flow (the speed of averaging) is
above a threshold, then distributed detection is asymptotically equivalent to
the optimal centralized detection, i.e., the exponential decay rate of the
error probability for distributed detection equals the Chernoff information.
When the rate of information flow is below a threshold, distributed detection
achieves only a fraction of the Chernoff information rate; we quantify this
achievable rate as a function of the network rate of information flow.
Simulation examples demonstrate our theoretical findings on the behavior of
distributed detection over random networks.Comment: 30 pages, journal, submitted on December 3rd, 201
Community Seismic Network
The article describes the design of the Community Seismic Network, which is a dense open seismic network based on low cost sensors. The inputs are from sensors hosted by volunteers from the community by direct connection to their personal computers, or through sensors built into mobile devices. The server is cloud-based for robustness and to dynamically handle the load of impulsive earthquake events. The main product of the network is a map of peak acceleration, delivered within seconds of the ground shaking. The lateral variations in the level of shaking will be valuable to first responders, and the waveform information from a dense network will allow detailed mapping of the rupture process. Sensors in buildings may be useful for monitoring the state-of-health of the structure after major shaking
Push & Pull: autonomous deployment of mobile sensors for a complete coverage
Mobile sensor networks are important for several strategic applications
devoted to monitoring critical areas. In such hostile scenarios, sensors cannot
be deployed manually and are either sent from a safe location or dropped from
an aircraft. Mobile devices permit a dynamic deployment reconfiguration that
improves the coverage in terms of completeness and uniformity.
In this paper we propose a distributed algorithm for the autonomous
deployment of mobile sensors called Push&Pull. According to our proposal,
movement decisions are made by each sensor on the basis of locally available
information and do not require any prior knowledge of the operating conditions
or any manual tuning of key parameters.
We formally prove that, when a sufficient number of sensors are available,
our approach guarantees a complete and uniform coverage. Furthermore, we
demonstrate that the algorithm execution always terminates preventing movement
oscillations.
Numerous simulations show that our algorithm reaches a complete coverage
within reasonable time with moderate energy consumption, even when the target
area has irregular shapes. Performance comparisons between Push&Pull and one of
the most acknowledged algorithms show how the former one can efficiently reach
a more uniform and complete coverage under a wide range of working scenarios.Comment: Technical Report. This paper has been published on Wireless Networks,
Springer. Animations and the complete code of the proposed algorithm are
available for download at the address:
http://www.dsi.uniroma1.it/~novella/mobile_sensors
An Overview of Mobile Ad Hoc Networks for the Existing Protocols and Applications
Mobile Ad Hoc Network (MANET) is a collection of two or more devices or nodes
or terminals with wireless communications and networking capability that
communicate with each other without the aid of any centralized administrator
also the wireless nodes that can dynamically form a network to exchange
information without using any existing fixed network infrastructure. And it's
an autonomous system in which mobile hosts connected by wireless links are free
to be dynamically and some time act as routers at the same time, and we discuss
in this paper the distinct characteristics of traditional wired networks,
including network configuration may change at any time, there is no direction
or limit the movement and so on, and thus needed a new optional path Agreement
(Routing Protocol) to identify nodes for these actions communicate with each
other path, An ideal choice way the agreement should not only be able to find
the right path, and the Ad Hoc Network must be able to adapt to changing
network of this type at any time. and we talk in details in this paper all the
information of Mobile Ad Hoc Network which include the History of ad hoc,
wireless ad hoc, wireless mobile approaches and types of mobile ad Hoc
networks, and then we present more than 13 types of the routing Ad Hoc Networks
protocols have been proposed. In this paper, the more representative of routing
protocols, analysis of individual characteristics and advantages and
disadvantages to collate and compare, and present the all applications or the
Possible Service of Ad Hoc Networks.Comment: 24 Pages, JGraph-Hoc Journa
CAREER: Data Management for Ad-Hoc Geosensor Networks
This project explores data management methods for geosensor networks, i.e. large collections of very small, battery-driven sensor nodes deployed in the geographic environment that measure the temporal and spatial variations of physical quantities such as temperature or ozone levels. An important task of such geosensor networks is to collect, analyze and estimate information about continuous phenomena under observation such as a toxic cloud close to a chemical plant in real-time and in an energy-efficient way. The main thrust of this project is the integration of spatial data analysis techniques with in-network data query execution in sensor networks. The project investigates novel algorithms such as incremental, in-network kriging that redefines a traditional, highly computationally intensive spatial data estimation method for a distributed, collaborative and incremental processing between tiny, energy and bandwidth constrained sensor nodes. This work includes the modeling of location and sensing characteristics of sensor devices with regard to observed phenomena, the support of temporal-spatial estimation queries, and a focus on in-network data aggregation algorithms for complex spatial estimation queries. Combining high-level data query interfaces with advanced spatial analysis methods will allow domain scientists to use sensor networks effectively in environmental observation. The project has a broad impact on the community involving undergraduate and graduate students in spatial database research at the University of Maine as well as being a key component of a current IGERT program in the areas of sensor materials, sensor devices and sensor. More information about this project, publications, simulation software, and empirical studies are available on the project\u27s web site (http://www.spatial.maine.edu/~nittel/career/)
- âŠ