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electronics seminars
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13-01-2010, 07:40 AM


Abstract”The unreachability problem (i.e., the so-called void problem) that exists in the greedy routing algorithms has been studied for the wireless sensor networks. Some of the current research work cannot fully resolve the void problem, while there exist other schemes that can guarantee the delivery of packets with the excessive consumption of control overheads. In this paper, a greedy antivoid routing (GAR) protocol is proposed to solve the void problem with increased routing efficiency by exploiting the boundary finding technique for the unit disk graph (UDG). The proposed rolling-ball UDG boundary traversal (RUT) is employed to completely guarantee the delivery of packets from the source to the destination node under the UDG network. The boundary map (BM) and the indirect map searching (IMS) scheme are proposed as efficient algorithms for the realization of the RUT technique. Moreover, the hop count reduction (HCR) scheme is utilized as a short-cutting technique to reduce the routing hops by listening to the neighbor™s traffic, while the intersection navigation (IN) mechanism is proposed to obtain the best rolling direction for boundary traversal with the adoption of shortest path criterion. In order to maintain the network requirement of the proposed RUT scheme under the non-UDG networks, the partial UDG construction (PUC) mechanism is proposed to transform the non-UDG into UDG setting for a portion of nodes that facilitate boundary traversal. These three schemes are incorporated within the GAR protocol to further enhance the routing performance with reduced communication overhead. The proofs of correctness for the GAR scheme are also given in this paper. Comparing with the existing localized routing algorithms, the simulation results show that the proposed GAR-based protocols can provide better routing efficiency.

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Beemanapally Esther
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08-06-2010, 10:41 AM

Hi friends can i get the ppt for greedy anti void routing for WSN
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08-06-2010, 01:22 PM

hey Beemanapally Esther
the paper (GREEDY ROUTING WITH ANTI-VOID TRAVERSAL FOR WIRELESS SENSOR NETWORKS) is ieee so you can download its from portal.acmcitation.cfm?id=1550407.1550626 (we dont have permission to share it ) or a similar paper available to learn see it also intechwebdownloadpdf.php?id=5835

i hope you enjoyed it
and come again for helping other students issues in this forum
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06-09-2010, 02:54 PM

I need the overall design of the project and implimentation greedy routing with anti void traversal
for wireless sensor network!
project topics
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28-04-2011, 05:54 PM

hi see topicideashow-to-greedy-routing-with-anti-void-traversal-for-wireless-sensor-networks-full-report for getting overall design of the project and implimentation greedy routing with anti void traversal
for wireless sensor network
Use Search at wisely To Get Information About Project Topic and Seminar ideas with report/source code along pdf and ppt presenaion
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09-05-2012, 03:53 PM

Greedy Routing with Anti-Void Traversal for Wireless Sensor Networks

.doc   GREEDY DOCUM.doc (Size: 631.5 KB / Downloads: 77)


All project and implimentations are feasible given unlimited resources and infinite time. But the development of software is plagued by the scarcity of resources and difficult delivery rates. It is both necessary and prudent to evaluate the feasibility of a project and implimentation at the earliest possible time.
Three key considerations are involved in the feasibility analysis.
Economic Feasibility:
This procedure is to determine the benefits and savings that are expected from a candidate system and compare them with costs. If benefits outweigh costs, then the decision is made to design and implement the system. Otherwise, further justification or alterations in proposed system will have to be made if it is to have a chance of being approved. This is an ongoing effort that improves in accuracy at each phase of the system life cycle.
Technical Feasibility:
Technical feasibility centers on the existing computer system (hardware, software, etc.,) and to what extent it can support the proposed addition. If the budget is a serious constraint, then the project and implimentation is judged not feasible.
Operational Feasibility:
People are inherently resistant to change, and computers have been known to facilitate change. It is understandable that the introduction of a candidate system requires special effort to educate, sell, and train the staff on new ways of conducting business.

A wireless sensor network (WSN) consists of spatially distributed autonomous sensors to cooperatively monitor physical or environmental conditions, such as temperature, sound, vibration, pressure, motion or pollutants. The development of wireless sensor networks was motivated by military applications such as battlefield surveillance. They are now used in many industrial and civilian application areas, including industrial process monitoring and control, machine health monitoring, environment and habitat monitoring, healthcare applications, home automation, and traffic control.
In addition to one or more sensors, each node in a sensor network is typically equipped with a radio transceiver or other wireless communications device, a small microcontroller, and an energy source, usually a battery. A sensor node might vary in size from that of a shoebox down to the size of a grain of dust, although functioning "motes" of genuine microscopic dimensions have yet to be created. The cost of sensor nodes is similarly variable, ranging from hundreds of dollars to a few pennies, depending on the size of the sensor network and the complexity required of individual sensor nodes. Size and cost constraints on sensor nodes result in corresponding constraints on resources such as energy, memory, computational speed and bandwidth.
A sensor network normally constitutes a wireless ad-hoc network, meaning that each sensor supports a multi-hop routing algorithm (several nodes may forward data packets to the base station).

The applications for WSNs are varied, typically involving some kind of monitoring, tracking, or controlling. Specific applications include habitat monitoring, object tracking, nuclear reactor control, fire detection, and traffic monitoring. In a typical application, a WSN is scattered in a region where it is meant to collect data through its sensor nodes.
Area monitoring

Area monitoring is a common application of WSNs. In area monitoring, the WSN is deployed over a region where some phenomenon is to be monitored. For example, a large quantity of sensor nodes could be deployed over a battlefield to detect enemy intrusion instead of using landmines. When the sensors detect the event being monitored (heat, pressure, sound, light, electro-magnetic field, vibration, etc), the event needs to be reported to one of the base stations, which can take appropriate action (e.g., send a message on the internet or to a satellite). Depending on the exact application, different objective functions will require different data-propagation strategies, depending on things such as need for real-time response, redundancy of the data (which can be tackled via data aggregation and information fusion techniques), need for security, etc.

Environmental monitoring
A number of WSNs have been deployed for environmental monitoring. Many of these have been short lived, often due to the prototype nature of the project and implimentations. Examples of longer-lived deployments are monitoring the state of permafrost in the Swiss Alps: The PermaSense Project, PermaSense Live Data Browser and glacier monitoring.
chandra pratap
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25-02-2013, 12:42 PM

sir i have all the documents but i don't know any thing so plz. explain these things through my e-mail id and also mention that how to run it?

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