location based final

Location Based Anti-Void Routing Protocol in Wireless Sensor Network

Chapter 1

PREAMBLE

1.1 Introduction

A sensor network is a computer network Composed of a large number of sensor

nodes. The sensor nodes are densely deployed inside the phenomenon, they deploy

random and have cooperative capabilities. Usually these devices are small and

inexpensive, so that they can be produced and deployed in large numbers, and so their

resources in terms of energy, memory, computational speed and bandwidth are severely

constrained.

Sensor network is an emerging field in distributed networks and there are many

challenges in sensor network, which includes Restricted Resources, Routing, Security,

Scalability, and Uncertainty etc…Routing is the most essential one among these. This

project deals with Location-based routing protocol.

1.2 Scope of the project

How to guarantee delivery of packets is considered an important issue for the

localized routing algorithms. The well-known greedy forwarding (GF) algorithm is

considered a superior scheme with its low routing overheads. However, the void problem

(unreachability), which makes the GF technique unable to find its next closer hop to the

destination. The void problem can only be either 1) partially alleviated or 2) resolved with

considerable routing overheads and significant converging time.

Our work deals with avoiding void-problem (unreachability) by using GAR

protocol in wireless sensor network. The proposed RUT (Rolling-ball UDG Boundary

Traversal) scheme is employed to completely guarantee the delivery of packets from

source to destination node under UDG network.

1.3 Objective of the project

1. Identified the problem in the GF protocol

2. Implement GAR protocol

Dept. Of CNE, BITM, Bellary Page No.1


3. Use the RUT scheme is to resolve the void problem such that the packet

delivery from NS (source node) to ND (destination node) can be guaranteed.

There are research works on the design of graph-based routing algorithms to deal

with the void problem. The nodes (NS, ND) are considered the transmission pair, while

NV represents the node that the void problem occurs.

In this project, a greedy anti-void routing (GAR) protocol is proposed to guarantee

packet delivery with increased routing efficiency by completely resolving the void

problem based on the UDG setting.

The GAR protocol is designed to be a combination of both the conventional GF

algorithm and the proposed rolling-ball UDG boundary traversal (RUT) scheme. The GF

scheme is executed by the GAR algorithm without the occurrence of the void problem, by

using the RUT scheme which is served as the remedy for resolving the void problem,

leading to the assurance for packet delivery. The implementation of the GAR protocol is

also explained, including that for the proposed boundary map (BM) and the indirect map

searching (IMS) schemes.

1.4 Literature survey

Wireless sensor network consists of sensor nodes with communication capabilities

specific sensing tasks. Due to the limited available resources, efficient design of localized

multihop routing protocol [1] becomes a crucial subject within the WSNs. How to

guarantee delivery of packets is considered an important issue for the localized routing

algorithms. The well known routing algorithm is GREEDY FORWARDING [2]

algorithm proposed by Finn in 1987.

This cause the problem called void-problem [3], which makes the GF technique

unable to find its next closer hop to the destination, will cause the GF ALGORITHM

failing to guarantee the delivery of data packets. Several routing algorithms are proposed

to resolve or reduce void- problem, which can be classified into non-graph-based and

based-graph schemes.

The intuitive schemes as Proposed in [4] construct a two-hop neighbor table for

implementing the GF algorithm. The network flooding mechanism is adopted within the

GRA [5], these are non-graph-based algorithms, [6, 7, 8]. GREEDY FORWARDING



leads a void problem (unreachability) this is found by Karp and Kung in 2000. And

Classified into non-graph based and graph based schemes.

On other hand the graph-based routing algorithms [9, 10, 11, 12, 13] to deal with

the void problem. To overcome or to reduce this problem implemented GREEDY

ROUTING WITH ANTI-VOID TRAVERSAL with the help of RUT (Rolling-ball UDG

Boundary Traversal) and IMS (Indirect Map Searching) schemes.

1.5 Organization of the report

This report is divided into eight chapters.

Chapter 1: This chapter contains introduction part of the project, scope of the

project, objective of the project, literature survey and organization

of the report.

Chapter 2: This chapter gives the background details of WSN, characteristics,

challenges, architecture and applications of WSN.

Chapter 3: This chapter gives the details of classification and overview of

WSN routing protocols.

Chapter 4: This chapter includes Software requirements specification,

feasibility study and design phase of the project.

Chapter 5: This chapter includes the Implementation phase which uses the

Microsoft visual studio .Net and SQL-Server, implementation of

GAR protocol and testing phase.

Chapter 6: This chapter contains different output screens.

Chapter 7: This chapter includes conclusion and future work of the project.

Chapter 8: This chapter depicts References used to develop the project.

Appendix I: This part of the report lists Abbreviations used in the project.

Appendix II: This part of the report provides Publications of this project.



Chapter 2

OVERVIEW OF SENSOR NETWORKS

2.1 Introduction to wireless sensor networks

Sensor networks randomly deploy tens to thousands of sensor nodes. Each sensor

node has a separate sensing, processing, storage and communication unit. The position of

sensor nodes need not be predetermined. This allows random deployment in inaccessible

terrains or disaster relief operations.

Figure 2.1: Structure of a Sensor Node

Sensor networks consist of a huge number of small sensor nodes, which communicate wirelessly. These sensor nodes can be spread out in hard accessible areas by what new applications fields can be pointed out.

Sensor node software is divided into three parts according to the main tasks (Figure 2.1).

• The Operating System handles the device-specific tasks. This contains bootup, initialization of the hardware, scheduling, and memory management as well as the process management. The OS consists of special tailored parts only needed by the specific application of the node.

• A sensor node combines the abilities to compute, communicate and sense. The aim is to fit all mentioned features in a one single chip solution. In principle, controlling of an Actuator is possible, too. Figure 2.1 shows the structure of a sensor node.

• Modules are additional components that increase the functionality of the middleware. Typical modules are routing modules or security modules.



2.2 The characteristics of sensor networks

a. Sensor nodes have constrained resources.

b. The topology changes very frequently due to node failures.

c. Sensor nodes are prone to failures.

d. Sensor nodes mainly use a broadcast communication paradigm.

e. It may contain several thousands of nodes based on application.

2.3 Challenges in sensor networks

a) Restricted Resources: Sensor network has constrainer resources such as

energy, computing power, memory and bandwidth.

b) Dynamic Networks: Due to node mobility, environmental obstructions,

restricted resources, etc, the sensor networks exhibit a highly dynamic network

topology.

c) Scalability: The sensor network should scale from ten to thousands or

millions of sensor nodes. This needs automatic-conjuration, maintenance,

upgrading of individual devices.

d) Integrating with Real World: Sensor networks can be used to monitor real

world phenomena. Hence, identifying time and location in sensor networks is

crucial.

e) Uncertainty in Sensor Readings: Signals detected at physical sensors have

uncertainty due to limitations of the sensor, and they may contain

environmental noise.

2.4 Architecture of sensor network

Sensor network is a combination of nodes that are used to sense data from its

environment and to send the aggregated data to its control node often called sink. Below

figure 2.2 shows typical sensor network.

The sink node communicates with the task manager via core network which can

be Internet or Satellite. Sensors are low cost, low power, and small in size. Due to small

size the transmission power of a sensor is limited.

The data transmitted by a node in the field may pass through multiple hops before

reaching the sink. Many route discovery protocols have been suggested for maintaining



routes from field sensors to the sink(s). Due to low memory, scarcity of available

bandwidth and low power of the sensors.

Figure 2.2: Typical sensor network

The development of sensor nodes is influenced by.

• Increasing device complexity on microchips

• High performance, wireless networking technologies

• A combination of digital signal processing and sensor data acquisition

• Progress within the development of micro-electromechanical systems (MEMS)

• Availability of high performance development tools

2.5 Applications of sensor networks

a. Environmental monitoring (eg. traffic, habitat, security): Nowadays sensor

networks are also widely applied in habitat monitoring, agriculture research,

fire detection and traffic control. Because there is no interruption to the

environment, sensor networks in environmental area is not that strict as in

battlefield.

b. Military applications: Because most of the elemental knowledge of sensor

networks is basic on the defense application at the beginning, especially two

important programs the Distributed Sensor Networks (DSN) and the Sensor

Information Technology (SenIT) form the Defense Advanced Research

Project Agency (DARPA), sensor networks are applied very successfully in

the military sensing. Now wireless sensor networks sensor can be an integral

part of military command, control, communications, computing, intelligence,

surveillance, reconnaissance and targeting systems.



c. Health applications: sensor networks are also widely in health care area. In

some modern hospital sensor networks are constructed to monitor patient

physiological data, to control the drug administration track and monitor

patients and doctors and inside a hospital.

d. Home applications (eg. Intelligent home, responsive environment): Along

with developing commercial application of sensor network it is no so hard to

image that Home application will step into our normal life in the future. Many

concepts are already designed by researcher and architects, like “Smart

Environment: Residential Laboratory” and “Smart Kindergarten” Some are

even realized.



Chapter 3

CLASSIFICATION AND OVERVIEW OF ROUTING

PROTOCOLS IN WIRELESS SENSOR NETWORK

3.1 Introduction to routing protocols

Wireless sensor networks (WSN) a number of independent systems, having each

one or more sensing devices. These systems are able to communicate together through the

use of wireless links. These networks must be easy to deploy and auto-configurable, and

are usually battery-operated.

Routing concept is mainly used while transforming the information from one node

to other nodes. The below section gives the details of routing protocols.

3.2 Classification of routing protocols

The state-of-the-art routing protocols for WSNs can be divided into flat-based

routing, hierarchical-based routing, and location-based routing depending on the network

structure. In flat-based routing, all nodes are typically assigned equal roles or

functionality. In hierarchical-based routing, however, nodes will play different roles in the

network. In location-based routing, sensor nodes' positions are exploited to route data in

the network.

A routing protocol is considered adaptive if certain system parameters can be

controlled in order to adapt to the current network conditions and available energy levels.

Furthermore, these protocols can be classified into multipath-based, query-based,

negotiation-based, QoS-based, or coherent-based routing techniques depending on the

protocol operation.

In general, routing in WSNs can be divided into three categories named as flat-

based routing, hierarchical-based routing, and location based routing protocols depending

on the network structure.

Based on this concept we can classify the protocols whether they are operating on

a flat topology or on a hierarchical topology. In Flat routing protocols all nodes in the

network are treated equally. When node needs to send data, it may find a route consisting



of several hops to the sink. A hierarchical routing protocol is a natural approach to take

for heterogeneous networks where some of the nodes are more powerful than the other

ones. The hierarchy does not always depend on the power of nodes. In Hierarchical

(Clustering) protocols different nodes are grouped to form clusters and data from nodes

belonging to a single cluster can be combined (aggregated).

Figure 3.1: Classification of routing protocols based on network structure.

3.3 Overview of routing protocols

In flat-based routing, all nodes play the same role. In hierarchical-based routing,

however, nodes will play different roles in the network. In location-based routing, sensor

nodes' positions are exploited to route data in the network.

Flat routing (Data Centric Routing protocols): It is not feasible to assign

global identifiers to each node due to the sheer number of nodes deployed in

many applications of sensor networks. Such lack of global identification along

with random deployment of sensor nodes makes it hard to select a specific set

of sensor nodes to be queried. Therefore, data is usually transmitted from

every sensor node within the deployment region with significant redundancy.

This consideration has led to data-centric routing. In data-centric routing, the


Flat Routing protocol.

Eg: SPIN, DD, RR, and GBR

Hierarchical Routing protocol

Eg: LEACH, VGA, GAF,

TEEN&APTEEN

Location-based Routing protocol

Eg: SPAN, GEAR, and SPEED

Routing protocols based on network structure


sink sends queries to certain regions and waits for data from the sensors

located in the selected regions. Eg: SPIN, DD, RR, and GBR.

Hierarchical protocols: The major design attributes of sensor networks are

scalability. Since the sensors are not capable of long-haul communication,

single gateway architecture is not scalable for a larger set of sensors.

Networking clustering has been pursued in some routing approaches to cope

with additional load and to be able to cover a large area of interest without

degrading the service. Hierarchical routing works in two layers, first layer is

used to choose cluster heads and the other layer is used for routing. To make

the WSN more energy efficient, clusters are created and special tasks (data

aggregation, fusion) are assigned to them. It increases the overall system

scalability, lifetime, and energy efficiency. Eg: LEACH, VGA, GAF, and TEEN &

APTEEN.

Location-based protocols: In most cases location information is needed in

order to calculate the distance between two particular nodes so that energy

consumption can be estimated. Generally two techniques are used to find

location, one is to find the coordinate of the neighboring node and other is to

use GPS (Global Positioning System). Since, there is no addressing scheme

for sensor networks like IP-addresses and they are spatially deployed on a

region, location information can be utilized in routing data in an energy

efficient way. Eg: SPAN, GEAR, and SPEED.



Chapter 4

SYSTEM ANALYSIS AND DESIGN

4.1 Feasibility study

The feasibility of the project is analyzed in this phase with a very general plan for

the project and some cost estimates. During system analysis the feasibility study of the

proposed system is to be carried out. For feasibility analysis, some understanding of the

major requirements for the system is essential.

Three key considerations involved in the feasibility analysis are

• Economical Feasibility

• Technical Feasibility

• Operational Feasibility

4.1.1 Economical feasibility

This study is carried out to check the economic impact that the system will have

on the organization. The system which we are developing here is less cost and more

flexible. The care has been taken while developing the system according to the user point

of view.

4.1.2 Technical feasibility

This study is carried out to check the technical feasibility, that is, the technical

requirements of the system is made as to whether the identified user need can be satisfied

using current software and hardware technologies. In the Technical feasibility we have

verified whether the proposed system covers all the requirements of the user or not.

4.1.3 Operational feasibility

This study is carried out to check the operational feasibility, we checked with all

the modules by solving all the debugs. And it can operate well with specified user

requirements.



4.2 Existing system

As mobile computing requires more computation as well as communication

activities, energy efficiency becomes the most critical issue for battery-operated mobile

devices. Specifically, in ad hoc networks where each node is responsible for forwarding

neighbor nodes' data packets, care has to be taken not only to reduce the overall energy

consumption of all relevant nodes but also to balance individual battery levels.

Unbalanced energy usage will result in earlier node failure in overloaded nodes, and in

turn may lead to network partitioning and reduced network lifetime.

Existing Localized Routing Algorithm i.e. GF scheme unable to find its next

closer hop to the destination will cause a problem called void problem (unreachability).

4.3 Proposed system

In this design, a greedy anti-void 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.

4.4 System requirements

Requirement analysis provides the software designer with models that are

translated into data and procedural design.

4.4.1 Hardware requirements

• System : Pentium IV 2.4 GHz.

• Hard Disk : 40 GB.

• Monitor : 15 VGA Colour.

• Mouse : Logitech.

• RAM : 256 Mb.



4.4.2 Software requirements

• Operating system : Windows XP Professional.

• Coding Language : Visual C# and .Net

• Back End : Microsoft SQL Server 2005

• IDE : Microsoft Visual Studio 2008.

4.5 Design approach

Flow chart: A flowchart is a common type of chart that represents an algorithm

or process showing the steps as boxes of various kinds, and their order by connecting

these with arrows. Flowcharts are used in analyzing, designing, documenting or managing

a process or program in various fields. The figure 4.1 shows flow diagram

Class diagram: The class describes a group of objects with the same attributes,

behavior, kinds of relationship, and semantics. Class diagram provide a graphic notation

for modeling classes and their relationships. The figure 4.2 shows class diagram.

Sequence Diagram: The sequence diagram shows the participants in an

interaction and the sequence of messages among them. A sequence diagram shows the

interaction of a system with its actors to perform all or part of a use case. The figure 4.3

shows sequence diagram. Each actor as well as system is represented by a vertical line

called a lifeline and each message by a horizontal arrow form the sender to the receiver.



Figure 4.1: Flow chart of GAR process


Yes

No

Source selects the file (target) which needs to be sent and specify the destination

(sink) address.

Greedy router (Intermediate sensor nodes)

selects the destination node where it has to

reach.

Source needs to transfer the file

Destination receives the files

Failed? Refresh router

Source

(Sensor node)


Figure 4.2: Class diagram


Source Class

Attributes: filedes, fileini, len, ser1

Methods : send( ),

btn open_click( ),

btn send _click ( ), normal_file( ), Normal_file_Load( ).

Destination class

Attributes: obj, ipend, recivepath, sock

Methods :button1_click() button2_click( ),Client( ), dest code( ), start source( ), Form1_laod( ).

Router class

Attributes: dest,etime,extime,obj,path,random,stime,t1,t2,t3,t4,t5,t6,curmsg,ipend msgstatus, recive path, send sock.

Methods :Random Number( ), refresh(),routers(),routers load(),

send(),transmitter(),wireless(), recive code(), start source().


Figure 4.3: Sequence diagram to reach the specified destination using multipath, multihop

routing scheme


Source Router1 Router2 Router3 Router4 Dest

Fail

ed

Alternative Path

Source

Destination


Chapter 5

IMPLEMENTATION AND TESTING

5.1 About tools

5.1.1 The .NET framework

Microsoft .NET is a set of Microsoft software technologies for rapidly building

and integrating XML Web services, Microsoft Windows-based applications, and Web

solutions.

The .NET Framework [15] is a language-neutral platform for writing programs

that can easily and securely interoperate. There’s no language barrier with .NET: there are

numerous languages available to the developer including Managed C++, C#, Visual Basic

and Java Script. The .NET framework provides the foundation for components to interact

seamlessly, whether locally or remotely on different platforms. It standardizes common

data types and communications protocols so that components created in different

languages can easily interoperate.

“.NET” is also the collective name given to various software components built

upon the .NET platform. These will be both products (Visual Studio.NET and

Windows.NET Server, for instance) and services (like Passport, .NET My Services, and

so on).

Asp.Net

xml web services

Windows Forms

Base Class Libraries

Common Language Runtime

Operating System



Figure 5.1: .Net Framework.

The .NET Framework has two main parts:

a. The Common Language Runtime (CLR).

b. A hierarchical set of class libraries.

The CLR is described as the “execution engine” of .NET. It provides the

environment within which programs run. The most important features are

• Conversion from a low-level assembler-style language, called Intermediate

Language (IL), into code native to the platform being executed on.

• Memory management, notably including garbage collection.

• Checking and enforcing security restrictions on the running code.

• Loading and executing programs, with version control and other such

features.

5.1.2 The class library

.NET provides a single-rooted hierarchy of classes, containing over 7000 types.

The root of the namespace is called System; this contains basic types like Byte, Double,

Boolean, and String, as well as Object. All objects derive from System. Object. As well as

objects, there are value types. Value types can be allocated on the stack, which can

provide useful flexibility. There are also efficient means of converting value types to

object types if and when necessary.

The set of classes is pretty comprehensive, providing collections, file, screen, and

network I/O, threading, and so on, as well as XML and database connectivity.

The class library is subdivided into a number of sets (or namespaces), each

providing distinct areas of functionality, with dependencies between the namespaces kept

to a minimum.

5.1.3 Objectives of .Net framework

a. To provide a consistent object-oriented programming environment whether

object codes is stored and executed locally on Internet-distributed, or executed

remotely.



b. To provide a code-execution environment to minimizes software deployment

and guarantees safe execution of code.

c. Eliminates the performance problems.

5.1.4 Features of .Net

The .NET [15, 16] Framework is a new computing platform that simplifies

application development in the highly distributed environment of the Internet. The .NET

Framework is designed to fulfill the following objectives:

• To provide a consistent object-oriented programming environment whether

object code is stored and executed locally, executed locally but Internet-

distributed, or executed remotely.

• To provide a code-execution environment that minimizes software deployment

and versioning conflicts.

• To provide a code-execution environment that guarantees safe execution of

code, including code created by an unknown or semi-trusted third party.

• To provide a code-execution environment that eliminates the performance

problems of scripted or interpreted environments.

• To make the deveCCloper experience consistent across widely varying types

of applications, such as Windows-based applications and Web-based

applications.

• To build all communication on industry standards to ensure that code based on

the .NET Framework can integrate with any other code.

5.2 Programming language used

C# (pronounced C Sharp) is a multi-paradigm programming language that

encompasses functional, imperative, generic, object-oriented (class-based) and

component-oriented programming disciplines [14]. It was developed by Microsoft as part

of the .NET initiative and later approved as a standard by ECMA (ECMA-334) and ISO

(ISO/IEC 23270). C# is one of the programming languages supported by the .NET

Framework's Common Language Runtime.

C# is intended to be a simple, modern, general-purpose, object-oriented

programming language. Its development team is led by Anders Hejlsberg, the designer of

Borland's Object Pascal language. It has an object-oriented syntax based on C++ and is



heavily influenced by Java. It was initially named Cool, which stood for "C-like Object

Oriented Language." However, in July 2000, when Microsoft made the project public, the

name of the programming language was given as C#. The most recent version of the

language is 3.0 which were released in conjunction with the .NET Framework 3.5 in

2007. The next proposed version, 4.0, is in development.

5.3 Microsoft visual studio 2008

Microsoft Visual Studio is an integrated development environment (IDE) from

Microsoft. It can be used to develop console and graphical user interface applications

along with Windows Forms applications, web sites, web applications and web services in

both native code together with managed code for all platforms supported by Microsoft

Windows, Windows Mobile, Windows CE, .NET Framework, .NET Compact

Framework and Microsoft Silver light.

Visual Studio includes a code editor supporting IntelliSense as well as code

refactoring. The integrated debugger works both as a source-level debugger and a

machine-level debugger.

Other built-in tools include a forms designer for building GUI applications, web

designer, class designer, and database schema designer. It allows plug-ins to be added that

enhance the functionality at almost every level - including adding support for source

control systems (like Subversion and Visual SourceSafe) to adding new toolsets like

editors and visual designers for domain-specific languages or toolsets for other aspects of

the software development lifecycle. Visual Studio supports languages by means of

language services, which allow any programming language to be supported (to varying

degrees) by the code editor and debugger, provided a language-specific service has been

authored.

Built-in languages include C/C++ (via Visual C++), VB.NET (via Visual

Basic .NET), and C# (via Visual C#). Support for other languages such as Chrome, F#,

Python, and Ruby among others has been made available via language services which are

to be installed separately.

It also supports XML/XSLT, HTML/XHTML, JavaScript and CSS. Language-

specific versions of Visual Studio also exist which provide more limited language

services to the user. These individual packages are called Microsoft Visual Basic, Visual

J#, Visual C#, and Visual C++.



Currently, Visual Studio 2008 and 2005 Professional Editions, along with

language-specific versions (Visual Basic, C++, C#, J#) of Visual Studio 2005 are

available for free to students as downloads via Microsoft's Dream Spark program. Visual

Studio 2010 is currently in development.

5.4 SQL-server

The OLAP Services feature available in SQL Server version 7.0 is now called

SQL Server 2005 Analysis Services. The term OLAP Services has been replaced with the

term Analysis Services. Analysis Services also includes a new data mining component.

The Repository component available in SQL Server version 7.0 is now called Microsoft

SQL Server 2005 Meta Data Services. References to the component now use the term

Meta Data Services. The term repository is used only in reference to the repository engine

within Meta Data Services.

5.5 Implementation of GAR protocol

5.5.1 Introduction to GAR protocol

The objective of the GAR protocol is to resolve the void problem such that the

packet delivery from NS to ND can be guaranteed. Before diving into the detail

formulation of the proposed GAR algorithm, an introductory example is described in

order to facilitate the understanding of the GAR protocol. As shown in Fig.5.2, the data

packets initiated from the source node NS to the destination node ND will arrive in NV

based on the GF algorithm. The void problem occurs as NV receives the packets, which

leads to the adoption of the RUT scheme as the forwarding strategy of the GAR protocol.

A circle is formed by centering at SV with its radius being equal to half of the

transmission range R/2. The circle is hinged at NV and starts to conduct counterclockwise

rolling until have been encountered by the boundary of the circle, i.e., NA, as in

Figure5.2: Consequently, the data packets in NV will be forwarded to the encountered

node NA.

Subsequently, a new equal-sized circle will be formed, which is centered at SA

and hinged at node NA. The counterclockwise rolling procedure will be proceeded in

order to select the next hop node, i.e., NB in this case. Similarly, same process will be

performed by other intermediate nodes (such as NB and NX) until the node NY is



reached, which is considered to have a smaller distance to ND than that of NV to ND.

The conventional GF scheme will be resumed at NY for delivering data packets to the

destination node ND. As a consequence, the resulting path by adopting the GAR protocol

becomes {NS, NV, NA, NB, NX, NY, NZ, ND}.

Fig.5.2: Example routing paths constructed by using the GAR

5.5.2 Steps involved in algorithm

The RUT scheme is adopted to solve the boundary finding problem, and the

combination of the GF and the RUT scheme (i.e., the GAR protocol) can resolve the void

problem, leading to the guaranteed packet delivery.

The definition of boundary and the problem statement are described as follows

Boundary If there exists a set B N such that 1) the nodes in B form a simple

unidirectional ring and 2) the nodes located on and inside the ring are disconnected with

those outside of the ring, B is denoted as the boundary set and the unidirectional ring is

called a boundary.

Boundary finding problem Given a UDG G (P, E) and the one-hop neighbor

tables T={TNi| Ni Є N}.



There are three phases within the RUT scheme, including the initialization, the

boundary traversal, and the termination phases.

1. Initialization Phase

Specific trigger event is required to execute an algorithm. The trigger event

within the RUT scheme is called the starting point (SP). The RUT scheme can

be initialized from any SP.

2. Boundary Traversal Phase

Given si as the SP associated with its RBNi (si, R/2) hinged at Ni, either the

counterclockwise or clockwise rolling direction can be utilized. As shown in

Figure.5.3, RBNi (si, R/2) is rolled counterclockwise until the next SN is

reached (i.e., Nj in Figure.5.3). The unidirectional edge E ij=(PNi , PNj) can

therefore be constructed. A new SP and the corresponding rolling ball hinged

at Nj (i.e., sj and RBNj (sj, R/2)) will be assigned, and consequently, the same

procedure can be conducted continuously.

3. Termination Phase

The termination condition for the RUT scheme happens while the first

unidirectional edge is revisited. As shown in Fig. 5.3, the RUT scheme will be

terminated if the edge Eij is visited again after the edges Eij, Ejk, Ekl, Elm, and

Emi are traversed. The boundary set initiated from Ni can therefore be obtained

as B = {Ni, Nj, Nk, Nl, Nm}.

Fig. 5.3 RUT scheme



As shown in Fig. 5.3, each node Ni can verify if there exists an SP since the

rolling ball RBNi (Si, R/2) is bounded by the transmission range of N i. It is noticed that

there should always exist an SP, while the void problem occurs within the network. At

this initial phase, the location Si can be selected as the SP for the RUT scheme.

5.5.3 Conditions for GAR protocol

Describes the implementation aspect of the GAR algorithm, which consists of the

GF and the RUT schemes.

• Implementation of GF scheme

GF scheme is considered a straightforward algorithm that only requires the

implementation of the one-hop neighbor table TNi. The next hop node can be

found by the linear search of TNi if the void problem does not occur; otherwise,

the RUT scheme will be adopted based on the proposed GAR protocol.

• Implementation of RUT scheme

The GAR protocol changes its routing mode into the RUT scheme while the

void problem occurs at NV. The boundary traversal phase is conducted by

assigning an SP (i.e., sv as shown in Fig.5.2) associated with the rolling ball

RBNV (sv ,R/2) hinged at NV. While there is no doubt regarding the description

of boundary traversal, there can be considerable efforts required in order to

realize the continuous rolling ball mechanism. A brute-force method can be

adopted as a potential solution by rotating the rolling ball incrementally and

verifying if a new SN has been encountered at each computing step.

In order to resolve the implementation issue of the boundary traversal as

mentioned above, a new parameter called BM (denoted as MNi for each Ni) is introduced

in this section. Moreover, the BM MNi is mainly derived from the one-hop neighbor table

TNi via the IMS method.

The purpose of the BM MNi is to provide a set of direct mappings between the

input SNs and their corresponding output SNs with respect to Ni



Figure 5.4: The process flow of the IMS algorithm

The concept of proposed IMS algorithm is described as follows: The converged

SP arc segments for each Ni can be obtained by acquiring its corresponding converged

non-SP arc segments, i.e., the complement arc segments on the circle C (N i, R/2).

Moreover, the converged non-SP arc segments of Ni can be acquired via the neighbor-

related non-SP arc segments. Consequently, the problem of finding the converged SP arc

segments with respect to Ni is transformed into the problem of obtaining the converged

non-SP arc segments with respect to Ni, which can be acquired via merging the

corresponding neighbor-related non-SP arc segments. IMS scheme is considered a

localized algorithm where only three parameters are required i.e. the maximum

communication distance R, The position of Ni (PNi), and one hop neighbor table TNi.

The IMS algorithm tasks

1. To identify each neighbor-related non-SP arc segment SNioNj (PA, PB) with

respect to Ni that is distinguished by its neighbor Nj.

2. To merge all the neighbor-related non-SP arc segments into the converged

non-SP arc segments with respect to Ni.

3. All the converged SP arc segments with respect to N i can be obtained by

excluding all the converged non-SP arc segments with respect to N i on the

circle C (PNi,R/2).

Partial class

Partial classes allow implementation of a class to be spread between several files,

with each file containing one or more class members. It is primarily useful when parts of

a class are automatically generated. For example, the feature is heavily used by code-

generating user interface designers in Visual Studio.

Source.cs



Name space source

{

Public partial class normal_file:form

{

Public void normal_file_load (object sender, EventArgs e)

{

// loads the form

}

private void btnOpen_Click(object sender, EventArgs e)

{

// selects the file

}

private void btnSend_Click(object sender, EventArgs e)

{

// initiaties the file sending

}

public void send( )

{

// File transferred

} }}

Destination.cs



namespace DestCode

{

public partial class Client : Form

{

public Client( )

{

// initiaties the destination part

}

private void Form1_Load(object sender, EventArgs e)

{

// loads the form

}

private void button2_Click(object sender, EventArgs e)

{

// Selects a File Receiving Path

} }}

Greedy Router.cs

namespace Greedy

{

public partial class Routers : Form

{

public Routers()



{

InitializeComponent( );

}

private void Routers_Load(object sender, EventArgs e)

{

// loads theform

}

public void send(byte[] des)

{

// selects the router

}

} }

Static classes

Static classes are classes that cannot be instantiated or inherited from and that only

allow static members. Their purpose is similar to that of modules in many procedural

languages.

Program.cs

namespace Source

static class Program

{

/// The main entry point for the application.

[STAThread]

static void Main( )



{

// creates the new source

}

}

Program.cs

namespace Destination


{


[STAThread]

static void Main( )

{

//creates the new destination

}

}

Program.cs

namespace Greedy


{


[STAThread]

static void Main( )

{

//creates the new Router

}

}



5.6 Modules of the System

5.6.1 Module description

Current application is differentiated into the following modules which are closely

integrated to each other.

1. Networking module.

2. Boundary evaluation module.

3. Greedy Anti-void Traversal module.

4. Performance evaluation module.

1. Networking module

Client-server computing or networking is a distributed application architecture

that partitions tasks or workloads between service providers (servers) and service

requesters, called clients. Often clients and servers operate over a computer

network on separate hardware. A server machine is a high-performance host that

is running one or more server programs which share its resources with clients. A

client also shares any of its resources; Clients therefore initiate communication

sessions with servers which await (listen to) incoming requests.

2. Boundary evaluation module

The RUT scheme is adopted to solve the boundary finding problem, and the

combination of the GF and the RUT scheme (i.e., the GAR protocol) can resolve

the void problem, leading to the guaranteed packet delivery. The definition of

boundary and the problem statement are described as follows: Definition 1

(boundary). If there exists a set B such that 1) the nodes in B form a simple

unidirectional ring and 2) the nodes located on and inside the ring are

disconnected with those outside of the ring, B is denoted as the boundary set and

the unidirectional ring is called a boundary.

3. Greedy Anti-void Traversal module



The objective of the GAR protocol is to resolve the void problem such that the

packet delivery from NS to ND can be guaranteed. Before diving into the detail

formulation of the proposed GAR algorithm, an introductory example is described

in order to facilitate the understanding of the GAR protocol, the data packets

initiated from the source node NS to the destination node ND will arrive in NV

based on the GF algorithm. The void problem occurs as NV receives the packets,

which leads to the adoption of the RUT scheme as the forwarding strategy of the

GAR protocol. A circle is formed by centering at SV with its radius being equal to

half of the transmission range R/2.

4. Performance evaluation module

The following five metrics are utilized in the simulations for performance

comparison:

Delivery Ratio: The ratio of the number of received data packets to the

number of total data packets sent by the source.

Average End-to-End Delay: The average time elapsed for delivering a data

packet within a successful transmission.

Path Efficiency: The ratio of the number of total hop counts within the entire

routing path over the number of hop counts for the shortest path.

Communication Overhead: The average number of transmitted

control bytes per second, including both the data packet header and the

control packets.

Energy Consumption: The energy consumption for the entire network,

including transmission energy consumption for both the data and control

packets under the bit rate of 11 Mbps and the transmitting power of 15 dBm

for each SN.



5.6.2 Module testing

1. Networking Module Test

Figure 5.5: Testing for Networking Module

When networking failure occurs between client and server or when client path is

not selected, then the data cannot be transferred from source to destination.



2. Boundary Evaluation Module Test



Figure 5.6: Testing for Boundary evaluation module

Void problem can resolved by selecting the boundary in a sensor field, if a

boundary is not selected in a particular sensor field then the data can not reach the

destination node.

Chapter 6



RESULTS

Figure 6.1: Source main page

Figure 6.2: Source selects a file to send



Figure 6.3: Destination selects the receiving path



Figure 6.4: Greedy Router main page

Figure 6.5: Selects the void node



Figure 6.6: Displays the void node

Figure 6.7: Selects the destination node



Figure 6.8: Transfer the selected file from the server

Figure 6.9: Reach the specified destination node.



Figure 6.10: Shows the packet arrival rate, average delay and Path efficiency

Figure 6.11: Unreachable node is reached



Destination Nodes Average delay in milliseconds

1 233.735

2 92.981

3 967.016

4 592.016

5 92.891

6 842.157

Table 6.1: Simulation results of average delay

Figure 6.12: Average delay in milliseconds



Destination Nodes Delivery Ratio

1 1

2 1

3 1

4 1

5 1

6 1

Table 6.2: Simulation results of Delivery ratio

Figure 6.13: Packet arrival rate in bytes



Figure 6.14: Destination received a file

Figure 6.15: File stored in specified in destination



Figure 6.16: Source gives the error message if didn’t select a file to send

Figure 6.17: Destination sends an error message if didn’t select a receiving path



Chapter 7

CONCLUSION AND FUTURE WORK

7.1 Conclusion

A greedy anti-void routing (GAR) protocol is proposed to completely resolve the

void problem incurred by the conventional greedy forwarding algorithm. The rolling-ball

UDG boundary traversal (RUT) scheme is adopted within the GAR protocol to solve the

boundary finding problem, which results in guaranteed delivery of data packets under the

UDG networks. The BM and the IMS are also proposed to conquer the computational

problem of the rolling mechanism in the RUT scheme, forming the direct mapping

between the input/output nodes. The correctness of the RUT scheme and the GAR

algorithm are properly proven.

7.2 Future work

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. 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.



Chapter 8

REFERENCES

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Scalable Coordination in Sensor Networks,” Proc. ACM MobiCom, pp. 263-270,

Aug. 1999.

[2] G.G. Finn, “Routing and Addressing Problems in Large Metropolitan-Scale

Internetworks,” Technical Report ISI/RR-87- 180, Information Sciences Inst., Mar.

1987.

[3] B. Karp and H.T. Kung, “GPSR: Greedy Perimeter Stateless Routing for Wireless

Networks,” Proc. ACM MobiCom, pp. 243- 254, Aug. 2000.

[4] I. Stojmenovi’c and X. Lin, “Loop-Free Hybrid Single-Path/ Flooding Routing

Algorithms with Guaranteed Delivery for Wireless Networks,” IEEE Trans. Parallel

and Distributed Systems, vol. 12, no. 10, pp. 1023-1032, Oct. 2001.

[5] R. Jain, A. Puri, and R. Sengupta, “Geographical Routing Using Partial Information

for Wireless Ad Hoc Networks,” IEEE Personal Comm. Magazine, vol. 8, no. 1, pp.

48-57, Feb. 2001.

[6] D.chen and P.K Varshney,”On-demand Geographic Forwarding for data delivery in

wireless sensor networks,” Elsevier computer comm., vol.30, no.14-15,pp.2954-

2967,oct.2007.

[7] I.stojmenovi’c, M. Russell,and B. Vukojevic,”Depth first search and location based

localized routing and Qos routing in wireless networks”, proc IEEE Int’l Conf.

parallel processing(ICPP ’00), PP.173-180,Aug. 2000.

[8] T.He, J.A Stankovic,C. Lu, and T.Abdelzaher,”SPEED:A stateless protocol for Real-

Time Communication in sensor networks”,proc.Int’l conf.Distributed computing

systems(ICDCS’03),pp.46-55,may 2003.

[9] H. Frey and I. Stojmenovi’c, “On Delivery Guarantees of Face and Combined Greedy

Face Routing in Ad Hoc and Sensor Networks,” Proc. ACM MobiCom ’06, pp. 390-

401, Sept. 2006.

[10] P. Bose, P. Morin, I. Stojmenovi’c, and J. Urrutia, “Routing with Guaranteed

Delivery in Ad Hoc Wireless Networks,” ACM/ Kluwer Wireless Networks, vol. 7,

no. 6, pp. 609-616, Nov. 2001.



[11] E. Kranakis, H. Singh, and J. Urrutia, “Compass Routing on Geometric Networks,”

Proc. Canadian Conf. Computational Geometry (CCCG ’99), pp. 51-54, Aug. 1999.

[12] Q.Fang J. Gao, and L. Guibas,”Locating and Bypassing Routing Holes in sensor

Networks”, proc IEEE INFOCOM ’04, pp.2458-2468, mar 2004

[13] D.B West, Introduction to Grapg Theoty, second ed. Prientice Hall,2000

[14] User Interfaces in C#: Windows Forms and Custom Controls by Matthew

MacDonald.

[15] Applied Microsoft® .NET Framework Programming (Pro-Developer) by Jeffrey

Richter.

[16] Practical .Net2 and C#2: Harness the Platform, the Language, and the Framework by

Patrick Smacchia.

[17] http://www.sourcefordgde.com

[18] http://www.networkcomputing.com/


http://www.networkcomputing.com/

http://www.sourcefordgde.com/


Appendix I

ABBREVIATIONS

BM Boundary Map

CLR Common Language Runtime

DD Directed Diffusion

GAF Geographic Adaptive Fidelity

GAR Greedy Anti-Void Routing

GBR Gradient Based Routing

GEAR Geographical and Energy Aware Routing

GF Greedy Forwarding

GRA Greedy Routing algorithm

GUI Graphical User Interface

HCR Hop Count Reduction

IDE Integrated Development Environment

IL Intermediate Language

IMS Indirect Map Searching

IP Internet Protocol

ND Destination Node

NS Source Node

NV Void Node

PUC Partial UDG Construction

QoS Quality of Service

RR Rumor Routing



RUT Rolling-ball UDG Boundary Traversal

SN Sensor Nodes

SP Starting point

SPIN Sensor Protocols for Information via Negotiation

SQL Structured Query Language

SV Starting node

TEEN & APTEEN [ Adaptive] Threshold

sensitive Energy Efficient sensor Network

UDG Unit Disk Graph

VB Visual Basic

VGA Virtual Grid Architecture Routing

WSN Wireless Sensor Network



Appendix II

PUBLICATIONS

1. Sudhakar Avareddy, Rajashree V.Biradar, S.R Sawant, “Location Based Anti-Void

Routing Protocol in Wireless Sensor Network”, accepted for International Conference

on communication Computation, Control and Nanotechnology (ICN-2010) to be held

at REC Bhalki, Karnataka, India during October 29-30,2010.

2. Sudhakar Avareddy, Rajashree V.Biradar “Wireless Sensor Network Simulators”, in

the proceedings of National conference on “Recent Trends in Computer Science&

Information Technology”RTICSIT-09 organized by the Department of computer

science & information and Engineering, at Guru Nanak Dev Engineering college,

Bidar held during 8th 9th may 2009.

3. Sudhakar Avareddy, Rajashree V.Biradar ,“Location Based Routing Protocol”,

presented for Tech fest(WONDER’S 10) at PDIT Hospet, held on 29 th and 30th of

April 2010.

WORKSHOP ATTENDED

1) Participated in the one day workshop on “Wireless sensor networks and

applications” conducted by Ballari Institute of Technology and Management, Bellary

on 13th November 2009.


location based final

Documents