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A Fault Node Recovery Algorithm to Reinforce the Lifetime and Routing in Wireless Sensor Network

发布时间:2017-03-30
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A Fault Node Recovery Algorithm to Reinforce the Lifetime and Routing in Wireless Sensor Network

Chapter 3

SYSTEM ANALYSIS AND REQUIREMENTS

3.1 Existing System

The directed diffusion (DD) [1] algorithmic rule along with the grade diffusion (GD) [8] algorithmic rule are two traditional approaches to sensor networks. The proposed algorithm is used in this project work is based on the GD algorithmic rule, with the objective of exchange fewer sensor nodes that are not working or hold depleted batteries, and of reusing the utmost range of routing paths. These optimizations can eventually enhance the WSN lifespan and replacement cost of the sensor nodes also reduced.

3.1.1 Directed Diffusion Algorithm

A series of routing algorithms designed for wireless sensor networks are designed in recent years. C. Intanagonwiwat et al. specified the Directed Diffusion (DD) algorithmic rule [1] in 2003. The aim of the Directed Diffusion rule is to decrease the data relay transmission counts used for power management. The DD algorithmic rule could also be a query-driven transmission protocol. The collected information is transmitting from source to sink node only if its query matches the sink node. Within the DD algorithmic rule, the sink node provides the queries surrounded by the kind of attribute-value pair off the neighbour or other sensor nodes by means of broadcasting the query packets to the entire network. Later, the sensor nodes send the information back to the sink node only if it fits the queries.

3.1.2 Grade Diffusion Algorithm

H. C. Shih et al. had specified the Grade Diffusion (GD) [8] rule in 2012 to reinforce the ladder diffusion algorithm by means that the ant colony optimization (LD-ACO) used for wireless sensor networks. The GD algorithmic rule not completely creates the routing for all sensor nodes on the other hand this also identifies a collection of neighbour nodes to decrease the transmission loading. Each sensor node can prefer a sensor node from the set of nearest neighbour nodes after its grade table lacks a node capable to do the relay operation.

The GD rule may additionally record some information about the information relay. After that, a sensor node can prefer a node with a lighter loading or extra offered energy than the opposite nodes to carry out the additional relay operation. That is, the routing path is updated by GD rule in real time, and moreover the event data is therefore sent to the sink node rapidly and appropriately and shown in Figure 3.1.2.

Fig. 3.1.2: Grade diffusion flowchart

Whether the DD or the GD algorithmic rule is used, the grade produce packages or concerned query packets ought to initial be broadcast. Then, the sensing element nodes transmit the event data to the sink node, with this rule, when appropriate events happen. The sensor routing ways are shown in Figure 3.1.2.

Fig. 3.1.2: Routing in Wireless sensor node.

Fig. 3.1.3: Routing path in Wireless sensor node when some nodes are not working.

The WSN might fail due to different reasons, this includes the following: a break in the routing path; a leak in the WSN sensing area; depletion of batteries of some sensor nodes, requiring extra relay nodes; or the nodes wear out due to long time. In Figure 3.1.3, the state in which the outer nodes transmit event information to the sink node through the within nodes (the sensor nodes close to the sink node) in a WSN demonstrate the accommodation method for non-functioning nodes.

The inside nodes consequently have the largest data transmission loading, intense energy at a quicker rate. If every one of the inner nodes uses their energy or else stop to control, the event information cannot be sent to the sink node, and thus the WSN will not operate. The power utilization of the sensor nodes in WSNs is predictable. This project work, however, proposes an algorithmic rule to looking for and alter fewer sensor nodes and to make use of the foremost routing ways. These conventional search techniques are frequently incapable of optimizing nonlinear functions with multiple variables.

One system, the genetic algorithm rule (GA), could also be a directed random search procedure developed in 1975, supported the idea of natural biology. This proposed work proposes a fault node recovery (FNR) rule supported the GD algorithmic rule combined with the GA. The FNR algorithmic rule creates a routing table by means of the GD algorithm and replaces sensor nodes by means of the GA when the total number of sensor nodes that are not working exceeds the threshold. These rule not only reuse the foremost routing paths to reinforce the WSN life however also reduces the cost.

3.1.3 Limitations of Existing System

The WSN could fail due to a variety of causes, as well as the following: the routing path may experience a break; leak in the WSN sensing area; depletion of the batteries of some sensor nodes, requiring extra relay nodes; or the nodes wear out once the WSN use an extended period of time.

3.2 Proposed System

This project work recommend a fault node recovery (FNR) rule addresses wireless sensor node death problem by avoiding the less fitness node in our routing process. Whenever the source node sending to destination node the message, the first step is to find possible routes and selecting the best route is tradition however in our system we are selecting best fitted nodes from more than one route and construct a new path which is used routing. For this purpose genetic algorithm is used. This consists of selection, crossover and mutation process.

3.2.3 Advantages of proposed system

This proposed system uses a fault node recovery (FNR) algorithm basis of the GD algorithmic rule combined with the GA. The FNR algorithmic rule creates a routing table by means of the GD algorithm and replaces sensor nodes by means of the GA when the total number of sensor nodes that are not working exceeds the threshold. These rule not only reuse the foremost routing paths to reinforce the WSN life however also reduces the cost.

3.3 System Requirements and System Specification

3.3.1 Hardware Requirements

  • System : Pentium IV 2.4 GHz.
  • Hard Disk : 40 GB.
  • Floppy Drive : 1.44 Mb.
  • Monitor : 15 VGA Color.
  • Mouse : Logitech.
  • Ram : 512 MB.

3.3.2 Software Requirements

  • Operating system : Windows XP Professional.
  • Coding Language : Java
  • Java Version:JDK 1.7 or 1.6
  • Front End:Java Swings
  • Database:MYSQL 5.5
  • Database Connectivity:Eclipse

3.3.3 Specific Requirements

Requirements are descriptions of the given services that a software system should offer and therefore the constraints underneath that it should operate Requirements will vary from high-level abstract statements of services or system constraints to elaborate mathematical functional specifications.

  1. Functional requirements

Statements of services that the system should offer, however the system should react to specific inputs and the way the system should behave in above all things the requirements have been elicited by interaction between source and destination.

The major functional requirements are:

  • Source interfaces can communicate with the destination through that level 1 and level 2 routers. Each levels having four nodes.
  • Level 1 will select the next hop node from level 2 nodes. Before selecting Level 1 can check the Node weight of each node.
  • Node weight is the combination of Trust Percentage and Energy Percentage of a respective node.
  • Trust percentage is calculated based on the total files received and for each received file it has to acknowledge to source with success message.
  • Finally Level 2 will forward the data to destination.
  1. Non Functional requirements

Constraints on the services or functions are given by the system namely timing constraints, constraints on the development method, standards, etc. Non-functional needs describe the overall qualities or attributes of the ensuing system. Non-functional requirements place limitations on the product being developed, the development method, and specify external constraints that the product should meet. Examples of NFR include safety, security, usability, dependability and performance needs.

  • Usability - Simple is the key here. The system must be simple that people like to use it, but not so complex that people avoid using it. The user must be familiar with the user interfaces and should not have problems in migrating to a new system with a new environment. The menus, buttons and dialog boxes should be named in a manner that they provide clear understanding of the functionality. Several users are going to use the system simultaneously, so the usability of the system should not get affected with respect to individual users.
  • Reliability - The system should be trustworthy and reliable in providing the functionalities. Once a user has created some changes, the changes must be made visible by the system. The changes made by the Programmer should be visible both to the Project leader as well as the Test engineer.
  • Security- Apart from bug tracking the system must provide necessary security and must secure the whole process from crashing. As technology began to grow in fast rate the security became the major concern of an organization. Millions of dollars are invested in providing security. Bug tracking delivers the maximum security available at the highest performance rate possible, ensuring with the aim of that unauthorized users cannot access vital issue information without permission. Bug tracking system issues different authenticated users their secret passwords so that there are restricted functionalities for all the users.

ï‚· Verifiability- The verifiability (sometimes referred as testability) of software is however it is to test your code for bugs. It’s frequently talked about the importance of creation of software maintainable however verifiability is an additional attribute that does not obtain enough attention.

  • Scalability-The system should be scalable enough to add new functionalities at a later stage. There should be a common channel, which can accommodate the new functionalities.
  • Performance- The system is going to be used by many employees simultaneously. Since the system will be hosted on a single web server with a single database server in the background, performance becomes a major concern. The system should not submit when several users would be using it simultaneously. It should allow fast accessibility to all of its users.
  • Maintainability- The system monitoring and maintenance should be simple and objective in its approach. There should not be too several rules running on different machines such that it gets difficult to monitor whether the jobs are running without errors.
  • Portability- The system should be easily portable to another system. This is required when the web server, which s hosting the system gets stuck due to some problems, which requires the system to be taken to another system.
  • Reusability- The system should be divided into such modules that it could be used as a part of another system without requiring much of work.

ï‚· Efficiency- The comparison is actually produced or performed with what may be achieved with identical consumption of resources (money, time, labour, etc.). It is a very important factor in determination of Productivity.

ï‚· Interoperability- Interoperability is that the ability of various systems and organizations to work together (interoperate). Whereas the term outlining for information technology or systems.

3.4 Feasibility Study

A feasibility study is an analysis of the viability of a thought or plan .The feasibility study focuses on serving to answer the essential question of should we tend to proceed with the proposed project plan. All activities of the study are measure directed toward serving to answer this query. Feasibility studies are often utilized in some ways however primarily concentrate on planned business ventures.

The farmers and others with a business plan should conduct a feasibility study to see the viability of their plan before continuing with the event of a business. Determinative early that a business plan cannot work easily saves money, time and heartache later. For the proposed system, the feasibility to measures that the project can be completed within the existing resources like hardware, software and whether the project matches the present trends of the technological world. And most significant is that, whether the proposed project can produce improved results than the existing system. These queries lead the project plan attempt to existing systems like direct diffusion algorithm .Then the feasibility analyzes question can be answered as proposed system can improve these ideas.

3.4.1 Technical Feasibility

The technical feasibility assessment is concentrated on gaining an understanding of the recent technical resources of the association and their applicability to the expected requirements of the proposed system. It is associate analysis of the hardware and software system and the way it meets the necessity of the proposed system. This study can answer for the question that whether the proposed system can be developed on the existing technology, hardware and the software. And the result of the study was positive that proposed system will developed with the available systems. This is considered with specifying equipment and software that will successful satisfy the user demand the technical needs of the system could vary significantly however may include

  • The facility to produce outputs in a given particular time.
  • Response time under some certain conditions.
  • Ability to process a certain column of transaction at a particular speed.

3.4.2 Economic Feasibility

The purpose of the economic feasibleness assessment is to find out the positive economic advantages to the group with the intention of the planned system will offer. It consists of quantification and detection of all the advantages expected. This estimation usually involves a cost/ benefits analysis. And proposed system can be economically feasible if mass produced and established in traffic detection.

Coming to the proposed system, economical feasibility is not a big issue here as the system uses open source libraries which are used and developed by number of developers all over the world, a public domain coding language with open use developer environment and use of public domain video data. Traffic Event Detection using Computer Vision.

3.4.3 Operational Feasibility

Feasibility studies aim to objectively associate degree reasonably discover the strong point and weak point of an existing business or planned venture, opportunities and threats gift within the setting, the resources needed to hold through, and ultimately the prospects for fulfilment . In its simplest terms, the 2 criteria to gauge feasibility are value needed and price to be earned.

In general, feasibility studies precede technological development and project operations. Feasibility studies assess the project's potential designed for success; so, perceived objectiveness is a very important think about the believability of the study for potential investors and loaning establishments. It should so be conducted with associate degree objective, unbiased approach to produce info upon that selections may be based mostly.

3.5 Summary

This chapter explains the existing system, limitations of existing system, advantages and requirements of the proposed system, starting from functional, non-functional, software and hardware requirements. And this also discusses the feasibility studies of a proposed system, starting from economical feasibility to technical feasibility.

Dept. of CS&E, KIT, TIPTUR. 2014-2015Page 1

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