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Title : THE IMPROVING POWER EFFICIENCY IN WIRELESS SENSOR NETWORK USING ANT BASED ROUTING ALGORITHM Author (s) : M.SANTHOSH, N.V.CHINNASAMY

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www.ijicse.com 19

THE IMPROVING POWER EFFICIENCY IN WIRELESS SENSOR NETWORK USING ANT BASED ROUTING ALGORITHM

M.SANTHOSH, N.V.CHINNASAMY

Department of Computer Science,

Sri Vijay Vidyalaya College of Arts and Science, Dharmapuri. [email protected]

ABSTRACT

Wireless Sensor Networks consisting of nodes with limited power are deployed to gather useful information from the field. In WSN, it is critical to collect the information in an

efficient manner. WSN is a collection of tiny, large number of densely deployed sensor node;

these sensor nodes are smart, effective which is very powerful and versatile networking

where traditional wired and wireless networking is unable to deploy. The lifetime of a WSN

significantly depends on the batteries of nodes and a long lifetime is vital in most of WSN

applications. It is applied in routing and difficult power supply area or area that cannot be

reached and some temporary situations, which do not need fixed network supporting and it

can fast deploy with strong anti-damage. In order to avoid the problem we proposed a new

technique called FN node mechanism for routing. ACO is one of the FN node mechanisms.

ACO is a dynamic and reliable protocol. Therefore, energy efficient routing is important in

WSN. Here, we are designing Ant Colony Optimization (ACO) algorithm for energy efficient

routing in WSN. Routing protocols for wireless sensor networks are responsible for

maintaining the energy efficient paths in the network and have to ensure extended network

lifetime. It provides energy-aware, data gathering routing structure in wireless sensor

network. It can avoid network congestion and fast consumption of energy of individual node.

Then it can prolong the life cycle of the whole network. ACO algorithm reduces the energy consumption. It optimizes the routing paths, providing an effective multi-path data

transmission to obtain reliable communications in the case of node faults. The main goal is to

maintain the maximum lifetime of network, during data transmission in an efficient manner.

This paper defines implementation of WSN and comparison of its performance with DSR

routing protocol based on ANT algorithm is done in terms of packet delivery ratio,

throughput and energy level.

Keywords: Routing protocols, Wireless sensor networks, Large-scale systems, Network

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www.ijicse.com 20

I. INTRODUCTION

A Wireless Sensor Network is a

collection of nodes using a wireless medium

to communicate, and cooperate together to

make possible the communication between

any pair of nodes in the network, without

using any pre-existing infrastructure or central administration. The opening of the

communication medium and the possible

mobility are the most important

characteristics, which make an ad hoc

network easy and less expensive to deploy.

The Wireless sensor network is a collection

of sensors that are spread over large

geographic regions.

A Wireless Sensor Networks (WSN),

or better a mesh WSN, usually consists of

one sink (or base station) able to manage all

the communications between other nodes.

This kind of network has fixed routes,

excepting when there are nodes failures.

Thus, the base station determines and

optimizes the paths of communication in the network. Instances of WSN are networks

monitoring a bridge, the temperature in

several parts of a city (although this case is

more complex due to the big area to monitor)

or an ancient monument.

Wireless Sensor Networks have

recently emerged as a hot, new research area

in the broad field of (wireless) computer

networking. Research interest in WSNs has

been stimulated by the very recent advances

in the Micro-Electro-Mechanical Systems

(MEMS) and the wireless communications

technology, which have made it possible to

produce low-cost, tiny-sized sensors with

wireless networking capabilities WSNs are

expected to be ubiquitous in the future, with

wide deployment both in the military and the

commercial sectors.

The WSN is built of "nodes" – from a

few to several hundreds or even thousands,

where each node is connected to one (or

sometimes several) sensors. Each such

sensor network node has typically several

parts: Size and cost constraints on sensor

nodes result in corresponding constraints on

resources such as energy, memory,

computational speed and communications

bandwidth.

II. RELATED WORK In our proposed system, we are

introducing Efficient-Ant Colony Algorithm,

Re-Route Processing Algorithm and RSA

Algorithm. In this EACO process, the

data-packets will be passed in efficiently without any packet loss. Re-routing will act as, if

there is an attacker node while routing this

algorithm will change its path and sends the

information to destination. The main process

is RSA Algorithm it will act as encryption

and decryption process. So the Security will

be high when this process is added.

The proposed routing protocol

consists of four stages which are listed as

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www.ijicse.com 21

(I) Route discovery

(II) Route selection

(III) Route security

(IV) Data forwarding.

WSNs have many real-life

applications such as military applications, healthcare applications, forest and habitat

monitoring, fire, heat, and pressure

monitoring in a given area Selection and

delivery of data packets from source to

destination is one of the important tasks in

WSN. Researchers have proposed many

routing mechanisms so however, majority of

WSN routing protocols are application

dependent without any consideration for

security aspect. Security concern is gaining

significant attention and many secure

mechanisms have been proposed for WSN.

However, many of these security

mechanisms operate at different layers to

counter specific risk situation. To counter

network layer security attacks, secure routing is more appropriate security mechanism. In

last few years, variety of secure routing

protocols is proposed for sensor networks.

Fig 1: Architecture of WSN

III. POWER EFFICIENCY IN WIRELESS SENSOR NETWORKS 3.1 Route Discovery

The Router Discovery Protocol,

which is an extension to the Internet Control

Message Protocol (ICMP), allows hosts to

discover routers on their networks and determine which router to use as the default

router. When a host needs to send a packet to

another network, it first sends the packet to a

router that forwards the packet toward the

destination. To accomplish this, the host

needs to know where the routers are on its

network and which one to send packets to.

When you configure the router

discovery mechanism, the router advertises

itself with periodic ICMP router

advertisement messages. Then the host

listens to this message and decides whether

to use a router as the default router.

You can configure the host to solicit

the router advertisement on attached

networks. All participating routers then reply to the inquiry. By collecting those replies,

the host discovers the routers on the network

and determines which router to use.

A host might not select the best

router (the router with the optimal path) to

forward packets to a specific destination.

When a router receives a packet from a host

that is better forwarded to another router on

the network, the router uses an ICMP

Redirect message to notify the host of the

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NetWare routing software provides

both host and router implementations of the

Router Discovery Protocol. The mode of

operation of the Router Discovery Protocol

is determined by whether the IP Packet

Forwarding parameter is enabled. If IP

Packet Forwarding is enabled, the Router Discovery Protocol sends Router

Advertisement messages. If IP Packet

Forwarding is disabled, the Router

Discovery Protocol sends Router Solicitation

Messages.

.3.2 Route Selection

Crucial to the proper ability of hosts

to exchange IP packets is the correct

selection of a route to the destination. The

rules for the selection of route path are

traditionally made on a hop-by-hop

basis based solely upon the destination

address of the packet. Linux behaves as a

conventional routing device in this way, but

can also provide a more flexible capability.

Routes can be chosen and prioritized based on other packet characteristics.

The route selection algorithm under

linux has been generalized to enable the

powerful latter scenario without

complicating the overwhelmingly common

case of the former scenario.

3.3 Route Security

The unit option is an optional function

that is called at the beginning of every request. It

is not given any special arguments.

This method serves as a gatekeeper for

the remaining middleware in the stack. It should

parse the request for authorization information

and setup the request for further middleware..

3.4 Route Forwarding

This chapter describes the level of

support that Cisco ANA provides for Virtual Routing and Forwarding (VRF), as follows:

• Technology Description

• Information Model Objects (IMOs)

• Vendor-Specific Inventory and IMOs

• Network Topology

• Service Alarms

3.5 Simulation Results

IV. CONCLUSION We studied the application of the Ant

Colony Optimization metaheuristic to solve

the routing problem in wireless sensor

networks. A basic ant-based routing

algorithm was proposed, and several

improvements, inspired by the features of

wireless sensor networks (low energy levels,

low processing and memory capabilities),

were considered and implemented. The

resulting routing protocol, called

Energy-Efficient Ant Based Routing (EEABR), uses

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between the sensor nodes and the sink nodes,

which are optimized in terms of distance and

energy levels. These special ants minimize

communication loads and maximize energy

savings, contributing to expand the lifetime

of the wireless network. The experimental

results showed that the algorithm leads to very good results in different WSN

scenarios. As future work we intend to study

the initialization method to populate the

routing tables with initial pheromone levels.

As shown in the literature such mechanisms

can increase even more the efficiency of the

networks. Another approach to be studied is

the integration of multiple sink-nodes.

REFERENCES

1) Estrin, D., et al., “Embedded, Everywhere: A

research Agenda for Network Systems of Embedded Computers”, National Research Council Report, 2001. 2) Handy, M., Haase, M., Timmermann, D., “Low

Energy Adaptive Clustering Hierarchy with

Deterministic Cluster-Head Selection,” 4th IEEE International Conference on Mobile and Wireless Communications Networks, Stockholm, 2002. 3) Lindsey, S., Raghavendra, C., “PEGASIS: Power Efficient Gathering in Sensor Information Systems”,

ICC, 2001.

[4] Lindsey, S., Raghavendra, C., Sivalingam, K., “Data Gathering in Sensor Networks using the EnergyDelay Metric”, 2000.

5) Intanagonwiwat, C., Govindan, R., Estrin, D., “Directed Diffusion: a scalable and robust communication paradigm for sensor networks”, ACM

Press, 2000.

6) Jeon, P., Rao, R., Kesidis, G., Two-Priority Routing in Sensor MANETs Using Both Energy and Delay Metrics in preparation, 2004.

7) Di Caro G., Dorigo M., "AntNet: Distributed Stigmergetic Control for Communications Networks", Journal of Artificial Intelligence Research (JAIR), Vol. 9, Pag. 317-365, 1998.

8) Zhang, Y., Kuhn, L., Fromherz, M.,

„Improvements on Ant Routing for Sensor Networks”. In: Ants 2004, Int. Workshop on Ant

Colony Optimization and Swarm Intelligence, Sept. 2004.

9) Singh, G., Das, S. Gosavi, S., Pujar, S., “Ant Colony Algorithms for Steiner Trees: An Application

to Routing in Sensor Networks”, Recent

Developments in Biologically Inspired Computing, Eds. L. N. de Castro, F. J. von Zuben, Idea Group Publishing, pp. 181-206, 2004.

10) Zuniga, M. Z.; Krishnamachari, B. "Integrating Future Large-Scale Wireless Sensor Networks with the Internet" - Department of Electrical Engineering, UNiversity of Southern California, 2002.

11) Alonso, J., Dunkels, A., Voigt. T, „Bounds on the energy consumption of routings in wireless sensor nodes” WiOpt'04: Modeling and Optimization in

Mobile, Ad Hoc and Wireless Networks, Cambridge, UK, March 2004.

12) Ye, W., Heidemann, J., "Medium Access Control in Wireless Sensor Networks" in Wireless Sensor Networks, Kluwer Academic Publishers, 2004.

13) Dorigo, M., Stützle, T., “Ant Colony

Optimization”, ISBN 0262042193, MIT Press, 2004.

14) Network Simulator-2,

Figure

Fig 1: Architecture of WSN

References

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