Enhanced energy efficient secure and dynamic wireless sensor communications with certificateless eff

International Journal of Research in Advanced Technology - IJORAT Vol. 2, Issue 2, FEBRUARY 2016

All Rights Reserved © 2016 IJORAT 1

Enhanced Energy Efficient Secure and

Dynamic Wireless Sensor Communications

with Certificateless Effective Key

Management Protocol

S. Murali1, Mrs. E. SrieVidhya Janani

2

1PG Scholar, Anna University Regional Centre Madurai

2Assistant Professor/CSE, Anna University Regional Centre Madurai

[email protected],

[email protected]

Abstract: Wireless sensor network (WSN) has been an active research area over the past few years. Due to

the limited energy and communication ability of sensor nodes, it seems especially important to design a

routing protocol for WSNs so that sensing data can be transmitted to the receiver effectively. An energy-

balanced routing method based on forward-aware factor is proposed here with effective key management

strategies. In this system, the next-hop node is selected according to the awareness of link weight and forward

energy density. Furthermore, a spontaneous reconstruction mechanism for local topology is designed

additionally. In the experiments results show that our system balances the energy consumption, prolongs the

function lifetime and guarantees high QoS of WSN.

Keywords: Wireless Sensor Networks, Forward Energy Density (FED), Network Simulator

I. INTRODUCTION

A wireless sensor network (WSN) contains

more number of autonomous sensors which are

spatially distributed and to monitor physical or

environmental conditions. And the sensors also

cooperatively pass their data through the network to a

specific or important location. The modern networks

are bi-directional, also controlling the activities of

sensor. The development of wireless sensor networks

was encouraged by military applications such as

battlefield surveillance. Today such sensor networks

are used in many industrial and consumer

applications, such as machine health monitoring and

industrial process monitoring and control. More

number of sensor networks are being used in

numerous application domains, and the collected data

are used in decision making for complicated

infrastructures. Data are obtained from various

sources by intermediate processing nodes that

aggregate information. A malicious node may

introduce some additional nodes in the network or it

can compromise the existing nodes in the network.

Therefore, high data trustworthiness is essential for

correct decision-making. Data provenance acts as a

key factor in evaluating the trustworthiness of data.

II. EXISTING SYSTEM

The importance of secure and efficient provenance

transmission and processing for sensor networks is

investigated and data provenance is used to detect

packet loss attacks staged by malicious sensor nodes.

A provenance encoding and decoding mechanism is

designed and satisfied security and performance

needs. A provenance encoding strategy is developed

whereby each node on the path of a data packet

securely embeds the provenance information within a

Bloom filter (BF) and the sane is transmitted along

with the data. Upon receiving the packet, the BS

extracts and verifies the provenance information. An

extension of the provenance encoding scheme that

detects the packet drop attack is also supported. The

sensor nodes in the network can act as both a sensor

and a router, and its computing ability, storage

capacity, communication ability, and power supply

are limited. Due to the limited energy and

communication ability of sensor nodes, it seems

especially important to design a routing protocol for

WSNs so that sensing data can be transmitted to the

receiver effectively.

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III. PROPOSED SYSTEM

The problem of routing around connectivity holes

that works in any connected topology without the

overhead is identified and the inaccuracies incurred

by methods based on topology planarization is also

focussed. A cross-layer protocol, named ALBA

(Adaptive Load-Balancing Algorithm) is developed,

whose main ingredients (geographic routing, load

balancing, contention-based relay selection) are

blended with a mechanism to route packets out and

around dead ends, the Rainbow protocol. The

combination of the two protocols, called ALBA-R,

results in an integrated solution for converge casting

in WSNs that, although connected, can be sparse and

with connectivity holes. The Rainbow mechanism

allows guarantee packet delivery in realistic

deployment and also shows better performance

superior to existing protocols in terms of energy

efficiency, packet delivery ratio (PDR), and latency.

IV. INPUT DESIGN

The input design is the link between the

information system and the user. It comprises the

developing specification and procedures for data

preparation and those steps are necessary to put

transaction data in to a usable form for processing

can be achieved by inspecting the computer to read

data from a written or printed document or it can

occur by having people keying the data directly into

the system. The design of input focuses on

controlling the amount of input required, controlling

the errors, avoiding delay, avoiding extra steps and

keeping the process simple. The input is designed in

such a way so that it provides security and ease of use

with retaining the privacy. Input Design considered

the following things:

What data should be given as input?

How the data should be arranged or coded?

The dialog to guide the operating personnel

in providing input.

Methods for preparing input validations and

steps to follow when error occur.

V. FAF-EBRM ARCHITECTURE

Fig. 1.Packet transmission from Source to Destination

VI. OUTPUT DESIGN

A quality output is one, which meets the

requirements of the end user and presents the

information clearly. In any system results of

processing are communicated to the users and to

other system through outputs. In output design it is

determined how the information is to be displaced for

immediate need and also the hard copy output. It is

the most important and direct source information to

the user. Efficient and intelligent output design

improves the system’s relationship to help user

decision-making.

1. Designing computer output should proceed in an

organized, well thought out manner; the right output

must be developed while ensuring that each output

element is designed so that people will find the

system can use easily and effectively. When analysis

design computer output, they should Identify the

specific output that is needed to meet the

requirements.

2. Select methods for presenting information.

3. Create document, report, or other formats that

contain information produced by the system.

The output form of an information system should

accomplish one or more of the following objectives.

Convey information about past activities,

current status or projections of the future.

Calculates

the Forward

Energy

Density

(FED)

Collect the

data packets

from cluster

members

Select the

cluster head

based on FED

Send the packet

from source to

destination

Using

reconstruction

mechanism



Signal important events, opportunities,

problems, or warnings.

Trigger an action.

Confirm an action.

VII. NETWORK SIMULATOR 2.33 (NS2)

Network Simulator (NS2) is a discrete event

driven simulator developed at UC Berkeley. It is part

of the VINT project. The goal of NS2 is to support

networking research and education. It is suitable for

designing new protocols, comparing different

protocols and traffic evaluations. NS2 is developed as

a collaborative environment. It is distributed freely

and open source. A large amount of institutes and

people in development and research use, maintain

and develop NS2. This increases the confidence in it.

Versions are available for FreeBSD, Linux, Solaris,

Windows and Mac OS X. Network simulator (NS) is

an object–oriented, discrete event simulator for

networking research. NS provides substantial support

for simulation of TCP, routing and multicast

protocols over wired and wireless networks. The

simulator is a result of an ongoing effort of research

and developed. Even though there is a considerable

confidence in NS, it is not a polished product yet and

bugs are being discovered and corrected

continuously. NS is written in C++, with an OTcl1

interpreter as a command and configuration interface.

The C++ part, which is fast to run but slower to

change, is used for detailed protocol implementation.

The OTcl part, on the other hand, which runs much

slower but can be changed very fast quickly, is used

for simulation configuration. One of the advantages

of this split-language program approach is that it

allows for fast generation of large scenarios. To

simply use the simulator, it is sufficient to know

OTcl. On the other hand, one disadvantage is that

modifying and extending the simulator requires

programming and debugging in both languages.

VIII. STRUCTURE OF NS2

NS2 interprets the simulation scripts written

in OTcl(Object Oriented Variant of Tcl). A user has

to set the different components (e.g. event scheduler

objects, network components libraries and setup

module libraries) up in the simulation environment.

Fig. 2.Simplified User’s View of NS

The user writes his simulation as a OTcl script,

plumbs the network components together to the

complete simulation. If he needs new network

components, he is free to implement them and to set

them up in his simulation as well. The event

scheduler as the other major component besides

network components triggers the events of the

simulation (e.g. sends packets, starts and stops

tracing). Some parts of NS2 are written in C++ for

efficiency reasons. The data path (written in C++) is

separated from the control path (written in OTcl).

Data path object are compiled and then made

available to the OTcl interpreter through an OTcl

linkage (tclcl) which maps methods and member

variables of the C++ object to methods and variables

of the linked OTcl object. The C++ objects are

controlled by OTcl objects. It is possible to add

methods and member variables to a C++ linked OTcl

object.

IX. NETWORK TOPOLOGY

Sensor nodes are randomly distributed in a

rectangular sensing field. Then find the

communication range for all nodes in the sensing

field. Each and every sensor node has a particular

energy level. During the process this energy level

will decrease. Nodes die after exhausting the energy

entirely. Data are sent to the cluster head, and then

transferred to the sink. The sensor node can broadcast

message to all nodes in the sensing field.



X. FAF – EBRM METHOD

In Forward Aware Factor-Energy Balanced Routing

Method (FAF-EBRM), the next hop node is selected

based on communication link quality and forward

energy density. Before selecting the cluster head, it

calculates the FED if it is higher than the neighbor

nodes, hat is select as a cluster head node. The cluster

head is collected the data packets from their neighbor

nodes and then forward to the sink node. The

communication launch node can calculate the weight

of edge between neighbors. Neighbors can get its

own FED. The FED can find using this formula,

FED(i,t) = ∑j€FTA(i) Ej(t)/SFTA(i)

XI. RECONSTRUCTION MECHANISM In the actual routing procedure, nodes with

greater signal strength will have more

communication link and result in faster energy

consumption. The whole network cannot work under

these topology structures. So in this systema

reconstruction mechanism is developed. And also

after every time node finishes the transmission, it

checks the energy density of its own. If it is less than

the average value of the strength, the reconstruction

mechanism should be launched. Before

reconfiguration mechanism is launched, remove the

link between the low level strength of the node and

get the new set nodes. According to this mechanism

we can balance energy level of nodes and avoid the

dead nodes.

XII. PERFORMANCE EVALUATION In order to measure the performance the

xgraph is implemented. The four evaluation metrics

such as Packet reception ratio, End-to-end delay,

Energy balanced factor and Energy level are chosen.

Packet reception ratio is the ratio between number of

received packets and number of sending packets.

End-to-End delay is the time taken to be data

transmitted from source to destination.

Fig. 2.Performance Evaluation in terms of Packet Recption

ratio

VIII. CONCLUSION

An energy-balanced routing method FAF-EBRM

based on forward-aware factor is proposed in this

paper. In FAF-EBRM, the next-hop node is selected

according to the awareness of link weight and

forward energy density. Furthermore, a spontaneous

reconstruction mechanism for local topology is

designed additionally. In the experiment, FAF-

EBRM is compared with LEACH and EEUC, and

experimental results show that FAFEBRM out-

performs LEACH and EEUC, which balances the

energy consumption, prolongs the function lifetime,

and guarantees high QoS ofWSN. Also, they show

that the distributions of node degree, strength, and

edge weight follow power law and represent “tail,” so

the topology has robustness and fault tolerance,

reduces the probability of successive node

breakdown, and enhances the synchronization of

WSN.

ACKNOWLEDGEMENT

The authors thank the management of the Anna

University Regional Office, Madurai,Tamil Nadu for

their continued support and encouragement

throughout the course of the project.

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Enhanced energy efficient secure and dynamic wireless sensor communications with certificateless eff

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