Simulation of MTMS Using TSSE and minimum energy consumption using

DVS for WSN ad hoc Network

Nishakumari Lodha Research Student

GHRIEM, Jalgaon Maharashtra nishalodha21@gmail.com

Prasant Rewagad HOD Computer Science & Engg GHRIEM, Jalgaon Maharashtra

prashant_rewagad@rediffmail.com

Yogita Pawar Research Student

GHRIEM, Jalgaon Maharashtra pawar.yogita09@rediffmail.com

Abstract— This paper focus on multi hop mobility management in WSN ad hoc Network using DVS algorithm for minimum energy consumption. To improve cross layer collaborative in wireless sensor network as well as to improve processing capacity according requirement. In WSN, senor do not only process information at application layer but also synchronize their communication. Using our propose architecture containing two main phases Mutihop task mapping and Multihop scheduling using DVS for minimum energy consumption in WSN ad hoc network. Simulation result show significant performance improvement compared with existing mechanism in term of multihope data transfer in NS2.

Keywords- Wireless Sensor Network; Multihop data Transfe; Energy consumption in NS2

I. INTRODUCTION

Wireless Sensor Networks consists of individual nodes that are able to interact with their environment by sensing or controlling physical parameter these nodes have to collaborate in order to fulfill their tasks as usually, a single node is incapable of doing so and they use wireless communication to enable this collaboration [1][7]. The definition of WSN, according to, Smart Dust program of DARPA is: "A sensor network is a deployment of massive numbers of small, inexpensive, self-powered devices that can sense, compute, and communicate with other devices for the purpose of gathering local information to make global decisions about a physical environment" [1].

II. LITERATURE SURVEY

In (WSN) Wireless Sensor network challenges that have limited resource capabilities of the hardware i.e. memory, processing power, bandwidth and energy deposits. Much research is currently being conducted in the following areas[6]:

a) Increasing network lifetime b) Improving reliability of data transfer. c) Finding solutions to assist easy deployment and

maintenance. d) Developing techniques that will enforce secure,

private and trustworthy network. Localized task mapping and task scheduling have been equally considered for mobile computing and for WSNs recently [2]. Task mapping and scheduling heuristics are presented in for heterogeneous mobile ad hoc grid environments [3]. Even though, the communication model adopted in is not well-matched for WSNs, which assumes individual channels for each node and the parallel data broadcast and reception ability of each node. Multi hop task mapping and scheduling, on the other hand, is specifically developed for WSNs adopting a more practical communication model. In the EcoMapS algorithm is proposed for energy constrained applications in single-hop clustered WSNs to map and schedule communication and computation simultaneously.

EcoMapS aims to schedule tasks with the minimum schedule length subject to energy utilization constraints[4].However, EcoMapS does not provide execution deadline guarantees for applications, which is addressed in MTMS. In Energy-balanced Task Allocation (EbTA) is introduced to minimize balanced energy consumption subject to application deadline constraints. In communications over multiple wireless channels are first modeled as additional linear constraints of an Integer Linear Programming problem. Then, a heuristic algorithm is existing to provide a realistic result[16]. However, the communication scheduling model in does not exploit the broadcast nature of wireless communication, which can conserve power and reduce schedule distance end to end. RT-MapS is existing in to provide a deadline guarantee with minimum application energy utilization[11]. The broadcast nature of wireless communication is utilized in RT-MapS to influence energy utilization.

In MTMS, broadcast and multicast are realized through the existing communication scheduling algorithm and the task mapping and scheduling algorithms. More ever, all localized mechanisms namely- CoRAl, DCA, EcoMapS, EbTA, and RTMapS, assume a single-hop cluster environment, which prevents their purpose to

2014 Fourth International Conference on Communication Systems and Network Technologies

978-1-4799-3070-8/14 $31.00 © 2014 IEEE

DOI 10.1109/CSNT.2014.20

54

2014 Fourth International Conference on Communication Systems and Network Technologies

978-1-4799-3070-8/14 $31.00 © 2014 IEEE

DOI 10.1109/CSNT.2014.20

54

general implementations. Different from these existing works, multi hop task mapping provides a more general solution for multihop clustered WSNs.In summary, MTMS is a generic task mapping and scheduling solution for multihop wireless sensor networks.

III PROPOSED ARCHITECTURE In our proposed work it consist of multihop task mapping and multihop task scheduling[14] using the minimum energy consumption in WSN ad hoc network. Existing single hop based routing in WSN and energy consumption gives the excellent results in data transfer but our work give the new concept related multihop task mapping & scheduling using minimum energy consumption in WSN ad hoc network.

Figure 1- Flow chart of multihop task mapping & scheduling using minimum energy consumption in WSN ad

hoc network

The flowchart of multi hop task mapping & scheduling using minimum energy consumption in WSN ad hoc network consist of three main sections. The first section designs the sensor network on the bases on number of sensor node. In second section containing TSSA algorithm to find the path from source to destination and last section calculated energy using Dynamic Voltage scaling algorithm for minimum energy consumption under the delay constraint.

IV SIMULATION PARAMETERS

Parameters ValuesChannel type Wireless channel

Radio-propagation Model TwoRayGroundAntenna type OmniAntenna

Interface queue Queue/DropTail/PriQueuePhysical Characteristics Radio propagation

MAC type 802_11Topology 50m × 50m

Routing Protocol AODV,DSDVSimulation Time 500 Sec

Network Interface type Phy / Wireless PhyEnergy model 100JoulesMobile node 10,50,100,150,200

V SIMULATION RESULTS

Figure 2 - Sensor Network

Figure 2.1- Sensor Network with range

Start

Enter the no of sensor node

Design the Sensor network using NS-2

Start data transfer using TSSA algorithm from Source to destination

If Destination node found

Search next hop in sensor Network

All Packet transfer form

source to

Calculate the energy form source node in sensor to destination node in sensor

Yes

NO

No

Stop

5555

The following graphical analysis shows the performance results of AODV and DSDV Protocols using the multi hop mobility management in WSN ad hoc Network using DVS algorithm for minimum energy consumption.

I) Energy Consume for communication between 10 nodes

AODV DSDV

II)Energy Consume for communication between 50 nodes

AODV DSDV

III) Energy Consume for communication between 100 nodes

AODV DSDV

VI. CONCLUSION

The proposed system based on application independent task mapping and task scheduling solution for multihope wireless sensor network using MTMS algorithm. In this project the application are executed in multihop clusters of a WSN with energy constraint. The design objective of this system is existing system have many problem related to broadcasting nature of wireless communication, schedule length, channel allocation and energy consumption using this proposed system. To overcome these problem and schedule the task of an application with improved power

efficiency. The results on simulation are calculated for 100 samples at different time for example at early morning and at evening. Hence we find the there was significant improvement in results.

In terms of energy consumption an improved algorithm can be implemented to overcome communication failures by retransmitting erroneous packets and adaptively adjusting sensor schedules. Also energy consumption can be reduced by using low complexity algorithm for WSN.

VII. REFERENCES

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