Iaetsd increasing network life span of manet by using by Iaetsd Iaetsd

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Increasing network life span of MANET by using cooperative MAC protocol B Suman Kanth1, P Venkateswara Rao2 1

M.Tech , Dept. of CSE, Audisankara College of Engineering & Technology, Gudur, A.P, India.

Professor, Dept. of CSE, Audisankara College of Engineering & Technology, Gudur, A.P, India.

Abstract â&#x20AC;&#x201C; Cooperative diversity has been shown

reducing the energy use for consistent data

to give important performance increases in

transmission becomes one of the most important

wireless

design concerns for such networks. As an

networks

where

communication

hindered by channel fading. In resource limit

promising

and

powerful

solution

that

can

networks, the advantages of cooperation can be

overcome the drawback of resource constraint

further exploited by optimally allocating the

wireless networks, cooperative communication has

energy and bandwidth resources among users in a

received major attention recently as one of the key

cross-layer way. In this paper, we examine the

candidates for meeting the stringent requirement

problem of transmission power minimization and

of the resource limited networks.

network lifetime maximization using cooperative Cooperative communication is developed from the

diversity for wireless sensor networks, under the

traditional MIMO (multiple-input and multiple-

restraint of a target end-to-end transmission

output) techniques and the model of relay

consistency and a given transmission rate. By using

cross-layer

optimization

channels. Though MIMO has been shown to be

scheme,

able to significantly enlarge the system throughput

distributive algorithms which mutually consider

and

routing, relay selection, and power allocation plans

reliability,

not

simple

straightforward to implement in the wireless

are proposed for the consistency constraint

sensor networks due to the control on the size and

wireless sensor networks.

hardware complexity of sensor nodes.

Index terms â&#x20AC;&#x201C; power minimization, cooperative Cooperative communication, however, is able to

diversity, relay selection, cross-layer optimization.

achieve the same space diversity by forming a I.

INTRODUCTION

virtual distributed antenna array where each antenna belongs to a separate node. With

Wireless sensor networks are composed of nodes

cooperation, users that understanding a deep fade

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in their link towards the destination can utilize

in MAC, and power allocation in PHY) for

quality of service (QoS).

cooperative networks is still an open issue. Although there are some efforts concerned in

a variety of cooperative schemes have been

optimizing some metrics such as throughput,

developed so far. Cooperative beam forming scheme

was

proposed for

delay, or power use under certain QoS conditions,

CDMA cellular

these efforts focus on either one-hop situation or

networks. Coded cooperation was proposed along

fading-free channels.

with analog-and-forward (AF) and decipher-andforward (DF) schemes. Diversity-multiplexing

Different from our work, we focus on various

tradeoff

the

optimization goal and conditions. We are planning

performance of diversive cooperative schemes

on energy minimization as well as network

such as fixed relaying, selection relaying, and

lifetime maximization. The QoS conditions in our

incremental relaying. Multi relay cooperative

work are end-to-end transfer reliability while the

protocol using space-time coding was proposed.

work is under the constraint of end-to-end

tools

were

used

analyze

transmission capacity. We believe in wireless Opportunistic relaying (or selective cooperation)

sensor

was proposed with various relay selection policies.

network

and

the

network

lifetime

maximization, and the guarantee for end-to-end

Power allocation problem and SER performance

reliability

analysis in resource constraint networks. These

important

than

other

considerations. Moreover, we extend our work of

works are primarily focused on enhancinging the

cross-layer optimization for cooperative network.

link performance in the physical layer.

We decomposes the problem of minimizing

Cooperative communication presents at birth a

network power consumption into a routing sub-

cross-layer

communication

problem in the network layer and a combined relay

resources have to be carefully allocated among

selection and power allocation sub-problem in the

different nodes in the network. Therefore, the

physical layer.

problem,

since

integration and interaction with higher layers has

However, the decomposition method to solve this

become an active research area in recent years.

cross-layer problem is faulty for its complexity.

There have been a lot of efforts towards this

Since the algorithm projected is non-heuristic, it

consideration such as combining node cooperation

needs comprehensive iterations, with long meet

with ARQ in the link layer, or resource allocation

time and huge overhead for message exchanging,

in the MAC layer, and routing algorithm in the

thus inappropriate for sensor network application.

network layer.

On opposite side, in our work, we try to derive a

However, a complete cross-layer optimization

closed-form solution (though may not be optimal)

incorporating three layers (routing, relay selection

and propose our algorithm in a heuristic way; thus,

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it can be distributively employed in wireless

selection, and power allocation in arbitrarily

sensor

distributed wireless sensor networks.

networks.

the

cooperative

communication and data-aggregation techniques are together implemented to reduce the energy

II. CROSS â&#x20AC;&#x201C; LAYER OPTIMIZATION PROBLEM IN COOPERATIVE SENSOR NETWORK

spending in wireless sensor networks by reducing the sum of data for transmission and better using

In this section, we prepare and analyze the min-

network

cooperative

power problem and the max-lifetime problem in

communication. There are also extra works in

the context of reliability conditioned cooperative

prolonging network lifetime using cooperative

networks and obtain relevant solutions, leading to

communication techniques.

our algorithms which will be explained in detail in

resources

through

the next section.

To address above stated problems, a cooperative scheme is proposed join the maximum lifetime

Problem Formulation

power allocation and the energy aware routing to Consider a multihop wireless sensor network

maximize the network lifetime. This method is not

containing of multiple arbitrarily disseminated

a cross-layer method since the energy saving routing

formed

first,

and

sensor nodes and one sink. Each sensor node has a

cooperative

single

transmission is applied based on the build routes. Therefore,

the

qualities

omnidirectional

antenna

and

can

dynamically adjust its transmitted power.

cooperative

transmission are not fully discovered since the best

cooperative route might be completely different

objectives. The first is called min-power problem:

from the noncooperative route.

given any source node, the goal is to find the route

consider

two

associated

optimization

that minimizes the total transmission power, while

A suboptimal algorithm for lifetime increasing is

fulfilling a required end-to-end broadcast success

developed based on the performance analysis for

probability and transmission rate.

MPSK modulation in the condition of adding some special cooperative relays at the best places

The second is called max-lifetime problem: given

to prolong the network lifetime, while, in our

a set of source nodes, the goal is to offers an

work, the nodes are randomly distributed and no

information transferring scheme that increases the

additional relay nodes deployed.

network lifetime, defined as the lifetime of the node whose battery consumes out first [1], while

In a word, we propose a fresh scheme to increase

fulfilling the same conditions as the min-power

the network lifetime by utilize the cooperative

problem.

diversity and together considering routing, relay

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and the relay to confirm a accurate reception. Otherwise, it sends a negative acknowledgment (NACK) that allows the relay, if it received the symbol properly, to transmit this symbol to the receiver in the next time slot. 3) Multirelay Cooperation

which

for

the

multirelay

collaboration mode, we use the opportunistic relaying scheme according to this opportunistic relaying scheme, for each frame, a node with the

Figure 1. Cooperative transmission (CT)

best immediate relaying channel condition among

and direct transmission (DT) modes as

several possible relays is selected to promote the

building blocks for any route.

packet in each frame.

From Figure 1, we can see that to promote data

Now consider the min-power problem described in

from node i to node j on link (i, j), either direct

the above. This is a convex problem and we can

transmission is used or a particular node r helps

solve it using Lagrangian multiplier techniques.

node i to forward data to node j using decipher-

To make best use of the lifetime of the entire

and-forward (DF) cooperative diversity.

network, the novel solution is that the lifetime of

The broadcast transmission

rate and

(DT)

power

mode

and

for

each node in the route of flow is equal to a target

direct

lifetime.

cooperative

transmission (CT) mode classified into three cases

III.

COOPERATION-BASED CROSS-LAYER

such as 1) Direct Transmission in which node i send the data to the node j. Cooperation

which

for

SCHEMES

2) Single-Relay the

In this section, we propose thorough minimum-

cooperative

transmission mode, the sender I sends its symbol

power

and

maximize-lifetime

in its time slot. Due to the transmit nature of the

algorithms, under the constraint of end-to-end

wireless medium, both the receiver and the relay

success probability and data rate, both in direct

receive noisy versions of the transmitted symbol.

mode and cooperative mode. We assume that each

We assume that the relay and the receiver decide

node transmits HELLO packet to its neighbors to

that the received symbol is properly received if the

update the local topology information. Our

received (SNR) is greater than a certain threshold.

algorithms are composed of two parts: routing

According to the incremental relaying scheme, if

(and relay selection) algorithm and power

the receiver deciphers the symbol suitably, then it

allocation algorithm. Algorithms are based on the

sends an acknowledgment (ACK) to the sender

conventional

Bellman-Ford

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cross-layer

shortest

path

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algorithm

which

can

distributively

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Algorithm 1 (Min-Power Cross-layer Scheme with Direct Transmission (MPCS-DT)). Consider

implemented. In Bellman-Ford algorithm, each node executes the iteration.

(1)

Notation ∝ ,

() Qs i)

∞ except Cost (0) = 0 (node 0 represents the sink).

Table 1 Symbol and Explanation Explanation The effective distance between node I and j The latest estimate cost of the shortest path from node j to the destination The set of neighboring nodes of node i Quality parameter

(2)

Every ∝ ,

distance

node

estimates

(3)

the

average

(4)

(5)

∝/ ,

Cost(i)

min ∈

(6)

optimization

( ) , and select node j as the next hop node. If the required QoS parameter

is a

If not, the source will deliver a message

along the path about the

. Then each node in the

First we select the minimum-power route with the

route will adjust the transmit power.

least

(7)

correlated to

though the constructed route, informing all nodes

problem into two sub-problems.

the

∝/ ,

will adjust the transmit power.

nothing to do with the QoS parameter. Thus we

Then,

( )

priori to the whole network, each node in the route

That means the formation of routing actually has

algorithm.

from

Every node updates its cost toward the

destination

We can see that to reduce is equal to minimizing.

conservative

SNR

Every node calculates the costs of its

outgoing links as

effective

periodically broadcasted HELLO message.

Transmission

based

the

of its outgoing links through the

measurement

Min-Power Cross-Layer Scheme with Direct

can decompose the cross-layer

Every node initiates its cost for routing as

Bellman-Ford

transmission

power i)

Got to Step (2).

Min-Power Cross-Layer Scheme with Cooperative

for each node in the route is

Transmission

adjusted. The

min-power

scheme

for

cooperative

Since the forward nodes in the route may not

communication is composed of two parts: single-

know

relay scheme and multirelay scheme. For single-

(if not a priori for the whole network),

the source node may need to transfer a message containing

relay scheme, that to minimize

to the destination through the path

minimizing ∑

is equal to

. Hence, the cross-layer best

to inform all the forward nodes. Thus, the cross-

strategy can be realized by three steps. First, the

layer scheme is as follows.

potential relay of each link is selected by minimizing

. Then, the min-power route is

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constructed as the route with the least ∑

opportunistic

relaying

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multirelay

scenario)).

Consider

Finally, the transmission power of the nodes in the route is adjusted. The algorithm as follows.

(1)

the similar as steps 1 & 2 Algorithm 1.

Algorithm 2 (Min-Power Cross-layer Scheme

(2)

the similar as steps 1 & 2 Algorithm 1.

Cooperative Transmission (MPCS-CT) (for single-

(3)

Every node sorts all its neighboring nodes

relay scenario)). Consider

ascending according to the value of

(1)

The similar as steps 1 & 2 in Algorithm 1.

(2)

The similar as steps 1 & 2 in Algorithm 1.

(3)

Every node calculates the costs of its

outgoing links as ∝ ,

= min

∈ (, )

∝ ,

min

∈ ( , )

∝

∝ ,

∏

(4)

select node j as the next hop node.

Every node updates its cost toward the +

∝

Every node updates its cost toward the

(4)

of both I and j.

destination as Costi = min ( /

where N(i, j) denotes the set of neighboring node

of both i and j.

( )

∝

Then it calculates the costs of its outgoing links as

where N(i, j) denotes the set of neighboring node

= min ∈

and selects the first K nodes as potential relays.

, and select node k as the relay of this link,

destination as

∝ ,

), and

(5) (5) & (6) The similar as steps 5 & 6 in algorithm 1

and select node j as the next hop node.

except each path node and relay node in the route

(5)

adjust the transmit power.

& (6) The similar as steps 5 & 6 in

Algorithm 1 except each path node and relay node ii) in the route adjust the transmit power.

(6)

Go to (2).

(6)

Transmission

Max-Lifetime Cross-Layer Scheme with Direct

Go to step (2).

The remaining energy of each node is decreasing For multirelay scheme (assume we need K relays

at unusual rates; the route may vary from time to

for each link), the difference with single-relay

time as the residual energy of the intermediate

scheme is that the K probable relays have to be

node in the route varies. The rate of the

selected and only the optimal relay is chosen from

recalculation of the route is determined by the rate

time-to-time in every transmission slot.

of HELLO message exchange. Thus, the algorithm

The best communicate is in charge of relaying the

is as follows.

packet, while further potential relays will turn off

Algorithm 4 (Max-Lifetime Cross-Layer Scheme

the radio and not receive the packet to save

with Direct Transmission (MLCS-DT)). Consider

energy. The algorithm is as follows.

(1)

& (2) The similar as steps 1 & 2 in

Algorithm 1. Algorithm 3 (Min-Power Cross-Layer Scheme Cooperative

Transmission

(MPCS-CT)

(for

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(3)

Every node measures its residual energy

(5)

and its total power for the ongoing flows. Then it ∝ ,

and its total power

Every node updates its cost toward the = min ∈

destination as

calculate the cost of its outgoing links as

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()

and selects node j as the next hop node.

for the ongoing

flows.

(6)

(4) Every node updates its cost toward the

Algorithm 1 except each forward node and relay

destination as Costi = min ∈

∝ ,

( )

& (7) The similar as steps 5 & 6 in

node in the route adjust the transmit power.

(8)

and select node j as the next hop node.

Go to (2).

(5) & (6) the similar as steps 5 & 6 in Algorithm 1

IV. EXPECTED RESULTS

except each node in the route adjust the transmit power.

In this section we compare the Min-Power

(7) Go to (2).

Algorithms to demonstrate the effect of cross-layer

iii) Max-Lifetime

Cross-Layer

Scheme

design for communication; we implement two

with

min-power algorithms: MPCS-DT and MPCS-CT

Cooperative Transmission

in random networks. For better comparison, we To find a route which can maximize, we should

also implement two other cooperation along the

find a path with the minimum, and the power of

shortest

nodes should be adjusted.

routing

(MPCR)

algorithm and cooperation along the shortest noncooperative path (CASNCP) algorithms.

Algorithm 5 (Max-Lifetime Cross-Layer Scheme with Cooperative Transmission (MLCS-CT)).

And also we compare the Max-Life Algorithms,

Consider (1)

non-cooperative

for that we consider three different schemes: (1) max-lifetime cross-layer scheme with direct

& (2) the similar as steps 1 & 2 in

Algorithm 1.

communication (MLCS-DT)and (2) max-lifetime

(3) Every node calculates the effective distance of

cross-layer

its

communication (MLCS-CT) and (3) greedy power

outgoing ,

= min

∈ ( , )

links ∝ ,

(

∝ ,

with

cooperative

allocation and cost-based routing (GPA-CR).

), and select

node k as the relay of this link. (4)

scheme

V. CONCLUSION

Every node measures its residual energy

In this paper, we build several cross-layer

and its total transmission power for the ongoing

algorithms for energy resourceful and consistent

flows. Then calculates the cost of its outgoing

data transfer in wireless sensor networks using

links.

cooperative diversity. We examine the problem of how to minimize transmission power consumption

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and

exploit

guaranteeing

the the

network end-to-end

lifetime

while

[4] L. Zheng and D. N. C. Tse, “Diversity and

accomplishment

freedom: a fundamental tradeoff in multiple

probability.

antenna channels,” in Proceedings of the IEEE International

REFERENCES

Theory

and E. Cayirci, “A survey on sensor

476,

Lausanne,

Transactions on Information Theory, vol. 25, no. 5, pp. 572–584, 1979.

[2] A. Nosratinia, T. E. Hunter, and A. Hedayat, in

wireless

[6] A. Sendonaris, E. Erkip, and B. Aazhang,

networks,” IEEE Communications Magazine,

“User cooperation diversity part I and part 2,”

vol. 42, no. 10, pp. 74–80, 2004.

IEEE Transactions on Communications, vol. 51, no. 11, pp. 1927–1938, 2003.

[3] Y.-W. Hong, W.-J. Huang, F.-H. Chiu, and C.C. J. Kuo, “Cooperative communications in wireless

'02),

Information

theorems for the relay channel,” IEEE

vol. 40, no. 8, pp. 102–105, 2002.

resource-constrained

(ISIT

[5] T. M. Cover and A. A. E. Gamal, “Capacity

networks,” IEEE Communications Magazine,

communication

Symposium

Switzerland, July 2002.

[1] F. Akyildiz, W. Su, Y. Sankarasubramaniam,

“Cooperative

ISBN: 378 - 26 - 138420 - 5

[7] J. N. Laneman, D. N. C. Tse, and G. W.

networks,”

Wornell, “Cooperative diversity in wireless

IEEE Signal Processing Magazine, vol. 24, no.

networks: efficient protocols and outage

3, pp. 47–57, 2007.

behavior,” IEEE Transactions on Information Theory, vol. 50, no. 12, pp. 3062–3080, 2004.

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