Lifetime Prediction Routing in Mobile Ad Hoc Networks

A mobile ad hoc network (MANET) is a      self-configuring  infrastructureless network of mobile devices connected by wireless. Ad hoc is Latin and means "for this purpose".

Each device in a MANET is free to move independently in any direction, and will therefore change its links to other devices frequently. Each must forward traffic unrelated to its own use, and therefore be a router. The primary challenge in building a MANET is equipping each device to continuously maintain the information required to properly route traffic. Such networks may operate by themselves or may be connected to the larger Internet.

MANETs are a kind of Wireless ad hoc network that usually has a routable networking environment on top of a Link Layer ad hoc network.

MANET Routing Protocols

Routing protocols in ad hoc networks are categorized in two

groups:

·        Proactive (Table Driven

·        Reactive (On-Demand)

    Ø Proactive (Table-Driven) Routing Protocols

These routing protocols are similar to and come as a natural Extension of those for the wired networks. In proactive routing, Initial  draft. Please do not distribute. each node has one or more tables that contain the latest information of the routes to any node in the network. Each row has the   next hop for reaching a node/subnet and the cost of this route.Various table-driven protocols differ in the way the information about a change in topology is propagated through all nodes in the network.

        ØReactive (On-Demand) Protocols

Reactive routing is also known as on-demand routing. These protocols take a lazy approach to routing. They do not maintain or constantly update their route tables with the latest route topology. Examples of reactive routing protocols are the dynamic source Routing, ad hoc on-demand distance vector routing and temporally ordered routing algorithm. Our power-aware source routing algorithm belongs to this category of routing algorithms. Since our approach is and enhancement over DSR, a brief description of DSR is warranted DSR is one of the more generally accepted reactive routing protocols. 

Previous Work

The main focus of research on routing protocols in MANETs has been network performance. There has been some study on poweraware routing protocols for MANETs. Presented below is a brief review of some of them.

    

        Ø Power–aware Routing

Reference  proposes a routing algorithm based on minimizing

the amount of power (or energy per bit) required to get a packet

from source to destination. More precisely, the problem is stated

as:

Σ∈

+

π i π

Min Ti ,i 1 (1)

where Ti,i+1 denotes the power expended for transmitting (and

receiving) between two consecutive nodes, i and i+1, in route π.

This link cost can be defined for two cases:

• When the transmit power is fixed

• When the transmit power is varied dynamically as a

function of the distance between the transmitter and intended receiver. For the first case, energy for each operation (receive, transmit, broadcast, discard, etc.) where b and c are the appropriate coefficients for each operation. Coefficient b denotes the packet size-dependent energy consumption whereas c is a fixed cost that accounts for acquiring the channel and for MAC layer control negotiation. The second case is more involved. Reference  proposes a local routing algorithm for this case. The authors assume that the power needed for transmission and reception is a linear function of dα where d is distance between the two neighboring nodes and α is a parameter that depends on the physical environment

         ØBattery-cost Lifetime-aware Routing

The main disadvantage of the problem formulation of reference is that it always selects the least-power cost routes. As a result, nodes along these least-power cost routes tend to “die” soon because of the battery energy exhaustion. This is doubly harmfulsince the nodes that die early are precisely the ones that are needed most to maintain the network connectivity (and hence useful service life). Therefore, it will be better to use a higher power costroute if this routing solution avoids using nodes that have a small amount of remaining battery energy.

1. Minimum battery cost routing algorithm minimizes thetotal cost of the route. More precisely, this algorithmminimizes the summation of inverse of remaining

battery capacity for all nodes on the routing path .

2. Min-Max battery cost routing algorithm is a modification of the minimum battery cost routing. This algorithm attempts to avoid the route with nodes having

the least battery capacity among all nodes in all possible routes. Thereby, it results in smooth use of the battery of each node

3. Conditional Max-Min battery capacity routing algorithm was proposed in .This algorithm chooses the route with minimal total transmission power if all nodes in the route have remaining battery capacities higher than a threshold; otherwise, routes that consist of nodes with the lowest remaining battery capacities are avoided. Several experiments have been performed in to compare different battery cost-aware routing in terms of the network lifetime.

4. Maximum Residual Packet Capacity (MRPC) was proposed in . MRPC is conceptually similar to the conditional Min-Max battery cost, but MRPC identifies

the capacity of a node not just by the residual battery capacity, but also by the expected energy spent inreliably forwarding a packet over a specific link.

5. Power-aware Source Routing (PSR) (proposed in  is an on-demand source routing that uses state of the charge of battery to maximize the lifetime of a MANET. PSR solves the problem of finding a route π at route

Lifetime Prediction Routing

         Ø Basic Mechanism

Lifetime Prediction Routing (LPR) is an on demand source routing protocol that uses battery lifetime prediction. The objective of this routing protocol is to extend the service life of MANET with dynamic topology. This protocol favors the path

whose lifetime is maximum. We represent our objective function

as follow:

Tπ (t) Min (Ti (t))

i

Max

π ∈π

= (5)

where:

π

π π

(t) : predicted lifetime of node i in path

T ( ) : lifetime of path

i

t

Τ

Lifetime Prediction: Each node tries to estimate its battery lifetime based on its past activity. This is achieved using a Simple Moving Average (SMA) predictor by keeping track of the last N values of residual energy and the corresponding time instances for the last N packets received/relayed by each mobile node. This information is recorded and stored in each node. We have carefully compared the predicted lifetimes based on the SMA approach to the actual lifetimes for different values of N and found N=10 to be a good value. Our motivation in using lifetime prediction is that mobility introduces different dynamics into the network. In the lifetime of a node is a function of residual energy in the node and energy to transmit a bit from the node to its neighbors. 

       Ø Route Discovery

In DSR, activity begins with the source node flooding the network

with RREQ packets when it has data to send. An intermediate

node broadcasts the RREQ unless:

• It gets a path to the destination from its cache, or

• It has previously broadcast the same RREQ packet. (this

fact is known from the sequence number of the RREQ

and the sender ID.) Consequently, intermediate nodes forward only the first received

RREQ packet. The destination node only replies to the first arrived RREQ since that packet tends to take the shortest path. In LPR, all nodes except the destination calculate their predicted lifetime, Ti and replace the min lifetime in the header with Ti if Ti is lower than the existing min lifetime value in the header.

Experimental Results

        Ø Simulation Setup

We used the event driven simulator ns-2  along with thewireless extensions provided by CMU . The simulationconsists of a network of 20 nodes confined in a 1000 X 1000 m2 area. Random connections were established using CBR traffic (at 4 packets/second) such that each node has chance to connect to every other node. Packet size was 512 bytes and each simulation was executed for 20000 sec

       

  Ø Simulation Results

The network lifetime is defined as the time taken for a fixed percentage of the nodes to die due to energy resource exhaustion. Network lifetime of DSR, PSR and LPR are compared for a given scenario. Here, the speed of each node is 10 m/s and radio

transmission range is 125 m. Figure 4 shows the time instances atwhich a certain number of nodes have died when simulating LPR, PSR and DSR. Note that in Similarly, in DSR 5 nodes die approximately 32% earlier than LPR and 27% earlier than LPR in the case of PSR.

Conclusion:

A routing protocol to enhance the lifetime of a given mobile adhoc network. We compare it with dynamic source routing (DSR), a popular routing technique used in MANETs which does not consider power but optimizes routing for shortest delay. The main objective of LPR is to minimize the variance in the remaining energies of all the nodes and thereby prolong the network lifetime. It achieves this by doing local decisions and with minimum overhead. We show that LPR brings about a clear increase in network lifetime. 

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