Evaluation of Power Aware Routing ProtocolsMohammad Mahmud

Wireless Networks

Professor: Dr. Lijun Qian

Power Aware Routing

In a typical network, the route of a packet will be determined by calculating which path is either fastest, or has the least amount of hops.

This may mean that some nodes in the network get far more usage than others.

If nodes have a limited power supply, such as portable computers, extreme usage could quickly drain the battery.

A temporary mobile network, such as an ad hoc network, would benefit from Power Aware Routing. Examples: Soldiers in the battlefield or rescue workers after a disaster.

Power Aware Routing

In this network, it is clear that node 6 will receive the most usage, causing its batteries to become quickly depleted.

This will cause node 6 to crash, disrupting the network.

Other nodes will also quickly crash as they try to absorb the traffic of node 6.

Power Aware routing

Power efficient schemes: Physical layer

Data transmission at the minimum power level to maintain links and to avoid interference

Data Link Layer Effective retransmission schemes for error free transmission. When and at what power level a mobile host should attempt

retransmission

Network Layer routing protocol can balance the traffic load inside the network

and thus increase the battery lifetime .

Power Aware Routing SPAN:

Topology based routing protocol based on network backbone

Connected by masters who take care of routing

Periodic Hello messages to discover their two hop neighborhood

eligible to be a coordinator if it discovers that two neighbors cannot communicate directly or via other coordinators

A backoff interval follows Nodes with greater

effectiveness at connecting new pairs of neighbors, and higher energy reserves announce themselves as coordinators more quickly than less effective ones

SPAN( cont..)

Proactive, as periodically exchanges Hello messages

Random back off, as all with similar energy level may want to decide coordinators

Periodically checks if it should withdraw from coordinating

As network density decreases, becomes more efficient

Minimum Total Transmission Power Routing (MTPR)

Minimizes total energy consumed in forwarding a packet form source to destination.

Exploits exponential path loss by forwarding traffic using a sequence of low power transmission rather than a single direct transmission.

Disadvantages Selects most power

efficient path. So nodes along this route may die early because of excessive power usage.

Minimum Battery Cost Routing (MBCR)

The remaining battery capacity of each host is a more accurate metric to describe the life time of each host

Battery cost function of a host

Battery cost Rj for route I To find the maximum

remaining battery capacity, we select route I that has the minimum battery cost.

Minimum Battery Cost Routing (MBCR)

If all nodes have similar battery capacity, this metric will select a shorter-hop route

Only consider the summation of values of battery cost; therefore can overuse any single node

Min-Max Battery Cost Routing (MMBCR)

The power of each host is being used more fairly in this scheme than previous scheme.

No guarantee of minimum total transmission power path under all circumstances

Consume more power to transmit mean reduce the lifetime of all nodes

Conditional Max-Min Battery Capacity Routing (CMMBCR) Using previous scheme, maximize the life

time of each node and use the battery fairly can’t be achieve simultaneously

When battery capacity of every node is greater than a threshold, it performs minimum energy routing.

If not , it switches to MMBCR.

PSR( Power Source Routing)

Modification of DSR ( Dynamic Source Routing)

Minimize sum of the energy cost of the links along the routing path

Link cost is proportional to the inverse of the remaining battery capacity (residual energy) of the transmitting node

Dynamic Source Routing (DSR)

Route discovery is done by flooding the network Nodes listen to control messages flowing through the network Caching techniques improve performance considerably Cost of a path is the number of hops along that path

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N2

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N4

N5

N6

N7

N8

N8

N5-N8

N2-N5-N8

Power-aware Source Routing (PSR)

A cost is associated with every node on the path

This cost is inversely proportional to the normalized residual energy of the node

The cost function is graded, i.e., nodes with very low battery capacity dominate the total cost of the path

,

,

( , ) ( )

where ( ) . ( )

: transmit power level of node i

: full-charge battery capacity of node i

( ) : remaining batt

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ery capacity of node i at time t

: a positive weighting factor

PSR ( Cont..)

Similar to DSR, but with some differences: An intermediate node passes on the first RREQ and all

subsequent lower-cost RREQ’s until a local timer expires Destination starts a timer after receiving the first RREQ and

replies back only after that timer expires

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N2

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N2-N5-N8

N3-N4-N7-N8N4-N7-N8

N7-N8

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EnergyLevel

DSR

PSR

LPR ( Lifetime Prediction Routing) Maximize the minimum link cost along routing Maximize the minimum link cost along routing

pathpath Link cost is remaining lifetime of transmitting Link cost is remaining lifetime of transmitting

nodenode Node lifetime is equal to the remaining Node lifetime is equal to the remaining

battery capacity divided by the energy battery capacity divided by the energy depletion ratedepletion rate

LPR

Similar to to PSR except that Each node predicts its lifetime

when it receives a RREQ Intermediate nodes attach their

predicted lifetime to the RREQ packet if it is lower than the current lifetime in the header of the packet

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path in i node of lifetime predicted : (t)path of lifetime : )(T

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Er,i(t): remaining energy at the ith packet is being sent or relayed through the current node

Rk(t): rate of energy depletion of current node

N: length of the history used for calculating the simple moving average

Simulation Environment

Simulation Environment Setting up simulation model

in ns-2 or OPNET Generating Network traffic

model Implement routing scheme Measure Data

Some of the commonly used parameters of performance analysis are:

Time needed to expire the first node in a networking

Time needed to expire some specific percentage of nodes in a network

Time needed to expire specific number of critical nodes in a network

Number of dead nodes at a specific time.

Power Aware Routing

Suggestions: For the stating point, I will choose some sort of on-demand protocol like

Lifetime Prediction Routing (LPR) discussed in [4] as it is more energy efficient than the table driven approaches. However, I propose three new metrics to incorporate in LPR. QoS: On demand protocols are inherently slower as it takes some initial time to

find out routing path. To mitigate this problem use QoS Essential Nodes:If the network environment is densely populated, we can use some

sort of algorithm to find out if a certain node is critical or non critical in routing applications.

Mobility History:If nodes can keep track their mobility history, it can be used as a factor in deciding the routing paths. Assume that less intermediate mobile nodes in a network will tend to be more static and

thus will be given priority over highly moving intermediate nodes when it comes to routing.

Power Aware Routing

Reference 1. C.K. Toh, "Maximum Battery Life Routing to Support Ubiquitous Mobile Computing in

Wireless Ad hoc Networks”, Communications Magazine, IEEE , Volume: 39 Issue: 6 , June 2001 Page(s): 138 –147

2. Benjie Chen, Kyle Jamieson, Hari Balakrishnan, and Robert Morris. Span: An energy efficient coordination algorithm for topology maintenance in ad hoc wireless networks. ACM Wireless Networks Journal, 8(5):481-494, September 2002.

3. M.Maleki, K.Dantu, and M.Pedram, "Lifetime Prediction Routing for Mobile Adhoc Networks" Wireless Communications and Networking, 2003. WCNC 2003. 2003 IEEE , Volume: 2 , 16-20 March 2003 Page(s): 1185 -1190

Power Aware Routing

Questions?