Background of Ad hoc Wireless Networks

Student Presentations

Wireless Communication Technology and Research

Ad hoc Routing and Mobile IP and Mobility

Wireless Sensor and Mesh Networks

Mobile and Ad hoc Networks

Energy Awareness in Adhoc NetworksEnergy Awareness in Adhoc Networkshttp://web.uettaxila.edu.pk/CMS/SP2012/teAWNms/

Outline Introduction Metrics for power awareness Routing Protocols

Power Source Routing (PSR) Local Energy Aware Routing (LEAR) Low Energy Adaptive Clustering Hierarchy (LEACH)

References

Introduction – Power Concerns

The lifetime of a network is defined as the time it takes for a fixed percentage of the nodes in a network to die out.

Portability of wireless nodes being critical its almost mandatory to keep the battery sizes to a bare necessary

Since battery capacity is fixed, a wireless mobile node is extremely energy constrained

Hence all network related transactions should be power aware to be able to make efficient use of the overall energy resources of the network

Traditional routing metrics

Aims to minimize hop counts and propagation delay Fails to take into account the power usage of nodes Results in poor lifetime of networks

Energy Models

Capture the effect of the limited energy reserves of mobile devices (i.e. batteries)

Models the power levels of the device during operation so that total energy consumption can be calculated

A number of different models are used in the literature Transmission Power Model Transmission & Reception Model Power State Model

Transmission Power Model

Assumes energy consumption is directly related to wireless output power Output power in typical cards range from 1mW to 200mW

Output power is related to the square of range Cutting transmission range in half cuts output power requirement by ¼ This means by choosing shorter hops, the total output power can be reduced (¼

+ ¼ < 1) Used by many papers (particularly theory papers)

Minimum energy routing Minimum energy broadcast Topology control

Flawed model ignores MANY sources of energy consumption Fixed transmission consumption overhead Consumption by receiver Consumption by idle nodes

Transmission & Reception Model

Energy consumption depends on the number of packets sent & received

Energy consumption of a packet is calculated using several constants

Not very commonly used Increased accuracy but still missing a significant contribution

to energy consumption (idle power)

DataLengthDataOverheadEnergyDataLengthDataOverheadEnergy

RXRXRX

TXTXTX

Power State Model

Uses different power levels depending on state of wireless card Transmit (1.33 Watts) Receive (0.97 Watts) Idle (0.84 Watts) Sleep (0.07 Watts)

Based on measurements of a real wireless card on lab equipment Captures the majority of card power consumption effects (most accurate

model in general use) Measured values only apply for the exact model of card Does not take into account transient consumption from mode switches Does not take into account power consumption of host

(i.e. from packet processing) Usually assumes fixed output power

(not normally used with transmission power control)

Sending Power Example

Sending Receiving

Receiving Power Example

Different Transmit Options

RF Transmit Power (mW)

Sleep Mode

High consumption while active High transmit power constant High idle & receive power

Sleep mode allows much of the electronics to be turned off Radio cannot send or receive packets Can be activated again by host in a small amount of time SIGNIFICANTLY lower power levels (0.07 Watts)

Only protocols that make extensive use of sleep mode can save a large fraction (>50%) of the card power consumption Sleep mode limit = <90% savings Transmit power control limit = <<35% savings

Power Aware Metrics

Intuition:Conserve power and share cost of routing packets to ensure increase in life of node and network

Metrics:1. Minimize energy consumed / packet2. Maximize time to Network Partition3. Minimize variance in node power levels4. Minimize cost / packet5. Minimize maximum node cost

1. Minimize energy consumed / packet

Definitions: T(a,b) = energy consumed in transmitting and receiving one

packet over one hop from a to b- ej = Σk-1

i=1 T(ni, ni+1) = total energy spent for packet j over k hops

Goal:- Minimize ej for all packets j

Note:- In lightly loaded networks this automatically finds shortest hop path- In heavily loaded networks due to contention it might not be shortest- The use of “energy/packet” alone as a cost may result in wide variations of

node power consumption

2. Maximize time to network partition

Definition:- Cut Set: set of nodes that divide the network into two partitions

As soon as one node in the set dies the delay experienced increases

Goal:- To balance load of the nodes in the Cut Set to maximize network life

Problems:- The problem is similar to scheduling tasks to multiple servers so that the response time is minimized, which is known to be NP-complete

3. Minimize variance in all node power levels

Goal:- To keep all nodes up and running together for as long as possible

Concept:- Build a route that takes into account the amount of data waiting to be transmitted in all

the intermediate nodes

Merit:- Achieve some kind of load balancing to ensure similar rates of dissipation of energy

throughout the network

4. Minimize cost / packet

Definition:We associate a cost fi(xi) with each node i. Thus total cost of sending packet j:

cj = Σk-1i=1 fi (xi)

Where,- xi is the total energy dissipated by node i till now (thus far)- fi(xi ) is the cost of node i. - Intuitively, fi(xi) indicates a node’s reluctance to forward packets (i.e. It is highly reluctant if

the cost is high, when the expended energy so far is high).

Goal:- Minimize cj

4. Minimize cost / packet (contd.)

Advantage:- The remaining batter power level is incorporated into the routing decision- This also balances load by avoiding usage of weak nodes in presence of stronger ones- The routing starts like shortest path routing, then the routes start to get longer as the

metric kicks-in to route around nodes that are reluctant to route (because they expended their energy during the shortest path mode).

5. Minimize maximum node cost

Definition:- Ci(t) = cost of routing a packet through node i at time t- Ĉ(t) = maximum of the Ci(t)’s

Goal:- Minimize Ĉ(t), for all t > 0

Merits:- Delays node failure- Reduces variance in node power levels

Power-Aware Source Routing (PSR)

This is a Reactive (On demand) protocol based on DSR This Cost function takes into account both transmission power and remaining

battery power RREQ broadcast is initiated by source Intermediate nodes can reply to RREQ from cache as in DSR If there is no cache entry, receiving a new RREQ an intermediate node does the

following: Starts a timer Keeps the path cost in the header as Min-cost Adds its own cost to the path cost in the header and broadcast

On receiving duplicate RREQ an intermediate node re-broadcasts it only if the following is true:

The timer for that RREQ has not expired The new path cost in the header is less than Min-cost

Destination also waits for a specific time after the first RREQ arrives It then replies to the best seen path in that period and ignores others that come later The path cost is added to the reply and is cached by all nodes that hear the reply

PSR Route Maintenance Node mobility: Connections between some nodes on the path are lost due to their movement. In this case a new RREQ is issued and the corresponding entry in the cache is purged.

Energy Depletion: Energy of some intermediate node maybe depleting very quickly. This can be

addressed in two ways: Semi-global approach:

Here the source monitors the remaining battery level of the path by periodically polling the intermediate nodes

Local approach: Each intermediate node is allowed to send back a route error at time t if

its battery level is too low

PSR vs DSR – Simulation on NS(2)

Test bed of 20 nodes confined in 1000 x 1000 m^2 area Range of each node is 250 m 100 reliable and random ftp connections Average duration of connection is 20 sec Total simulation time 10000 sec Speed of movement is 10 m/s Random mobility with pause time of 4 sec

PSR vs DSR – network lifetime

Local Energy-Aware Routing (LEAR)

Aims to balance energy consumption with shortest routing delays

Takes into account a node’s willingness to participate in the routing path which is based on its remaining battery power

Destination does not wait to reply –> non-blocking Efficient use of route cache

The basic LEAR Algorithm

• Source uses a sequence number for new request

• If it gets no reply back it increases the sequence number and

re-broadcasts

LEAR – Simulation on GloMoSim Test bed of 40 nodes confined in 1000 x 1000 m^2 area Range of each node is 250 m 5 Constant Bit Rate source and destination pair chosen 1024 byte packets sent every sec for a specified duration Total simulation time 500 sec Random waypoint mobility Speed of movement is 5 m/s Pause time is varied from 50 to 400 sec Simulation results shown next are average of 100 runs Initial Threshold value set to 90% of node’s initial power The value of adjustment ‘d’ is taken as 0.1 or 0.4

LEAR – Standard Deviation of energy distribution• Energy Consumption measured at radio layer

• 35% improved energy balance with high mobility (50 sec pause time)

• 10% improvement with moderate mobility (400 sec pause time)

• The ‘d’ value does not affect much

LEAR – Ratio of accepted ROUTE_REQ

• Ratio = total route_reqs accepted / total route_reqs received

• Even DSR does not have 100% ratio due to TTL

• ‘d’ = 0.1 drops requests more frequently due to lower adjustment

Low Energy Adaptive Clustering Hierarchy (LEACH)

In this we consider a micro-sensor network where: 1. The base station is fixed and located far from sensors 2. All nodes are homogeneous and energy constrained

Key features of LEACH:1. Localized coordination and control for cluster setup and operation2. Randomized rotation of the cluster heads and the corresponding

clusters.

Data Transmission

Radios of non-heads are off when its not transmitting, to preserve energy.

When all data has been received from all the nodes the head performs signal processing to compress the data into a single signal

This is then send directly to the base station by a high energy transmission.

Direct Transmission –vs- LEACH

References - I[1] Power-Aware Routing in Mobile Ad Hoc Networks – Suresh Singh, Mike Woo, C.S. Raghavendra

[1] Power-aware Source Routing Protocol for Mobile Ad Hoc Networks – Morteza Maleki, Karthik Dantu, and Massoud Pedram

[2] Non-Blocking Localized Routing Algorithm for Balanced Energy Consumption in Mobile Ad Hoc Networks – Kyungtae Woo, Chansu Yu, Hee Yong Youn, Ben Lee

[3] Hierarchical Power-aware Routing in Sensor Networks – Qun Li, Javed Aslam, Daniela Rus

[4] Minimum Energy Mobile Wireless Networks – Volkan Rodoplu, Teresa H. Meng

[5] A Location-aided Power-aware Routing Protocol in Mobile Ad Hoc Networks – Yuan Xue, Baochun Li

References - II

[6] Geographical and Energy Aware Routing: a recursive data dissemination protocol for wireless sensor networks – Yan Yu, Ramesh Govindan, Deborah Estrin

[7] Energy-Efficient Communication Protocol for Wireless Microsensor Networks - Wendi Rabiner Heinzelman, Anantha Chandrakasan, Hari Balakrishnan

[8] Adaptive Protocols for Information Dissemination in Wireless Sensor Networks - Wendi Rabiner Heinzelman, Joanna Kulik, Hari Balakrishnan

Assignment #7

What is meant by NP-Complete? What is the difference between NP-HARD and NP-

Complete Problems Go through the research papers of energy aware

routing protocols given in References.

Q&A

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