performance evaluation of a multi-radio energy …...performance evaluation of a multi-radio energy...

Performance Evaluation of a Multi-Radio

Energy Conservation Scheme for Disruption

Tolerant Networks

Iyad Tumar

Birzeit University

MOBIWAC 2010, Bodrum, Turkey

October 18, 2010

Iyad Tumar Performance Evaluation of a Multi-Radio Energy Conservation Scheme for Disruption Tolerant Networks1

Disruption Tolerant Networks (DTNs)

Developing network communication when connectivity isintermittent and prone to disruptions

DTNs differ from traditional networks due to specialcharacteristics

Frequent partitions, no end-to-end connectionIntermittent connectivityMessage delivery delayLimited resources

Efficient energy conservation schemes are necessary toprolong the network life time

: message transmission

R2S

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D

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R1 R2

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(b) From node R1 to R2

DR2

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(c) From node R2 to D

Figure 1: An example scenario of message forwarding in a DTN as time passes

nodes provides a routing path from a source toward a destination. This route can be com-

pletely predictable if nodes move on fixed schedules, while it can be completely unpre-

dictable (i.e., opportunistic) if nodes move in an arbitrary manner. Many studies have

identified the characteristics of a set of DTNs and proposed routing protocols on them.

Such routing protocols can be classified into three categories: knowledge-based mechanisms,

designated delivery mechanisms, and opportunistic mechanisms. First, knowledge-basedmech-

anisms utilize available knowledge about network dynamics and apply Dijkstra’s algo-

rithm to find the shortest path in terms of expected delay [30, 18]. Second, designated

delivery mechanisms designate special mobile nodes to deliver messages among other

nodes as in Message Ferrying [78, 79, 80] and Data Mule [62]. Finally, opportunistic mech-

anisms forward one or more copy of messages to other nodes without any knowledge

about network dynamics and hope for eventual delivery [72, 69, 73, 31].

Another major issue in DTNs is energy conservation. In the class of DTNs, there are

important applications with energy constraints. For example, nodes deployed in a remote

or hazardous area may have limited access to energy sources, yet the need for long net-

work lifetime. Even if some nodes have abundant energy, a heterogeneous network may

include key devices with limited energy. Thus, efficient power management mechanisms

are necessary to allow these networks to remain operational over a long period of time.

However, mobile devices exhibit a tension between saving energy and providing connec-

tivity. In order to pass messages, the device must discover other nodes, typically using the

3

Figure 1.1: An example scenario of message forwarding in a DTN as time passes [14].

delivery services within DTN environments. DTNs can be applied to wireless networks withno end-to-end connectivity, satellite networks with long delays, wireless sensor networks withintermittent connectivity, and underwater acoustic networks with frequent interruptions.

Another major issue in DTNs is energy conservation. In general, DTNs are applicable inremote and hazardous areas where the energy sources are often constrained. DTNs are alsooften assumed to operate over a long period of time. Therefore, several research efforts havebeen devoted to developing power management schemes for DTNs to allow these networks toremain operational over a long period of time.

The wireless interface is one of the largest consumers of energy in energy limited devices [19]and it can work in four different modes: listening, transmitting, receiving, and sleeping. Wire-less interfaces consume a significant amount of energy even in the idle listening mode. Mea-surements have shown that transmitting a single bit of information requires the same amountof energy as that needed for processing a thousand operations in a sensor node [20]. Studiesalso show that energy consumption of some radios in idle mode is almost as high as in receiv-ing mode [21, 22]. Therefore, a significant amount of energy can be saved by allowing nodesto put their wireless interfaces into sleep mode.

In DTNs, nodes need to discover neighbors to establish communication. Searching for neigh-bors in sparse DTNs can consume a large amount of power compared to the power consumedby infrequent data transfers. Therefore, novel power management schemes are needed toaddress this problem and to save energy. Designing such power management schemes ischallenging, because nodes need to know when to sleep, to save power, and when to wake upto search for neighbors. Ideally, power management schemes should not reduce network con-nectivity opportunities, which would negatively affect the overall performance of the network.

1.1.1 Disruption Tolerant Networks Characteristics

DTNs are supposed to operate over a long period of time, and they differ from traditionalnetworks because of their characteristics. In this section we briefly review some importantproperties of DTNs [15, 23, 24]:

Latency: Due to frequent and random mobility of the nodes in DTNs, any two nodes maynever meet each other for a long time. Therefore, the transmission rate may be considerablysmall and largely asymmetric with long latency of data delivery.

2


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Energy Constrained / Sparse Wireless Sensor Networks

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Contribution

Single Radio

Alternate between sleep mode and active mode to searchfor contacts and to exchange data

Multi-Radio

Based only on the low power radio to discover contactsand to awake the high-power

Based on the high power radio to undertake the datatransmission

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Outline

1 BackgroundMobility ModelsPower Management of Disruption Tolerant Networks

2 Multi-Radio Power Management Scheme for DTNsPerformance Evaluation of the MR Power managementSchemeImpact of Different Mobility Models on the MR Powermanagement Scheme

3 Summary, Conclusions and Future Directions


Outline





Mobility Models

Random Waypoint (RWP)

The most common model used to evaluate routingprotocols such as DSR and AODV

Each node chooses some destination randomly and movesthere in different speed

Message Ferry Mobility Model (MF)

Regular nodes (often static nodes)

Ferries which move around the deployed area in a deterministic path

Collect messages from the regular nodesDeliver messages to their destinations or to other ferries


Mobility Models

Manhattan Mobility Model

It uses a grid road topology for the movement in urbanareas

Nodes move in horizontal or vertical streets

ZebraNet Mobility Model

Zebra Mobility models are based on zebra’s movementhabit

Human (Orlando) Mobility Model

The Orlando mobility model is based on actual datagathered from human mobility


Power Management of DTNs

Oracles and Knowledge-Based Mechanisms

These power management mechanisms based on knowledge offuture contacts

Assume that nodes have synchronized clocks

Save 50% of the energy compared to the case when no powermanagement apply

Hierarchical Power Management

It is based on the previous mechanisms and assumessynchronization among nodes

Use additional low-power radio to discover contacts and to awakethe high-power radio to exchange data

Saves 73% of the energy compared to the case when no powermanagement apply


Power Management of DTNs

The Context Aware power Management Scheme (CAPM)

Asynchronous mechanism (each node works on its own wake-upschedule)

The CAPM scheme has a fixed duty cycle

Each node wakes up for a fixed or adaptive period and sleeps forthe remaining time

The CAPM achieves 80% energy saving while PSM in Hierarchicalpower management scheme saves 40%


Outline





Multi-Radio Power Management Scheme for DTNs

Multi-Radio combines concepts of on-demand andasynchronous schemes by using

Low-power radio (LPR) interface to search for neighbors

High-power radio (HPR) interface that is wokenon-demand to exchange data

Power usage of low and high power radios (in Watt)

Radio Tx Rx Idle Sleep Bit RateWaveLan 1.3272 0.9670 0.8437 0.0664 2 Mbps

XTend 1 0.36 0.36 0.01 115.2 Kbps


Neighbor Discovery and Data Delivery

Each node periodically wakes up for a period W in a fixedduty cycle of length C

it broadcasts a beacon with a piggybacked delivery send a delivery acceptance message to node 2 when it hears

a b

c d

Multiple possible neighbor discovery scenarios


Simulation Setup

Simulation Scenarios

Each scenario is set up with 40 nodes, distributed over

1000 x 1000 m2 1150 x 1150 m2

1400 x 1400 m2 2000 x 2000 m2

3000 x 3000 m2

Traffic Model

We use constant bit rate traffic with 10 CBR flows and apacket size of 512 bytes.

The traffic generation for each flow varied from 0.25pkts/s to 3 pkts/s.

Only a maximum of 10 connections are allowed duringeach run.


Evaluation Metrics

1 Normalized Energy Consumption (NEC):

The ratio of the energy consumption when multi-radio scheme isapplied divided by the energy consumption in the absence of energyconservation

2 Delivery Ratio:

The ratio of the number of the successfully received data packetsdivided by the number of the data packets sent

3 Average End-to-End Delay:

The average delay it takes to deliver a data packet from the sourceto the destination


Impact of Node Density on Delivery Ratio of the

MR using RWP

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SR−3pkts/sMR−3pkts/sSR−0.25pkts/sMR−0.25pkts/s


Impact of Node Density on Average Delay using

RWP

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Impact of Node Density on Normalized Energy

Consumption using RWP

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Impact of Varying Node Density and Traffic Load

on the Delivery Ratio for Different Mobility Models

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on the Average Delay for Different Mobility Models

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on the NEC for Different Mobility Models

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Summary I

Energy saving of different mobility models at low data rate(0.25 pkt/s)

Mobility Model SR Eng. Saving MR Eng. Saving Delta

RWP 85% 90% 5%MF 86% 93% 7%

Zebra 85% 91% 6%Manhattan 84% 89% 5%

Orlando 77% 87% 10%


Summary II

Energy saving of different mobility models at high data rate(3 pkt/s)

Mobility Model SR Eng. Saving MR Eng. Saving Delta

RWP 73% 88% 15%MF 76% 90% 14%

Zebra 73% 89% 16%Manhattan 72% 86% 14%

Orlando 67% 84% 17%


Outline





Summary and Conclusion

Summary

We designed a MR power management scheme for DTNs

The MR uses two complementary radios: a low-power radiofor neighbor discovery and a high-power radio to undertakethe data transmission

We evaluated the MR scheme with different mobility modelsand we compared it with a single radio scheme (CAPM)

Conclusion

The MR scheme is adaptive to different mobility models

The MR scheme can achieve almost the same delivery ratiocompared to the single radio power management scheme


Future Directions

Routing Protocols

It would be interesting to study the behavior of the MRscheme with other routing protocols such as MaxProp

Traffic Models

It would be interesting to evaluate the MR powermanagement scheme with different traffic models

Adaptive Radios

To explore adaptive radios for energy saving techniques indisruption tolerant networks


THANK YOU

Questions???


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