topology management in sensor networks. –what is it? othe physical or logical interconnection...

Topology Management

In Sensor Networks

– What is it?What is it?

o The physical or logical interconnection pattern of a networkThe physical or logical interconnection pattern of a network

– Topology schemes in wired networks:Topology schemes in wired networks:

o BusBus

o StarStar

o RingRing

– Why do we need different schemes in sensor networks?Why do we need different schemes in sensor networks?

o location of sensors is not deterministiclocation of sensors is not deterministic

o resource constraints resource constraints

The Need for Topology Management

– Energy/Power consumptionEnergy/Power consumption

– InterferenceInterference

– ThroughputThroughput

– ConnectivityConnectivity

The Need for Topology Management

– Topology Control Topology Control

o Does not describe a new topologyDoes not describe a new topology

o Provides a mechanism to build certain topologyProvides a mechanism to build certain topology

– DistributedDistributed

o No central control or central source of informationNo central control or central source of information

– Asymmetric LinksAsymmetric Links

o Due to the presence of heterogeneous devicesDue to the presence of heterogeneous devices

Distributed Topology Control in Wireless Sensor Networks with Asymmetric Links

[Liu+ 2003]

Objective

– Reachability between any two nodes is guaranteed to be like initial Reachability between any two nodes is guaranteed to be like initial

topologytopology

– Nodal power consumption is minimizedNodal power consumption is minimized


[Liu+ 2003]

Model

– Network of heterogeneous sensors (called nodes)Network of heterogeneous sensors (called nodes)

– Nodes deployed in a two dimensional planeNodes deployed in a two dimensional plane

– Each node equipped with omni-directional antenna with adjustable Each node equipped with omni-directional antenna with adjustable

transmission powertransmission power

– Nodes have different maximum powerNodes have different maximum power

o PPii = Transmission Power of Node i = Transmission Power of Node i

o PPiimaxmax = Maximum Transmission Power of Node i = Maximum Transmission Power of Node i

o PPijij = Transmission Power required for node i to reach j = Transmission Power required for node i to reach j

o LLijij = Asymmetric link from i to j = Asymmetric link from i to j

o G = (V, L) : directed graph of topology with max powerG = (V, L) : directed graph of topology with max power

o G is strongly connectedG is strongly connected


[Liu+ 2003]

Algorithm

– Fully distributed with no synchronization requiredFully distributed with no synchronization required

– Takes G as input and produces G’ where G’ has:Takes G as input and produces G’ where G’ has:

o Same bi-directional reachabilitySame bi-directional reachability

o Consumes minimum powerConsumes minimum power

– PhasesPhases

o Establishing the vicinity topologyEstablishing the vicinity topology

o Deriving the minimum power vicinity treeDeriving the minimum power vicinity tree

o Propagation of transmission powersPropagation of transmission powers

o OptimizationsOptimizations


[Liu+ 2003]

Establishing the vicinity topology

– Node i broadcasts initialization request (IRQ) with PNode i broadcasts initialization request (IRQ) with P iimaxmax

– VVii is the set of nodes that receive the message {i.e. location is the set of nodes that receive the message {i.e. location ii, P, Piimaxmax}}

– Each node j in VEach node j in Vii sends initialization reply (IRP) message {i.e. location sends initialization reply (IRP) message {i.e. location jj, P, Pjjmaxmax}}

o If PIf Pjjmax max > P > Pij , ij , j can reach I with single hop Lj can reach I with single hop L jiji

o Otherwise find a multi-hop path to reach iOtherwise find a multi-hop path to reach i

– Given the knowledge of location and max power of itself and all vicinity Given the knowledge of location and max power of itself and all vicinity

nodes, node i can determine the vicinity edgesnodes, node i can determine the vicinity edges

– Node i establishes a vicinity topology , GNode i establishes a vicinity topology , Gii =(V =(Vii, E, Eii))


[Liu+ 2003]

Deriving Minimum Power Vicinity Tree

– Derive Minimum power path in GDerive Minimum power path in Gii, to reach from a node i to node j using , to reach from a node i to node j using

Dijkstra or Bellman-Ford algortihms based on sum of power consumption on Dijkstra or Bellman-Ford algortihms based on sum of power consumption on

that path.that path.

– Compute it for each node in VCompute it for each node in Vii to obtain minimum-power vicinity tree, to obtain minimum-power vicinity tree,

GGisis = (V = (Vii, E, Eisis))


[Liu+ 2003]


[Liu+ 2003]

Propagation of transmission powers

– Node i computes minimum power requirement for itself and others nodes in VNode i computes minimum power requirement for itself and others nodes in V ii

– Node i sends a power request (PR) message to each node in VNode i sends a power request (PR) message to each node in V ii, describing the , describing the

minimum power required for that node to reach farthest hopminimum power required for that node to reach farthest hop

– A node j in VA node j in Vii, receiving the PR message increases its power requirement if the , receiving the PR message increases its power requirement if the

requested power in PR is greater than current onerequested power in PR is greater than current one

– Otherwise, it discards the PR messageOtherwise, it discards the PR message

Optimizations

– Achieved via discarding PR messages whenAchieved via discarding PR messages when

o A node already has run the algorithm to find its shortest vicinity treeA node already has run the algorithm to find its shortest vicinity tree

o A node receives a PR message for a node in its vicinityA node receives a PR message for a node in its vicinity

– Example: A asks B for PExample: A asks B for PBCBC while B already has P while B already has PBD BD to reach node Cto reach node C


[Liu+ 2003]

Figure 1: A scenario of further optimized nodal transmission rangeFigure 1: A scenario of further optimized nodal transmission range

Advantages:

– Guarantees same bi-directional interconnection while reducing per node Guarantees same bi-directional interconnection while reducing per node

power consumptionpower consumption

– Distributed algorithm:Distributed algorithm:

o No synchronization requiredNo synchronization required

o No central control node with network informationNo central control node with network information

o Easy to add/remove nodes from the networkEasy to add/remove nodes from the network

– Uses existing well known algorithms to obtain minimum power consumptionUses existing well known algorithms to obtain minimum power consumption

– Works on network with asymmetric links, which seem more realisticWorks on network with asymmetric links, which seem more realistic

– Assumption of asymmetric links, makes it possible to obtain minimum power Assumption of asymmetric links, makes it possible to obtain minimum power

path via multi-hop rather than using a single hop high power linkpath via multi-hop rather than using a single hop high power link


[Liu+ 2003]

Disadvantages:

– Computationally expensive to be run on network with mobile sensorsComputationally expensive to be run on network with mobile sensors

– Overhead of sending IRQ, IRP and RP in a large network of sensorsOverhead of sending IRQ, IRP and RP in a large network of sensors

– Time to converge for the algorithm is largeTime to converge for the algorithm is large

Suggestions/Improvements/Future Work:

– More details on how multi-hop paths will be discoveredMore details on how multi-hop paths will be discovered

– Detailed example covering more complex scenariosDetailed example covering more complex scenarios


[Liu+ 2003]

– Describes Describes

o a topology management technique that is power efficienta topology management technique that is power efficient

o energy, Latency and Density trade-offsenergy, Latency and Density trade-offs

– Provides Provides

o a theoretical analysis of these techniques, including a a theoretical analysis of these techniques, including a

mathematical formulation that can be used to design a network mathematical formulation that can be used to design a network

with required energy, latency and density configurationwith required energy, latency and density configuration

o a hybrid solution with existing topology management scheme a hybrid solution with existing topology management scheme

(GAF) to provide energy saving of over two order of magnitude(GAF) to provide energy saving of over two order of magnitude

– The proposed new topology management scheme is calledThe proposed new topology management scheme is called

STEMSTEM (Sparse Topology and Energy Management) (Sparse Topology and Energy Management)

Optimizing Sensor Networks in the Energy-Latency-Density Design Space

[Schurgers+ 2002]

– Two states for sensor nodes:Two states for sensor nodes:

o Monitoring StateMonitoring State

o Transfer StateTransfer State

– Most of the time a sensor remains in monitoring state (i.e. sensing Most of the time a sensor remains in monitoring state (i.e. sensing

environment)environment)

– When an event occurs, nodes come into transfer mode and transfer When an event occurs, nodes come into transfer mode and transfer

their datatheir data


[Schurgers+ 2002]

Issues:Issues:

– Nodes must listen periodically for call to duty (i.e transfer)Nodes must listen periodically for call to duty (i.e transfer)

– But if they poll periodically on the same frequency, it will collide with But if they poll periodically on the same frequency, it will collide with

other data transferother data transfer

Solution:Solution:

– Use two radios, one for polling while the other for data transferUse two radios, one for polling while the other for data transfer

STEM-B (Beacon Approach):STEM-B (Beacon Approach):

– Initiator sends a stream of beacon packets to poll a target with initiator Initiator sends a stream of beacon packets to poll a target with initiator

and target MAC addressesand target MAC addresses

– Target node sends acknowledgement on receiving the packetTarget node sends acknowledgement on receiving the packet

– Target node turns its transfer radio onTarget node turns its transfer radio on


[Schurgers+ 2002]

STEM-T (Tone Approach)STEM-T (Tone Approach)

– Initiator sends a wake up toneInitiator sends a wake up tone

– Every node receiving that tone starts its data transfer radioEvery node receiving that tone starts its data transfer radio

– No need to send acknowledgementNo need to send acknowledgement

– Every node in the neighborhood of initiator wakes upEvery node in the neighborhood of initiator wakes up

STEM/GAF HybridSTEM/GAF Hybrid

– GAF proposes a scheme in which a sensor network is divided in a gridGAF proposes a scheme in which a sensor network is divided in a grid

– One node in a region has its radio on, others have it turned offOne node in a region has its radio on, others have it turned off

– Nodes alternate the responsibility of being the active nodeNodes alternate the responsibility of being the active node

– GAF uses network density to conserve energyGAF uses network density to conserve energy

– Assuming the active node to be the virtual node, STEM can be used Assuming the active node to be the virtual node, STEM can be used

on the virtual node to manage whole networkon the virtual node to manage whole network


[Schurgers+ 2002]

Advantages:

– Highly efficient in environments where events are rareHighly efficient in environments where events are rare

– Flexible in term of design trade-off for energy, latency and densityFlexible in term of design trade-off for energy, latency and density

– Transition from monitoring state to transfer state is easily achievedTransition from monitoring state to transfer state is easily achieved

– No synchronization requiredNo synchronization required

– Can be use with other topology management schemes like GAFCan be use with other topology management schemes like GAF

Disadvantages:

– Continuous polling consumes energyContinuous polling consumes energy

– Not suitable for highly reactive environmentsNot suitable for highly reactive environments

– Requires extra radio on sensor nodesRequires extra radio on sensor nodes


– Analysis of STEM with clustered networksAnalysis of STEM with clustered networks


[Schurgers+ 2002]

– In In ASCENTASCENT, the nodes coordinate to exploit the redundancy provided by , the nodes coordinate to exploit the redundancy provided by

high density to extend the overall system lifetimehigh density to extend the overall system lifetime

– Nodes achieve self-configuration to establish a topology that provides Nodes achieve self-configuration to establish a topology that provides

communication and sensing coverage under energy constraintscommunication and sensing coverage under energy constraints

– Each node examines its connectivity and adapts its participation in the Each node examines its connectivity and adapts its participation in the

multi-hop network topology based on the operating regionmulti-hop network topology based on the operating region

– The nodeThe node

o Signals when it detects high message loss, requesting additional nodes to Signals when it detects high message loss, requesting additional nodes to

join the network to continue relaying messagesjoin the network to continue relaying messages

o Reduces its duty cycle if high messages losses are detected due to Reduces its duty cycle if high messages losses are detected due to

collisionscollisions

o Probes local communication environment and only joins to the multi-hop Probes local communication environment and only joins to the multi-hop

routing infrastructure if it is usefulrouting infrastructure if it is useful

ASCENT: Adaptive Self-Configuring sEnsor Networks Topologies

[Cerpa+ 2002]

– Sensor nodes do local processing to reduce communication and energy costsSensor nodes do local processing to reduce communication and energy costs

– Challenges arises from the increased level of Challenges arises from the increased level of dynamicsdynamics (systems and (systems and

environmental)environmental)

– One of the most important challenge arises from One of the most important challenge arises from energy constraintsenergy constraints imposed imposed

by by unattended systemsunattended systems

o These systems must be long-lived and operate without manual intervention These systems must be long-lived and operate without manual intervention

o They need to self-configure and adapt to environmental dynamics and some They need to self-configure and adapt to environmental dynamics and some

terrain conditions may result regions with non-uniform communication densityterrain conditions may result regions with non-uniform communication density

o These issues can be addressed by deploying redundant nodes and designing These issues can be addressed by deploying redundant nodes and designing

algorithms to use redundancy to extend the system lifetimealgorithms to use redundancy to extend the system lifetime

o Scaling challenges are associated with spatial coverage and robustnessScaling challenges are associated with spatial coverage and robustness

Central vs. DistributedCentral vs. Distributed

– When energy is constraint and environment is dynamic, distributed approaches are When energy is constraint and environment is dynamic, distributed approaches are

preferable and practicalpreferable and practical


[Cerpa+ 2002]

– Scalable wireless sensor networks require to avoid large amounts of data Scalable wireless sensor networks require to avoid large amounts of data

being transmitted over long distancesbeing transmitted over long distances

– ASCENT applies well-known techniques from MAC layer protocols to the ASCENT applies well-known techniques from MAC layer protocols to the

problem of distributed topology formationproblem of distributed topology formation

– Imagine a habitat monitoring sensor network that is deployed in remote forestImagine a habitat monitoring sensor network that is deployed in remote forest

– The deployed systems must confer with the following conditions The deployed systems must confer with the following conditions

o Ad-hoc deploymentAd-hoc deployment

o Energy constraintsEnergy constraints

o Unattended operation under dynamicsUnattended operation under dynamics

– If we use too few nodes initially:If we use too few nodes initially:

o the distance between neighboring nodes will be too farthe distance between neighboring nodes will be too far

o packet loss rate may increasepacket loss rate may increase

o energy required to transmit over larger distances may be prohibitiveenergy required to transmit over larger distances may be prohibitive


[Cerpa+ 2002]

– If we use all deployed nodes simultaneously:If we use all deployed nodes simultaneously:

o system will expand unnecessary energysystem will expand unnecessary energy

o nodes interfere with each other by congesting the channelnodes interfere with each other by congesting the channel

– ASCENT does not use localized distributed algorithm to find a single solutionASCENT does not use localized distributed algorithm to find a single solution

– Adaptive self-configuration using localized is suited to problem spaces which Adaptive self-configuration using localized is suited to problem spaces which

have a vast number of possible solutions (in this case, large solution spaces have a vast number of possible solutions (in this case, large solution spaces

means dense node deployment)means dense node deployment)

– ASCENT has the following two assumptions:ASCENT has the following two assumptions:

o Carrier Sense Multiple Access (CSMA) MAC protocolCarrier Sense Multiple Access (CSMA) MAC protocol

Possibilities for resource contention when too many neighboring Possibilities for resource contention when too many neighboring

nodes participate in the multi-hop networknodes participate in the multi-hop network

o Reacts when links have high packet lossReacts when links have high packet loss

Does not detect or repair network partitions and assumes that there Does not detect or repair network partitions and assumes that there

is enough node density to connect the entire regionis enough node density to connect the entire region


[Cerpa+ 2002]

– Two essential contributions of ASCENT design are:Two essential contributions of ASCENT design are:

1.1. Adaptive techniques that allow applications to Adaptive techniques that allow applications to configureconfigure the topology the topology

based on the needs while saving energy to extend network lifetime. The based on the needs while saving energy to extend network lifetime. The

techniques do not assume a specific model or fairness, degree of techniques do not assume a specific model or fairness, degree of

connectivity, or capacity requiredconnectivity, or capacity required

2.2. Self-configuring techniques that react to operating conditions are Self-configuring techniques that react to operating conditions are

measured locallymeasured locally. It does not assume any specific radio propagation . It does not assume any specific radio propagation

model, geographical distribution of nodes, or routing mechanisms usedmodel, geographical distribution of nodes, or routing mechanisms used

ASCENT DesignASCENT Design

– Adaptively elects Adaptively elects activeactive nodes from all the nodes nodes from all the nodes

– Active nodes stay awake always and participate in routing while the other Active nodes stay awake always and participate in routing while the other

nodes remain nodes remain passivepassive and periodically checks if they should become active and periodically checks if they should become active


[Cerpa+ 2002]


– Initially, only some nodes are active while other are passively listening to Initially, only some nodes are active while other are passively listening to

packets but not transmittingpackets but not transmitting

– When source starts transmitting data packets towards the sink, the sink gets When source starts transmitting data packets towards the sink, the sink gets

high message loss from the source due to limited radio range, called high message loss from the source due to limited radio range, called

communication holecommunication hole

– The receiver gets high packet loss due to poor connectivity with the senderThe receiver gets high packet loss due to poor connectivity with the sender


[Cerpa+ 2002]

Help Messages

Data Message

SinkSource

Active NeighborPassive Neighbor

Figure 2(a): Communication HoleFigure 2(a): Communication Hole


– Sink start sending Sink start sending help messageshelp messages to neighbors that are in listen-only mode, to neighbors that are in listen-only mode,

called called passive neighborspassive neighbors, to join the network, to join the network

– When a neighbor receive a When a neighbor receive a help messagehelp message, it decides to join the network or not, it decides to join the network or not

– If the node joins, it becomes an If the node joins, it becomes an active neighboractive neighbor and signals the existence of a and signals the existence of a

new active neighbor to other passive neighbors by sending a new active neighbor to other passive neighbors by sending a neighbor neighbor

announcement messageannouncement message

– It continues until the number of active nodes stabilizes on a certain value and It continues until the number of active nodes stabilizes on a certain value and

the cycle stopsthe cycle stops


[Cerpa+ 2002]


– When the process is completed, the newly joined nodes participate in the data When the process is completed, the newly joined nodes participate in the data

delivery process from source to sink more reliablydelivery process from source to sink more reliably

– The process will be repeated in the case of network event (e.g., node failure) The process will be repeated in the case of network event (e.g., node failure)

or environmental effect (e.g., new obstacle) causes message lossor environmental effect (e.g., new obstacle) causes message loss

Sink

SinkSource

Neighbor AnnouncementsMessages

Data Message

Source


[Cerpa+ 2002]

Figure 2(b-c): Self-configuration transition and final stateFigure 2(b-c): Self-configuration transition and final state

NT: neighbor threshold

LT: loss threshold

T?: state timer values (p: passive, s: sleep, t: test)

DL: Data loss rate

Test

Passive Sleep

Activeafter Tt

after Tp

after Ts

neighbors < NT and• loss > LT• loss < LT & help

neighbors > NT (high ID for ties); orloss > loss T0

ASCENT State TransactionsASCENT State Transactions


[Cerpa+ 2002]


– Initially, a random timer turns on the nodes to avoid synchronizationInitially, a random timer turns on the nodes to avoid synchronization

– Node initializes to test state:Node initializes to test state:

Sends data and routing control messagesSends data and routing control messages

Sets up a timer, Tt and sends neighbor announcement messagesSets up a timer, Tt and sends neighbor announcement messages

Moves into passive state if the conditions are met before Tt expiresMoves into passive state if the conditions are met before Tt expires

When Tt expires, it enters to active stateWhen Tt expires, it enters to active state

– The reasoning behind theThe reasoning behind the test test state is to probe the network to decide whether state is to probe the network to decide whether

the addition of a new node would improve connectivitythe addition of a new node would improve connectivity

– On entering the passive state, node:On entering the passive state, node:

Sets up a timer Tp and when Tp expires, it enters to sleep stateSets up a timer Tp and when Tp expires, it enters to sleep state

If before Tp expires, it enters to test state only if the conditions are metIf before Tp expires, it enters to test state only if the conditions are met

Nodes in passive state can hear all packets transmitted, but no routing Nodes in passive state can hear all packets transmitted, but no routing

or data packets are forwarded in this state since this is listen-only stateor data packets are forwarded in this state since this is listen-only state


[Cerpa+ 2002]


– The reasoning behind theThe reasoning behind the passive passive state is to gather information about the state is to gather information about the

state of the network without causing interference with other nodesstate of the network without causing interference with other nodes

– Nodes in passive and test states update the number of active neighbors and Nodes in passive and test states update the number of active neighbors and

data loss ratesdata loss rates

– In passive states, the nodes still consume energy since the radio is on In passive states, the nodes still consume energy since the radio is on

– The nodes in sleep state turns the radio off, sets up timer Ts and goes to The nodes in sleep state turns the radio off, sets up timer Ts and goes to

sleepsleep

– When Ts expires, the nodes moves into passive stateWhen Ts expires, the nodes moves into passive state

– A node in the active state continuous to forward data and routing packets A node in the active state continuous to forward data and routing packets

until it runs out of energyuntil it runs out of energy


[Cerpa+ 2002]

ASCENT Parameters TuningASCENT Parameters Tuning

– ASCENT has many parameters and the choices are left to the applications ASCENT has many parameters and the choices are left to the applications

such as a particular application may trade energy savings for greater sensing such as a particular application may trade energy savings for greater sensing

coveragecoverage

Neighbor Threshold (NT):Neighbor Threshold (NT):

Determines the average connectivity if the networkDetermines the average connectivity if the network

Tradeoff between energy consumed and/or level of interference (packet Tradeoff between energy consumed and/or level of interference (packet

loss) vs. desired sensing coverageloss) vs. desired sensing coverage

Loss Threshold (LT):Loss Threshold (LT):

Determines the maximum amount of data loss an application can tolerate Determines the maximum amount of data loss an application can tolerate

before requesting help to improve network connectivitybefore requesting help to improve network connectivity

This value is highly application dependentThis value is highly application dependent


[Cerpa+ 2002]

ASCENT Parameters TuningASCENT Parameters Tuning

Test timer (Tt), Passive timer (Tp), Sleep timer (Ts):Test timer (Tt), Passive timer (Tp), Sleep timer (Ts):

Determines the maximum time a node remains in test, passive, sleep statesDetermines the maximum time a node remains in test, passive, sleep states

Tradeoff between power consumption vs. decision qualityTradeoff between power consumption vs. decision quality


[Cerpa+ 2002]

– The primary design constraints of the sensor network algorithms and The primary design constraints of the sensor network algorithms and

protocols are: protocols are: energy-efficiencyenergy-efficiency, , scalabilityscalability and and localizationlocalization

– The improved energy efficiency can be achieved by designing protocols The improved energy efficiency can be achieved by designing protocols

and algorithms with and algorithms with cross-layer approachcross-layer approach, i.e., considering interactions , i.e., considering interactions

between different layers of the communication process such that overall between different layers of the communication process such that overall

energy consumption is minimizedenergy consumption is minimized

– A A scalablescalable algorithm algorithm performs well in a large network

– The scalability for an algorithm is related to that of localization: in a scalable algorithm each node exchanges information only with its neighbors (localized information exchange) in a very large wireless network

Optimal Local Topology for Energy Efficient Geographical Routing in Sensor Networks

[Melodia+ 2004]

– This paper considers the interaction between topology control and This paper considers the interaction between topology control and

energy efficient geographical routingenergy efficient geographical routing

– The question to answer is: The question to answer is: ““How extensive should be the Local Knowledge of the global topology in each sensor node, so that an energy efficient geographical routing can be guaranteed?”

– This question is related to the degree of localization of the routing scheme

– If each sensor node have the complete knowledge of the topology, it could compute the “global” optimal next hop to minimize the energy consumption

– However, the knowledge of complete topology information has an associated cost, i.e., energy used to exchange the signaling traffic


[Melodia+ 2004]

– An analytical framework is developed to capture the tradeoff between the topology information cost, which increases with the Knowledge Range of each node, and the communication cost, which decreases when the knowledge becomes more complete

– This analytical framework is then applied to different position based forwarding schemes and demonstrated by using Monte Carlo simulations that a limited knowledge is sufficient to make energy efficient routing decisions

– A “neighbor” for a certain sensor node is another node which falls into its topology Knowledge Range, denoted as KR


[Melodia+ 2004]

– The contributions of this work are:

o Introduction of a novel analytical framework to evaluate the energy consumption of geographical routing algorithms for sensor networks

o Integer Linear Programming (ILP) formulation of the topology Knowledge Range optimization problem

o Detailed comparison of the leading existing forwarding schemes [Takagi+ 1984, Hou+ , Finn 1987, Kranakis+ 1999, Nelson+ 1984] and introduced a new scheme called Partial Topology Knowledge Forwarding (PTKF)

o Introduction of PRobe-bAsed Distributed protocol for knowledge rAnge adjustment (PRADA) for the on-line solution of the problem that allows nodes to select near-optimal Knowledge Ranges in a distributed way


[Melodia+ 2004]

Advantages:

– No need for knowing the global topology of the networkNo need for knowing the global topology of the network

– PRADA can be run independently in the nodes, thus the nodes do not PRADA can be run independently in the nodes, thus the nodes do not

require time synchronizationrequire time synchronization

– Demonstrates a limited amount of topology knowledge is sufficient in Demonstrates a limited amount of topology knowledge is sufficient in

order for energy conserving routing protocols to be implementedorder for energy conserving routing protocols to be implemented

– The nodes periodically update their knowledge range, thus the The nodes periodically update their knowledge range, thus the

algorithm could be implemented in sensor networks where the nodes algorithm could be implemented in sensor networks where the nodes

are mobileare mobile

– Draws a fine line between topology information cost and communication Draws a fine line between topology information cost and communication

costcost


[Melodia+ 2004]

Disadvantages:

– No mentioning about the sensitivity towards location error of their No mentioning about the sensitivity towards location error of their

proposed protocolproposed protocol

– For a pair of source-destination path, the most optimal path is always For a pair of source-destination path, the most optimal path is always

chosen; however, this would lead to a starvation of some of the nodes chosen; however, this would lead to a starvation of some of the nodes

that would not get any trafficthat would not get any traffic

– The performance evaluation of protocol does not consider the lower The performance evaluation of protocol does not consider the lower

layers, such as MAClayers, such as MAC


[Melodia+ 2004]


– Extending the optimization objectives to include not only power but also Extending the optimization objectives to include not only power but also

battery level of each node (thus improving network lifetime)battery level of each node (thus improving network lifetime)

– Implementing the proposed routing protocol within a simulator which Implementing the proposed routing protocol within a simulator which

considers routing and MAC layer together to draw a more convincible considers routing and MAC layer together to draw a more convincible

conclusionconclusion


[Melodia+ 2004]

[Cerpa+ 2002] A. Cerpa and D. Estrin, ASCENT: Adaptive Self-Configuring Sensor Networks Topologies, Proceedings of the Twenty First International Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM 2002), New York, NY, USA, June 23-27 2002.

[Finn 1987] G.G. Finn, Routing and Addressing Problems in Large Metropolitan-Scale Internetworks, ISI res. rep ISU/RR- 87-180, Mar. 1987.

[Hou+ ] T.C. Hou and V.O.K. Li, Transmission Range Control in multihop packet radio networks, IEEE Transactions on Communications, Vol. 34, No.1, pp. 38-44.

[Kranakis+ 1999] E. Kranakis, H. Singh, and J. Urrutia, Compass routing on geometric networks, Proceedings of the 11th Canadian Conference on Computational Geometry, Vancouver, Canada, August 1999.

[Liu+ 2003] J. Liu and B. Li, Distributed Topology Control in Wireless Sensor Networks with Asymmetric Links, GLOBECOM 2003.

[Melodia+ 2004] T. Melodia, D. Pompili, and I.F. Akyildiz, Optimal Topology Knowledge for Energy Efficient Geographical Routing in Sensor Networks, Proceedings of the Twenty First International Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM 2004), Hong Kong, P.R., China, March 2004.

[Nelson+ 1984] R. Nelson and L. Kleinrock, The spatial capacity of a slotted ALOHA multihop packet radio network with capture, IEEE Transactions on Communications, Vol. 32, No.6, pp. 684-694, 1984.

References

[Takagi+ 1984] H. Takagi and L. Kleinrock, Optimal Transmission Ranges for Randomly Distributed Packet Radio Terminals, IEEE Transactions on Communications, Vol. 32, No.3, pp. 246-57, 1984.

[Schurgers+ 2002] C. Schurgers, V. Tsiatsis, S. Ganeriwal, and M.B, Srivastava, Optimizing Sensor Networks in the Energy-Latency-Density Design Space, IEEE Transactions on Mobile Computing, Vol. 1, No.1, pp. 70-80, January-March 2002.

References

topology management in sensor networks. –what is it? othe physical or logical interconnection...

Documents