a survey on routing protocols for wireless sensor networks kemal akkaya, mohamed younis 19 th july,...
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A Survey on Routing Protocols for Wireless Sensor
Networks
Kemal Akkaya, Mohamed Younis19th July, 2005Seo, DongMahn
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Contents Introduction Data-centric protocols Hierarchical protocols Location-based protocols Network flow and QoS-aware protocols Conclusion and Open Issues
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Introduction (1) Micro Sensor
micro-electro-mechanical systems (MEMS) , low power and highly integrated digital electronics
data processing, communication capabilitiesambient conditionsan electric signalcommand center (sink)data concentration center (gateway)disposable, unattendedmilitary, civil application, dangerous mission,
landmineconstraints – energy supply, bandwidth
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Introduction (2) Routing in sensor networks
Characteristics No global addressing scheme require the flow of sensed data from multiple regions (sources) to a
particular sink redundancy of data traffic constraints - transmission power, on-board energy, processing capac
ity and storage classification
data-centric hierarchical location-based network flow QoS awareness
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Introduction (3)
System Architecture and Design IssuesNetwork DynamicsNode DeploymentEnergy ConsiderationsData Delivery ModelsNode CapabilitiesData Aggregation/Fusion
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Introduction (4) Related Work
I.F. Akyildiz et al., “Wireless sensor networks: a survey”, Computer Networks, Vol. 38, pp. 393-422, March 2002.
survey of design issues and techniques physical constraints protocols proposed in all layers of network stack No classification of routing protocol
S.Tilak et al., “A Taxonomy of Wireless Microsensor Network Models”, in ACM Mobile Computing and Communication Review (MC2R), June 2002.
high level description of typical sensor network architecture classification of sensor network with considering several architectur
al factors No routing protocol
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Data-centric protocols (1)
Flooding and Gossiping
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Data-centric protocols (2)
Sensor Protocols for Information via Negotiation (SPIN)
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Data-centric protocols (3)
Directed Diffusion
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Data-centric protocols (4) Energy-aware routing
set of sub-optimal pathmeans of a probability function, energy
consumption of each pathnetwork survivability3 phases
Setup phase localized flooding - to find routes and to create the
routing tables)Data Communication Phase
randomly choosing a nodeRoute maintenance phase
localized flooding - to keep all the paths alive
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Data-centric protocols (5)
Rumor routingvariation of DDbetween event flooding and query floodingagent (event flooding), query floodingevent tableSimulation result
significant evergy savingcan handle node’s failureonly when the number of events is small
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Data-centric protocols (6) Gradient-Based Routing (GBR)
changed version of DDheight of the node – number of hopsgradient – difference between a node’s
height and that of is neighborthe largest gradientdata combining entity (to aggregate data)three different data spreading techniques
Stochastic SchemeEnergy-based schemeStream-based scheme
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Data-centric protocols (7) Constrained anisotropic diffusion routing
(CADR) information-driven sensor querying (IDSQ)constrained anisotropic diffusion routing (CADR)maximizing the information gainminimizing the latency and bandwidthCADR
evaluation of information/cost/cost objective and routes
based on local information/cost gradient and end-user requirements
IDSQquery node - the most useful information
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Data-centric protocols (8) COUGAR
a huge distributed database system
select a leader nodenetwork-layer
independent solutiondrawbacks
extra overheadsynchronizationfailure of leader nodes
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Data-centric protocols (9) Active Query forwarding In sensoR nEtworks (A
CQUIRE)new data-centric mechanisma distributed database, complex queriesone-shot respond partially and forward to another sensor look-ahead of d hopsd = 4, mathematical modelingno validation of result through simulation
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Hierarchical protocols (1)
Low-Energy Adaptive Clustering Hierarchy (LEACH)clusters of the sensor nodes5% of the total number of all sensor nodeschoosing header with random number
between 0 and 1not for large networkdynamic clustering with extra overhead
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Hierarchical protocols (2)
PEGASIS & Hierarchical-PEGASISPower-Efficient Gathering in Sensor
Information Systemschains from sensor nodes
Hierarchical-PEGASISchain based binary schemeCDMA, spatially separated nodes
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Hierarchical protocols (3) TEEN and APTEEN
Threshold sensitive Energy Efficient sensor Network Protocol
clustering, hard and soft thresholds, TDMAnot good for periodic applications
AdaPtive Threshold sensitive Energy Efficient sensor Network protocol
hybrid network, TDMA (intra), CDMA (inter)periodic data collections and reacting to time-critical eve
ntsthree query types
historical, to analyze past data values one-tome, to take a snapshot view of the network persistent to monitor an event for a period of time
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Hierarchical protocols (4)
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Hierarchical protocols (5)
Energy-aware routing for cluster-based sensor networks 3 tier architecture
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Hierarchical protocols (6)
Self-organizing protocolbased on taxonomyRouter nodeLocal Markov Loops (LML)4 phases
Discovery phaseOrganization phaseMaintenance phaseSelf-reorganization phase
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Location-based protocols (1) MECN & SMECN
Minimum Energy Communication Networkminimum energy network for wireless networksutilizing low power GPS2 phases
two-dimensional plane,sparse graph (enclosure)
find optimal links with distributed Belmann-Ford shortest pathalgorithm
Small MECNcan transmit to every
other node
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Location-based protocols (2)
Geographic Adaptive Fidelity (GAF)energy-aware location-based routing
algorithmad hoc networks, GPS
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Location-based protocols (3)
Geographic and Energy Aware Routing (GEAR)use of geographic information to restrict the number of interests in DD2 phases
Forwarding packet towards the target region
Forwarding the pachkts within the region
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Network flow and QoS-awareprotocols (1) Maximum lifetime energy routing
network flow approachmaximize network lifetimeMinimum Transmitted Energy (MTE)
algorithmBellman-Ford shortest path algorithm
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Network flow and QoS-awareprotocols (2) Maximum lifetime data gathering
Maximum Lifetime Data Aggregation (MLDA)
Lifetime Tdata-gathering schedule SMaximum Lifetime Data Routing (MLDR)
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Network flow and QoS-awareprotocols (3) Minimum cost forwarding
minimum cost patheffect of delay, throughput and energy
consumption from any node to the sink2 phases
setup phasesecond phase
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Network flow and QoS-awareprotocols (4) Sequential Assignment Routing (SAR)
the first protocol table-driven multi-path approach taking QoS metric, energy resource on each path a
nd priority level of each packet fault-tolerance and easy recoveryoverhead of maintaining the tables and states at e
ach sensor node
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Network flow and QoS-awareprotocols (5) Energy-Aware QoS Routing Protocol
extended versionof Dijkstra’salgorithm
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Network flow and QoS-awareprotocols (6) SPEED
soft real-time end-to-end guaranteesend-to-end delay for the packetscongestion avoidancerouting module – Stateless Geographic Non-
Deterministic forwarding (SNFG)
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Conclusion and Open Issues (1)
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Conclusion and Open Issues (2)
more issuesQuality of Service (QoS)
video and imaging sensorsreal-time applications
Energy-aware QoS routingnode mobility integration of WSN with wired networks
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