lightweight routing with qos support in wireless sensor and actor networks (lrp-qs)
DESCRIPTION
Wireless sensor and actor networks (WSANs) can be used for monitoring physical environments and acting according to the observations. In order to differentiate the actions based on the sensed information, WSANs comprise of various applications with different quality of service (QoS) requirements. QoS solutions for WSANs are challenging compared to traditional networks because of the limited resource capabilities of sensor nodes. In terms of QoS requirements, WSANs also differ from WSNs since actors and sensors have distinct resource constraints. In this paper we present LRP-QS, lightweight routing protocol with QoS support for WSANs. Our protocol provides QoS by differentiating the rates among different types of applications with dynamic packet tagging at the sensor nodes and per flow management at the actor nodes. Through extensive simulations we observe a greater packet delivery ratio and a better memory consumption rate in comparison with the related mechanisms.TRANSCRIPT
Lightweight Routing with
QoS Support in
Wireless Sensor and Actor
Networks Mustafa İlhan Akbaş and Damla Turgut
University of Central Florida
December 8, 2010
Problem Definition
• WSANs used in various settings
• Variance in applications → QoS
• Heterogeneous node structure → Not same as WSNs
• Objective
• Lightweight
• QoS aware routing
Related Work
• QBRP – QoS Based Routing Protocol for WSANs
• Similarities
• WSAN protocol
• Network organization
• Differences
• Data collection from the network
• Central processing for routing
Phase 1: Dividing the network
into acting areas
•Actors flood area
configuration
messages
•The sensor nodes
get their hop values
and actor IDs
•The network among actors
•Sink starts formation with
the area integration packet
•First transmitting neighbor
is the data destination
•The others saved in a
redundancy list
Phase 2: Formation of communication
backbone
Phase 3: Interest subscription
•Sink transmits the
interests via the
communication
backbone
•Actors distribute
interests in their areas
•Sensor nodes get the
interest information
Phase 4: Data transmission
• Packet tags: interest, rate, weight
• Tags based on local information
• The efficient rate for each interest: 𝑂𝑢𝑡𝑝𝑢𝑡 𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦
𝑁𝑜. 𝑜𝑓 𝑎𝑐𝑡𝑖𝑣𝑒 𝑖𝑛𝑡𝑒𝑟𝑒𝑠𝑡𝑠
• FIFO queuing & probabilistic dropping at sensor
nodes
𝐷𝑝 = 1 − 𝐶𝑠/(𝑁𝑠 ∙ 𝑅𝑝)
𝐷𝑝=Dropping probability, 𝐶𝑠=Shared capacity, 𝑁𝑠=Number of sharing flows
𝑅𝑝=Rate of the packet
• Stateful approach for actors
• Actors estimate per-flow rate, update tags
𝑅𝑖𝑛𝑒𝑤=(1-𝑒−𝑇/𝐾)
𝑙
𝑇+𝑒−𝑇/𝐾𝑅𝑖
𝑜𝑙𝑑
where 𝑖 = interest,
𝑇= time between last two packets of 𝑖, 𝑙 = packet length
• Actors may request changes
Phase 4: Data transmission (2)
Example (1)
output
capacity
9
Rate: 8
Rate: 6
Rate: 2
Input Output
4
4
2
8 > 3
6 > 3
2 < 3
8 > 3.5
6 > 3.5
Black = 𝑫𝒑= 3.5/8
Red = 𝑫𝒑 = 3.5/6
Blue = no drop
𝟗
𝟑 = 3
𝟗−𝟐
𝟐=3.5
output
capacity
10
8, w = 2
6, w = 1
2, w = 1
Input Output
5,2
2,6
2
8/2 > 2,5
6 > 2,5
2 < 2,5
8/2 > 2,6
6 > 2,6
Black = 5,2
Red = 2,6
Blue = 2
Example (2)
𝟏𝟎
𝟒 =2.5
𝟏𝟎−𝟐
𝟑 =2.6
Simulation Study • OPNET
• LRP-QS vs QBRP
• Network • Interest area: 200 m x 200 m
• No. of actor/sensor nodes: 4/60
• Sensor transmission range: 50 m
• Actor transmission range: 180 m
• Metrics • Packet loss
• Memory consumption
• Control traffic overhead
• Delay
Packet loss
Control Overhead
Memory consumption
End-to-end delay
Conclusion
• LRP-QS is developed considering the
heterogeneous structure of nodes in WSAN
• LRP-QS outperforms QBRP with a lightweight
approach
• Future work
• Integrate actor placement
• Improve the performance with data aggregation
• Mobile actors and sensor nodes
• Dynamic network organization