ASCENT: Adaptive Self-Configuring sEnsor Networks Topologies

1. ASCENT: Adaptive Self-Configuring sEnsor Networks Topologies Authors: Alberto Cerpa, Deborah Estrin Presented by Suganthie Shanmugam

2. Presentation Topics • Introduction • Assumptions and Contributions • ASCENT Design • Analytical Performance Analysis • Experimental Simulation • Simulation Results • Related Work • Conclusion

3. Introduction • Advances in micro-sensor and radio technology • Smart sensors deployed in wireless network • Nodes perform local processing • Reduce communications and energy costs • Low per-node cost → densely distributed network • Results in non-uniform communication density • ASCENT • Only a subset of nodes necessary to establish routing as node density increases • Each node assesses its connectivity and adaptively self-configures to underlying topology

4. ASCENT Introduction • How It works • A node signals when it detects high packet loss • Requests other nodes to join the network • Reduces its load and does not join network till it is “helpful” to do so • Adaptive configuration cannot be done from a central node • Single node cannot sense conditions of nodes distributed in space • Other nodes will be required to communicate detailed information to central node

5. Assumptions and Contributions • Distributed Sensor Network Scenario • Ex: A habitat monitoring sensor network • Sensors hand-placed or dropped from a plane • Conditions • Ad-hoc deployment • Sensor network cannot be deployed in regular fashion • Uniform deployment does not correspond to uniform connectivity • Energy Constraints • Expend minimal energy to maximize network lifetime • Unattended operation under dynamics • Preclude manual configuration and design-time pre-configuration

6. Assumptions and Contributions • Easier to deploy large number of nodes initially • Too few nodes used • Distance between neighboring nodes – large • Packet loss rate increases • Energy required to transmit – prohibitive • All nodes used • Unnecessary energy expended • Nodes interfere with each other – channel congestion • Perfect platform for ASCENT design

7. Assumptions and Contributions • Assumption – CSMA MAC protocol used in network • Resource contention when many nodes involved in routing • ASCENT • Does not detect or repair network partitions • Is not suitable when node density is low • All nodes required to form effective network • Two primary contributions • Use of adaptive techniques to configure the underlying network • Saves Energy, Extends Network lifetime • Use of self-configuring techniques • Reacts to operating conditions locally

8. ASCENT Design • ASCENT adaptively elects “Active” nodes • Awake all the time and perform multi-hop packet routing • Passive nodes • Periodically check if they should become active

9. ASCENT Design - State Transitions

10. ASCENT Design - Parameters Tuning • NT (Neighbor Threshold) • Average degree of connectivity in the network - Set to 4 • LT (Loss Threshold) • Max. amount of data loss that an application can tolerate • Application dependent – Set to 20% • Tt, Tp – Test Timer, Passive Timer • Max. time a node remains in test and passive states • Tt = 2 minutes ; Tp = 4 minutes • Ts – Sleep Timer • Amount of time a node sleeps to conserve energy • Large Ts – Large energy savings but doesn’t react to dynamics

11. Neighbor and Data Loss Determination • Number of active neighbors, Avg. data loss rate • Values measured locally by each node while in passive and test states • Definitions • Neighbor node - From which certain % of packets received • History Window CW – Keep track of packets received from each node • Each node increases the sequence number when each packet is transmitted • When a sequence number is skipped, loss is detected • Final packet loss: • Filter constant ρ set to 0.3

12. Neighbor and Data Loss Determination • The number of active neighbors (N) • Number of neighbors with link packet loss smaller than the neighbor loss threshold (NLS) • NLS = 1- (1/N) • N : the number of neighbors calculated in the previous cycle • If neighbor packet loss > NLS, node deleted from list • As number of neighbors increase, NLS should be increased • Average data loss rate (DL) • Calculated based on application data packets • Detected using data sequence numbers • If message not received from any neighbor - data loss • Control messages are not considered • Help, neighbor announcement and routing control

13. Interactions with Routing • ASCENT • runs above link and MAC layer below routing layer • is not a routing or data dissemination protocol • decides which nodes should join the routing infrastructure • Nodes become active or passive independent of routing protocol • Does not use state gathered by the routing protocol • Does not require changing the routing state • Test state (actively routing packets)  passive state (listen-only) • Cause some packet loss • Improvement : Traffic could be rerouted in advance by informing the routing protocol of ASCENT’s state changes

14. Performance Analysis – Goals and Metrics • One-Hop Delivery Rate • Measures % of packets received by any node in network • Indicates effective one-hop bandwidth available to nodes • When all nodes are turned on –Active case – packet reception includes all nodes. • ASCENT case - includes all except nodes in sleep state. • End-to-End Delivery Rate • Ratio of Number of distinct packets received by destination to the Number originally sent by source • Provides an idea of quality of paths in the network and the effective multi-hop bandwidth

15. Performance Analysis – Goals and Metrics • Energy Savings • Ratio of energy consumed by Active case to Energy consumed by the ASCENT case • Average Per-Hop Latency • Measures average delay in packet forwarding in a multi-hop network • Provides estimate of end-to-end delay in packet forwarding

16. Analytical Performance Analysis • Assumptions • Nodes randomly distributed in an area A • Average degree of connectivity (n) • Packets propagated using flooding with random back-off • Probability of successfully transmitting a packet • P (success) = [(S – 1)/S]T • Node density increase → P (success) decreases • When all nodes can transmit and receive, T = n • Since every node in vicinity can transmit • Node density increase → P (collisions) increases

17. Analytical Performance Analysis • Average latency per hop related to S and T • S = No. of slots • T = No. of active nodes • Each T node picks a random slot • S1, S2…ST • Mean = S / 2 • Uniform probability distribution

18. Analytical Performance Analysis

19. Analytical Performance Analysis • P(δ) distribution for different T and S =20 • T = n • When all nodes can transmit and receive • As n ↑, P(δ) ↓ • In ASCENT case • T = NT • Independent of n • P(δ) remains constant

20. 1 2 3 Analytical Performance Analysis • Energy Savings • Numerator – Power consumed by all nodes without ASCENT • Denominator – Power consumed by all nodes running ASCENT • 1: Power consumed by NT nodes selected by ASCENT to have their radios on • 2: Energy of non-active nodes in passive state • 3: Energy consumed in sleep state

21. Analytical Performance Analysis • Energy Savings • α = Ratio of passive timer to sleep timer • β = Ratio of sleep mode to idle mode power consumption • NT = fixed, β = small, as density ↑ power consumption is dominated by passive nodes • When α = small and Ts >>Tp, large energy savings • Large Ts → slow reaction of passive nodes

22. Analytical Performance Analysis • Energy savings of ASCENT with Adaptive timers • No asymptotic behavior • Energy savings increase linearly with density • Slope of line primarily determined by Probability Threshold Pt

23. Simulation & Experimental Methodology • Implementation • LinkStats module • Adds increasing sequence number to each packet • Monitors packets • Maintains packets statistics • Neighbor Discovery module • Sends and receives Heartbeat messages • Maintains list of active neighbors • Energy Manager module • Evaluate Energy Usage • Acts as simulated battery

24. Simulation & Experimental Methodology • Simulator • Built-in simulator (emsim) of EmStar used • Provides channel simulator to model environment behavior • Statistical model • Experimental Test bed • Total of 55 nodes used, All nodes wall-powered • Routing • Flooding used as routing protocol for simplicity • On receiving a packet, flood module waits for a random time • Randomization interval = 5 seconds

25. Simulation & Experimental Methodology • Scenarios and Environment • Experiments conducted with different densities ranging from 5 to 40 nodes • Density defined topologically • Defined by average degree of connectivity between all nodes not by physical location • Achieved by adjusting transmit power of the RF transceiver • Average number of hops = 3 • Traffic • One source sends approximately 200 messages • Data Rate = 3 messages / minute • Nodes do not experience congestion

26. Simulation Results – Network Capacity • No major difference between analytical and simulated performance • Active case • All nodes join network and forward packets • Low delivery rate • As node density increases, P (collisions) increases • ASCENT case • Limits active nodes • Channel contention does not increase

27. Simulation Results – Network Capacity • No. of hops = 3 • Experiments • No. of hops = 6 • Simulations • Increase in density • ASCENT performs better than ACTIVE case • Remains stable

28. Simulation Results – Energy Savings • ASCENT provides significant Energy savings • As density increases • Fixed State Timers • Energy savings do not increase proportionally • Number of Active nodes remains stable • Adaptive State Timers • Energy savings increase proportionally • Passive nodes aggressive

29. Simulation Results – Latency • ACTIVE case • As density ↑, average per-hop latency is reduced • Larger probability of a node picking a smaller random interval to forward the packet • ASCENT • As density ↑, average per-hop latency remains stable • Number of nodes able to forward packets remains constant

30. Results – Reaction to Dynamics • Evaluate how ASCENT reacts to node failures • Let system run till stable topology reached • Manually kill set of active nodes • At high density, end-to-end delivery rate does not decrease • High probability of a passive node to fix communication hole • ASCENT with adaptive state timers – more stable

31. Results – Sensitivity to Parameters • Larger randomization interval • average one-hop delivery rate increases • Increases end-to-end latency • ASCENT outperforms ACTIVE case

32. Conclusions and Future Work • Paper describes design, implementation, analysis, simulation and experimental evaluation of ASCENT • ASCENT • Has potential to significantly reduce packet loss • Increases Energy efficiency • Was responsive & stable under varied conditions • Future Work • Evaluate interactions of ASCENT with MAC • Investigate use of load balancing techniques • Understand relationships between ASCENT and other routing strategies