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11/15/20051 ASCENT: Adaptive Self- Configuring sEnsor Networks Topologies Authors: Alberto Cerpa, Deborah Estrin Presented by Suganthie Shanmugam.

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Presentation on theme: "11/15/20051 ASCENT: Adaptive Self- Configuring sEnsor Networks Topologies Authors: Alberto Cerpa, Deborah Estrin Presented by Suganthie Shanmugam."— Presentation transcript:

1 11/15/20051 ASCENT: Adaptive Self- Configuring sEnsor Networks Topologies Authors: Alberto Cerpa, Deborah Estrin Presented by Suganthie Shanmugam

2 11/15/20052 Presentation Topics Introduction Assumptions and Contributions ASCENT Design Analytical Performance Analysis Experimental Simulation Simulation Results Related Work Conclusion

3 11/15/20053 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 11/15/20054 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 11/15/20055 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 11/15/20056 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 11/15/20057 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 11/15/20058 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 11/15/20059 ASCENT Design - State Transitions

10 11/15/200510 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% T t, T p – Test Timer, Passive Timer  Max. time a node remains in test and passive states  T t = 2 minutes ; T p = 4 minutes T s – Sleep Timer  Amount of time a node sleeps to conserve energy  Large T s – Large energy savings but doesn’t react to dynamics

11 11/15/200511 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 11/15/200512 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 11/15/200513 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 11/15/200514 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 11/15/200515 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 11/15/200516 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 11/15/200517 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 S 1, S 2 …S T  Mean = S / 2 Uniform probability distribution

18 11/15/200518 Analytical Performance Analysis

19 11/15/200519 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 11/15/200520 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 2 1 3

21 11/15/200521 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 11/15/200522 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 P t

23 11/15/200523 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 11/15/200524 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 11/15/200525 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 11/15/200526 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 11/15/200527 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 11/15/200528 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 11/15/200529 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 11/15/200530 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 11/15/200531 Results – Sensitivity to Parameters Larger randomization interval  average one-hop delivery rate increases  Increases end-to-end latency ASCENT outperforms ACTIVE case

32 11/15/200532 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


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