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A review prepared for CEG 790 By: Patrick Flaherty

An Application-Specific Protocol Architecture for Wireless Microsensor Networks By: W. Heinzelman, A. Chandrakasan & H. Balakrishnan. A review prepared for CEG 790 By: Patrick Flaherty. Presentation Outline. What is a Wireless Sensor Network? Why are Protocols for Self-Organizing an issue?

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A review prepared for CEG 790 By: Patrick Flaherty

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  1. An Application-Specific Protocol Architecture for Wireless Microsensor NetworksBy: W. Heinzelman, A. Chandrakasan & H. Balakrishnan A review prepared for CEG 790 By: Patrick Flaherty

  2. Presentation Outline • What is a Wireless Sensor Network? • Why are Protocols for Self-Organizing an issue? • The proposed “Low-energy adaptive clustering hierarchy” (LEACH) protocol • Concept • Algorithms • Analysis and simulation of LEACH • Conclusions

  3. Base Station (sink) What Is A Wireless Sensor Network? • Sensor devices (source) • Wireless communication • Network structure

  4. Wireless Sensor Networks • 10’s to 1,000’s of wireless sensors placed into an environment • May be put into structures where truckloads of cabling would be required to connect to the data collection point (e.g., Golden Gate Bridge) • May be placed in a natural environment to monitor wildlife (e.g., study relationship between weather conditions and animal behavior) • May be used in hostile environments to detect movement of opponents

  5. Devices that: Battery Light Heat Vibration … Sensors Processor Radio • Measure some input variable • Process the measurement • Transmit data to higher level Panasonic CR2354 560 mAh • Small & inexpensive (ideally) • Powered by battery (typically) Wireless Sensors

  6. Radio power consumption dominates (even in receive mode) • Standby mode supports long life Energy Consumption is a Function of Device Activity • Telos is a recently released microsensor platform design Source: “Telos Fourth Generation WSN Platform”Presented at: TinyOS Technology Exchange, Feb. 11, 2005

  7. d d Tx Rx Tx Rx Tx Tx Rx Wireless Transmission Issues • Line-of-sight (LOS) transmission attenuation • Power falls off as d 2 • Multiple paths lead to reflection and scattering • Power falls off as d 4beyond a certain distance • Receiver may fail to discriminate valid signals due to • Interference from other Tx • Noise (internal to the Rx)

  8. Characteristics That Affect Wireless Sensor Network Design

  9. Authors’ Design Assumptions • All nodes can transmit with enough power to reach the base station if needed • Individual nodes can adjust the amount of transmit power • Each node has sufficient computational power to support different MAC protocols, perform signal processing, etc. • Nodes always have data to send • Nodes that are sufficiently close have correlated data

  10. Consider 3 Different Network Protocols To Clarify Concepts • “Simple” network -- every node talks directly to the base station • Minimum Transfer Energy (MTE) – nodes minimize transmit distance energy loss • Static Cluster – group nodes spatially, aggregate data, and assign one node to handle communications with the base station

  11. Far away --> Hi-power --> Short life Network Scenario -- Simple • All nodes communicate directly with the base station – always on • Problems: • Who talks next? • Out of power fast! • Especially distant nodes Recall: Signal strength is inversely proportional to the square of the distance (best case) Base Station

  12. Network Scenario – MTE • Each node discovers the best hop-by-hop path to the base station during an initialization phase Problem: close-in nodes overused • Data transmitted every tdelay seconds • Collision avoidance via CSMA protocol • As nodes run out of energy, routes are recomputed to maintain connection to base station • Problems: Base Station Problem: multiple hops --> latency

  13. Nodes send data to “Cluster Head” • Access via TDMA • Cluster head aggregates the data and sends results to base station • Problem: When cluster head’s energy depleted, no further data is sent from this cluster Network Scenario -- Static Clustering • Organize nodes into clusters Base Station

  14. How to improve this idea? Summary of Previous Protocols Less Energy Consumption

  15. Low-Energy Adaptive Clustering Hierarchy (LEACH) Protocol • Structure of rounds occurring over time • Nodes organize themselves into local clusters • One node acts as the cluster head • Member nodes transmit data to the cluster head during the timeslot allocated by a TDMA algorithm • Cluster head aggregates the data from the member nodes (e.g., computes mean value) • Cluster head transmits aggregated data to base station • Repeat until time to begin a new round

  16. Organize new cluster Time Cluster Behavior During a Round Round • Each member node (in turn) transmits their data to the cluster head during the assigned timeslot • Cluster head processes the data • Cluster head transmits to base station Base Station

  17. … Round 1 Round 2 Round n … Frame Cluster Heads Clusters Reform Periodically • Each round consists of a setup period and some number of frames Round 1 • Each round establishes a new structure of clusters • Each cluster has a new cluster head Round 2 • Repeat rounds until the network fails (due to energy depletion)

  18. Now For Some Details • Cluster head selection algorithms • Cluster formation algorithm • Steady-state phase • Alternate scheme LAECH-C

  19. Cluster Head Selection Algorithms • Need: distributed Algorithms • Desired results • Specified number of cluster heads formed for each round • Cluster head duties rotated among nodes so as to evenly draw power from the nodes over time (no overly-utilized nodes) • Case 1: • Nodes begin with equal energy • All nodes transmit data during each frame • Case 2: • Nodes begin with unequal energy, and/or • Nodes transmit “upon event”

  20. Cluster Head Selection – Case 1 • Each node elects itself to be a cluster head with probability Pi(t) such that for N total network nodes Where: k = # cluster heads • To ensure that each node becomes a cluster head only once in each of N/k rounds, assign Ci(t) = 0 if the node has already been a cluster head in the current round and Ci(t) = 1 otherwise. • Each individual node chooses to become a cluster head in round r with probability

  21. Base Station Cluster Head Selection – Case 1 (continued) • Value of N - k*(rmod N/k) represents the number of unpicked nodes • Use of rmod N/k ensures restarting after all nodes have been picked Example N = 9 k = 2

  22. Cluster Head Selection – Case 2 • Nodes with more energy should have a higher probability of being chosen than nodes with less energy • Thus, the probability that a given node will be chosen is determined by that node’s share of the total remaining energy • Where Ei(t) is the energy of the ith node and

  23. Cluster Head Selection – Case 2 (continued) • Notice that this algorithm requires each node to know (or have an estimate for) the value of Etotal(t) • To know the exact value would take time and consume energy • As an estimate we could compute the average energy of each node in a given cluster and multiply by N • Nodes report current energy to cluster head • Cluster head computes estimated Etotal(t) and returns the value to all nodes in the cluster

  24. Distributed Cluster Formation • Cluster heads broadcasts “advertisement” message (ADV) using CSMA MAC protocol • Non-cluster head nodes measure received strength of ADV and select strongest sender as their cluster head • Nodes notify cluster head of their selection with a “Join-REQ” message • Cluster head creates TDMA schedule for nodes in its cluster

  25. Round 1 Frame 2 Frame 1 Steady State Phase • Recall: Rounds are divided into frames • Each node sends data once per frame • TDMA requires accurate synchronization • Possible method  base station sends synchronization signals • Energy saved at non-cluster head nodes since • Power is reduced to only that required to reach local cluster head • Radio turned off except for short period provided by TDMA • Cluster head steady state tasks: • Listen to non-cluster head nodes • Aggregate the data • Transmit the data to the base station

  26. Steady State Phase (continued) • Transmissions must succeed even though other nodes and cluster heads are broadcasting • LEACH uses Direct-Sequence Spread Spectrum (DSSS) • Each cluster uses a unique spreading code • Chosen from a pre-defined list • With enough spreading, potentially interfering signals can be filtered out during de-correlation • Easier to implement than dynamically assigned frequency bands • Difficulty is need for tight timing synchronization • How does DSSS work? (Not addressed in this paper)

  27. Wireless Technologies Narrow Band Spread Spectrum Frequency Hopping Direct Sequence Digital Signal (Data) RFModulator Source X Tx Code Bits (Code) CodeGenerator f f 1 Mhz 11 Mhz Frequency Spectrum “Spread” FrequencySpectrum DSSS Key Ideas • A wireless transmission technology that enables multiple users to share the same bandwidth • Spreading: Data signal is multiplied by a unique, high rate code which spreads the bandwidth before sending (1 data bit now represented by many bits) • The resulting “Spread Spectrum” is less susceptible to interference • Receiver must have the same code to recover the original data

  28. LEACH-C -- A Variation of LEACH • Idea: using a central control algorithm may produce better clusterings • Each node sends location information and energy level to the base station • Base station: • Eliminates low energy nodes from consideration • Finds k optimal clusters (since this is NP-hard, uses the “Simulated annealing algorithm” ) • Goal is to minimize the total sum of squared distances between non-cluster heads and the nearest cluster head

  29. Performance Analysis • Simulate the performance of four protocols (Static Clustering, MTE, LEACH, & LEACH-C) • How? • Set up the simulation • Find the optimal number of clusters • Compare the protocols’ energy consumption performance • Conclusions

  30. Simulation of Protocol Performance • Analytical model of even moderately-sized realistic networks is “difficult” • Authors used the network simulator “ns“ • Comparison of performance over four metrics • System lifetime • Energy dissipation • Amount of data transferred • Latency

  31. do d d<do d d>do do Experiment - Setup Base Station • 100 nodes randomly distributed over a 100 X 100 grid: (0, 0) to (100, 100) • Base station placed outside the grid: (50, 175) • Channel bandwidth = 1 Mb/s • Packets have 25 byte header and 500 byte data size • Power loss determined by distance d • If d < do, loss µd 2 Free space model • If d >= do, loss µd 4 Multi-path model

  32. Experiment - Setup (continued) • Radio energy dissipation model • lEelec: energy consumed by the electronics to process l bits • l efs: energy consumed by the amplifier to transmit l bits over distance d where d < do • l emp: energy consumed by the amplifier to transmit l bits over distance d where d >= do • Then total energy consumed by the transmitter: • Total energy consumed by the receiver:

  33. Experiment - Setup (continued) • Energy parameters used: • Eelec = 50 nJ/bit • efs = 10 pJ/bit/m2 • emp = 0.0013pJ/bit/m4 • Energy for Data Aggregation: EDA = 5 nJ/bit/signal • Question: How many clusters should be used?

  34. Case 2 Base Station Base Station Case 3 Base Station How Will The Number Of Clusters Affect Results? Case 1: Baseline (BL) • S non-cluster head energy = ENCHBL • S Cluster head energy = ECHBL Case 1 Case 2: Fewer Clusters (FC) • ENCHFC > ENCHBL • ECHFC < ECHBL Does Case 2 use less energy than case 1? Case 3: More Clusters (MC) • ENCHMC < ENCHBL • ECHMC > ECHBL Does Case 3 use less energy than case 1? Is there an optimal number of clusters?

  35. Listening Aggregating Transmitting Optimal Number Of Clusters • With a given spatial distribution of nodes and known energy consumption parameters, we can compute an optimal number of cluster heads (k) • Step 1: Develop expressions for node energy use • Cluster heads (always on): (assumes dtoBS > do) • Non-cluster heads: (assumes dtoCH < do) • Step 2: Develop an expression for the expected squared distance from the nodes in a cluster to the cluster head

  36. Optimum Number Of Clusters (continued) • Step 2 (continued): Assumptions • In an M x M grid, each cluster occupies an area of M2/k • Clusters have a node distribution of p(x, y) • The cluster head is at the center of mass of the cluster • Then the expected d2 from the nodes to the cluster head is (in Cartesian coordinates) (in polar coordinates) • Further assume the area is a circle  radius R = (M/(pk)1/2) • And p(r, q) constant for r and q, then

  37. Optimum Number Of Clusters (continued) • Step 2 (continued): Assumptions • Node density is uniform across all clusters  p = (1/( M2/k)) • Then simplifies to • Step 3: • Combine energy and distance expression for non-cluster heads: • Then for the entire cluster: (During a single frame)

  38. Optimum Number Of Clusters (continued) • Step 3 (continued): • Total energy for a frame: • Step 4: Set derivative of Etotal with respect to k to zero Simulation results agree with analytical prediction • Results for this case (100 nodes, etc.): Analytical method predicts 1 < kopt < 6

  39. Comparison of Algorithms • Each node was given 2 Joules of energy (def: J = W·s) • This is equivalent to a 5 volt device @ 20 mA for 20 s • Parameters tracked during simulations • Rate at which data packets were transferred to the BS • Energy required to get the data to the BS • What is not in the simulation • No static energy loss (e.g., RTC energy use) • Energy for CSMA is ignored ( CSMA energy use in MTE is understated) • Energy expended during cluster organization (not mentioned in the paper)

  40. Simulation Results – Data Received ~40% more data for the same energy as LEACH • LEACH-C and LEACH deliver far more data than MTE and Static Clustering (SC) and they are far more energy efficient (as measured by signals per Joule) • SC fails when all cluster heads die, even with most energy still unused • MTE slow to deliver data due to multi-hops • LEACH-C is the best performer due to optimal cluster design

  41. Simulation Results – Nodes Alive LEACH-C delivers more data due to higher data rate/J • LEACH-C and LEACH maintain full network availability far longer than MTE and SC • MTE lasts the longest, but at the price of very limited effective data delivery due to • Lack of data aggregation • Energy wasted in CSMA collisions • LEACH-C is again the best performer

  42. Conclusions • Wireless Sensor Networks which meet the original assumptions will benefit from: • Rotating the cluster head position among all nodes • Adapting cluster organization to new cluster heads • Aggregating data • Disadvantages • LEACH & LEACH-C are very dependent on nodes having correlated data • Both require tight time synchronization • LEACH-C requires location information

  43. Future Work • If nodes send data “on condition” • They can be on standby for longer periods than TDMA permits • Efficient bandwidth use will require a different communication protocol • If nodes are beyond max possible communication range • Multi-hop protocols may be required • “Super cluster heads” may prove a better solution • If the original cluster is kept and the nodes within the existing clusters just rotate the cluster head job • No setup overhead is used after round one • Downside  nodes may expend more energy communicating since current cluster head may be far away

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