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Data Storage Placement in Sensor Networks

Data Storage Placement in Sensor Networks. Bo Sheng Weizhen Mao Qun Li Department of Computer Science College of William and Mary. MobiHoc 2006. Outline. Introduction Problem Formulation Placement Algorithms Stochastic Analysis Simulation Conclusion. Background. Forwarding node.

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Data Storage Placement in Sensor Networks

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  1. Data Storage Placement in Sensor Networks Bo Sheng Weizhen Mao Qun Li Department of Computer Science College of William and Mary MobiHoc 2006 / 47

  2. Outline • Introduction • Problem Formulation • Placement Algorithms • Stochastic Analysis • Simulation • Conclusion / 47

  3. Background Forwarding node Storage node query data sink / 47

  4. Motivations • Placing storage nodes can reduce the transmission cost • The query diffused by flooding is not suitable / 47

  5. Goal • Design a storage node placement to reduce the energy consumption / 47

  6. Network Assumptions • The transmission cost is only proportional to the data size • The receiving energy cost is assigned to the transmitter without changing the total energy cost / 47

  7. Notational • rd: The number of readings per node per time unit • sd: The data size of each readings • rq: The number of queries per time unit • sq: The size of the query message • α: A percentage of the data to reply a query / 47

  8. Energy cost per node per time unit →e(i) • Different environments • i is a forwarding node and no storage nodes in Ti • i is a storage node and no storage nodes in Ti • i is a forwarding node and at least one storage node in Ti • i is a storage node and at least one storage node in Ti / 47

  9. e(i)_Case A • Environment • i is a forwarding node and no storage nodes in Ti • Energy cost i / 47

  10. e(i)_Case B • Environment • i is a storage node and no storage nodes in Ti • Energy cost i / 47

  11. e(i)_Case C • Environment • i is a storage node and at least one storage node in Ti • Energy cost i Case B / 47

  12. e(i)_Case D • Environment • i is a forwarding node and at least one storage node in Ti • Energy cost i j k / 47

  13. Placement Algorithms • Unlimited number of storage nodes • Limited number of storage nodes / 47

  14. Unlimited Number of Storage Nodes i i Case A Case B / 47

  15. Unlimited Number of Storage Nodes i i j k Case D Case C / 47

  16. Unlimited Number of Storage Nodes • Case A, B • Case C, D become forwarding node become storage node / 47

  17. Limited number of storage nodes / 47

  18. Notation • k: The maximum number of storage nodes, include sink • n: The number of sensors, include sink • di: The depth of node i • m: The maximum number of storage nodes in Ti i j / 47

  19. Transmission Cost of Query node i node i is a forwarding node node i is a storage node / 47

  20. Transmission Cost of Data i i / 47

  21. Transmission Cost of Data i is a leaf node / 47

  22. Transmission Cost of Data i is a forwarding non-leaf node with a child set of Ci / 47

  23. Transmission Cost of Data i is a storage non-leaf node and non-root node / 47

  24. Stochastic Analysis • Fixed Tree Model • Dynamic Tree Model / 47

  25. Fixed Tree Model the total number of the forwarding nodes whose depth values are t / 47

  26. Fixed Tree Model The expected hop distance to its closest storage ancestor ( The probability that a node is a storage node ) / 47

  27. Fixed Tree Model The maximum depth ( The cost of query diffusion ) / 47

  28. Dynamic Tree Model • x: The location of forwarding node • y: The location of storage node • F(x, y): The energy cost of transmission from x to y • |x|: The distance from node x to sink / 47

  29. Dynamic Tree Model / 47

  30. Dynamic Tree Model / 47

  31. Dynamic Tree Model / 47

  32. Dynamic Tree Model / 47

  33. Dynamic Tree Model / 47

  34. Dynamic Tree Model / 47

  35. Dynamic Tree Model / 47

  36. Dynamic Tree Model / 47

  37. Simulation • R = 5 • Number of sensor nodes: 10 • Transmission range: 0.65 • k: Number of storage nodes • rd= rq = sd = sq = 1 / 47

  38. Models • FT-DD (fixed tree model with deterministic deployment) • FT-RD (fixed tree model with random deployment) • DT-RD (dynamic tree model with random deployment) • ST-RD (semi-dynamic tree model with random deployment) / 47

  39. The Energy Cost of FT-RD / 47

  40. The Energy Cost of FT-RD / 47

  41. The Energy Cost of DT-RD / 47

  42. The Energy Cost of DT-RD / 47

  43. The Energy Cost of Different Models / 47

  44. Load-Balancing of Different Models / 47

  45. The Life Time of Different Models / 47

  46. Conclusion • Different storage node placement models • The theoretical estimate and simulation match well • Optimize the query reply is the future work / 47

  47. Thank You ! / 47

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