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AIC group: Networking Protocols and agent methodology research for Sensor Networks

AIC group: Networking Protocols and agent methodology research for Sensor Networks. Antonio G. Ruzzelli School of Informatics and Computer Science University College Dublin Dublin, Ireland ruzzelli@ucd.ie www.adaptiveinformation.ie. 1: Dual channel multiple access. Background .

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AIC group: Networking Protocols and agent methodology research for Sensor Networks

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  1. AIC group:Networking Protocols and agent methodology research for Sensor Networks Antonio G. Ruzzelli School of Informatics and Computer Science University College Dublin Dublin, Ireland ruzzelli@ucd.ie www.adaptiveinformation.ie

  2. 1: Dual channel multiple access

  3. Background • Traditional low cost radios for wireless sensors operate with one frequency channel at any given time, e.g Tr1001, CC1000, CC1010 • A profusion of MAC protocols focus on energy efficiency over one frequency channels

  4. Unique frequency channel issues • MACs like IEEE802.11, SMAC, TRAMA or BMAC suffer from: • High latency (e.g. due to RTS/CTS/ACK in CSMA/CA) • Low flexibility (Difficult to release slots unused in TDMA) • Inefficient usage of the wireless channel (e.g. the ETP problem in CSMA/CA)

  5. Advances in WSNs • Novel transceivers can operate with two channels simultaneously with a relative small increase of energy consumption e.g. nRF2401 • nRF2401 is effectively mounted on the motes developed at the University of Cork (Ireland)

  6. DCMA/AP: Dual channel multiple access with adaptive preamble • Usage of 2 frequency channels • Data channel Cd for data • Control channel Cc for notifications Pros • No table of neighbours required • No handshake mechanisms like RTS/CTS • Reduced idle listening at the receiver • Adaptive wake-up node preamble Cons • Small increase of current consumption in dual channel reception mode (18ma23mA) • Suitable for: • Nodes working at very low duty cycle • Dual channel transceiver

  7. The minimum wakeup concept LCCA Ts Sleep period Wakeup period LCCA Time • Nodes alternate long period of inactivity to tiny period of channel assessment; • The Least Clear Channel Assessment LCCA is the shortest time period needed for nodes to sense any activity on the channel (~2.5msec in BMAC) • LCCA time period is much shorter than the time required for a packet transmission (e.g. 35msec for 5byte transmission with Tr1001) • LCCA can reduce node duty cycle to less than 1% • Wakeup period : longest period of consecutive node activity when a signal is detected (Sensing time)

  8. DCMA communication mechanism (1) • Node are unsynchronized  asynchronous transmission • All nodes apply LCCA periodically on the data channel Cd only • A node with data to transmit apply LCCA on control channel Cc firstly.

  9. DCMA communication mechanism (2) The transmitter • If the channel is clear then the transmitter starts sending the adaptive preamble Pa on Cd • At the same time TX keeps on listening to Cc

  10. DCMA communication mechanism (3) The receiver • During regular CCA, the receiver can sense channel activity on Cd then reply with a TIP packet on Cc TIP =transmission / reception in progress • TIP contains (1)the receiver ID, (2) next Rx ID, (3) packet length

  11. DCMA communication mechanism (4) • In case of error, the notification is transmitted on Cc • The error packet contain the PackID • In case of error the packet is rescheduled

  12. The exposed terminal problem removal • TIP is sent by the receiver  only nodes around the receiver refrain from transmitting The communication mechanism removes the ETP!

  13. Adaptive Preamble mechanism • In case of multiple transmission, asynchronous packets help the receiver to obtain the node ID of the later transmitter Tx2. • Consequently Tx2 can be enabled by means of a RIP packet • The Preamble transmission stops as soon as the RIP packet is received adaptive! Note: RIP content = TIP content Difference: RIP is used to identify multiple Tx

  14. Opportunistic Crossover mechanism Next RX RX TX Channel Cc Channel Cd • During periodical LCCA, if activity is sensed, nodes switches to Cc to get the TIP/RIP packet • TIP/RIP packet contains info about the next scheduled RX node (nextRx) and ongoing packet length • The nextRx is in the position to set up a NAV alarm to wake up right after the packet is transmitted. • Other nodes set up a double NAV to wake up just before the packet has been forwarded Note: Opportunistic crossover needs the next receiver to sense the channel busy (not only the case)

  15. Implementation • DCMA/AP has been coded within the OmNet++ based on the object oriented C++.

  16. Preliminary results • Decrease of transmission packet delay • Increase of network flexibility in terms of access to the channel and node scalability. • Some increase of partial overlapping transmissions on the control channel Cc following an increase of packet generation rate • In general, initial results follow our expectation that an improved performance could compensate for the increase of energy consumption due to two channel utilization

  17. The MERLIN architecture: The TDMA/CSMA hybrid approach, the MERLIN protocol as an example

  18. Scheduling tables: V-schedule vs. X- Schedule • Frame is divided in 8 slots; • Nodes in the same zone transmit simultaneously • The X scheduling is obtained by super positioning 2 V-sched one of which upside-down • Nodes go into sleep immediately after the transmission

  19. X-scheduling vs V-scheduling 300 250 200 Network Lifetime (days) 150 100 50 0 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 Frametime (sec) X Scheduling V-Scheduling Operational network lifetime Average end-to-end packet delay 1 Gateway 100 Nodes rand. Distributed. 800*500 area network Min signal strength(12 m) 50 msg/min sent by 5 rand. nodes Static network Delay calculated in the worst case scenario: 2 sec frametime The X scheduling used for applications in which some energy can be traded off for a decrease of latency of messages and for applications in which latency is a tighter constraint; V-scheduling used for low data traffic applications where the need for saving energy is of paramount importance.

  20. What about an augmented intelligence of decision making? …A multi agent systems to: • Planning to take long term decisions (not only if the-else based) • Migrate to an area affected by an anomalous event • To improve the adaptivity of the networks • Decision based on information from different layers • Better cope with dynamic changes of the network conditions. • To take local decision between neighbouring nodes rather than at the gateway. Hence: • Energy saving • More accurate and faster response to network changes • Increase of preciseness of the action taken

  21. Multi agent system

  22. Application: Dynamic scheduling change due to localized anomaly Possible solution: Multiple Notification messages High energy consuming Our proposed solution: Migrating agent Moderate energy consuming An example:

  23. Disadvantages • Accommodate BDI agents is very challenging due to devices computationally limited • Debugging agent systems during ongoing applications is very challenging (sensors have only 3 leds provided) • Traditionally Multi agent systems (MAS) are java oriented -> JVM needed

  24. Debugging:Agents-nodes mapping at the BS • One-to-One • Each node is controlled by one agent that deliberates accordingly • Nodes can be seen as agent perceptors • Many-to-One • Many agents map to an individual node • E.g. useful when nodes have several sensory modalities • One-to-Many • A single agent map to a group of neighbouring nodes • E.g. useful when decision may be taken by analysing a group of nodes locally placed

  25. Methodology phase 1: Centralised Base station implementation • A single agent placed at the BS • The agent receives raw data from nodes then analyse them • The agent identifies and solve anomalous behaviour of the network or part of it. • The agent communicate to the BS what action to take.

  26. Methodology phase 2: Distributed Base station implementation • The second phase transforms the centralised solution in a distributed agent-base implementation • The key point of this phase is to have a mapping between agents of a MAS and sensor nodes

  27. Methodology phase 3: Distributed agents implementation • Agents on the nodes can be modelled through the agents at the BS • Hence, agents on the nodes can be easily debugged at the BS • The distributed implementation can be achieved by mapping the statements that govern the agents behaviour (such as commitment rules) to the language of the device .

  28. Power managementthrough network coverage:

  29. gateway Integrated Sensor and Routing Coverage Agents • Definitions: • Sensing Coverage: If any node within the sensed area is covered by at least 1 sensor • Routing Coverage: It exists at least one communication path from any node within the network to the gateway • Redundant node: It can be switched off without affecting the level of coverage provided by the network;

  30. Gateway Transmission radius Redundant based on sensor coverage Disconnected Integrated Sensor and Routing Coverage Agents Opportunistic Power Management • Disconnecting sensors based on solely sensing coverage may lead to a disconnected network; for example: • Interpolation for sensing Coverage can be used when nodes does not have a well defined sensing radius e.g sensing temperature • A Time-Zones network division for Routing coverage can be used when nodes does not have a well defined transmitting radius e.g channel irregularities • Hibernating redundant sensors, must be decided based on both routing and sensing connectivity! Zone n-1 Zone n Zone n+1 u Redundant based on routing and sensing coverage

  31. Questions and comments are welcome Thank you for your kind attention!

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