System Architecture of

1
System Architecture of Networked Sensor
Platforms and Sensor Networks Applications
2
Introduction
Wireless sensor networks (WSN) consists of group
of sensor nodes to perform distributed sensing
task using wireless medium. Characteristics-
low-cost, low-power, lightweight - densely
deployed - prone to failures - two ways of
deployment randomly, pre-determined or
engineered Objectives- Monitor
activities- Gather and fuse information -
Communicate with global data processing unit
3
Introduction

• Recent sensor networks research involves almost
  all the layers and can be categorized into the
  following three aspects Akyildiz2002,
  Elson2002
• Energy Efficiency
• small devices, limited amount of energy,
  essential to prolong system lifetime
• Scalability
• deployment of thousands of sensor nodes,
  low-cost
• Locality
• smallest networks cannot depend on having global
  states

4
Why Sensor Platforms?

• Traditional mechanisms of exploring the network
  (analysis and simulation) are not satisfied for
  exploring such a large-scale, dynamic and
  resource-constrained networks due to their
  difficulties to modeling every aspect of the
  system as a whole
• For example, energy consumption model of the
  hardware platforms, including sensing,
  computation and communication, is not fully
  considered and overly-simplified assumptions have
  been made
• Application-specific property of WSN makes the
  existing research mechanisms even harder to
  obtain meaningful results
• Therefore, the demand to build a platform is
  increasing e.g., Berkeleys motes and MANTIS

5
Why Sensor Platforms?

• Compared to analysis and simulation techniques,
  designing a system platform has the following
  advantages
• Provides genuine executive environment various
  proposed algorithms can be exactly evaluated
  good way to examine existing design principles
  and discover new ones under different
  configurations
• More attention can be focused on the
  application-layer
• A real system platform can accelerate the pace of
  research and development

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General WSN System Architecture

• Constructing a platform for WSN falls into the
  area of embedded system development which usually
  consists of developing environment, hardware and
  software platforms.
• Hardware Platform
• Consists of the following four components
• a) Processing Unit
• Associates with small storage unit (tens of kilo
  bytes order) and
• manages the procedures to collaborate with other
  nodes to carry out the
• assigned sensing task
• b) Transceiver Unit
• Connects the node to the network via various
  possible transmission
• medias such as infra, light, radio and so on

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General WSN System Architecture

• Hardware Platform
• c) Power Unit
• Supplies power to the system by small size
  batteries which makes the
• energy a scarce resource
• d) Sensing Units
• Usually composed of two subunits sensors and
  analog-to-digital
• Converters (ADCs). The analog signal produced by
  the sensors are
• converted to digital signals by the ADC, and fed
  into the processing unit
• e) Other Application Dependent Components
• Location finding system is needed to determine
  the location of sensor
• nodes with high accuracy mobilizer may be needed
  to move sensor
• nodes when it is required to carry out the task

8
General WSN System Architecture

• Hardware Platform

Figure 1 The components of a sensor node
Akyildiz2002
9
General WSN System Architecture

• Software Platform
• Consists of the following four components
• a) Embedded Operating System (EOS)
• Manages the hardware capability efficiently as
  well as supports
• concurrency-intense operations. Apart from
  traditional OS tasks such as
• processor, memory and I/O management, it must be
  real-time to rapidly
• respond the hardware triggered events,
  multi-threading to handle
• concurrent flows
• b) Application Programming Interface (API)
• A series of functions provided by OS and other
  system-level components
• for assisting developers to build applications
  upon itself

10
General WSN System Architecture

• Software Platform
• c) Device Drivers
• A series of routines that determine how the upper
  layer entities
• communicate with the peripheral devices
• d) Hardware Abstract Layer (HAL)
• Intermediate layer between the hardware and the
  OS. Provides uniform
• interfaces to the upper layer while its
  implementation is highly dependent
• on the lower layer hardware. With the use of HAL,
  the OS and
• applications easily transplant from one hardware
  platform to another

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General WSN System Architecture

• Software Platform

Figure 2 The software platform for WSN
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General WSN System Architecture

• System Development Environment
• Provides various of tools for every stage of
  software development over
• the specific hardware platform
• a) Cross-Platform Development
• Generally, an embedded system unlike PC and does
  not have the ability
• of self-development. The final binary code run on
  that system, termed as
• target system, will be generated on the PC,
  termed as host system, by
• cross-platform compilers and linkers, and
  download the resulted image
• via the communication port onto the target system

13
General WSN System Architecture

• System Development Environment
• Provides various of tools for every stage of
  software development over
• the specific hardware platform
• b) Debug Techniques
• Due to the difficulties introduced by
  cross-platform development mode,
• the debug techniques become critical for the
  efficiency of software
• production. For this reason, many chips on the
  system provide the
• on-chip debugger, such as JTAF, to reduce the
  development time.

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Berkeley Motes Hill 2000

• Motes are tiny, self-contained, battery powered
  computers with radio links, which enable them to
  communicate and exchange data with one another,
  and to self-organize into ad hoc networks
• Motes form the building blocks of wireless sensor
  networks
• TinyOS TinyOS, component-based runtime
  environment, is designed to provide support for
  these motes which require concurrency intensive
  operations while constrained by minimal hardware
  resources

Figure 3 Berkeley Mote
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Berkeley Motes Hill 2000

• Hardware Platform
• Consists of
• micro-controller with internal flash program
  memory
• data SRAM
• data EEPROM
• a set of actuator and sensor devices, including
  LEDs
• a low-power transceiver
• an analog photo-sensor
• a digital temperature sensor
• a serial port
• a small coprocessor unit

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Berkeley Motes Hill 2000

• Hardware Platform

Figure 4 The schematic for representative
network sensor platform
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Berkeley Motes Hill 2000

• Hardware Platform
• The processing unit
• MCU (ATMEL 90LS8535), an 8-bit architecture with
  16-bit addresses
• provides 32 8-bit general registers and runs at
  4 MHz and 3.0 V
• has 8 KB flash as the program memory and 512
  Bytes of SRAM as the data memory
• MCU is designed such that the processor cannot
  write to instruction memory the prototype uses a
  coprocessor to perform this function
• the processor integrates a set of timers and
  counters which can be configured to generate
  interrupts at regular time intervals
• three sleep modes idle (shuts off the
  processor), power down (shuts off everything, but
  the watchdog and asynchronous interrupt logic
  necessary to wake up), power save (keep
  asynchronous timer on)

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Berkeley Motes Hill 2000

• Hardware Platform
• The sensing units
• contains two sub-components photo sensor and
  temperature sensor
• photo sensor represents an analog input device
  with simple control lines which eliminate power
  drain through the photo resistor when not in use
• temperature sensor (Analog Devices AD7418)
  represents a large class of digital sensors which
  have internal A/D converters and interface over a
  standard chip-to-chip protocol (the synchronous
  two-wire I2C protocol with software on the
  micro-controller synthesizing the I2C master over
  general I/O pins. There is no explicit arbiter
  and bus negotiations are carried out by the
  software on the micro-controller

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Berkeley Motes Hill 2000

• Hardware Platform
• The transceiver unit
• consist of an RF Monolithics 916.50 MHz
  transceiver (TR1000), antenna, and a collection
  of discrete components to configure the physical
  layer characteristics such as signal strength and
  sensitivity
• operates in an ON-OFF key mode at speeds up to
  19.2 Kbps
• control signals configure the radio to operate in
  either transmit, receive, or power-off mode
• the radio contains no buffering, so each bit must
  be serviced by the controller on time
• the transmitted value is not latched by the
  radio, so the jitter at the radio input is
  propagated into the transmission signal

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Berkeley Motes Hill 2000

• Hardware Platform
• The transceiver unit is an Energizer CR2450
  lithium battery rated at
• 575 mAh
• The other auxiliary components include
• The coprocessor
• represents a synchronous bit-level device with
  byte-level support
• MCU (AT09LS2343, with 2KB instruction memory, 128
  bytes of SRAM and EEPROM) that uses I/O pins
  connected to an SPI controller where SPI is a
  synchronous serial data link, providing high
  speed full-duplex connections (up to 1 Mbit)
  between peripherals
• the sensor can be reprogrammed by transferring
  data from the network into the coprocessors 256
  KB EEPROM (24LC256)
• can be used as a gateway to extra storage by the
  main processor

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Berkeley Motes Hill 2000

• Hardware Platform
• The other auxiliary components include
• The serial port
• represents a synchronous bit-level device with
  byte-level controller support
• uses I/O pins that are connected to an internal
  UART controller
• in transmit mode, the UART takes a byte of data
  and shifts it out serially at a specified
  interval
• in receive mode, it samples the input pin for a
  transition and shifts in bits at a specified
  interval from the edge
• interrupts are triggered in the processor to
  signal completion of the events

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Berkeley Motes Hill 2000, TinyOS

• Hardware Platform
• The other auxiliary components include
• Three LEDs
• represent outputs connected through general I/O
  ports they may be used to display digital values
  or status
• Software Platform
• based on Tiny Micro-Threading Operating System
  (TinyOS) which is designed for resource-constraine
  d MEMS sensors
• TinyOS adopts an event model so that high levels
  of concurrency can be handled in a small amount
  of space
• A stack-based threaded approach would require
  that stack space be reserved for each execution
  context

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Berkeley Motes Hill 2000, TinyOS

• Software Platform
• A complete system configuration consists of a
  tiny scheduler and a graph of components
• A component has four interrelated parts a set of
  
• a set of command handlers
• a set of event handlers
• an encapsulated fixed-size frame
• Bundle of simple tasks
• tasks, commands and event handlers execute in the
  context of the frame and operate on its state
• each component declares the commands it uses and
  the events it signals
• these declarations are used to compose the
  modular components in a per-application
  configuration

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Berkeley Motes Hill 2000, TinyOS

• Software Platform
• the composition process creates layers of
  components where higher-level components issue
  commands to lower-level components and
  lower-level components signal events to the
  higher-level components
• Frames
• fixed-size and statistically allocated which
  allows us to know memory requirements of a
  component at a compile time -- prevents overhead
  associated with dynamic allocation
• Commands
• non-blocking requests made to lower level
  components
• typically, a command will deposit request
  parameters into its frame and conditionally post
  a task for later execution

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Berkeley Motes Hill 2000, TinyOS

• Software Platform
• Commands
• can invoke lower commands, but it must not wait
  for long
• must provide feedback to its caller by returning
  status indicating whether it was successful or
  not
• Event handlers
• Invoked to deal with hardware events, either
  directly or indirectly
• The lowest level components have handlers
  connected directly to hardware interrupts which
  may be external interrupts, timer events, or
  counter events
• An event handler can deposit information into its
  frame, post tasks, signal higher level events or
  call lower level commands

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Berkeley Motes Hill 2000, TinyOS

• Software Platform
• Event handlers
• in order to avoid cycles in the command/event
  chain, commands cannot signal events
• both signals and events are intended to perform a
  small, fixed amount of work, which occurs within
  the context of their components state
• Tasks
• perform the primary work
• atomic entities with respect to other tasks, run
  to completion and can be preempted by events
• can call lower level commands, signal higher
  level events, and schedule other tasks within a
  component

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Berkeley Motes Hill 2000, TinyOS

• Software Platform
• Tasks
• run-to-completion semantics make it possible to
  allocate a single stack that is assigned to the
  currently executing task which is essential in
  memory constrained systems
• allows to simulate concurrency within each
  component, since tasks execute asynchronously
  with respect to the events
• must never block or spin wait, otherwise, they
  will prevent progress in other components
• Task scheduler
• Utilizes a bounded size scheduling data structure
  to schedule various tasks base on FIFO,
  priority-based or deadline-based policy which is
  dependent on the requirements of the application

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Berkeley Motes Hill 2000, TinyOS
Software Platform
Figure 5 The schematic for the architecture of
TinyOS
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MANTIS Abrach 2003

• MANTIS (MultimodAl system for NeTworks of In-situ
  wireless Sensors) provides a new multi-threaded
  embedded operating system integrated with a
  general-purpose single-board hardware platform to
  enable flexible and rapid prototyping of wireless
  sensor networks
• the key design goals of MANTIS are
• ease of use, i.e., a small learning curve that
  encourages novice programmers to rapidly
  prototype sensor applications
• flexibility such that expert researchers can
  continue to adapt and extend the
  hardware/software system to suit the needs of
  advanced research

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MANTIS Abrach 2003

• MANTIS OS is called MOS
• MOS selects its model as classical structure of
  layered multi-threaded operating systems which
  includes multi-threading, preemptive scheduling
  with time slicing, I/O synchronization via mutual
  exclusion, a standard network stack, and device
  drivers
• MOS choose a standard programming language that
  the entire kernel and API are written in standard
  C. This design choice not only almost eliminates
  the learning curve, but also accrues many of the
  other benefits of a standard programming
  language, including cross-platform support and
  reuse of a vast legacy code base. C also eases
  development of cross-platform multimodal
  prototyping environments on X86 PCs

31
MANTIS Abrach 2003

• Hardware Platform
• MANTIS hardware nymphs design was inspired by
  the Berkeley MICA an MICA2 Mote architecture
• MANTIS Nymph is a single-board design,
  incorporating the micro-controller, analog sensor
  ports, RF communication, EEPROM, and serial ports
  on one dual-layer 3.5 x 5.5 cm printed circuit
  board
• the Nymph is centered around the AMTEL
  ATmega128(L) MCU, including interfaces for two
  UARTs, an SPI bus, an I2C bus, and eight
  analog-to-digital converter channels. It provides
  additional 64KB EEPROM external to MCU in
  addition to 4KB EEPROM included in MCU
• the unit is powered either by batteries or an AC
  adapter, and a set of three on-board LEDs are
  included to aid in the debugging process. It is
  designed to hold a 24mm diameter lithium ion coin
  cell battery (CR2477), but any battery in the
  range of 1.8V to 3.6V can be connected

32
MANTIS Abrach 2003

• Hardware Platform
• in order to facilitate rapid prototyping in
  research environment, the Nymph has solderless
  plug connections for both analog and digital
  sensors, which eliminates the external sensor
  board for many applications
• each connector provides lines for ground, power
  and sensor signal, allowing basic sensors such as
  photo sensors or complex devices such as infrared
  an ultra sounds receivers to be connected easily
• the Chipcon CC1000 radio was chosen to handle
  wireless communication. It supports four carrier
  frequency bands (315, 433, 868, and 915 MHz) and
  allows for frequency hopping which is useful for
  multi-channel communication. It is one of the
  lowest power commercial radios and allows MOS to
  optimize the radio to further reduce the power
  consumption

33
MANTIS Abrach 2003

• Hardware Platform
• for additional modules, the Nymph includes JTAG
  interface which allows the user to easily
  download code to the hardware. This addition
  eliminates a need for separate programming board,
  simplifying the process of reprogramming the
  nodes while reducing the cost of overall system.
  As added benefit, the JTAG port allows the user
  to single-step through code on the MCU and also
  supports the remote shell
• the Nymph uses one of the UARTs to supply a
  serial port (RS232) for connection to a PC while
  the second one is used as an interface to the
  optional GPS unit
• MAX3221 RS232 serial chip is used and may be set
  in three different power saving modes
  power-down, receive only and shut down

34
MANTIS Abrach 2003

• Hardware Platform

Figure 6 MANTIS Nymph
35
MANTIS Abrach 2003

• Software Platform
• MANTIS OS (MOS) adheres to classical layered
  multi-threaded design
• top application and API layers show a simple C
  API which promotes the ease of use,
  cross-platform portability, and reuse of a large
  installed code base
• in lower layers of MOS, it adapts the classical
  OS structures to achieve small memory footprint
• System APIs
• MANTIS provides comprehensive System APIs for I/O
  and system interaction
• the choice of C language API simplifies
  cross-platform support and the development of a
  multimodal prototyping environment

36
MANTIS Abrach 2003

• Software Platform
• System APIs
• since MANTIS System API is preserved across both
  physical sensor nodes as well as virtual sensor
  nodes running on X86 platforms, the same C code
  developed for MANTIS sensor Nymphs with AMTEL MCU
  can be compiled to run on X86 PCs with little or
  no alteration
• Kernel and Scheduler
• design of MOS kernel resembles classical
  UNIX-style schedulers
• The services provided are subset of POSIX
  threads, most notably priority-based thread
  scheduling with round-robin semantics within a
  priority level
• binary (mutex) and counting semaphores are also
  supported
• the goal of the kernel design is to implement
  these familiar services in an efficient manner
  for resource-constrained environment of a sensor
  node

37
MANTIS Abrach 2003

• Software Platform
• Network Stack
• focused on efficient use of limited memory,
  flexibility, and convenience
• implemented as one or more user-level threads
• different layers can be implemented in different
  threads, or all layers in the stack can be
  implemented in one thread
• the tradeoff is between performance and
  flexibility
• designed to minimize memory buffer allocation
  through layers
• the data body for a packet is common through all
  layers within a thread
• the headers for a packet is variably-sized and
  are pre-pended to the single data body
• designed in a modular manner with standard APIs
  between each layers, thereby allowing developers
  easily modify or replace layer modules

38
MANTIS Abrach 2003

• Software Platform
• Device Drivers
• Adopts the traditional logical/physical
  partitioning with respect to device driver design
  for the hardware
• The application developer need not to interact
  with the hardware to accomplish a given task

39
MANTIS Abrach 2003

• Software Platform

Figure 7 MANTIS OS Architecture
40
MANTIS Abrach 2003

• System Development
• application developers need to be able to
  prototype and test applications prior to
  distribution and physical deployment in the field
• during deployment, in-situ sensor nodes need to
  be capable of being both dynamically reprogrammed
  and remotely debugged
• in order to facilitates these issues, MANTIS
  identifies and implements three key advanced
  features for expert users of general-purpose
  sensor systems
• multimodal prototyping environment
• dynamic reprogramming
• remote shell and commander server

41
MANTIS Abrach 2003

• System Development
• Multimodal Prototyping Environment
• Provides a framework for prototyping diverse
  applications across heterogeneous platforms
• A key requirement of sensor systems is the need
  to provide a prototyping environment to test
  sensor networking applications prior to
  deployment
• Postponing testing of an application until after
  its deployment across a distributed sensor
  network can incur severe consequences
• MANTIS prototyping environment extends beyond
  simulation to provide larger framework for
  development of network management and
  visualization applications as virtual nodes
  within a MANTIS network
• MANTIS has property of enabling an application
  developer to test execution of the same C code on
  both virtual sensor nodes and later on in-situ
  physical sensor nodes

42
MANTIS Abrach 2003

• System Development
• Multimodal Prototyping Environment
• Seamlessly integrates virtual environment with
  the real deployment network such that both
  virtual and physical nodes can co-exit and
  communicate with each other in the prototyping
  environment
• Permits a virtual node to leverage other APIs
  outside of the MANTIS API, e.g., a virtual node
  with the MANTIS API could be realized as a UNIX
  X windows application that communicates with
  other rendering or database APIs to build
  visualization and network management applications

43
MANTIS Abrach 2003

• System Development
• Multimodal Prototyping Environment

Figure 8 Multimodal prototyping integrates both
virtual and physical sensor nodes across
heterogeneous X86 and AMTEL sensor platforms
44
MANTIS Abrach 2003

• System Development
• Dynamic Reprogramming
• Sensor nodes should be remotely reconfigurable
  over a wireless multi-hop network after being
  deployed in the field. Since sensor nodes may be
  deployed in inaccessible areas and may scale to
  thousands of nodes, this simplifies management of
  the sensor network
• MOS achieves dynamic reprogramming in several
  granularities re-flashing the entire OS
  reprogramming of a single thread and changing of
  variables within a thread
• Another useful feature would be the ability to
  remotely debug a running thread. MOS provides a
  remote shell that enables a user to login and
  inspect the sensor nodes memory
• MOS includes two programming modes (simpler and
  more advanced) in order to overcome the
  difficulty of reprogramming the network

45
MANTIS Abrach 2003

• System Development
• Dynamic Reprogramming
• The simpler programming mode is similar to that
  used in many other systems and involves a direct
  communication with a specific MANTIS node
• On a Nymph, this would be accomplished via a
  serial port the user simply connects the node to
  a PC and opens the MANTIS shell
• Upon reset, MOS enters a boot loader that checks
  for communication from the shell. At this point,
  the node will accept a new code image, which is
  downloaded from the PC over the direct
  communication line
• From the shell, the user has the ability to
  inspect and modify the nodes memory directly as
  well as spawn threads and retrieve debugging
  information including thread status, stack fill,
  and other statistics from OS
• The boot loader transfers control to the MOS
  kernel on command from the shell, or at a startup
  if the shell is not present

46
MANTIS Abrach 2003

• System Development
• Dynamic Reprogramming
• The more advanced programming mode is used when a
  node is already deployed, and does not require
  direct access to the node
• The spectrum of dynamic reprogramming of in-situ
  sensor networks ranges from fine grained
  reprogramming to complete reprogramming
• MOS has a provision for reprogramming any portion
  of the node up to and including the OS itself
  while the node is deployed in the field
• This is accomplished through the MOS dynamic
  reprogramming interface

47
MANTIS Abrach 2003

• System Development
• Remote Shell and Commander Server
• MOS includes the MANTIS Command Server (MCS)
  which is implemented as an application thread
• From any device in the network equipped with a
  terminal, the user may invoke the command server
  client (also referred to as the shell) and log in
  to either a physical node (e.g., on a Nymph or
  Mica board) or a virtual node running as a
  process on a PC
• MCS listens on a network port for commands and
  replies with the results, in a manner similar to
  RPC
• The shell gains the ability to control a node
  remotely through MCS

48
MANTIS Abrach 2003

• System Development
• Remote Shell and Commander Server
• The user may alter the nodes configuration
  settings, run or kill programs, display the
  thread table and other OS data, inspect and
  modify the nodes data memory, and call arbitrary
  user-defined functions
• The shell is powerful debugging tool since it
  allows the user to examine and modify the state
  of any node, without requiring physical access to
  the node

49
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002

• Introduction
• Habitat and environmental monitoring represent
  essential class of sensor network applications by
  placing numerous networked micro-sensors in an
  environment where long-term data collection can
  be achieved
• The sensor nodes perform filtering and triggering
  functions as well as application-specific or
  sensor-specific data compression algorithms thru
  the integration of local processing and storage
• The ability to communicate allows nodes to
  cooperate in performing tasks such as statistical
  sampling, data aggregation, and system health and
  status monitoring
• Increased power efficiency assists in resolving
  fundamental design tradeoffs, e.g., between
  sampling rates and battery lifetimes

50
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002

• Introduction
• The sensor nodes can be reprogrammed or retasked
  after deployment in the field by the networking
  and computing capabilities provided
• Nodes can adapt their operation over time in
  response to changes in the environment
• The application context helps to differentiate
  problems with simple and concrete solutions from
  open research areas
• An effective sensor network architecture and
  general solutions should be developed for the
  domain
• The impact of sensor networks for habitat and
  environmental monitoring is measured by their
  ability to enable new applications and produce
  new results

51
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002

• Introduction
• This paper develops a specific habitat monitoring
  application, but yet a representative of the
  domain
• It presents a collection of requirements,
  constraints and guidelines that serve as a basis
  for general sensor network architecture
• It describes the core components of the sensor
  network for this domain hardware and sensor
  platforms, the distinct networks involved, their
  interconnection, and the data management
  facilities
• The design and implementation of the essential
  network services power management,
  communications, re-tasking, and node management
  can be evaluated in this context

52
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002

• Habitat Monitoring
• Researchers in the Life Sciences are concerned
  about the impacts of human presence in monitoring
  plants and animals in the field conditions
• It is possible that chronic human disturbance may
  adversely effect results by changing behavioral
  patterns or distributions
• Disturbance effects are of concern in small
  island situations where it may be physically
  impossible for researchers to avoid some impact
  on an entire population
• Seabird colonies are extreme sensitive to human
  disturbance
• Research in Maine Anderson 1995, suggests that
  a 15 minute visit to a cormorant colony can
  result in up to 20 mortality among eggs and
  chicks in a given breeding year. Repeated
  disturbance can lead to the end of the colony

53
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002

• Habitat Monitoring
• On Kent Island, Nova Scotia, research learned
  that Leachs Storm Petrels are likely to desert
  their nesting burrows in case of disturbance
  during the first two weeks of incubation
• Sensor networks advances the monitoring methods
  over the traditional invasive ones
• Sensors can be deployed prior to the breeding
  season or other sensitive period or while plants
  are dormant or the ground is frozen on small
  islets where it would be unsafe or unwise to
  repeatedly attempt field studies
• Sensor network deployment may be more economical
  method for conducting long-term studies than
  traditional personnel-rich methods
• A deploy em and leave em strategy of wireless
  sensor usage would decrease the logistical needs
  to initial placement and occasional servicing

54
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002

• Great Duck Island
• The College of Atlantic (COA) is field testing
  in-situ sensor networks for habitat monitoring
• Great Duck Island (GDI) is a 237 acre island
  located 15 km south of Mount Desert Island, Maine
• At GDI, three major questions in monitoring the
  Leachs Storm Petrel Anderson 1995
• What is the usage pattern of nesting burrows over
  the 24-72 hour cycle when one or both members of
  a breeding pair may alternate incubation duties
  with feeding at sea?
• What changes can be observed in the burrow and
  surface environmental parameters during the
  course of the approximately 7 month breeding
  season (April-October)?

55
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002

• Great Duck Island
• What are the differences in the
  micro-environments with and without large numbers
  of nesting petrels?
• Presence/absence data is obtained through
  occupancy detection and temperature differentials
  between burrows with adult birds and burrows that
  contain eggs, chicks, or are empty
• Petrels will most likely enter or leave during
  the daytime however, 5-10 minutes during late
  evening and early morning measurements are needed
  to capture the entry and exit timings
• More general environmental differentials between
  burrow and surface conditions can be captured by
  records every 2-4 hours during the extended
  breeding season whereas, the differences between
  popular and unpopular sites benefit from
  hourly sampling

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Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002

• Great Duck Island Requirements
• Internet Access
• The sensor networks at GDI must be accessible via
  the Internet since the ability to support remote
  interactions with in-situ networks is essential
• Hierarchical Network
• Habitats of interest are located up to several
  kilometers away. A second tier of wireless
  networking provides connectivity to multiple
  patches of sensor networks deployed at each of
  the areas.
• Sensor Network Longevity
• Sensor networks that runs for several month from
  non-rechargeable power sources would be desirable
  since studies at GDI can span multiple field
  seasons

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Wireless Sensor Networks for Habitat Monitoring
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• Great Duck Island Requirements
• Operating off-the grid
• Every level of the network must operate with
  bounded energy supplies
• Renewable energy such as solar power may be
  available some locations, disconnected operation
  is a possibility
• GDI has enough solar power that run the
  application 24x7 with small probabilities of
  service interruptions due to power loss
• Management at-a-distance
• Remoteness of the field sites requires the
  ability to monitor and manage sensor networks
  over the Internet. The goal is no on-site
  presence for maintenance and administration
  during the field season, except for installation
  and removal of nodes

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Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002

• Great Duck Island Requirements
• Inconspicuous operation
• It should not disrupt the natural processes or
  behaviors under study
• Removing human presence from the study areas
  would eliminate a source of error and variation
  in data collection and source of disturbance
• System behavior
• Sensor networks should present stable,
  predictable, and repeatable behavior at all times
  since unpredictable system is difficult to debug
  and maintain
• Predictability is essential in developing trust
  in these new technologies for life scientists

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Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002

• Great Duck Island Requirements
• In-situ interactions
• Local interactions are required during initial
  development, maintenance and on-site visits
• PDAs can be useful in accomplishing these tasks
  they may directly query a sensor, adjust
  operational parameters and so on
• Sensors and sampling
• The ability to sense light, temperature,
  infrared, relative humidity, and barometric
  pressure are essential set of measurements
• Additional measurements may include
  acceleration/vibration, weight, chemical vapors,
  gas concentrations, pH, and noise levels

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Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002

• Great Duck Island Requirements
• Data archiving
• Sensor readings must be achieved for off-line
  data mining and analysis
• The reliable offloading of sensor logs to
  databases in the wired, powered infrastructure is
  essential
• It is desirable to interactively drill-down and
  explore sensors in near real-time complement
  log-based studies. In this mode of operation, the
  timely delivery of sensor data is the key
• Nodal data summaries and periodic
  health-and-status monitoring also requires timely
  delivery of the data

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Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002

• System Architecture
• A tiered architecture is developed
• The lowest level consists of the sensor nodes
  that perform general purpose computing and
  networking as well as application-specific
  sensing
• The sensor nodes may be deployed in dense patches
  and transmit their data through the sensor
  network to the sensor network gateway
• Gateway is responsible for transmitting sensor
  data from the sensor patch through a local
  transit network to the remote base station that
  provides WAN connectivity and data logging
• The base station connects to database replicas
  across the internet
• At last, the data is displayed to researchers
  through a user interface

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Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002

• System Architecture

Figure 1 System architecture for habitat
monitoring
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Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002

• System Architecture
• The autonomous sensor nodes are placed in the
  areas of interest where each sensor node collects
  environmental data about its immediate
  surroundings
• Since these sensors are placed close to the area
  of interest, they can be built using small and
  inexpensive individual sensors high spatial
  resolution can be achieved through dense
  deployment of sensor nodes
• This architecture offers higher robustness
  compared to traditional approaches which use a
  few high quality sensors with complex signal
  processing
• The computational module is a programmable unit
  that provides computation, storage and
  bidirectional communication with other nodes

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Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002

• System Architecture
• The computational module interfaces with the
  analog and digital sensors on the sensor module,
  performs basic signal processing and dispatches
  the data according to the needs of the
  application
• Compared to traditional data logging systems,
  networked sensors offer two main advantages they
  can be re-tasked in the field and they can
  communicate with the rest of the system
• In-situ re-tasking gives researchers the ability
  to refocus their observations based on the
  analysis of the initial results initially,
  absolute temperature readings are desired, after
  a while, only significant temperature changes
  exceeding a threshold may become more useful

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Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002

• System Architecture
• Individual sensor nodes communicate and
  coordinate with one another
• These nodes form a multi-hop network by
  forwarding each others messages and if needed,
  the network can perform in-network aggregation
  (e.g., relaying the average temperature across
  the region)
• Eventually, data from each sensor needs to be
  propagated to the Internet
• The propagated data may be raw, filtered or
  processed data
• Since direct wide area connectivity cannot be
  brought to each sensor path due to several
  reasons (e.g., cost of equipment, power,
  disturbance created by the installation of the
  equipment in the environment), wide are
  connectivity is brought to a base station instead

66
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002

• System Architecture
• The base station may communicate with the sensor
  patch using a wireless LAN where each sensor
  patch is equipped with a gateway that can
  communicate with the sensor network and provides
  connectivity to the transit network
• The transit network may consist of a single hop
  link or series of networked wireless nodes and
  each transit network design has different
  characteristics with respect to expected
  robustness, bandwidth, energy efficiency, cost
  and manageability
• To provide data to remote end-users, the base
  station includes WAN connectivity and persistent
  data storage for the collection of sensor patches

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Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002

• System Architecture
• It is expected that WAN connection will be
  wireless
• The architecture needs to address the
  disconnection possibilities
• Each layer (sensor nodes, gateways, base
  stations) has some persistent storage to protect
  against data loss due to power outage as well as
  data management services
• At the sensor level, these will be primitive,
  taking the form of data logging
• The base station may provide relational database
  service while the data management at the gateways
  falls somewhere in between
• When it comes to data collection, long-latency is
  preferable to data loss
• Users interact with the sensor network in two ways

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Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002

• System Architecture
• Remote users access the replica of the base
  station database
• This approach assists on integration with data
  analysis and mining tools while masking the
  potential wide area disconnections with the base
  stations
• On-site users may require direct interaction with
  the network and this can be accomplished with a
  small, PDA-sized device, referred to as gizmo
• Gizmo allows the user to interactively control
  the network parameters by adjusting the sampling
  rates, power management parameters and other
  network parameters
• The connectivity between any sensor node and
  gizmo may or may not rely on functioning on
  multi-hop sensor network routing

69
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002

• Implementation Strategies
• Sensor Network Node
• UC Berkeley motes are used as the sensor nodes
• Mica uses a single channel, 916 MHz radio from RF
  Monolithics to provide bi-directional
  communication at 40 Kbps, an Atmel Atmega 103
  microcontroller running at 4 MHz and 512 KB
  nonvolatile storage
• A pair of conventional AA batteries and a DC
  boost converter provide the power source
  however, other renewable energy sources can be
  used

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Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002

• Implementation Strategies
• Sensor Board
• The Mica Weather Board provides sensors that
  monitor changing environmental conditions with
  the same functionality as a traditional weather
  station
• The Mica Weather Board includes temperature,
  photoresistor, barometric pressure, humidity, and
  passive infrared (thermopile) sensors

Table 1 Mica Weather Board
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Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002

• Implementation Strategies
• Sensor Board

Figure 2 Mica Hardware Platform The Mica sensor
node (left) with the Mica Weather Board developed
for environmental monitoring applications
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Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002

• Implementation Strategies
• Energy Budget
• Typical habitat monitoring applications need to
  run for nine months
• The application chooses how to allocate the
  energy budget between sleep modes, sensing, local
  calculations and communications
• Since different nodes have different functions,
  they also have different power requirements, for
  instance, the nodes near the gateway may need to
  forward all messages from a patch while a node in
  a nest may only need to report its own readings
• When a set of power limited nodes exhaust their
  power supplies, the network can become
  disconnected and inoperable
• There is a need to budget the power with respect
  to the energy bottlenecks of the network

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Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002

• Implementation Strategies
• Energy Budget
• The baseline life time of the node is determined
  by the current draw in the sleep state
• Minimizing power in sleep mode means turning off
  the sensors, the radio and putting the processor
  into a deep sleep mode

Table 2 Power required by various Mica operations
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Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002

• Implementation Strategies
• Sensor Deployment
• A wireless sensor network using Mica motes with
  Mica Weather Board has been deployed in July 2002
• Environmental protective packaging has been
  designed which minimally obstruct sensing
  functionality

Figure 3 Acrylic enclosure used for deploying
the Mica mote
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Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002

• Implementation Strategies
• Patch Gateways
• Usage of different gateway nodes directly affects
  the underlying available transit network
• Two designs implemented an 802.11b single hop
  with an embedded Linux system and a single hop
  mote-to-mote network
• Initially, CerfCube Cerfcube which is a small
  StrongARM-based embedded system to act as a
  sensor patch gateway, is chosen
• Each gateway is equipped with a CompactFlash
  802.11b adapter
• Gateway use permanent storage of up to 1GB
• The mote-to-mote solution consisted of a mote
  connected to the base station and a mote in the
  sensor patch

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Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002

• Implementation Strategies
• Patch Gateways
• The differences between the mote and CerfCube
  include different
• communication frequency
• power requirements
• software components
• The motes MAC layer does not require
  bi-directional link like 802.11b
• In addition, the mote sends raw data with a small
  packet header (4 bytes) directly over the radio
  as opposed to overheads imposed by 802.11b and
  TCP/IP connections

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Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002

• Implementation Strategies
• Base-station installation
• For achieve remote access, collection of sensor
  patches is connected to the Internet through a
  wide-area link
• On GDI, Internet connectivity is accomplished
  through a two-way satellite connection provided
  by Hughes and similar to DirecTV system
• The satellite system is connected to a laptop
  which coordinates the sensor patches and provides
  a relational database service
• Database Management System
• The base station uses Postgres SQL database which
  stores time-stamped readings from the sensors,
  health status of the individual sensors, and
  metadata (e.g., sensor locations)

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Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002

• Implementation Strategies
• Database Management System
• The GDI database is replicated every fifteen
  minutes over the wide-area satellite link to
  Postgres database in Berkeley
• User Interfaces
• Many user interfaces can be implemented on top of
  the sensor database
• GIS systems provide a widely used standard for
  analyzing geographical data and most statistics
  and data analysis packages implement interfaces
  to relational databases
• Number of web interfaces can be implemented to
  provide the ubiquitous interfaces to the habitat
  data

79
Energy-Efficient Computing for Wildlife Tracking
Design Tradeoffs and Early Experiences with
ZebraNet Juang 2002

• Introduction
• Focus is on issues related to dynamic sensor
  networks with mobile nodes and wireless
  communication between them
• In this system, the sensor nodes collars carried
  by the animals under study wireless ad hoc
  networking techniques are used to swap and store
  data in a peer-to-peer manner and to pass it
  towards a mobile base station that sporadically
  traverses the area to upload data
• Biology and biocomplexity research has been
  focused on gathering data and observations on a
  range of species to understand their interactions
  and influences on each other
• For example, how human development into
  wilderness areas affects indigenous species
  there understand the migration patterns of wild
  animals and how they may be affected by changes
  in weather patterns or plant life, by
  introduction of non-native species, and by other
  influences

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Energy-Efficient Computing for Wildlife Tracking
Design Tradeoffs and Early Experiences with
ZebraNet Juang 2002

• Introduction
• Finding and learning these details require
  long-term position logs and other biometric data
  such as heart rate, body temperature, and
  frequency feeding
• Current wildlife tracking studies rely on simple
  technology, for example, many studies rely on
  collaring a sample subset of animals with simple
  VHF transmitters
• Researchers periodically drive through and/or fly
  over an area with a receiver antenna, and listen
  for pings from previously collared animals
• Once animal is found, its behavior can be
  observed and its observed position can be logged
  however, there are limits to such studies
• First, data collection is infrequent and can miss
  many interesting events

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Energy-Efficient Computing for Wildlife Tracking
Design Tradeoffs and Early Experiences with
ZebraNet Juang 2002

• Introduction
• Second, data collection is mostly limited to
  daylight hours, but animal behavior and movements
  in night hours can be different
• Third, data collection is impossible or very
  limited for secluded species that avoid human
  contact
• The most elegant trackers commercially available
  use GPS to track position and use satellite
  uploads to transfer data to a base station
• These systems also suffer from several
  limitations
• First, at most a log of 3000 position samples can
  be logged and no biometric data
• Second, since satellite uploads are slow and uses
  high power consumption, they are done
  infrequently this limits how often position
  samples can be gathered without overflowing
  3000-entry log storage

82
Energy-Efficient Computing for Wildlife Tracking
Design Tradeoffs and Early Experiences with
ZebraNet Juang 2002

• Introduction
• Third, downloads of data from the satellite to
  the researchers are both slow and expensive,
  therefore, constraining the amount of data
  collected
• Finally, these systems operate on batteries
  without recharge when power is drained, the
  system become unusable unless it is retrieved,
  recharged and re-deployed
• ZebraNet project is building tracking nodes that
  include a low-power miniature GPS system with
  user-programmable CPU, non-volatile storage for
  data logs, and radio transceivers for
  communicating either with other nodes or with a
  base station

83
Energy-Efficient Computing for Wildlife Tracking
Design Tradeoffs and Early Experiences with
ZebraNet Juang 2002

• Introduction
• One of the key principles of ZebraNet is that the
  system should work in arbitrary wilderness
  locations no assumptions are made about the
  presence of of fixed antenna towers or cellular
  phone service
• The system uses peer-to-peer data swaps to move
  the data around periodic researcher drives bys
  and/or fly-overs can collect logged data from
  several animals despite encountering relatively
  few within range
• Even though ad hoc sensor networks have been
  heavily studied, not much has been published
  about the characteristics of mobile sensor
  networks with mobile base stations and very few
  studies focus on building real systems

84
Energy-Efficient Computing for Wildlife Tracking
Design Tradeoffs and Early Experiences with
ZebraNet Juang 2002

• Introduction
• This paper has the following unique
  contributions
• To the best knowledge of authors, this is the
  first study of mobile sensor networks protocols
  in which the base station is also mobile. It is
  presumed that researchers will upload data while
  driving or flying by the region
• Zebra-tracking is a domain in which the node
  mobility models are unknown which makes it a
  research goal. Understanding how, when and why
  zebras undertake long-term migrations is the most
  essential biological question of this work.
• ZebraNets data collection has communication
  patterns in which data can be cooperatively
  passed towards a base station
• Energy tradeoffs are examined in detail using
  real system energy measurements for ZebraNet
  prototype hardware in operation

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Energy-Efficient Computing for Wildlife Tracking
Design Tradeoffs and Early Experiences with
ZebraNet Juang 2002

• Introduction
• Some of the interesting research questions to be
  explored are
• How to make the communications protocol both
  effective and power-efficient?
• To what extent can we rely on ad hoc,
  peer-to-peer transfers in a sparsely-connected
  spatially-huge sensor network?
• How can we provide comprehensive tracking of a
  collection of animals, even if some of the
  animals are reclusive and rarely are close enough
  to humans to have their data logs updated
  directly?
• This research work gives quantitative
  explorations of the design decisions behind some
  of these questions

86
Energy-Efficient Computing for Wildlife Tracking
Design Tradeoffs and Early Experiences with
ZebraNet Juang 2002

• ZebraNet Design Goals
• The ZebraNet project is a direct and ongoing
  collaboration between researchers in experimental
  computer systems and in wildlife biology
• The wildlife biologists have determined the
  trackers overall design goals
• GPS position samples are taken every three
  minutes
• Detailed activity logs taken for three minutes
  every hour
• One year of operation without direct human
  intervention that is, not counting on
  tranquilizing and re-collaring an animal more
  than once per year
• No fixed base stations, antennas, or cellular
  service
• A high success rate for eventually delivering all
  logged data is essential while latency is not as
  critical
• For a zebra collar, a weight limit of 3-5 lbs is
  recommended

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Energy-Efficient Computing for Wildlife Tracking
Design Tradeoffs and Early Experiences with
ZebraNet Juang 2002

• ZebraNet Design Goals
• Ultimately, this detailed information may include
  several position estimates, temperature
  information, weather data, environmental data,
  and body movements that will serve as signatures
  of behavior however, in this initial system, the
  focus is only on position data
• Overall, the key goal is to deliver to
  researchers a very high fraction of the data
  collected over the months or years that the
  system is in operation
• Therefore, ZebraNet must be power-efficient,
  designed with appropriate data log storage, and
  must be rugged to ensure reliability under tough
  environmental conditions

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Energy-Efficient Computing for Wildlife Tracking
Design Tradeoffs and Early Experiences with
ZebraNet Juang 2002

• ZebraNet Problem Statement
• The biologists design goals need to be translated
  into the engineering task at hand
• Success rate at delivering position data to the
  researchers data homing rate should approach
  100
• Weight limits on each node translate almost
  directly to computational energy limits since
  weight of the battery and solar panel takes bulk
  of the total weight of a ZebraNet node
  therefore, collar and protocol design decisions
  must manage the number and size of data
  transmissions required
• System design choices must be made that limit the
  range of transmissions since the required
  transmitter energy increases dramatically with
  the distance transmitted

89
Energy-Efficient Computing for Wildlife Tracking
Design Tradeoffs and Early Experiences with
ZebraNet Juang 2002

• ZebraNet Problem Statement
• The amount of storage needed to hold position
  logs must be limited if many redundant copies
  are stored and swapped, the storage requirements
  can scale as O(n2)
• Although the energy cost of storage is small
  compared to that of transmissions, it is still
  necessary to develop storage-efficient design
• Due to limited transceiver, coverage and a base
  station only sporadically available, ZebraNet
  must forward data through other nodes in
  peer-to-peer manner and store redundant copies of
  position logs in other tracking nodes
• Some of the key challenges in ZebraNet come from
  the spatial and temporal scale of the system

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Energy-Efficient Computing for Wildl