Sensor Network

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Sensor Network and its middlewares design principles and examples

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  • Grape Networks has deployed the world's largest wireless Sensor network for agriculture in the Central Valley of California. The Wireless Sensor Network covers over 50 acres, and consists of more than 200 sensors, all broadcasting critical vineyard data over the Internet.Sensed data: temperature, humidity and lightThe vineyard operations' manager can view the data on any WEB enabled cellular phone or PC, and can also set the threshold values for alerts over the Internet or via Email. 
  • Electronic sensor clothing like this Under Armour E39 Shirt lets the athlete understand what is going on inside there body while training. This Under Armour Electronic sensor clothing contains a removable sensor pack, nicknamed 'the bug' near the sternum which provides instant feedback on breathing rate, heart rate, temperature, movements etc. All this data can then ne viewed on wireless devices such as laptops, iPhones, or iPads. 
  • Processing unitAssociated with a small storage unitManages the procedures that make the sensor node collaborate with the other nodes to carry out the assigned sensing tasks
  • additional application dependent components: mobilizer, location finding system (most of the sensing tasks require the knowledge of position), Power Generator(solar cell) …
  • WSN needs middleware to integrate the sensed data from different sensor network and provide for user application. Esp., to convert various raw data from sensor networks to available information for service of user application.
  • *Limited power and resources - Advance microelectronics technology allows tiny devices but limited in energy and resources, i.e. CPU and memory*Scalability, mobility, and dynamic network topology –As the application grows, device failure, moving obstacles, mobility, and interference, the network will change frequently.Scalability is defined as follows: if an application grows, the network should be flexible enough toallow this growth anywhere and anytime without affecting network performance. Efficientmiddleware services must be capable of maintaining acceptable performance levels as the networkgrows. Network topology is subject to frequent changes owing to factors such as malfunctioning,device failure, moving obstacles, mobility, and interference. Middleware should support sensornetworks' robust operation despite these dynamics by adapting to the changing network environment.Middleware also should support mechanisms for fault tolerance and sensor node self-configurationand self-maintenance.* Heterogeneity - provide low-level programming models to meet the major challenge of bridgingthe gap between hardware technology's raw potential and the necessary broad activities such asreconfiguration, execution, and communication. It should establish system mechanisms that interfaceto the various types of hardware and networks, supported only by distributed, primitive operatingsystemabstractions.
  • *Dynamic network organization : Unlike traditional networks, sensor networks must deal with resources that are dynamic, such asenergy, bandwidth, and processing power. Sensor networks also must support long-running applications, so routing protocols must be efficiently designed to enable the network to run as long as Possible. Because knowledge of the network is essential for it to operate properly, the middleware should provide ad hoc network resource discovery. A sensor node needs to know its location in thenetwork and in the whole network topology. In some cases, self-location by GPS is impossible,unfeasible, or expensive. Important system parameter issues, such as network size and density persquare mile, affect the trade-offs among latency, reliability, and energy.* Real-time integration : Most sensor network applications are real-time phenomena, where time and space are extremelyimportant. Hence, middleware should provide real-time services to adapt to the changes and provideconsistent data.*Data aggregation: Most sensor network applications involve nodes that contain redundant data and are located in aspecific local region. These traits open the possibility for in-network aggregation of data fromdifferent sources, eliminating redundancy and minimizing the number of transmissions to the sink.This aggregation saves considerable energy and resources, given that communications cost is muchhigher than computation costs. This paradigm shifts the focus from the traditional address-centricapproaches for networking to a more data-centric approach*Security: WSNs are being widely deployed in domains that involve sensitive information for example,healthcare and rescue. The untethered and large deployment of WSNs in harsh environments increasestheir exposure to malicious intrusions and attacks such as denial of service. 11In addition, the wireless medium facilitates eavesdropping and adversarial packet injection to compromise the network'sfunctioning. All these factors make security extremely important. Furthermore, sensor nodes havelimited power and processing resources, so standard security mechanisms, which are heavy in weightand resource consumption, are unsuitable. These challenges increase the need to developcomprehensive and secure solutions that achieve wider protection, while maintaining desirablenetwork performance. Middleware efforts should concentrate on developing and integrating securityin the initial phases of software design, hence achieving different security requirements such asconfidentiality, authentication, integrity, freshness, and availability.
  • Communication model (not mentioned here)* Programming abtrstraction : providing systems, services, and runtime mechanisms such as reliable code distribution, safe code execution, and application-specific services. * Programming support: the way we view a sensor network and provides concepts and abstractions of sensor nodes and sensor data.
  • * Programming abtrstraction : providing systems, services, and runtime mechanisms such as reliable code distribution, safe code execution, and application-specific services. * Programming support: the way we view a sensor network and provides concepts and abstractions of sensor nodes and sensor data.
  • This subclass introduces a new and completely different view on how to program sensor networks. Macroprogramming involves programming thesensor network as a whole, rather than writing low-level software to drive individual nodes. The WSN global behavior is programmed at a high-level specification, enabling automatically generated nodal behaviors. This relieves application developers from dealing with low-level concerns at each network node.
  • In most sensor network applications, the focus is more on the nature of the sensed data, which generally involves a group of sensor nodes in a specified region. In region or Hood style, the interest is on a specific location in a sensor network for example, applications are morelikely to ask for a location where the temperature exceeds a certain value, rather than for an individual sensor reading. In data-centric sensor networks, nodes are addressed according to the data produced for example, detect a target having a shape of "tank" in military applications.
  • This system is flexible and contains virtual machines (VMs), interpreters, andmobile agents. It lets developers write applications in separate, small modules. The system injects anddistributes the modules through the network using tailored algorithms, such as overall energyconsumption and resource use are minimized. The VM then interprets the modules. This approach,however, suffers from the overhead that the instructions introduce
  • It provides an easy-to-use interface that lets the user issue queries to the sensor network to extract the data of interest. However, the approach provides only approximate results, and it lacks the support of realtime applications that need the detection of spatio-temporal relationships between events
  • The key to this approach is that applications are as modular as possible to facilitate their injection and distribution through the network using mobile code. Transmitting small modules consumes considerably less energy than a whole application. For example, Impala provides mechanisms for network updates that are efficient enough to support dynamic applications. Its autonomic behavior increases its fault tolerance and network selforganization. However, the nature of its code instruction doesn't allow hardware heterogeneity, whichmakes it unsuitable for devices with limited resources
  • Mainly a communication model in a distributed-sensor network, message-oriented middleware uses the publish-subscribe mechanism to facilitate message exchange between nodes and the sink nodes. The strength of this paradigm lies in that it supports asynchronous communication very naturally, allowing a loose coupling between the sender and the receiver. This approach is quite suitable in pervasive environments such as wireless sensor networks, where most applications are based on events.Mire - Communication occurs in three phases. First, the nodes in the network advertise their sensed data (topic) through the publish service. Next, Mires routes the advertised messages to the sink, using the multi-hop routing algorithm. Finally, the user application subscribes to topics of interest using only a suitable GUI. The publish-subscribe service also maintains the topics list and the subscribed application to marshal the right topic to the related application. Mires sends only messages referring to subscribed topics, hence reducing the number of transmissions andenergy consumption. It includes a data aggregation service that lets the user specify how data will beaggregated and the association between topics of interest and aggregates.
  • Sensor Network

    1. 1. SOK PhearinDepartment of Computer Science MBC Lab., Konkuk University
    2. 2. OutlineI. Introduction to Wireless Sensor Network 1) What is Wireless Sensor Network and its applications 2) Communication Architectures 3) Sensor Node Basic ComponentsII. Introduction to Middleware 1) What is Middleware 2) Middleware Design Principles for Wireless Sensor Networks 3) Middleware Approaches
    3. 3. What is Wireless Sensor Network Wireless Sensor Network consists of spatially distributed autonomous sensor nodes used to monitor and control physical or environmental conditions at different locations cooperatively.
    4. 4. Wireless Sensor Network Applications Intelligent agricultural and environmental sensing Grapes Networks - Central Valley of California
    5. 5. Wireless Sensor Network Applications Health monitoring Home automation and consumer electronics Security and military sensing Structural monitoring…
    6. 6. Communication Architectures Sensor Node: senses data or events, and collect the data among the nodes via radio link and route to the sink using multi hop infrastructure architecture Sensor Field: scope or area within sensor nodes can detect or collect the sensed data Sink: communicates with the End Users via Internet or any network (WAN) connection
    7. 7. Sensor Node Basic Components The basic components of a sensor node  sensing unit o Sensor: produce analog signal based on the sensed environment o Analog to Digital Converter (ADC): convert from analog to digital signal and transfer to processing unit  processing unit: manages the procedures for sensing tasks and collaborations  transceiver unit: connects the node to network (RF radio communication is preferred)  power unit
    8. 8. Sensor Node Basic Components
    9. 9. What is Middleware Software layer between the operating system and applications to manage the complexity and heterogeneity in the distributed system or network. Why middleware in wireless sensor networks?  a software infrastructure that glues together the network hardware, operating systems, network stacks, and applications
    10. 10. Middleware Design Principles Limited power and resources  Provide efficient CPU and memory Ex. sleep mode, minimize number of transmission Scalability, mobility, and dynamic network topology  adapt to the changing network environment, fault tolerance and sensor node self-configuration and self-maintenance Heterogeneity  able to interface various kinds of hardware, software and networks
    11. 11. Middleware Design Principles Dynamic network organization  provide ad hoc network resource discovery and its location Real-world integration  provide real-time services to adapt to the changes and provide consistent data Data aggregation  able to aggregate data to eliminate redundancy and minimize the number of transmissions to the sink Security  able to develop and integrate security in the initial phases of software design to achieve different security requirements such as authentication, integrity, freshness, and availability
    12. 12. Middleware Approaches Based on the Programming models Global behavior (macroprogramming) Programming Abstraction Local behavior (data centric, geometric) Programming Virtual machine Wireless Sensor Networks Database Programming Modular (agents) Support Message-oriented middleware
    13. 13. Middleware Approaches Programming abstraction : provides systems, services, and runtime mechanisms Programming support: provides concepts and abstractions of sensor nodes and sensor data
    14. 14. Middleware Approaches Global behavior (macroprogramming) Programming Abstraction Local behavior (data centric, geometric)Programming Virtual machineWireless Sensor Networks Database Programming Modular (agents) Support Message-oriented middleware
    15. 15. Global behavior the sensor network as a whole, not to drive individual node high-level specification Example: Kairos  provides notions and concepts to design, develop, and implement a macroprogramming model on WSN  express a single centralized program
    16. 16. Middleware Approaches Global behavior (macroprogramming) Programming Abstraction Local behavior (data centric, geometric)Programming Virtual machineWireless Sensor Networks Database Programming Modular (agents) Support Message-oriented middleware
    17. 17. Local behavior the nature of the sensed data a group of sensor nodes in a specified region Example: Abstract regions  local computation, data aggregation, and communication occur  aggregate all sensor readings from nodes near the object to generate accurate information locally
    18. 18. Middleware Approaches Global behavior (macroprogramming) Programming Abstraction Local behavior (data centric, geometric)Programming Virtual machineWireless Sensor Networks Database Programming Modular (agents) Support Message-oriented middleware
    19. 19. Virtual Machine Approach lets developers write applications in separate, small modules system injects and distributes the modules through the network using tailored algorithms VM then interprets the modules Example: Mate  uses codes broken into capsules of 24 byte-long instructions, easy for distribution.  synchronous model, makes the programming simpler  avoids message buffering and large storage
    20. 20. Middleware Approaches Global behavior (macroprogramming) Programming Abstraction Local behavior (data centric, geometric)Programming Virtual machineWireless Sensor Networks Database Programming Modular (agents) Support Message-oriented middleware
    21. 21. Database Approach views the whole network as a virtual database system lets the user issue queries to the sensor network Example: Cougar  Represents all sensors and sensor data in a relational database.  Control of sensors and extracting data occurs through special SQL-like queries  Allows the scheduling of ongoing queries that provide incremental results
    22. 22. Middleware Approaches Global behavior (macroprogramming) Programming Abstraction Local behavior (data centric, geometric)Programming Virtual machineWireless Sensor Networks Database Programming Modular (agents) Support Message-oriented middleware
    23. 23. Modular Approach applications are as modular as possible Only parts of the program need to be updated, propagate efficiently Example: Impala  provides mechanisms for network updates and support dynamic applications  fault tolerance and network self organization  nature of its code instruction doesnt allow hardware heterogeneity
    24. 24. Middleware Approaches Global behavior (macroprogramming) Programming Abstraction Local behavior (data centric, geometric)Programming Virtual machineWireless Sensor Networks Database Programming Modular (agents) Support Message-oriented middleware
    25. 25. Message Oriented Approach uses the publish-subscribe mechanism supports asynchronous communication – loose coupling Example: Mires  advertise their sensed data(topic) through publish service  Multi-hop routes the advertised messages to the sink  user application subscribes to topics of interest
    26. 26. Reference [1] Salem Hadim & Nader Mohamed, “Middleware: Middleware Challenges and Approaches for Wireless Sensor Networks”, IEEE 01621014, Vol. 7, No. 3; March 2006 [2] Jong-Wan Yoon, Young-Ki Ku, Choon-Sung Nam, & Dong-Ryeol Shin, “Sensor Network Middleware for Distributed and Heterogeneous Environment”, 2009, IEEE 05260722,
    27. 27. Thank You

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