KALALAYATHIL NINNUM ADHIKAARATHILEKKU - EDITORIAL about the victory of Arvind kejriwal

 KALALAYATHIL NINNUM ADHIKAARATHILEKKU - EDITORIAL  about the victory of Arvind kejriwal

A MALAYALAM POEM -- SHANTHIKAVAADATHILEKKU ORU YAATHRA

A MALAYALAM POEM -- SHANTHIKAVAADATHILEKKU ORU YAATHRA

A MALAYALAM POEM -- KANALAAYI KATHUMEE PRENAYAM

A MALAYALAM POEM "KANALAAYI KATHUMEE PRENAYAM"

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Wireless sensor network -3

 Wireless sensor network -3

Operating systems

Operating systems for wireless sensor network nodes are typically less complex than general-purpose operating systems both because of the special requirements of sensor network applications and because of the resource constraints in sensor network hardware platforms. For example, sensor network applications are usually not interactive in the same way as applications for PCs. Because of this, the operating system does not need to include support for user interfaces. Furthermore, the resource constraints in terms of memory and memory mapping hardware support make mechanisms such as virtual memory either unnecessary or impossible to implement.

Wireless sensor network hardware is not different from traditional embedded systems and it is therefore possible to use embedded operating systems such as eCos or uC/OS for sensor networks. However, such operating systems are often designed with real-time properties. Unlike traditional embedded operating systems, however, operating systems specifically targeting sensor networks often do not have real-time support.

TinyOS[6] is perhaps the first[citation needed] operating system specifically designed for wireless sensor networks. Unlike most other operating systems, TinyOS is based on an event-driven programming model instead of multithreading. TinyOS programs are composed into event handlers and tasks with run to completion-semantics. When an external event occurs, such as an incoming data packet or a sensor reading, TinyOS calls the appropriate event handler to handle the event. Event handlers can post tasks that are scheduled by the TinyOS kernel some time later. Both the TinyOS system and programs written for TinyOS are written in a special programming language called nesC which is an extension to the C programming language. NesC is designed to detect race conditions between tasks and event handlers.

There are also operating systems that allow programming in C. Examples of such operating systems include Contiki,[7] MANTIS,[8] BTnut,[9] SOS[10] and Nano-RK.[11] Contiki is designed to support loading modules over the network and supports run-time loading of standard ELF files.[12] The Contiki kernel is event-driven, like TinyOS, but the system supports multithreading on a per-application basis.[13] Furthermore, Contiki includes protothreads that provide a thread-like programming abstraction but with a very small memory overhead.[14] Unlike the event-driven Contiki kernel, the MANTIS and Nano-RK kernels are based on preemptive multithreading.[15][16] With preemptive multithreading, applications do not need to explicitly yield the microprocessor to other processes. Instead, the kernel divides the time between the active processes and decides which process that currently can be run which makes application programming easier. Nano-RK is a real-time resource kernel that allows fine grained control of the way tasks get access to CPU time, networking and sensors. Like TinyOS and Contiki, SOS is an event-driven operating system.[17] The prime feature of SOS is its support for loadable modules. A complete system is built from smaller modules, possibly at run-time. To support the inherent dynamism in its module interface, SOS also focuses on support for dynamic memory management.[18] BTnut[19] is based on cooperative multi-threading and plain C code, and is packaged with a developer kit and tutorial[20]

Middleware

There is considerable research effort currently invested in the design of middleware for WSN's.[3] In general approaches can be classified into distributed database, mobile agents, and event-based.[21]

Programming languages

Programming the sensor nodes is difficult when compared to normal computer systems. The resource constrained nature of these nodes gives rise to new programming models. Although most nodes are currently programmed in C.

c@t (Computation at a point in space (@) Time)

DCL (Distributed Compositional Language)

galsC

nesC

Protothreads

SNACK

SQTL

Java "Sentilla". Sun SPOT

Algorithms      This article does not cite any references or sources.

Please help improve this article by adding citations to reliable sources. Unverifiable material may be challenged and removed. (August 2006)

WSNs are composed of a large number of sensor nodes, therefore, an algorithm for a WSN is implicitly a distributed algorithm. In WSNs the scarcest resource is energy, and one of the most energy-expensive operations is data transmission. For this reason, algorithmic research in WSN mostly focuses on the study and design of energy aware algorithms for data transmission from the sensor nodes to the base stations. Data transmission is usually multi-hop (from node to node, towards the base stations), due to the polynomial growth in the energy-cost of radio transmission with respect to the transmission distance.

The algorithmic approach to WSN differentiates itself from the protocol approach by the fact that the mathematical models used are more abstract, more general, but sometimes less realistic than the models used for protocol design.

Simulators

There are platforms specifically designed to simulate Wireless Sensor Networks, like TOSSIM, which is a part of TinyOS. Traditional network simulators like ns-2 have also been used. A platform independent component based simulator with wireless sensor network framework,J-Sim(www.j-sim.org) can also be used. An extensive list of simulation tools for Wireless Sensor Networks can be found at the CRUISE WSN Simulation Tool Knowledgebase

Data visualization

The data gathered from wireless sensor networks is usually saved in the form of numerical data in a central base station. There are many programs, like Octopus[2], SpyGlass[3], TosGUI, SenSor and MonSense,GSN that facilitate the viewing of these large amounts of data. Additionally, the Open Geospatial Consortium (OGC) is specifying standards for interoperability interfaces and metadata encodings that enable real time integration of heterogeneous sensor webs into the Internet, allowing any individual to monitor or control Wireless Sensor Networks through a Web Browser.