Editing Wireless sensor network (section)

===Software===
Energy is the scarcest resource of WSN nodes, and it determines the lifetime of WSNs. WSNs may be deployed in large numbers in various environments, including remote and hostile regions, where ad hoc communications are a key component. For this reason, algorithms and protocols need to address the following issues:

* Increased lifespan<ref>{{Cite book |last1=Janakiram |first1=Kottnana |last2=Reginald |first2=P. Joshua |title=2023 7th International Conference on Computing Methodologies and Communication (ICCMC) |chapter=Extending the Lifespan of Wireless Sensor Networks using Graph Theory Approaches |date=2023-02-23 |chapter-url=https://ieeexplore.ieee.org/document/10084135 |location=Erode, India |publisher=IEEE |pages=993–997 |doi=10.1109/ICCMC56507.2023.10084135 |isbn=978-1-6654-6408-6|s2cid=257959382 }}</ref>
* Robustness and fault tolerance<ref>{{Cite journal |last1=Lyakhov |first1=P. A. |last2=Kalita |first2=D. I. |date=2023-05-03 |title=Reliable Kalman Filtering with Conditionally Local Calculations in Wireless Sensor Networks |url=https://link.springer.com/10.3103/S0146411623020062 |journal=Automatic Control and Computer Sciences |language=en |volume=57 |issue=2 |pages=154–166 |doi=10.3103/S0146411623020062 |s2cid=258465232 |issn=0146-4116}}</ref>
* Self-configuration<ref>{{Cite book |last1=Shi |first1=Junyang |last2=Sha |first2=Mo |title=IEEE INFOCOM 2019 - IEEE Conference on Computer Communications |chapter=Parameter Self-Configuration and Self-Adaptation in Industrial Wireless Sensor-Actuator Networks |date=2019-06-17 |chapter-url=https://ieeexplore.ieee.org/document/8737467 |location=Paris, France |publisher=IEEE |pages=658–666 |doi=10.1109/INFOCOM.2019.8737467 |isbn=978-1-7281-0515-4|s2cid=86721016 }}</ref>

Lifetime maximization: Energy/Power Consumption of the sensing device should be minimized and sensor nodes should be energy efficient since their limited energy resource determines their lifetime. To conserve power, wireless sensor nodes normally power off both the radio transmitter and the radio receiver when not in use.<ref name=Zander/>

====Routing protocols====
Wireless sensor networks are composed of low-energy, small-size, and low-range unattended sensor nodes. Recently, it has been observed that by periodically turning on and off the sensing and communication capabilities of sensor nodes, we can significantly reduce the active time and thus prolong network lifetime.<ref>{{cite book|first1=A.|last1=Xenakis|first2=F.|last2=Foukalas|first3=G.|last3=Stamoulis|title=Proceedings of the 19th Panhellenic Conference on Informatics |chapter=Minimum weighted clustering algorithm for wireless sensor networks |doi=10.1145/2801948.2801999|date=October 2015|pages=255–260|isbn=978-1-4503-3551-5|s2cid=9188571}}</ref><ref>{{cite book|first1=T. A. H.|last1=Hassan|first2=G.|last2=Selim|first3=R.|last3=Sadek |publisher=IEEE |title=2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS) |chapter=A novel energy efficient vice Cluster Head routing protocol in Wireless Sensor Networks |location=Cairo|year=2015|pages=313–320|doi=10.1109/IntelCIS.2015.7397240|isbn=978-1-5090-1949-6|s2cid=10688614}}</ref> However, this duty cycling may result in high network latency, routing overhead, and neighbor discovery delays due to asynchronous sleep and wake-up scheduling. These limitations call for a countermeasure for duty-cycled wireless sensor networks which should minimize routing information, routing traffic load, and energy consumption. Researchers from Sungkyunkwan University have proposed a lightweight non-increasing delivery-latency interval routing referred as LNDIR. This scheme can discover minimum latency routes at each non-increasing delivery-latency interval instead of each time slot.{{clarify|date=September 2020}} Simulation experiments demonstrated the validity of this novel approach in minimizing routing information stored at each sensor. Furthermore, this novel routing can also guarantee the minimum delivery latency from each source to the sink. Performance improvements of up to 12-fold and 11-fold are observed in terms of routing traffic load reduction and energy efficiency, respectively, as compared to existing schemes.<ref name="LNDIR">{{cite journal |last1=K Shahzad |first1=Muhammad |last2=Nguyen |first2=Dang Tu |last3=Zalyubovskiy |first3=Vyacheslav |last4=Choo |first4=Hyunseung |date=2018 |title=LNDIR: A lightweight non-increasing delivery-latency interval-based routing for duty-cycled sensor networks |journal= International Journal of Distributed Sensor Networks |volume=14 |issue=4 |page=1550147718767605 |doi=10.1177/1550147718767605|doi-access=free }} [[File:CC-BY icon.svg|50px]] Material was copied from this source, which is available under a [https://creativecommons.org/licenses/by/4.0/ Creative Commons Attribution 4.0 International License].</ref>

====Operating systems====
[[Operating system]]s for wireless sensor network nodes are typically less complex than general-purpose operating systems. They more strongly resemble [[embedded system]]s, for two reasons. First, wireless sensor networks are typically deployed with a particular application in mind, rather than as a general platform. Second, a need for low costs and low power leads most wireless sensor nodes to have low-power microcontrollers ensuring that mechanisms such as virtual memory are either unnecessary or too expensive to implement.

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.

[[TinyOS]], developed by [[David Culler]], is perhaps the first operating system specifically designed for wireless sensor networks. TinyOS is based on an [[event-driven programming]] model instead of [[Thread (computer science)|multithreading]]. TinyOS programs are composed of ''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 signals the appropriate event handler to handle the event. Event handlers can post tasks that are scheduled by the TinyOS kernel some time later.

[[LiteOS]] is a newly developed OS for wireless sensor networks, which provides UNIX-like abstraction and support for the C programming language.

[[Contiki]], developed by [[Adam Dunkels]], is an OS which uses a simpler programming style in C while providing advances such as [[6LoWPAN]] and [[Protothreads]].

[[RIOT (operating system)]] is a more recent real-time OS including similar functionality to Contiki.

PreonVM<ref>{{cite web|url=https://www.virtenio.com/en/preonvm-virtual-maschine.html|title=PreonVM – Virtual maschine for wireless sensor devices|archive-url=https://web.archive.org/web/20171111094628/https://www.virtenio.com/en/preonvm-virtual-maschine.html|archive-date=2017-11-11 }}</ref> is an OS for wireless sensor networks, which provides [[6LoWPAN]] based on [[Contiki]] and support for the [[Java (programming language)|Java]] programming language.