Mobile wireless sensor network

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Mobile wireless sensor networks (MWSNs) can simply be defined as a wireless sensor network (WSN) in which the sensor nodes are mobile. MWSNs are a smaller, emerging field of research in contrast to their well-established predecessor. MWSNs are much more versatile than static sensor networks as they can be deployed in any scenario and cope with rapid topology changes. However, many of their applications are similar, such as environment monitoring or surveillance Commonly the nodes consist of a radio transceiver and a microcontroller powered by a battery. As well as some kind of sensor for detecting light, heat, humidity, temperature, etc.


Broadly speaking there are two sets of challenges in MWSNs; hardware and environment. The main hardware constraints are limited battery power and low cost requirements. The limited power means that it's important for the nodes to be energy efficient. Price limitations often demand low complexity algorithms for simpler microcontrollers and use of only a simplex radio. The major environmental factors are the shared medium and varying topology. The shared medium dictates that channel access must be regulated in some way. This is often done using a medium access control (MAC) scheme, such as carrier sense multiple access (CSMA), frequency division multiple access (FDMA) or code division multiple access (CDMA). The varying topology of the network comes from the mobility of nodes, which means that multihop paths from the sensors to the sink are not stable.


Currently there is no standard for MWSNs, so often protocols from MANETs are borrowed, such as Ad hoc On-Demand Distance Vector Routing (AODV), Dynamic Source Routing (DSR) and Greedy Perimeter Stateless Routing (GPSR).[1] MANET protocols are preferred as they are able to work in mobile environments, whereas WSN protocols often aren't suitable.


Since there is no fixed topology in these networks, one of the greatest challenges is routing data from its source to the destination. Generally these routing protocols draw inspiration from two fields; WSNs and mobile ad hoc networks (MANETs). WSN routing protocols provide the required functionality but cannot handle the high frequency of topology changes. Whereas, MANET routing protocols are can deal with mobility in the network but they are designed for two way communication, which in sensor networks is often not required.[2]

Protocols designed specifically for MWSNs are almost always multihop and sometimes adaptations of existing protocols. For example, Angle-based Dynamic Source Routing (ADSR),[3] is an adaptation of the wireless mesh network protocol Dynamic Source Routing (DSR) for MWSNs. ADSR uses location information to work out the angle between the node intending to transmit, potential forwarding nodes and the sink. This is then used to insure that packets are always forwarded towards the sink. Also, Low Energy Adaptive Clustering Hierarchy (LEACH) protocol for WSNs has been adapted to LEACH-M (LEACH-Mobile),[4] for MWSNs. The main issue with hierarchical protocols is that mobile nodes are prone to frequently switching between clusters, which can cause large amounts of overhead from the nodes having to regularly re-associate themselves with different cluster heads.

Another popular routing technique is to utilise location information from a GPS module attached to the nodes. This can be seen in protocols such as Zone Based Routing (ZBR),[5] which defines clusters geographically and uses the location information to keep nodes updated with the cluster they're in. In comparison, Geographically Opportunistic Routing (GOR),[6] is a flat protocol that divides the network area into grids and then uses the location information to opportunistically forward data as far as possible in each hop.

Multipath protocols provide a robust mechanism for routing and therefore seem like a promising direction for MWSN routing protocols. One such protocol is the query based Data Centric Braided Multipath (DCBM).[7]


Protocols designed for MWSNs are usually validated with the use of either analytical, simulation or experimental results. Detailed analytical results are mathematical in nature and can provide good approximations of protocol behaviour. Simulations can be performed using software such as OPNET, NetSim and NS2 and is the most common method of validation. Simulations can provide close approximations to the real behaviour of a protocol under various scenarios. Physical experiments are the most expensive to perform and, unlike the other two methods, no assumptions need to be made. This makes them the most reliable form of information, when determining how a protocol will perform under certain conditions.


The advantage of allowing the sensors to be mobile increases the number of applications beyond those for which static WSNs are used. Sensors can be attached to people for health monitoring, which may include heart rate, blood pressure etc.[8] Animals can have sensors attached to them in order to track their movements for migration patterns, feeding habits or other research purposes.[9] Sensors may also be attached to unmanned aerial vehicles (UAVs) for surveillance or environment mapping.[10]


  1. ^ B. Karp and H. T. Kung. 2000. GPSR: Greedy Perimeter Stateless Routing for Wireless Networks. In Proceedings of the 6th Annual International Conference on Mobile Computing and Networking (MobiCom '00). pp.243-254.
  2. ^ T.P. Lambrou and C.G. Panayiotou. 2009. A Survey on Routing Techniques Supporting Mobility in Sensor Networks. In Proceedings of the 5th international conference on Mobile Ad Hoc and Sensor Networks (MSN'09). pp.78-85.
  3. ^ S. Kwangcheol, K. Kim and S. Kim. 2011. ADSR: Angle-Based Multi-hop Routing Strategy for Mobile Wireless Sensor Networks. In proceedings of the IEEE Asia-Pacific Services Computing Conference (APSCC). pp.373-376.
  4. ^ D. Kim and Y. Chung. 2006. Self-Organization Routing Protocol Supporting Mobile Nodes for Wireless Sensor Network. In proceedings of the 1st international multi-symposiums on Computer and Computational Sciences (IMSCCS’06). pp.622-626.
  5. ^ U. Ahmed and F.B. Hussain. 2011. Energy efficient routing protocol for zone based mobile sensor networks. In proceedings of the 7th international Wireless Communications and Mobile Computing conference (IWCMC). pp.1081-1086.
  6. ^ Y. Han and Z. Lin. 2012. A geographically opportunistic routing protocol used in mobile wireless sensor networks. In proceedings of the 9th IEEE international conference on Networking, Sensing and Control (ICNSC). pp.216-221.
  7. ^ A. Aronsky and A. Segall. 2010. A multipath routing algorithm for mobile Wireless Sensor Networks. In proceedings of the 3rd Joint IFIP Wireless and Mobile Networking Conference. pp.1-6.
  8. ^ H. Yan, H. Huo, Y. Xu and M. Gidlund. 2010. Wireless Sensor Network Based E-Health System – Implementation and Experimental Results. IEEE Transactions on Consumer Electronics, vol. 56, no. 4, pp. 2288-2295.
  9. ^ S. Ehsan et al. 2012. Design and Analysis of Delay-Tolerant Sensor Networks for Monitoring and Tracking Free-Roaming Animals. IEEE Transactions on Wireless Communications, vol. 11, no. 3, pp. 1220-1227.
  10. ^ B. White et al. 2008. Contaminant Cloud Boundary Monitoring Using Network of UAV Sensors. IEEE Sensors Journal, vol. 8, no. 10, pp. 1681-1692.