Mobile wireless sensor network

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A mobile wireless sensor network (MWSN) [1] 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.

Contents

Challenges

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.

Standards

Currently there is no standard for MWSNs, so often protocols from MANETs are borrowed, such as Associativity-Based Routing (AR), Ad hoc On-Demand Distance Vector Routing (AODV), Dynamic Source Routing (DSR) and Greedy Perimeter Stateless Routing (GPSR). [2] MANET protocols are preferred as they are able to work in mobile environments, whereas WSN protocols often aren't suitable.

Topology

Topology selection plays an important role in routing because the network topology decides the transmission path of the data packets to reach the proper destination. Here, all the topologies (Flat / Unstructured, cluster, tree, chain and hybrid topology) are not feasible for reliable data transmission on sensor nodes mobility. Instead of single topology, hybrid topology plays a vital role in data collection, and the performance is good. Hybrid topology management schemes include the Cluster Independent Data Collection Tree (CIDT). [3] and the Velocity Energy-efficient and Link-aware Cluster-Tree (VELCT); [4] both have been proposed for mobile wireless sensor networks (MWSNs).

Routing

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 can deal with mobility in the network but they are designed for two way communication, which in sensor networks is often not required. [5]

Protocols designed specifically for MWSNs are almost always multihop and sometimes adaptations of existing protocols. For example, Angle-based Dynamic Source Routing (ADSR), [6] 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), [7] 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), [8] 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), [9] 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). [10]

Furthermore, Robust Ad-hoc Sensor Routing (RASeR) [11] and Location Aware Sensor Routing (LASeR) [12] are two protocols that are designed specifically for high speed MWSN applications, such as those that incorporate UAVs. They both take advantage of multipath routing, which is facilitated by a 'blind forwarding' technique. Blind forwarding simply allows the transmitting node to broadcast a packet to its neighbors, it is then the responsibility of the receiving nodes to decide whether they should forward the packet or drop it. The decision of whether to forward a packet or not is made using a network-wide gradient metric, such that the values of the transmitting and receiving nodes are compared to determine which is closer to the sink. The key difference between RASeR and LASeR is in the way they maintain their gradient metrics; RASeR uses the regular transmission of small beacon packets, in which nodes broadcast their current gradient. Whereas, LASeR relies on taking advantage of geographical location information that is already present on the mobile sensor node, which is likely the case in many applications.

Medium access control

There are three types of medium access control (MAC) techniques: based on time division, frequency division and code division. Due to the relative ease of implementation, the most common choice of MAC is time-division-based, closely related to the popular CSMA/CA MAC. The vast majority of MAC protocols that have been designed with MWSNs in mind, are adapted from existing WSN MACs and focus on low power consumption, duty-cycled schemes.

Validation

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.

Applications

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 a number of platforms:

In order to characterise the requirements of an application, it can be categorised as either constant monitoring, event monitoring, constant mapping or event mapping. [1] Constant type applications are time-based and as such data is generated periodically, whereas event type applications are event drive and so data is only generated when an event occurs. The monitoring applications are constantly running over a period of time, whereas mapping applications are usually deployed once in order to assess the current state of a phenomenon. Examples of applications include health monitoring, which may include heart rate, blood pressure etc. [13] This can be constant, in the case of a patient in a hospital, or event driven in the case of a wearable sensor that automatically reports your location to an ambulance team in the case of an emergency. Animals can have sensors attached to them in order to track their movements for migration patterns, feeding habits or other research purposes. [14] Sensors may also be attached to unmanned aerial vehicles (UAVs) for surveillance or environment mapping. [15] In the case of autonomous UAV aided search and rescue, this would be considered an event mapping application, since the UAVs are deployed to search an area but will only transmit data back when a person has been found.

See also

Related Research Articles

Zigbee is an IEEE 802.15.4-based specification for a suite of high-level communication protocols used to create personal area networks with small, low-power digital radios, such as for home automation, medical device data collection, and other low-power low-bandwidth needs, designed for small scale projects which need wireless connection. Hence, Zigbee is a low-power, low data rate, and close proximity wireless ad hoc network.

Wireless mesh network Radio nodes organized in a mesh topology

A wireless mesh network (WMN) is a communications network made up of radio nodes organized in a mesh topology. It can also be a form of wireless ad hoc network.

Optimized Link State Routing Protocol IP routing protocol optimized for mobile ad hoc networks

The Optimized Link State Routing Protocol (OLSR) is an IP routing protocol optimized for mobile ad hoc networks, which can also be used on other wireless ad hoc networks. OLSR is a proactive link-state routing protocol, which uses hello and topology control (TC) messages to discover and then disseminate link state information throughout the mobile ad hoc network. Individual nodes use this topology information to compute next hop destinations for all nodes in the network using shortest hop forwarding paths.

Wireless sensor networks (WSNs) refer to networks of spatially dispersed and dedicated sensors that monitor and record the physical conditions of the environment and forward the collected data to a central location. WSNs can measure environmental conditions such as temperature, sound, pollution levels, humidity and wind.

In computer network research, network simulation is a technique whereby a software program replicates the behavior of a real network. This is achieved by calculating the interactions between the different network entities such as routers, switches, nodes, access points, links, etc. Most simulators use discrete event simulation in which the modeling of systems in which state variables change at discrete points in time. The behavior of the network and the various applications and services it supports can then be observed in a test lab; various attributes of the environment can also be modified in a controlled manner to assess how the network/protocols would behave under different conditions.

Delay-tolerant networking (DTN) is an approach to computer network architecture that seeks to address the technical issues in heterogeneous networks that may lack continuous network connectivity. Examples of such networks are those operating in mobile or extreme terrestrial environments, or planned networks in space.

Vehicular ad hoc networks (VANETs) are created by applying the principles of mobile ad hoc networks (MANETs) – the spontaneous creation of a wireless network of mobile devices – to the domain of vehicles. VANETs were first mentioned and introduced in 2001 under "car-to-car ad-hoc mobile communication and networking" applications, where networks can be formed and information can be relayed among cars. It was shown that vehicle-to-vehicle and vehicle-to-roadside communications architectures will co-exist in VANETs to provide road safety, navigation, and other roadside services. VANETs are a key part of the intelligent transportation systems (ITS) framework. Sometimes, VANETs are referred as Intelligent Transportation Networks. They are understood as having evolved into a broader "Internet of vehicles". which itself is expected to ultimately evolve into an "Internet of autonomous vehicles".

A wireless ad hoc network (WANET) or mobile ad hoc network (MANET) is a decentralized type of wireless network. The network is ad hoc because it does not rely on a pre-existing infrastructure, such as routers in wired networks or access points in wireless networks. Instead, each node participates in routing by forwarding data for other nodes, so the determination of which nodes forward data is made dynamically on the basis of network connectivity and the routing algorithm in use.

Geographic routing is a routing principle that relies on geographic position information. It is mainly proposed for wireless networks and based on the idea that the source sends a message to the geographic location of the destination instead of using the network address. In the area of packet radio networks, the idea of using position information for routing was first proposed in the 1980s for interconnection networks. Geographic routing requires that each node can determine its own location and that the source is aware of the location of the destination. With this information, a message can be routed to the destination without knowledge of the network topology or a prior route discovery.

Sensor node

A sensor node, also known as a mote, is a node in a sensor network that is capable of performing some processing, gathering sensory information and communicating with other connected nodes in the network. A mote is a node but a node is not always a mote.

In multi-hop networks, Adaptive Quality of Service routing protocols have become increasingly popular and have numerous applications. One application in which it may be useful is in Mobile ad hoc networking (MANET).

Multipath routing is a routing technique simultaneously using multiple alternative paths through a network. This can yield a variety of benefits such as fault tolerance, increased bandwidth, and improved security.

Topology control is a technique used in distributed computing to alter the underlying network to reduce the cost of distributed algorithms if run over the resulting graphs. It is a basic technique in distributed algorithms. For instance, a (minimum) spanning tree is used as a backbone to reduce the cost of broadcast from O(m) to O(n), where m and n are the number of edges and vertices in the graph, respectively.

OCARI

OCARI is a low-rate wireless personal area networks (LR-WPAN) communication protocol that derives from the IEEE 802.15.4 standard. It was developed by the following consortium during the OCARI project that is funded by the French National Research Agency (ANR):

Scalable Source Routing (SSR) is a routing protocol for unstructured networks such as mobile ad hoc networks, mesh networks, or sensor networks. It combines source routing with routing along a virtual ring, and is based on the idea of "pushing Chord into the underlay".

IEEE 802.11s is a wireless local area network (WLAN) standard and an IEEE 802.11 amendment for mesh networking, defining how wireless devices can interconnect to create a wireless LAN mesh network, which may be used for relatively fixed topologies and wireless ad hoc networks. The IEEE 802.11s task group drew upon volunteers from university and industry to provide specifications and possible design solutions for wireless mesh networking. As a standard, the document was iterated and revised many times prior to finalization.

Ramesh Govindan is an Indian-American professor of computer science. He is the Northrop Grumman Chair in Engineering and Professor of Computer Science and Electrical Engineering at the University of Southern California.

Associativity-based routing is a mobile routing protocol invented for wireless ad hoc networks, also known as mobile ad hoc networks (MANETs) and wireless mesh networks. ABR was invented in 1993, filed for a U.S. patent in 1996, and granted the patent in 1999. ABR was invented by Chai Keong Toh while doing his Ph.D. at Cambridge University.

Atta ur Rehman Khan

Atta ur Rehman Khan is a computer scientist and academician who has contributed to multiple domains of the field. According to a Stanford University report, he is among World's Top 2% Scientists. He is the founder of National Cyber Crime Forensics Lab Pakistan. The Cyber Crime Forensics Lab operates in partnership with NR3C. He has published numerous research articles and books. He is a Senior Member of IEEE (SMIEEE) and ACM (SMACM).

References

  1. 1 2 T. Hayes and F.H. Ali. 2016. "Mobile Wireless Sensor Networks: Applications and Routing Protocols". Handbook of Research on Next Generation Mobile Communications Systems. IGI Global. ISBN   9781466687325. pp. 256–292.
  2. ↑ B. Karp and H. T. Kung. 2000. GPSR: Greedy Perimeter Stateless Routing for Wireless Networks [ dead link ]. In Proceedings of the 6th Annual International Conference on Mobile Computing and Networking (MobiCom '00). pp. 243–254.
  3. ↑ R. Velmani, and B. Kaarthick, 2014. An Energy Efficient Data Gathering in Dense Mobile Wireless Sensor Networks,” ISRN Sensor Networks, vol. 2014, Article ID 518268, 10 pages. doi:10.1155/2014/518268.
  4. ↑ R. Velmani, and B. Kaarthick, 2015. An Efficient Cluster-Tree Based Data Collection Scheme for Large Mobile Wireless Sensor Networks. IEEE Sensors Journal, vol. 15, no. 4, pp. 2377–2390. doi: 10.1109/JSEN.2014.2377200.
  5. ↑ 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.
  6. ↑ 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.
  7. ↑ 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.
  8. ↑ 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.
  9. ↑ 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.
  10. ↑ 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.
  11. ↑ T. Hayes and F. Ali. 2016. Robust Ad-hoc Sensor Routing (RASeR) Protocol for Mobile Wireless Sensor Networks. Elsevier Ad Hoc Networks, vol. 50, no. 1, pp. 128–144.
  12. ↑ T. Hayes and F. Ali. 2016. Location Aware Sensor Routing (LASeR) Protocol for Mobile Wireless Sensor Networks. IET Wireless Sensor Systems, vol. 6, no. 2, pp. 49–57.
  13. ↑ 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.
  14. ↑ 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.
  15. ↑ B. White et al. 2008. Contaminant Cloud Boundary Monitoring Using Network of UAV Sensors. IEEE Sensors Journal, vol. 8, no. 10, pp. 1681–1692.
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