Wireless ad hoc network
A wireless ad hoc network (WANET) 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 managed (infrastructure) 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. In addition to the classic routing, ad hoc networks can use flooding for forwarding data.
An ad hoc network typically refers to any set of networks where all devices have equal status on a network and are free to associate with any other ad hoc network device in link range. Ad hoc network often refers to a mode of operation of IEEE 802.11 wireless networks.
It also refers to a network device's ability to maintain link status information for any number of devices in a 1-link (aka "hop") range, and thus, this is most often a Layer 2 activity. Because this is only a Layer 2 activity, ad hoc networks alone may not support a routeable IP network environment without additional Layer 2 or Layer 3 capabilities.
The decentralized nature of wireless ad-hoc networks makes them suitable for a variety of applications where central nodes can't be relied on and may improve the scalability of networks compared to wireless managed networks, though theoretical and practical limits to the overall capacity of such networks have been identified.
Minimal configuration and quick deployment make ad hoc networks suitable for emergency situations like natural disasters or military conflicts. The presence of dynamic and adaptive routing protocols enables ad hoc networks to be formed quickly.
Wireless ad-hoc networks can be further classified by their application:
- mobile ad hoc networks (MANET)
An ad hoc network is made up of multiple “nodes” connected by “links.”
Links are influenced by the node's resources (e.g., transmitter power, computing power and memory) and behavioral properties (e.g., reliability), as well as link properties (e.g. length-of-link and signal loss, interference and noise). Since links can be connected or disconnected at any time, a functioning network must be able to cope with this dynamic restructuring, preferably in a way that is timely, efficient, reliable, robust, and scalable.
The network must allow any two nodes to communicate by relaying the information via other nodes. A “path” is a series of links that connects two nodes. Various routing methods use one or two paths between any two nodes; flooding methods use all or most of the available paths.
In most wireless ad hoc networks, the nodes compete for access to shared wireless medium, often resulting in collisions (interference). Using cooperative wireless communications improves immunity to interference by having the destination node combine self-interference and other-node interference to improve decoding of the desired signal.
The traditional model is the random geometric graph.
These are graph structures consisting of a set of nodes placed according to a point process in some usually bounded subset of the n-dimensional plane, mutually coupled according to a boolean probability mass function of their spatial separation (which may be a step function, see unit disk graphs). One then analyses the group of network observables (such as connectivity the distribution of centralities  or the distribution of node degrees) from a graph-theoretic perspective.
Microsoft does not allow advanced encryption and security protocols for wireless Ad hoc networks on Windows. In fact, the security hole provided by Ad hoc networking is not only the Ad hoc network itself, but the bridge it provides into other networks (see Ad hoc networks in the article Wireless security).
Simulation of wireless ad hoc networks
One key problem in Wireless Ad Hoc networks is foreseeing the variety of possible situations that can occur. As a result, Modeling and Simulation using extensive parameter sweeping and what-if analysis becomes an extremely important paradigm for use in ad hoc networks. Traditional M&S tools include NS2,(and recently NS3), OPNET Modeler, and NetSim.
However, these tools focus primarily on the simulation of the entire protocol stack of the system. Although this can be important in the proof-of-concept implementations of systems, the need for a more advanced simulation methodology is always there. Agent-based modeling and simulation offers such a paradigm. Not to be confused with multi-agent systems and intelligent agents, agent-based modeling originated from social sciences, where the goal was to evaluate and view large-scale systems with numerous interacting "AGENT" or components in a wide variety of random situations to observe global phenomena. Unlike traditional AI systems with Intelligent agents, agent-based modeling is similar to the real world. Agent-based models are thus effective in modeling bio-inspired and nature-inspired systems. In these systems, the basic interactions of the components of the system, also called Complex Adaptive System, are simple but result in advanced global phenomena such as emergence.
- Independent Basic Service Set (IBSS)
- List of ad hoc routing protocols
- Mobile ad hoc network (MANET)
- Wi-Fi Direct
- Chai Keong Toh Ad Hoc Mobile Wireless Networks, Prentice Hall Publishers , 2002.
- C. Siva Ram Murthy and B. S. Manoj, Ad hoc Wireless Networks: Architectures and Protocols, Prentice Hall PTR, May 2004 
- P. Gupta and P.R. Kumar. Capacity of wireless networks. IEEE Transactions on Information Theory, Volume 46, Issue 2, March 2000, doi:10.1109/18.825799
- Jinyang Li, Charles Blake, Douglas S. J. De Couto, Hu Imm Lee, and Robert Morris, Capacity of Ad Hoc Wireless Networks, in the proceedings of the 7th ACM International Conference on Mobile Computing and Networking, Rome, Italy, July 2001
- Wu S.L., Tseng Y.C., "Wireless Ad Hoc Networking, Auerbach Publications", 2007 ISBN 978-0-8493-9254-2
- J.P. Coon, C.P. Dettmann, O.Georgiou. "Full Connectivity: Corners, edges and faces".
- A.P. Giles, O. Georgiou, C.P. Dettmann. "Betweenness Centrality in Dense Random Geometric Networks".
- Muaz Niazi, Amir Hussain (March 2009). "Agent based Tools for Modeling and Simulation of Self-Organization in Peer-to-Peer, Ad Hoc and other Complex Networks, Feature Issue" (PDF). IEEE Communications Magazine. 47 No.3. Cs.stir.ac.uk. pp. 163–173.