• What is AntNet?
• Nice properties
• Performance
• Scientific papers
• Implementations
• ACO routing in general

​What is AntNet?
AntNet is an algorithm for adaptive best-effort routing in IP networks. AntNet's design is based on the Ant Colony Optimization (ACO) framework, which exploits the mechanisms behind the shortest path behavior observed in ant colonies to define a Nature-inspired metaheuristic for combinatorial optimization. 

AntNet has been the first ACO algorithm for routing in packet-switched networks. My first work on AntNet, under the supervision of Prof. Marco Dorigo, dates back to 1997. As a matter of fact, AntNet is the reference for routing algorithms designed following  ACO or Swarm Intelligence principles. According to GoogleScholar, my AntNet's papers have got overall more than 3000 citations. 

Nice Properties
AntNet, as well as most of the other ACO routing algorithms designed after AntNet, exhibits a number of interesting properties: it works in a fully distributed way, is highly adaptive to network and traffic changes, uses lightweight mobile agents (called ants) for active path sampling, is robust to agent failures, provides multipath routing, and automatically takes care of data load spreading. 

Performance
AntNet's performance has been extensively tested in simulation, considering different networks and traffic patterns, and compared to several state-of-the-art routing algorithms (based on both distance-vector and link-state approaches). In the great majority of the considered situations, AntNet has largely outperformed all its competitors, showing excellent adaptivity and robustness. AntNet has been also tested in small physical networks, confirming the good performance also in these real-world tests.

Reference works

Di Caro G. A. Ant Colony Optimization and its application to adaptive routing in telecommunication networks, PhD thesis in Applied Sciences, Polytechnic School, Université Libre de Bruxelles, Brussels, Belgium, 2004. [BibTeX]

Di Caro G.A., Dorigo M., AntNet: Distributed Stigmergetic Control for Communications Networks, Journal of Artificial Intelligence Research (JAIR), Vol. 9, Pag. 317-365, 1998. [BibTeX]

Di Caro G.A., Dorigo M., Two Ant Colony Algorithms for Best-Effort Routing in Datagram Networks , Proceedings of PDCS'98 - 10th International Conference on Parallel and Distributed Computing and Systems, Las Vegas, Nevada, October 28-31, 1998, (also Technical Report IRIDIA 98-09). [BibTeX]

Software implementations of AntNet

​​Don't ask me about my original code! I implemented the code for my own personal use, such that the code has no comments, no user manual, makes use of commercial libraries, etc. However, some software implementations of AntNet for popular network simulators are around:

• Muddassar Farooq made an implementation of AntNet for OmNet++. The implementation is very close to the original algorithm, but I didn't fully checked and tested the code.
  
  
• Lavina Jain made an implementation of AntNet for NS-2 (that can be also downloaded here).
  
  
• Richardson Lima has also released, more recently, a version of AntNet for NS-2. He also made an AntNet web page.
  Since I'm not an NS-2 user, I haven't checked these implementations, but I guess the Lima's implementation can be used as a good starting point. If you plan to use Lima's code, please feel free to contact me to check/improve the quality of the implementation.
  
  
• At IDSIA, Frederick Ducatelle and Liliana Carrillo made an implementation of AntNet for QualNet (ver. 3.8), the commercial network simulator from Scalable Network Technologies. The implementation has not been fully tested and the code needs to be polished. However, it works and can be definitely used as a starting point (anybody willing to check, improve, or port this code to newer QualNet versions, is most welcomed!).

General principles and applications of ACO and Swarm Intelligence to routing in telecommunication networks
​

• Ducatelle F., Di Caro G.A., Gambardella L.M., Principles and applications of swarm intelligence for telecommunications networks, Swarm Intelligence Journal Vol. 4, N. 3, pp. 173-198, 2010 [DOI] [BibTeX]


• Saleem M., Di Caro G.A., Farooq M., Swarm intelligence based routing protocol for wireless sensor networks: Survey and future directions, Information Sciences, Volume 181, Issue 20, pp. 4597-4624, October 2011 [DOI] [BibTeX]


• Farooq M., Di Caro G.A., Routing protocols for next-generation intelligent networks inspired by collective behaviors of insect societies in Blum C., Merkle D. (Eds.), Swarm Intelligence: Introduction and Applications, Springer, Natural Computing Series, 2008 [BibTeX]


• Di Caro G.A., Ducatelle F., Gambardella L.M., Theory and practice of Ant Colony Optimization for routing in dynamic telecommunications networks, in Sala N., Orsucci F. (Eds.), Reflecting interfaces: the complex coevolution of information technology ecosystems, pp. 185-216, Idea Group, Hershey, PA, USA. 2008 [BibTeX]                                                             
• Di Caro, G. A, Principi di swarm intelligence per problemi di routing adattivo in reti di telecomunicazione (in Italian), Sistemi Intelligenti, vol. 26, n. 3, pp. 443-464, 2014 [BibTeX]

Back