'ACO' is metaheuristic approach for solving hard combinatorial optimisation problems .In ACO local search is extremely important for obtaining efficient results.

In an Ant Based Algorithm the three important phases w.r.t WSN would be 1. Route Discovery Phase, 2. Route Maintenance Phase and 3. Route Failure handlers.

The following are some references that you may search and obtain a good overview.

Dorigo M. and G. Di Caro (1999). The Ant Colony Optimization Meta-Heuristic. In D. Corne, M. Dorigo and F. Glover, editors, New Ideas in Optimization, McGraw-Hill, 11-32.

M. Dorigo and L. M. Gambardella. Ant colonies for the traveling salesman problem. BioSystems, 43:73–81, 1997.

M. Dorigo and L. M. Gambardella. Ant Colony System: A cooperative learning approach to the traveling salesman problem. IEEE Transactions on Evolutionary Computation, 1(1):53–66, 1997.

G. Di Caro and M. Dorigo. Mobile agents for adaptive routing. In H. El-Rewini, editor, Proceedings of the 31st International Conference on System Sciences (HICSS-31), pages 74–83. IEEE Computer Society Press, Los Alamitos, CA, 1998.

M. Dorigo, V. Maniezzo, and A. Colorni. The Ant System: An autocatalytic optimizing process. Technical Report 91-016 Revised, Dipartimento di Elettronica,Politecnico di Milano, Italy, 1991.

L. M. Gambardella, ` E. D. Taillard, and G. Agazzi. MACS-VRPTW: A multiple ant colony system for vehicle routing problems with time windows. In D. Corne, M. Dorigo, and F. Glover, editors, New Ideas in Optimization, pages 63–76. McGraw Hill, London, UK, 1999.

L. M. Gambardella, ` E. D. Taillard, and M. Dorigo. Ant colonies for the quadratic assignment problem. Journal of the Operational Research Society,50(2):167–176, 1999.

V. Maniezzo and A. Colorni. The Ant System applied to the quadratic assignment problem. IEEE Transactions on Data and Knowledge Engineering, 11(5):769–778, 1999.

Gambardella L. M., E. Taillard and M. Dorigo (1999). Ant Colonies for the Quadratic Assignment Problem. Journal of the Operational Research Society, 50:167-176.

You can gain valuable information about ACO routing algorithms in our proposal:

R. Attia, Rawya Rizk, and M. Mariee, “An ant inspired QoS routing algorithm for MANETs,” The International Journal of Ad Hoc & Sensor Wireless Networks, Old City Publishing, vol. 10, no. 2-3, pp. 111-134, 2010.

In this paper, HMAnt routing algorithm is proposed. It combines the features of proactive and reactive algorithms. It solves the more overhead and the long convergence time problems of the ACO algorithms. The following four phases are discussed:

1. Reactive Path Setup Phase (Reactive Forward Ants+Reactive Backward Ants)

2. Proactive Data Routing Phase

3. Proactive Path Maintenance Phase

4. Reactive Path Recovery Phase