Wireless Sensor Networks, Location Based On Ant Colony Optimization Routing Algorithm

Wireless Sensor Networks are distributed networks constituted by a large number of tiny sensors with the ability of communication and computation.These sensors work in multi-hop and self-organized way.The computation,storage and communication of the sensors are so limited that they can only communicate with their neighbor nodes.WSN has been widely applied in military, environmental monitoring,health care,urban transportation,space exploration etc.Due to its great value in science and application,it has aroused a lot of concern in military,academic and industrial fields and becomes a hot research area in recent years.The application environment of WSN and the function of sensors are very limited,especially in the power of nodes,which lead to great challenge in designing high-efficient routing protocols. Energy consumption has been a key problem in the way of development of WSN.As a result,it's also a hot study area on how to design an algorithm to save energy and balance network energy consumption of WSN.It's also a key problem of WSN study.An energy-efficiency location-aware ACO-based routing algorithm(ELACO) is proposed.It can be concluded that there are great advantages to optimize WSN routing using ACO,after studying the specialty of ACO algorithm combined with the character of WSN.This algorithm gives a forward routing mode,which uses the nodes' location information to decide the forward field and the set of forward neighbor nodes.The forward field can reduce searching area and make it more efficient.Then use ACO algorithm to search the path from source node to target node at the base of forward pattern.The ants in the network can choose next node according to the location,rest energy of the neighbor node and information of the path.Considering the energy and location of the neighbor nodes can save and balance the energy consumption during routing.The algorithm defines an ant probability selection algorithm(APSA),which used by ants to choose next hop node from the set of forward neighbor nodes.This paper gives a routing back off strategy to solve the hollow problem in the searching process,which makes it more successful.This paper also gives a routing existence and non-ring routing theorem.The existent theorem indicates that if there's a path,ants can finally find it and the non-ring theorem tells that the result path has no rings in it.It has been proved that the time complexity of ELACO is O(t·|V|~2·m).It has also been proved to be convergent from ants quantity and time,in which the time convergence divides into value convergence and solution convergence. Take the searching field of original DREAM,LAR and LARDAR algorithm as the forward field and use ELAOC routing strategy,we can form newly changed DREAM,LAR and LARDAR algorithms.Due to the lack of guidance in setting values of information heuristic factorα,energy heuristic factorβand ant number m in ACO algorithm,this paper decides their values by making experiments. We make simulation experiment from time delay,energy consumption,energy efficiency,energy balance,sending successful rate and network life,and compare with the newly changed algorithms. The results indicate that ELACO is better on successful rate,energy efficiency,energy standard deviation and network life.