Improved DV-Hop Algorithm Based on Artificial Bee Colony

Abstract

In order to reduce the node position error of DV-Hop algorithm in wireless sensor network, the artificial bee colony algorithm is introduced to design the DV-Hop algorithm. A new ABCDV-Hop (Artificial Bee Colony DV-Hop) algorithm is proposed in this paper. Based on the traditional DV-Hop algorithm, by using the minimum hops of nodes and position information of anchor nodes, the average distance per hop is solved by artificial bee colony algorithm to make it more close to the actual value. The simulation results show that compared with the traditional DV-Hop algorithm, the improved algorithm can effectively reduce the positioning error without increasing the node hardware overhead. Keywords: DV-Hop algorithm, artificial bee colony algorithm, the average distance per-hop IntroductionWireless sensor network has been widely used in industrial production, environmental monitoring, military reconnaissance and other fields [1]. Positioning technology of node is the basis of all kinds of application [2][3][4]. Wireless sensor network has characteristics of limited energy of the nodes, poor reliability, large scale and random distribution, the communication distance is limited and so on [5], so the positioning technology are researched more without ranging at this stage.DV-Hop [6] positioning algorithm is the range free localization algorithm which is the most extensive research and application, but the precision of this algorithm is low. Aiming at this problem, the literature [7-12] has made some improvement on it. In view of the error which caused by average distance per-hop of anchor nodes, combining the theory of artificial bee colony algorithm, an improved DV-Hop algorithm based on artificial bee colony is proposed in this paper. The simulation results show that the improved algorithm without extra hardware and communication overhead, the positioning accuracy has obvious improvement compared with the original algorithm. Error Analysis of DV-Hop AlgorithmThe basic idea of DV-Hop positioning algorithm is that distance between unknown nodes and other nodes is expressed by product of the average distance per-hop between nodes in the network and the number of hops between nodes, and then uses three sided measurement or the maximum likelihood estimation method to obtain the location information of nodes. The positioning process is as follows:(1) By flooding with controllable, each anchor node broadcasts packet which contains identification number, its coordinate position and hop to the network. Neighbour nodes record packet information ignoring packet from the same node with larger hops. Then packet's hops value plus 1 and forwarded to their neighbour nodes. By this stage, all the nodes obtain the minimum number of hops for each beacon node.(2) The anchor nodes by using the Eq. (1) to calculate the average distance of each hop.

A Two-Stage Wireless Sensor Grey Wolf Optimization Node Location Algorithm Based on K-Value Collinearity

“…In order to reduce the impact of the Euclidean distance estimation error in the first stage on the final localization result, in this paper, the distance (d Au , d Bu , d Cu ) of the beacon nodes and the sensor node u in the localization unit is included in the vector of each individual for synchronous iteration, according to the vector to design the fitness function. is method can not only solve the influence of distance estimation errors on the final localization results, but also add constraints of the fitness function, thereby greatly reducing the times of iterations [17]. In this paper, the specific steps of applying the improved grey wolf optimization algorithm to wireless sensor node location are as follows:…”