L. Guan

Publications (2)0.69 Total impact

• Article: A new load balancing and data collection algorithm for energy saving in wireless sensor networks

  Xin Guan, L. Guan, X. G. Wang, Tomoaki Ohtsuki
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  ABSTRACT: Data gathering is a major function of many applications in wireless sensor networks. The most important issue in designing a data gathering algorithm is how to save energy of sensor nodes while meeting the requirements of special applications or users. Wireless sensor networks are characterized by centralized data gathering, multi-hop communication and many to one traffic pattern. These three characteristics can lead to severe packet collision, network congestion and packet loss, and even result in hot-spots of energy consumption thus causing premature death of sensor nodes and entire network. In this paper, we propose a load balance data gathering algorithm that classifies sensor nodes into different layers according to their distance to sink node and furthermore, divides the sense zone into several clusters. Routing trees are established between sensor node and sink depending on the energy metric and communication cost. For saving energy consumption, the target of data aggregation scheme is adopted as well. Analysis and simulation results show that the algorithm we proposed provides more uniform energy consumption among sensor nodes and can prolong the lifetime of sensor networks. KeywordsData aggregation-Data gathering-Hop count-Load balance
  Telecommunication Systems 04/2012; 45(4):313-322. · 0.69 Impact Factor
• Conference Proceeding: A Novel Routing Algorithm Based on Ant Colony System for Wireless Sensor Networks

  Xin Guan, L. Guan, X.G. Wang, T. Ohtsuki
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  ABSTRACT: In this paper, we introduce a novel routing algorithm which is based on ant colony system. The objective of this novel algorithm is to solve the problem of energy and congestion control on wireless sensor network routing process. This novel algorithm is able to achieve better load balance and prolong the network lifetime. In this novel algorithm we combine the pheromone released by multi-ant colonies and residual energy as the algorithm control factor. Furthermore, we also introduce the competition mechanism among multiant colonies to avoid the simplex convergence in our algorithm. In this way, the novel algorithm controls the network traffic congestion effectively and balances the energy consumption for sensor networks. Simulation results in this paper demonstrate that this novel algorithm has better performance on load balance comparing with fundamental ant colony algorithm.
  Computer Communications and Networks, 2009. ICCCN 2009. Proceedings of 18th Internatonal Conference on; 09/2009