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Int. J. Communication Systems. 01/2010; 23:1311-1333.
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Proceedings of the 3rd International Conference on Ubiquitous Information Management and Communication, ICUIMC 2009, Suwon, Korea, January 15-16, 2009; 01/2009
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Human Interface and the Management of Information. Designing Information Environments, Symposium on Human Interface 2009, Held as Part of HCI International 2009, San Diego, CA, USA, July 19-24, 2009, Procceedings, Part I; 01/2009
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ABSTRACT: In the development of various large-scale sensor systems, a particularly challenging problem is how to dynamically organize the sensor nodes into clusters and route the sensing information to a remote base station. By leveraging the spatial correlation, there have been some noteworthy clustering schemes proposed recently, such as EEDC and ASAP. However, they are based on an impractical assumption of single-hop network architecture, and the cluster construction communication cost is relatively high. With such motivation, we introduce a novel distributed clustering scheme to group the sensor nodes that have the highest similarity in observations into the same cluster and also construct a dynamic backbone of efficient data collection in wireless sensor networks. Accordingly, with a given spatial accuracy requirement, only part of the sensor nodes in each cluster should be required to work for sampling and data transmitting in order to save energy. Comprehensive computer simulations show that the proposed scheme significantly reduces the overall number of communications in the cluster construction phase, whilst maintaining the small variance between the readings of sensor nodes in the same clusters.
Wireless Communications and Mobile Computing Conference, 2008. IWCMC '08. International; 09/2008
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ABSTRACT: Continuous data collection applications in wireless sensor networks require sensor nodes to continuously sample the surrounding physical phenomenon and then return the data to a processing center. Battery-operated sensors have to avoid heavy use of their wireless radio by compressing the time series sensed data instead of transmitting it in raw form. One of the most commonly used compacting methods is piecewise linear approximation. Previously, Liu et al. proposed a greedy PLAMLiS algorithm to approximate the time series into a number of line segments running in Theta(n<sup>2</sup>logn) time, however this is not appropriate for processing in the sensors. Therefore, based on our study we propose an alternative algorithm which obtains the same result but needs a shorter running time. Based on theoretical analysis and comprehensive simulations, it is shown that the new proposed algorithm has a competitive computational cost of Theta(nlogn) as well as reducing the number of line segments and so it can decrease the overall radio transmission load in order to save energy of the sensor nodes.
Research, Innovation and Vision for the Future, 2008. RIVF 2008. IEEE International Conference on; 08/2008
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ABSTRACT: A mobile ad-hoc network is a self-configuring network of user devices that are connected by wireless links in infrastructure-less situation. These kinds of networks have many challenges such as unreliable links, lack of scalability, limited resources, etc. and energy consumption is a major issue in designing network protocols because of battery constraints. In on-demand multi-hop routing protocols e.g. AODV and DSR, the route discovery process uses expanding ring search heuristic algorithm for reducing broadcast overhead and saving energy consumption. However, based on our observation we see that there are still some redundant broadcasts of this process that causes overhead, wasted energy, and increased collisions in the network. Here we propose a method which solves the redundant broadcasts of route discovery based on expanding ring search. The performance evaluation results show that by applying the proposed scheme, we can reduce the overhead of expanding ring search based route discovery up to about 20%, and therefore the total energy consumption of AODV is decreased by 15%.
Communications, 2008. ICC '08. IEEE International Conference on; 06/2008
