Review on Swarm Intelligence Optimization Techniques for Obstacle-Avoidance Localization in Wireless Sensor Networks

Wireless sensor network (WSN) is an evolving research topic with potential applications. In WSN, the nodes are spatially distributed and determining the path of transmission high challenging. Localization eases the path determining process between source and destination. The article, describes the localization techniques based on wireless sensor networks. Sensor network has been made viable by the convergence of Micro Electro- Mechanical Systems technology. The mobile anchor is used for optimizing the path planning location-aware mobile node. Two optimization algorithms have been used for reviewing the performacne. They are Grey Wolf Optimizer(GWO) and Whale Optimization Algorithm(WOA). The results show that WOA outperforms in maximizing the localization accuracy

Review on Swarm Intelligence Optimization Techniques for Obstacle-Avoidance Localization in Wireless Sensor Networks

Wireless sensor network (WSN) is an evolving research topic with potential applications. In WSN, the nodes are spatially distributed and determining the path of transmission high challenging. Localization eases the path determining process between source and destination. The article, describes the localization techniques based on wireless sensor networks. Sensor network has been made viable by the convergence of Micro Electro- Mechanical Systems technology. The mobile anchor is used for optimizing the path planning location-aware mobile node. Two optimization algorithms have been used for reviewing the performacne. They are Grey Wolf Optimizer(GWO) and Whale Optimization Algorithm(WOA). The results show that WOA outperforms in maximizing the localization accuracy

A mobile anchor assisted localization algorithm based on regular hexagon in wireless sensor networks

Localization is one of the key technologies in wireless sensor networks (WSNs), since it provides fundamental support for many location-aware protocols and applications. Constraints of cost and power consumption make it infeasible to equip each sensor node in the network with a global position system(GPS) unit, especially for large-scale WSNs. A promising method to localize unknown nodes is to use several mobile anchors which are equipped with GPS units moving among unknown nodes and periodically broadcasting their current locations to help nearby unknown nodes with localization. This paper proposes a mobile anchor assisted localization algorithm based on regular hexagon (MAALRH) in two-dimensional WSNs, which can cover the whole monitoring area with a boundary compensation method. Unknown nodes calculate their positions by using trilateration. We compare the MAALRH with HILBERT, CIRCLES, and S-CURVES algorithms in terms of localization ratio, localization accuracy, and path length. Simulations show that the MAALRH can achieve high localization ratio and localization accuracy when the communication range is not smaller than the trajectory resolution.The work is supported by the Natural Science Foundation of Jiangsu Province of China, no. BK20131137; the Applied Basic Research Program of Nantong Science and Technology Bureau, no. BK2013032; and the Guangdong University of Petrochemical Technology's Internal Project, no. 2012RC0106. Jaime Lloret's work has been partially supported by the "Ministerio de Ciencia e Innovacion," through the "Plan Nacional de I+D+i 2008-2011" in the "Subprograma de Proyectos de Investigacion Fundamental," Project TEC2011-27516. Joel J. P. C. Rodrigues's work has been supported by "Instituto de Telecomunicacoes," Next Generation Networks and Applications Group (NetGNA), Covilha Delegation, by national funding from the Fundacao para a Ciencia e a Tecnologia (FCT) through the Pest-OE/EEI/LA0008/2013 Project.Han, G.; Zhang, C.; Lloret, J.; Shu, L.; Rodrigues, JJPC. (2014). A mobile anchor assisted localization algorithm based on regular hexagon in wireless sensor networks. Scientific World Journal. https://doi.org/10.1155/2014/219371SLiu, Y., Yang, Z., Wang, X., & Jian, L. (2010). Location, Localization, and Localizability. Journal of Computer Science and Technology, 25(2), 274-297. doi:10.1007/s11390-010-9324-2Akcan, H., Kriakov, V., Brönnimann, H., & Delis, A. (2010). Managing cohort movement of mobile sensors via GPS-free and compass-free node localization. Journal of Parallel and Distributed Computing, 70(7), 743-757. doi:10.1016/j.jpdc.2010.03.007Akyildiz, I. F., Weilian Su, Sankarasubramaniam, Y., & Cayirci, E. (2002). 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K., Jain, N., & Nandi, G. C. (2014). A novel distance estimation approach for 3D localization in wireless sensor network using multi dimensional scaling. Information Fusion, 15, 5-18. doi:10.1016/j.inffus.2013.06.003Diallo, O., Rodrigues, J. J. P. C., & Sene, M. (2012). Real-time data management on wireless sensor networks: A survey. Journal of Network and Computer Applications, 35(3), 1013-1021. doi:10.1016/j.jnca.2011.12.006Amundson, I., & Koutsoukos, X. D. (2009). A Survey on Localization for Mobile Wireless Sensor Networks. Lecture Notes in Computer Science, 235-254. doi:10.1007/978-3-642-04385-7_16Ding, Y., Wang, C., & Xiao, L. (2010). Using mobile beacons to locate sensors in obstructed environments. Journal of Parallel and Distributed Computing, 70(6), 644-656. doi:10.1016/j.jpdc.2010.03.002Chenji, H., & Stoleru, R. (2010). Mobile Sensor Network Localization in Harsh Environments. Lecture Notes in Computer Science, 244-257. doi:10.1007/978-3-642-13651-1_18Campos, A. N., Souza, E. L., Nakamura, F. G., Nakamura, E. F., & Rodrigues, J. J. P. C. (2012). On the Impact of Localization and Density Control Algorithms in Target Tracking Applications for Wireless Sensor Networks. Sensors, 12(6), 6930-6952. doi:10.3390/s120606930Ou, C.-H., & He, W.-L. (2013). Path Planning Algorithm for Mobile Anchor-Based Localization in Wireless Sensor Networks. IEEE Sensors Journal, 13(2), 466-475. doi:10.1109/jsen.2012.2218100Koutsonikolas, D., Das, S. M., & Hu, Y. C. (2007). Path planning of mobile landmarks for localization in wireless sensor networks. Computer Communications, 30(13), 2577-2592. doi:10.1016/j.comcom.2007.05.048Cui, H., & Wang, Y. (2012). Four-mobile-beacon assisted localization in three-dimensional wireless sensor networks. Computers & Electrical Engineering, 38(3), 652-661. doi:10.1016/j.compeleceng.2011.10.012Ssu, K.-F., Ou, C.-H., & Jiau, H. C. (2005). Localization With Mobile Anchor Points in Wireless Sensor Networks. IEEE Transactions on Vehicular Technology, 54(3), 1187-1197. doi:10.1109/tvt.2005.844642Guo, Z., Guo, Y., Hong, F., Jin, Z., He, Y., Feng, Y., & Liu, Y. (2010). Perpendicular Intersection: Locating Wireless Sensors With Mobile Beacon. IEEE Transactions on Vehicular Technology, 59(7), 3501-3509. doi:10.1109/tvt.2010.2049391Bin Xiao, Hekang Chen, & Shuigeng Zhou. (2008). Distributed Localization Using a Moving Beacon in Wireless Sensor Networks. IEEE Transactions on Parallel and Distributed Systems, 19(5), 587-600. doi:10.1109/tpds.2007.70773Lee, S., Kim, E., Kim, C., & Kim, K. (2009). Localization with a mobile beacon based on geometric constraints in wireless sensor networks. IEEE Transactions on Wireless Communications, 8(12), 5801-5805. doi:10.1109/twc.2009.12.090319Han, G., Choi, D., & Lim, W. (2009). Reference node placement and selection algorithm based on trilateration for indoor sensor networks. Wireless Communications and Mobile Computing, 9(8), 1017-1027. doi:10.1002/wcm.65

Embracing Localization Inaccuracy: A Case Study

In recent years, indoor localization has become a hot research topic with some sophisticated solutions reaching accuracy on the order of ten centimeters. While certain classes of applications can justify the corresponding costs that come with these solutions, a wealth of applications have requirements that can be met at much lower cost by accepting lower accuracy. This paper explores one specific application for monitoring patients in a nursing home, showing that sufficient accuracy can be achieved with a carefully designed deployment of low-cost wireless sensor network nodes in combination with a simple RSSI-based localization technique. Notably our solution uses a single radio sample per period, a number that is much lower than similar approaches. This greatly eases the power burden of the nodes, resulting in a significant lifetime increase. This paper evaluates a concrete deployment from summer 2012 composed of fixed anchor motes throughout one floor of a nursing home and mobile units carried by patients. We show how two localization algorithms perform and demonstrate a clear improvement by following a set of simple guidelines to tune the anchor node placement. We show both quantitatively and qualitatively that the results meet the functional and non-functional system requirements

Dynamic mobile anchor path planning for underwater wireless sensor networks

In an underwater wireless sensor network (UWSN), the location of the sensor nodes plays a significant role in the localization process. The location information is obtained by using the known positions of anchor nodes. For underwater environments, instead of using various static anchor nodes, mobile anchor nodes are more efficient and cost-effective to cover the monitoring area. Nevertheless, the utilization of these mobile anchors requires adequate path planning strategy. Mzost of the path planning algorithms do not consider irregular deployment, caused by the effects of water currents. Consequently, this leads towards the inefficient energy consumption by mobile anchors due to unnecessary transmission of beacon messages at unnecessary areas. Therefore, an efficient dynamic mobile path planning (EDMPP) algorithm to tackle the irregular deployment and non-collinear virtual beacon point placement, targeting the underwater environment settings is presented in this paper. In addition, EDMPP controls the redundant beacon message deployment and overlapping, for beacon message distribution in mobile assistant localization. The simulation results show that the performance of the EDMPP is improved by increasing the localization accuracy and decreasing the energy consumption with optimum path length

Research Trend Topic Area on Mobile Anchor Localization: A Systematic Mapping Study

Localization in a dynamic environment is one of the challenges in WSN localization involving dynamic sensor nodes or anchor nodes. Mobile anchors can be an efficient solution for the number of anchors in a 3-dimensional environment requiring more local anchors. The reliability of a localization system using mobile anchors is determined by various parameters such as energy efficiency, coverage, computational complexity, and cost. Various methods have been proposed by researchers to build a reliable mobile anchor localization system. This certainly shows the many research opportunities that can be carried out in mobile anchor localization. The many opportunities in this topic will be very confusing for researchers who want to research in this field in choosing a topic area early. However, until now there is still no paper that discusses systematic mapping studies that can provide information on topic areas and trends in the field of mobile anchor localization. A systematic Mapping Study (SMS) was conducted to determine the topic area and its trends, influential authors, and produce modeling topics and trends from the resulting modeling topics. This SMS can be a solution for researchers who are interested in research in the field of mobile anchor localization in determining the research topics they are interested in for further research. This paper gives information on the mobile anchor research area, the author who has influenced mobile anchor localization research, and the topic modeling and trend that potentially promissing research in the future. The SMS includes a chronology of publications from 2017-2022, bibliometric co-occurrence, co-author analysis, topic modeling, and trends. The results show that the development of mobile anchor localization publications is still developing until 2022. There are 10 topic models with 6 of them included in the promising topic. The results of this SMS can be used as preliminary research from the literacy stage, namely Systematic Literature Review (SLR)

Robotic Wireless Sensor Networks

In this chapter, we present a literature survey of an emerging, cutting-edge, and multi-disciplinary field of research at the intersection of Robotics and Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system that aims to achieve certain sensing goals while meeting and maintaining certain communication performance requirements, through cooperative control, learning and adaptation. While both of the component areas, i.e., Robotics and WSN, are very well-known and well-explored, there exist a whole set of new opportunities and research directions at the intersection of these two fields which are relatively or even completely unexplored. One such example would be the use of a set of robotic routers to set up a temporary communication path between a sender and a receiver that uses the controlled mobility to the advantage of packet routing. We find that there exist only a limited number of articles to be directly categorized as RWSN related works whereas there exist a range of articles in the robotics and the WSN literature that are also relevant to this new field of research. To connect the dots, we first identify the core problems and research trends related to RWSN such as connectivity, localization, routing, and robust flow of information. Next, we classify the existing research on RWSN as well as the relevant state-of-the-arts from robotics and WSN community according to the problems and trends identified in the first step. Lastly, we analyze what is missing in the existing literature, and identify topics that require more research attention in the future