{"title":"MINDS: Mobile Agent Itinerary Planning Using Named Data Networking in Wireless Sensor Networks","authors":"Saeid Pourroostaei Ardakani","doi":"10.3390/jsan10020028","DOIUrl":"https://doi.org/10.3390/jsan10020028","url":null,"abstract":"Mobile agents have the potential to offer benefits, as they are able to either independently or cooperatively move throughout networks and collect/aggregate sensory data samples. They are programmed to autonomously move and visit sensory data stations through optimal paths, which are established according to the application requirements. However, mobile agent routing protocols still suffer heavy computation/communication overheads, lack of route planning accuracy and long-delay mobile agent migrations. For this, mobile agent route planning protocols aim to find the best-fitted paths for completing missions (e.g., data collection) with minimised delay, maximised performance and minimised transmitted traffic. This article proposes a mobile agent route planning protocol for sensory data collection called MINDS. The key goal of this MINDS is to reduce network traffic, maximise data robustness and minimise delay at the same time. This protocol utilises the Hamming distance technique to partition a sensor network into a number of data-centric clusters. In turn, a named data networking approach is used to form the cluster-heads as a data-centric, tree-based communication infrastructure. The mobile agents utilise a modified version of the Depth-First Search algorithm to move through the tree infrastructure according to a hop-count-aware fashion. As the simulation results show, MINDS reduces path length, reduces network traffic and increases data robustness as compared with two conventional benchmarks (ZMA and TBID) in dense and large wireless sensor networks.","PeriodicalId":37584,"journal":{"name":"Journal of Sensor and Actuator Networks","volume":"89 Pt A 1","pages":"28"},"PeriodicalIF":3.5,"publicationDate":"2021-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77270399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Albano, Carl Anthony, A. Arefi, A. Arriola, G. Barton, An Beongku, Kim Boström, Pedro Brandao, J. Calbimonte, J. Decotignie, J. Delsing, H. Eguiraun, Lloyd E. Emokpae, F. Farahmand, Piedad Garrido, Mouzhi Ge, A. Giani, Luis Sanchez Gonzalez, A. Gotta, Shi-Jun He, Noelia Hernandez, Chien-Chang Hsu, P. Jayaraman, Keonwook Kim, P. Kokkinos, Timilehin Labeodan, Duc Le, Tian-Fu Lee, Yingsong Li, Chin-Feng Lin, Jaime Lloret-Mauri, Andrea Marin, M. Martalò, R. Meseguer, P. Minet, N. Mitton, Antonio Moreno, J. P. Muñoz-Gea, C. Pham, A. Piras, A. Puliafito, Yuansong Qiao, Dariusz Rzońca, N. Savage, Marialisa Scatá, M. Sha, Farhad Shahnia, I. Silva, D. Singh, V. Soares, S. Szott, Rui Teng, J. Tervonen, K. Tsang, L. Vangelista, Praneeth Vepakomma, G. Verticale, J. Villadangos, Jiafu Wan, K. Wang, Xin Wang, Yuan-Ting Wu, Boachang Yang, M. Zappatore, Xinming Zhang, Yanjun Zhao
{"title":"Acknowledgement to Reviewers of JSAN in 2016","authors":"M. Albano, Carl Anthony, A. Arefi, A. Arriola, G. Barton, An Beongku, Kim Boström, Pedro Brandao, J. Calbimonte, J. Decotignie, J. Delsing, H. Eguiraun, Lloyd E. Emokpae, F. Farahmand, Piedad Garrido, Mouzhi Ge, A. Giani, Luis Sanchez Gonzalez, A. Gotta, Shi-Jun He, Noelia Hernandez, Chien-Chang Hsu, P. Jayaraman, Keonwook Kim, P. Kokkinos, Timilehin Labeodan, Duc Le, Tian-Fu Lee, Yingsong Li, Chin-Feng Lin, Jaime Lloret-Mauri, Andrea Marin, M. Martalò, R. Meseguer, P. Minet, N. Mitton, Antonio Moreno, J. P. Muñoz-Gea, C. Pham, A. Piras, A. Puliafito, Yuansong Qiao, Dariusz Rzońca, N. Savage, Marialisa Scatá, M. Sha, Farhad Shahnia, I. Silva, D. Singh, V. Soares, S. Szott, Rui Teng, J. Tervonen, K. Tsang, L. Vangelista, Praneeth Vepakomma, G. Verticale, J. Villadangos, Jiafu Wan, K. Wang, Xin Wang, Yuan-Ting Wu, Boachang Yang, M. Zappatore, Xinming Zhang, Yanjun Zhao","doi":"10.3390/JSAN6010001","DOIUrl":"https://doi.org/10.3390/JSAN6010001","url":null,"abstract":"The editors of JSAN would like to express their sincere gratitude to the following reviewers for assessing manuscripts in 2015. We greatly appreciate the contribution of expert reviewers, which is crucial to the journal’s editorial decision-making process. Several steps have been taken in 2015 to thank and acknowledge reviewers. Good, timely reviews are rewarded with a discount off their next MDPI publication. By creating an account on the submission system, reviewers can access details of their past reviews, see the comments of other reviewers, and download a letter of acknowledgement for their records. This is all done, of course, within the constraints of reviewer confidentiality. Feedback from reviewers shows that most see their task as a voluntary and mostly unseen work in service to the scientific community. We are grateful to our reviewers for the contribution they make.","PeriodicalId":37584,"journal":{"name":"Journal of Sensor and Actuator Networks","volume":"6 1","pages":""},"PeriodicalIF":3.5,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3390/JSAN6010001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47540340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}