{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:32:12Z","timestamp":1760243532203,"version":"build-2065373602"},"reference-count":25,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2013,8,21]],"date-time":"2013-08-21T00:00:00Z","timestamp":1377043200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Sensor network simulations require high fidelity and timing accuracy to be used as an implementation and evaluation tool. The cycle-accurate and instruction-level simulator is the known solution for these purposes. However, this type of simulation incurs a high computation cost since it has to model not only the instruction level behavior but also the synchronization between multiple sensors for their causality. This paper presents a novel technique that exploits asynchronous simulations of interrupt service routines (ISR). We can avoid the synchronization overheads when the interrupt service routines are simulated without preemption. If the causality errors occur, we devise a rollback procedure to restore the original synchronized simulation. This concept can be extended to any instruction-level sensor network simulator. Evaluation results show our method can enhance the simulation speed up to 52% in the case of our experiments. For applications with longer interrupt service routines and smaller number of preemptions, the speedup becomes greater. In addition, our simulator is 2 to 11 times faster than the well-known sensor network simulator.<\/jats:p>","DOI":"10.3390\/s130811128","type":"journal-article","created":{"date-parts":[[2013,8,21]],"date-time":"2013-08-21T12:49:13Z","timestamp":1377089353000},"page":"11128-11145","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Enhancing the Simulation Speed of Sensor Network Applications by Asynchronization of Interrupt Service Routines"],"prefix":"10.3390","volume":"13","author":[{"given":"Hyunwoo","family":"Joe","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, Chungnam National University, 99 Daehak-ro, Yuseoung-gu, Daejeon 305-764, Korea"}]},{"given":"Duk-Kyun","family":"Woo","sequence":"additional","affiliation":[{"name":"Embedded Software Research Division, Electronics and Telecommunications Research Institute (ETRI), 218 Gajeng-ro, Yuseoung-gu, Daejeon 305-700, Korea"}]},{"given":"Hyungshin","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Chungnam National University, 99 Daehak-ro, Yuseoung-gu, Daejeon 305-764, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2013,8,21]]},"reference":[{"key":"ref_1","unstructured":"NS-2. Available online: http:\/\/isi.edu\/nsnam\/ns\/."},{"key":"ref_2","unstructured":"Park, S., Savvides, A., and Srivastava, M.B. SensorSim: A Simulation Framework for Sensor Networks. Boston, MA, USA."},{"key":"ref_3","unstructured":"Available online: http:\/\/pcl.cs.ucla.edu\/projects\/glomosim\/academic\/license.html."},{"key":"ref_4","unstructured":"QualNet. Available online: http:\/\/www.scalable-networks.com."},{"key":"ref_5","unstructured":"Polley, J., Blazakis, D., McGee, J., Rusk, D., and Baras, J.S. ATEMU: A Fine-Grained Sensor Network Simulator. Santa Clara, CA, USA."},{"key":"ref_6","unstructured":"Joe, H., Lee, J., Woo, D.-K., Mah, P., and Kim, H. (April, January 13\u2013). A High-Fidelity Sensor Network Simulator Using Accurate CC2420 Model. San Francisco, CA, USA."},{"key":"ref_7","unstructured":"Titzer, B.L., Lee, D.K., and Palsberg, J. (April, January 25\u2013). Avrora: Scalable Sensor Network Simulation with Precise Timing. 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Available online: http:\/\/telecom.dei.unipd.it\/pages\/read\/58\/."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"7454","DOI":"10.3390\/s130607454","article-title":"A Proposal for modeling real hardware, weather and marine conditions for underwater sensor networks","volume":"13","author":"Climent","year":"2013","journal-title":"Sensors"},{"key":"ref_19","unstructured":"NS-3. Available online: http:\/\/www.nsnam.org."},{"key":"ref_20","unstructured":"Levis, P., Lee, N., Welsh, M., and Culler, D. TOSSIM: Accurate and Scalable Simulation of Entire TinyOS Applications. Los Angeles, CA, USA."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"47","DOI":"10.4218\/etrij.08.0106.0240","article-title":"Instruction-level power estimator for sensor networks","volume":"30","author":"Joe","year":"2008","journal-title":"ETRI J."},{"key":"ref_22","unstructured":"Wen, Y., Wolski, R., and Moore, G. (March, January 14\u2013). Disens: Scalable Distributed Sensor Network Simulation. San Jose, CA, USA."},{"key":"ref_23","unstructured":"Osterlind, F., Dunkels, A., Eriksson, J., Finne, N., and Voigt, T. (November, January 14\u2013). Cross-Level Sensor Network Simulation with COOJA. Tempa, FL, USA."},{"key":"ref_24","unstructured":"Osterlind, F., Dunkels, A., Voigt, T., Tsiftes, N., Eriksson, J., and Finne, N. (February, January 11\u2013). Sensornet Checkpointing: Enabling Repeatability in Testbeds and Realism in Simulations. Cork, Ireland."},{"key":"ref_25","unstructured":"Eriksson, J., Dunkels, A., Finne, N., Osterlind, F., and Voigt, T. (January, January 29\u2013). MSPsim\u2013an Extensible Simulator for MSP430-equipped Sensor Boards. Delft, The Netherlands."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/13\/8\/11128\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:48:47Z","timestamp":1760219327000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/13\/8\/11128"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,8,21]]},"references-count":25,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2013,8]]}},"alternative-id":["s130811128"],"URL":"https:\/\/doi.org\/10.3390\/s130811128","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2013,8,21]]}}}