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Systematic Review of Mobile Database Systems for Green Mobile Computing Ecosystem

Vol 1 , Issue 2 , July - December 2021 | Pages: 1-13 | Research Paper  

https://doi.org/10.17492/computology.v1i2.2101


Author Details ( * ) denotes Corresponding author

1. * Kingsley Theophilus Igulu, Department of Computer Science, Kenule Beeson Saro-Wiwa Polytechnic, Bori, Rivers State, Nigeria (Igulu.kingsley@kenpoly.edu.ng)

Access to essential and corporate information through mobile devices has become a routine activity. Vehicle navigation systems, like audio systems, are becoming standard equipment. These devices are very handy and user-friendly and such users can access needed information from databases from any location, anytime utilizing wireless and cellular communications. This study systematically reviews Mobile Database Systems for Green Mobile Computing Ecosystem. 343 papers where sourced. 42 of them made it to the final stage. 341 were excluded based on title and abstract. We presented the review in a table. 90% of the work focused on MDS and 10 on GMC. The study shows that Green Mobile Database Systems has very few literatures and it is a promising research niche.

Keywords

Mobile Database Systems; Database; Green Computing; Mobile Computing; Green Mobile Computing


  1. Abbasi, Z., Jonas, M., Banerjee, A., Gupta, S., & Varsamopoulos, G. (2013). Evolutionary Green Computing Solutions for Distributed Cyber Physical Systems. Berlin Heidelberg: Springer.

  2. Ahmad, R., Gani, A., Hamid, S., Xia, F., & Shiraz, M. (2015). A review on mobile application energy profiling: Taxonomy, state-of-the-art, and open research issues. Journal of Networking Application, 42–59.

  3. Alzughaibi, A. A., Ibrahim, A. M., Eltawil, A. M., Na, Y., & El-Tawil, S. (2019). Post-Disaster Structural Health Monitoring System Using Personal Mobile-Phones. 2019 IEEE Topical Conference on Wireless Sensors and Sensor Networks (WiSNet), 1–4. https://doi.org/10.1109/WISNET.2019.8711805

  4. Andrianto, H., Suhardi, & Faizal, A. (2020). Development of Smart Greenhouse System for Hydroponic Agriculture. 2020 International Conference on Information Technology Systems and Innovation (ICITSI), 335–340. https://doi.org/10.1109/ICITSI50517.2020.9264917

  5. Bernard, G., Roncancio, C., Serrano-Alvarado, P., & Valduriez, P. (2004). Mobile Databases: a Selection of Open Issues and Research Directions,”. ACM SIGMOD Record, 33(2), 78-83.

  6. Cai, L., Fang, Z., Xie, S., Cai, G., & Geng, S. (2020). Research on Backup and Concurrency Control Technology of Embedded Database. Proceedings of the 2020 4th International Conference on Electronic Information Technology and Computer Engineering, 907–912. https://doi.org/10.1145/3443467.3443877

  7. Li, Z., Ortiz, P., Browne, J., Franklin, D., Oliver, J., Geyer, R., . . . Chong, F. (2010). Smartphone evolution and reuse: Establishing a more sustainable model. 39th International Conference on Parallel Processing Workshops (pp. 476–847.). IEEE.

  8. Choi, S. (2018). SSD as SQLite Engine. Proceedings of the 2018 International Conference on Management of Data, 1829–1831. https://doi.org/10.1145/3183713.3183720

  9. Cordova, D., Laube, A., Nguyen, T.-M.-T., & Pujolle, G. (2020). Blockgraph: A blockchain for mobile ad hoc networks. 2020 4th Cyber Security in Networking Conference (CSNet), 1–8. https://doi.org/10.1109/CSNet50428.2020.9265532

  10. Dedeepya, P., Srinija, U. S. A., Gowtham Krishna, M., Sindhusha, G., & Gnanesh, T. (2018). Smart Greenhouse Farming based on IOT. 2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA), 1890–1893. https://doi.org/10.1109/ICECA.2018.8474713

  11. Fernandes, E., Turine, M., & Cagnin, M. I. (2015). SIGS-S Mobile Saude: A Mobile Application to Support the Collection of Health Data. Proceedings of the Annual Conference on Brazilian Symposium on Information Systems: Information Systems: A Computer Socio-Technical Perspective - Volume 1, 639–646.

  12. Godbole, N. S., & Lamb, J. (2015). Using data science amp; big data analytics to make healthcare green. 2015 12th International Conference Expo on Emerging Technologies for a Smarter World (CEWIT), 1–6. https://doi.org/10.1109/CEWIT.2015.7338161

  13. Gupta, A. Kr. (2020). Some Issues for Location Dependent Information System Query in Mobile Environment. In Proceedings of the 29th ACM International Conference on Information & Knowledge Management (pp. 3233–3236). Association for Computing Machinery. https://doi.org/10.1145/3340531.3418504

  14. Gupta, A. K., & Shanker, U. (2018). Modified predicted region based cache replacement policy for location-dependent data in mobile environment. Procedia Computer Science, 125, 917–924. https://doi.org/https://doi.org/10.1016/j.procs.2017.12.117

  15. Gupta, A. K., & Shanker, U. (2020). MAD-RAPPEL: Mobility Aware Data Replacement And Prefetching Policy Enrooted LBS. Journal of King Saud University - Computer and Information Sciences. https://doi.org/https://doi.org/10.1016/j.jksuci.2020.05.007

  16. Halvorsen, H.-P., Grytten, O. A., Svendsen, M. V., & Mylvaganam, S. (2018). Environmental Monitoring with Focus on Emissions Using IoT Platform for Mobile Alert. 2018 28th EAEEIE Annual Conference (EAEEIE), 1–7. https://doi.org/10.1109/EAEEIE.2018.8534197

  17. Hemalatha M.; Prithiviraj V.Jayasri T. (n.d.). Scheduling BTS power levels for green mobile computing . Journal of Green Engineering.

  18. Hisham Che Soh, Z., Azeer Al-Hami Husa, M., Afzal Che Abdullah, S., & Affandi Shafie, M. (2019). Smart Waste Collection Monitoring and Alert System via IoT. 2019 IEEE 9th Symposium on Computer Applications Industrial Electronics (ISCAIE), 50–54. https://doi.org/10.1109/ISCAIE.2019.8743746

  19. Hsu, W.-Y., Lien, K.-S., Wang, Y.-C., Zheng, Y.-T., & Li, G.-H. (2016). Real-Time Driving Monitor System: Combined Cloud Database with GPS. 2016 49th Hawaii International Conference on System Sciences (HICSS), 1740–1748. https://doi.org/10.1109/HICSS.2016.219

  20. Jagdale, B. N., & Bakal, J. W. (2016). Controlled Broadcast Protocol for Location Privacy in Mobile Applications. Procedia Computer Science, 78, 782–789. https://doi.org/https://doi.org/10.1016/j.procs.2016.02.053

  21. Jiang, C., Ou, D., Wang, Y., You, X., Zhang, J., Wan, J., Luo, B., & Shi, W. (2016). Energy efficiency comparison of hypervisors. 2016 Seventh International Green and Sustainable Computing Conference (IGSC), 1–8. https://doi.org/10.1109/IGCC.2016.7892607

  22. Jimale, A. O., Ridzuan, F., & Wan Zainon, W. M. N. (2019). Square Matrix Multiplication Using CUDA on GP-GU. Procedia Computer Science, 161, 398–405. https://doi.org/https://doi.org/10.1016/j.procs.2019.11.138

  23. Kobiela, J. (2020). The Security of Mobile Business Applications Based on MCRM. Proceedings of the 18th International Conference on Advances in Mobile Computing & Multimedia, 179–186. https://doi.org/10.1145/3428690.3429155

  24. Kumar, V. (2006). Mobile Database System. New Jersey: John Wiley & Sons, Inc.

  25. Lahiri, P. K., Das, D., Mansoor, W., Banerjee, S., & Chatterjee, P. (2020). A Trustworthy Blockchain based framework for Impregnable IoV in Edge Computing. 2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS), 26–31. https://doi.org/10.1109/MASS50613.2020.00013

  26. Lai, Y., Zhang, L., Yang, F., Zheng, L., Wang, T., & Li, K. C. (2019). CASQ: Adaptive and cloud-assisted query processing in vehicular sensor networks. Future Generation Computer Systems, 94. https://doi.org/10.1016/j.future.2018.11.034

  27. Li, L., Qian, K., Chen, Q., Hasan, R., & Shao, G. (2016). Developing Hands-on Labware for Emerging Database Security. Proceedings of the 17th Annual Conference on Information Technology Education, 60–64. https://doi.org/10.1145/2978192.2978225

  28. Liu, C., Zhang, L., Liu, Z., Liu, K., Li, X., & Liu, Y. (2016). Lasagna: Towards Deep Hierarchical Understanding and Searching over Mobile Sensing Data. Proceedings of the 22nd Annual International Conference on Mobile Computing and Networking, 334–347. https://doi.org/10.1145/2973750.2973752

  29. Mahali, M. I., Marpanaji, E., Dewanto, S. A., Wulandari, B., Rochayati, U., & Hasanah, N. (2018). Smart Traffic Light based on IoT and mBaaS using High Priority Vehicles Method. 2018 5th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI), 703–707. https://doi.org/10.1109/EECSI.2018.8752694

  30. Mandal, R., Mondal, M. K., Banerjee, S., Chakraborty, C., & Biswas, U. (2021). 11 - A survey and critical analysis on energy generation from datacenter. In T. T. Thwel & G. R. Sinha (Eds.), Data Deduplication Approaches (pp. 203–230). Academic Press. https://doi.org/https://doi.org/10.1016/B978-0-12-823395-5.00005-7

  31. Mohana, M., & Jaykumar, C. (2017). Hierarchical replication and multiversion concurrency control model for mobile database systems (MDS). Wireless Networks, 23(5). https://doi.org/10.1007/s11276-015-1190-y

  32. Moher, D., Liberati, A., Jennifer Tetzlaff, & Altman, D. G. (2009). Preferred reporting items for systematic reviews and meta‐analyses: the PRISMA Statement. Open Medicine, 3(2), 123-130.

  33. Mokhtar, Y. F., Darwish, S. M., & Madbouly, M. M. (2021). An Enhanced Database Recovery Model Based on Game Theory for Mobile Applications. Advances in Intelligent Systems and Computing, 1261 AISC. https://doi.org/10.1007/978-3-030-58669-0_2

  34. Nizami, S., Basharat, A., Shoukat, A., Hameed, U., Raza, S. A., Bekele, A., Giffen, R., & Green, J. R. (2018). CEA: Clinical Event Annotator mHealth Application for Real-time Patient Monitoring. 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2921–2924. https://doi.org/10.1109/EMBC.2018.8512898

  35. Oh, G., Kim, S., Lee, S.-W., & Moon, B. (2015). SQLite Optimization with Phase Change Memory for Mobile Applications. Proc. VLDB Endow., 8(12), 1454–1465. https://doi.org/10.14778/2824032.2824044

  36. Papadopoulos, P., Loukopoulos, T., Anagnostopoulos, I., Tziritas, N., & Vassilakopoulos, M. (2015). RAC: A Remote Application Calling Framework for Coordination of Mobile Apps. Proceedings of the 19th Panhellenic Conference on Informatics, 394–399. https://doi.org/10.1145/2801948.2801978

  37. Park, J.-H., Oh, G., & Lee, S.-W. (2017). SQL Statement Logging for Making SQLite Truly Lite. Proc. VLDB Endow., 11(4), 513–525. https://doi.org/10.1145/3164135.3164146

  38. Peng, Y., Wang, N., & Wang, G. (2015). An Optimization Strategy of Energy Consumption for Data Transmission Based on Optimal Stopping Theory in Mobile Networks. .

  39. Petticrew, M., & Roberts, H. (2008). Systematic Reviews in the Social Sciences: A Practical Guide. In Systematic Reviews in the Social Sciences: A Practical Guide. https://doi.org/10.1002/9780470754887

  40. Qayyum, M., Khan, K. U. R., & Nazeer, M. (2015). Cluster based data replication technique based on mobility prediction in Mobile Ad Hoc Networks. Advances in Intelligent Systems and Computing, 338. https://doi.org/10.1007/978-3-319-13731-5_35

  41. Qian, K., Shahriar, H., Wu, F., Tao, L., & Bhattacharya, P. (2017). Labware for Secure Mobile Software Development (SMSD) Education. Proceedings of the 2017 ACM Conference on Innovation and Technology in Computer Science Education, 375. https://doi.org/10.1145/3059009.3072983

  42. Qian, K., Shahriar, H., Wu, F., Thomas, C., & Agu, E. (2017). Broadening Secure Mobile Software Development (SMSD) Through Curriculum Development. Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education, 715. https://doi.org/10.1145/3017680.3022438

  43. Roh, H.-G., Kim, C., Woo, J., & Kim, S. (2017). Kaleido: Implementing a Novel Data System for Multi-Device Synchronization. 2017 18th IEEE International Conference on Mobile Data Management (MDM), 286–290. https://doi.org/10.1109/MDM.2017.46

  44. Salem, A. O. A., & Al-Qeerm, A. H. (2015). Classification of transaction models in mobile database system. 2015 2nd World Symposium on Web Applications and Networking, WSWAN 2015. https://doi.org/10.1109/WSWAN.2015.7209086

  45. Saradha, B. J., Vijayshri, G., & Subha, T. (2017). Intelligent traffic signal control system for ambulance using RFID and cloud. 2017 2nd International Conference on Computing and Communications Technologies (ICCCT), 90–96. https://doi.org/10.1109/ICCCT2.2017.7972255

  46. Sathe, A. D., & Deshmukh, V. D. (2016). Advance vehicle-road interaction and vehicle monitoring system using smart phone applications. 2016 Online International Conference on Green Engineering and Technologies (IC-GET), 1–6. https://doi.org/10.1109/GET.2016.7916825

  47. Shahid, A. R., Pissinou, N., Staier, C., & Kwan, R. (2019). Sensor-Chain: A Lightweight Scalable Blockchain Framework for Internet of Things. 2019 International Conference on Internet of Things (IThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), 1154–1161. https://doi.org/10.1109/iThings/GreenCom/CPSCom/SmartData.2019.00195

  48. Sharma, S., & Sharma, G. (2016). Impact of Energy-Efficient and Eco-Friendly Green Computing. International Journal of Computer Applications, 143(7). https://doi.org/10.5120/ijca2016910250

  49. Kumar, V. (2006). Mobile Database System. New Jersey: John Wiley & Sons, Inc.

  50. Li, Z., Ortiz, P., Browne, J., Franklin, D., Oliver, J., Geyer, R., . . . Chong, F. (2010). Smartphone evolution and reuse: Establishing a more sustainable model. 39th International Conference on Parallel Processing Workshops (pp. 476–847.). IEEE.

  51. Moher, D., Liberati, A., Jennifer Tetzlaff, & Altman, D. G. (2009). Preferred reporting items for systematic reviews and meta‐analyses: the PRISMA Statement. Open Medicine, 3(2), 123-130.

  52. Petticrew, M., & Roberts, H. (2008). Systematic Reviews in the Social Sciences: A Practical Guide.

  53. Salem, A. O., & Al-Qeerm, A. H. (2015). Classification of transaction models in mobile database system. 2nd World Symposium on Web Applications and Networking (WSWAN), (pp. 1-6). Sousse, Tunisia.

  54. Serrano-Alvarado, P., Roncancio, C., & Adiba, M. (2004). A Survey of Mobile Transactions. Journal of Distributed and Parallel Databases, 16(2), 193-230.

  55. Shuja, J., Ahmad, R. W., Gani, A., Abdalla Ahmed, A. I., Siddiqa, A., Nisar, K., Khan, S. U., & Zomaya, A. Y. (2017). Greening emerging IT technologies: techniques and practices. Journal of Internet Services and Applications, 8(1). https://doi.org/10.1186/s13174-017-0060-5

  56. Systematic reviews in the social sciences: a practical guide. (2006). Choice Reviews Online, 43(10). https://doi.org/10.5860/choice.43-5664

  57. Tuan, D. Q., Cheon, S., & Won, Y. (2016). On the IO Characteristics of the SQLite Transactions. Proceedings of the International Conference on Mobile Software Engineering and Systems, 214–224. https://doi.org/10.1145/2897073.2897093

  58. Vanmathi, C., Mangayarkarasi, R., & Subalakshmi R., J. (2020). Real Time Weather Monitoring using Internet of Things. 2020 International Conference on Emerging Trends in Information Technology and Engineering (Ic-ETITE), 1–6. https://doi.org/10.1109/ic-ETITE47903.2020.348

  59. Vaupel, S., Wlochowitz, D., & Taentzer, G. (2016). A Generic Architecture Supporting Context-Aware Data and Transaction Management for Mobile Applications. Proceedings of the International Conference on Mobile Software Engineering and Systems, 111–122. https://doi.org/10.1145/2897073.2897091

  60. Vidhya, P., Parthipan, V., & Anusuya, S. (2016). Design of green data center. International Journal of Pharmacy and Technology, 8(4). https://doi.org/10.15623/ijret.2014.0305068

  61. Vimal, P. v, & Shivaprakasha, K. S. (2017). IOT based greenhouse environment monitoring and controlling system using Arduino platform. 2017 International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT), 1514–1519. https://doi.org/10.1109/ICICICT1.2017.8342795

  62. Wang, B., Lu, K., Chang, P., & Sun, S. (2015). Multi-terminal monitoring system for campus ecological environment based on sensor network. 2015 10th International Conference on Computer Science Education (ICCSE), 107–110. https://doi.org/10.1109/ICCSE.2015.7250226

  63. Winderbank-Scott, P., & Barnaghi, P. (2017). A Non-invasive Wireless Monitoring Device for Children and Infants in Pre-Hospital and Acute Hospital Environments. 2017 IEEE International Conference on Internet of Things (IThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), 591–597. https://doi.org/10.1109/iThings-GreenCom-CPSCom-SmartData.2017.93

  64. Xu, B., Zheng, J., & Wang, Q. (2016). Analysis and Design of Real-Time Micro-Environment Parameter Monitoring System Based on Internet of Things. 2016 IEEE International Conference on Internet of Things (IThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), 368–371. https://doi.org/10.1109/iThings-GreenCom-CPSCom-SmartData.2016.87

  65. Yadav, R., & Zhang, W. (2017). MeReg: Managing energy-SLA tradeoff for green mobile cloud computing. Wireless Communications and Mobile Computing, 2017. https://doi.org/10.1155/2017/6741972

  66. Zhang, X., Zhang, J., Wang, W., Zhang, Y., Chih-Lin, I., Pan, Z., Li, G., & Chen, Y. (2015). Macro-assisted data-only carrier for 5G green cellular systems. IEEE Communications Magazine, 53(5). https://doi.org/10.1109/MCOM.2015.7105669

  67. Zhang, Y., Li, B., & Sun, Y. (2020). Android Encryption Database Forensic Analysis Based on Static Analysis. Proceedings of the 4th International Conference on Computer Science and Application Engineering. https://doi.org/10.1145/3424978.3425068


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