A collaborative model for post flood activities exploiting an enhanced expanding neighborhood search algorithm

• Main Author: Hasan, Md Munirul
• Format: Thesis
• Language: English
• Published: 2019
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://umpir.ump.edu.my/id/eprint/31122/1/A%20collaborative%20model%20for%20post%20flood%20activities%20exploiting%20an%20enhanced%20expanding%20neighborhood%20search%20algorithm.wm.pdf; http://umpir.ump.edu.my/id/eprint/31122/

Among all natural disasters, flood is considered as the most civilization-destroying disaster which causes considerable damage to all life and property. Every country has its own rescue teams and techniques to minimize the loss and suffering during the flood. Communication and collaboration are one of the major issues for successful performing search and rescue operations during the flood occurrence. Such as, a crucial problem in post-flood recovery actions is the ability to rapidly establish communication and collaboration among rescuers to conduct timely and effective search and rescue (SAR) missions. The cyber-physical system can be incorporated for solving such a challenging task, as the researchers are exploiting it successfully in different domains. This thesis proposes a novel network architecture in the form of a cyber-physical enabled air-ground collaborative model (CP-AGCM). The aim of this model is to extend the proximity service (ProSe) and expand integrated global-local information exchange in the post-flood SAR activities. In this model, exploiting TV White Space spectrum as network backhaul links for acquiring and communicating post-flood emergency data. The primary method of developing the proposed system builds upon a layered architecture of wireless local, regional and wide-area communications, and incorporates collaborative network components among these layers. The desirable functionalities of CP-AGCM are showcased through formulation and development of an efficient global search strategy exploiting a wide range of collaboration among network agents. The experimental results show the proposed collaborative model offers a more resilient communication platform in harsh flood environments, which in turn can significantly improve the number of rescued victims in the simulated SAR activities. The comparative study demonstrates the performance of the proposed model improves 30% compared to the existing model. The network performance (e.g., packet delivery ratio nearing 80-90%) also demonstrates the capability of CP-AGCM to provide ProSe in the post-flood scenarios and optimality of efficient search algorithm.