Ad Hoc Network as a solution in Disaster Management

Whenever some natural disaster occurs, the immediate and most dreadful impact is a communication failure. It can easily be understood that communication systems can make a significant difference between survivals for life and death for those affected areas. In many situations, ad hoc networks have been used for recovery or communication links. The main reason behind the concept is that they are infrastructure less and can adopt any topology. Though in the research arena disaster situations are one of the challenging areas. The situation can be disastrous in many ways, in this paper underwater situation like flood etc. have been considered as a case study. It has been observed that a significant gain in the signal strength ranges from 50% to 70% have been achieved which is quite respectable in disaster situations. The performance has been evaluated in terms of energy and signals gained.

These days underwater networks are established and these are used for many applications. These can be environment monitoring, disaster applications, undersea explorations, assisted navigation, underwater sea space and ocean water level monitoring, etc. Several discrete items, such as batteries, sensors, modems, and robots, cover the underwater network. The major points that come into sight at first instance in case of a disaster are (a) Communication which gets demolished immediately, (b) Data handling in a proper manner, (c) trying visual data capture as much as possible (d) multiple connectivity.
In the case of UWMANET, the network established can be assumed as; Sensor nodes, Gateway nodes, Mobile nodes and Mobile base station node. Firstly, topology can be a major issue in an underwater sensor network. MANET is known for adaptability in any topology. Secondly, the distribution of nodes in an underwater while setting up MANET can be a point. These nodes will be used for underwater communications. Thirdly, in MANET energy is one of the major constraints. This becomes even more important underwater. The proposed plan must take care of the issue that it consumes a very limited amount of energy for reliable data transmission. Lastly, robustness as the network must be able to communicate for a longer time and that too in a stable manner. There should be least malicious nodes. [4,5,6]: This paper has been designed to make use of an ad hoc network as a concept used in one of the solutions. It has been observed that it can be used as a technological tool to boost dying or depleting signals. This concept can be used in recovery operations during a disaster. In this work a new concept has been introduced, this will create a new ad hoc environment, deploy it in critical situations with components available. This will be able to get as many signals as available within the constraints. Rest of paper has been distributed as: section II indicates the problem to set up points. section III is the proposed plan, section IV discusses the results, section V draws the conclusion and section VI discusses the future works.

II. PROBLEM SETUP AND CONCEPT SETUP
In the case of natural disasters, the most common thing that occurs very quickly is network failure and loss of links. The reasons for the failure of communication in disaster situations can be some of the few outlined below as: 1) Network infrastructure gets demaged with the devices for establishing a new network.
2) Cabels and mast gets broken and can be destroyed ofently.
3) Natural phenomemon like rain, fog or heavy smog can innturrupt wireless network signals. 4) Burst of data can create congestion and can be difficult to handle.
The concept was visualized as a research area and some suggestions were introduced for carrying out the problem. Initial setup was for underwater setup and later on, it was generalized for all situations. It is very clear that if setup can work underwater, then it will be able to work in all situations in a better manner. The setup created as shown in  In underwater situations, sensor nodes [7,8,9,10] are deployed, these sensor nodes have a lifetime suitable for communication and are also able to charge using solar light or other mediums. Sensor nodes are stable deployed randomly. Sensor nodes are used to trace any signals, these signals can send to next level suing mobile nodes. The mobile nodes can act as routers as well. These nodes take the data to gateway nodes and these nodes take data to the base station. Transmission speed is approx. 50 kilobits per second (kbps), packet size mostly is 1024 bytes. This data is handled using satellite communication by telecommunication agencies. Comparison based performance (CBR) is adopted as it is used for any type of data for which end-systems require a predictable response time and amount of bandwidth.
Simulation has been done for assessing real-life situations. In case of disaster response, many models have been highlighted. Some most widely used are synthetic, mapbased, and trace-based mobility models [11].
The most used can be identified as synthetic mobility model. Their creation is mostly done using Generator, something like BonnMotion [12]. In this type of model, the case area, i.e. disaster area can be categorized into three parts. One will be designated as an incident site, the other two are casualty and transport. Communication methods built on physical communication infrastructure used to have several limitations. Wireless communication networks have limited range and signal strengths and energy also plays a crucial role in the overall working of the network as well as infrastructure. [13] Another model used is Map-based. As the name suggests it is based on some sort of Global Positioning System (GPS) system or real maps. The map-based scheme uses the realtime centers such as fire station, neighborhood, houses and medical camps for using as infrastructure which is established after the disaster [14]. As is obvious in the application of map-based systems, this is more accurate also, there is another scheme called Trace-based. It is slightly different in the manner that it takes care of the real movements of people. In this case, movements can be obtained using sensors or sort of smartphones.

III. PROPOSED SOLUTION
The ad hoc solution still has been considered as a major solution in rescue operations. It seems that in future whenever some undue disaster happens, the deployment of ad hoc networks [15,16] can be a solution. Various essentials things are categorized as:

A. Antenna
These are deployed to boost dying signals or fading signals. This was essential to provide some sort of communication (if possible). Though many options exist, for the said propose TL-ANT Model was used as shown in Fig.  2. These Antennas are good and suffice the purpose as they can handle the severe conditions like fast winds blowing off the order of around 100 km/hr., dramatic temperature swings. These also have a life of at least 10-20 days without getting destroyed.

B. Carrier
These are needed to carry these antennas to the desired place. The distances can vary. Sometimes 10-20 km distance and sometimes 3 to 10 meters above the earth. It is important that these remain active and for the purpose either solar panel or other media to remain active can be used. The process is difficult and may need Government help. As it requires either air transfer or road transport. As usual, the better way out is to transfer via air media. Cranes can be used as shown in

C. Location finding
The Antennas can communicate about 10-20 km without fail and will be able to gather data and transmit that data. To trace the locations GPS can be used. One of the popular media was Garmin drive 61 lifetime maps + traffic (LMT) and was able to deliver good links. Connections are made using telecommunication agencies working in the area which is vital for internet access and phone services.

D. Recovery Process
The track's location of each antenna is carried out using GPS to bring each safely to the ground from disastrous locations. In addition to this more Wireless Access points can be used for the higher gain in signal quality. This may increase budget issues. In place of these Range extenders can be used. This can be the best solution and also more economical.

IV. RESULTS
A case study has been taken as an example, the area used is 1 kilometer (km) and approx. 72 houses have been used. The simulations have been used to create scenarios. Network Simulator (NS-3) has been used. Houses have been used as Nodes, 100 nodes have been taken as a replacement for 72 houses. Out of 100 nodes, 72 nodes have been connected for communication. The area used is 1.5 km × 1.5 km. Traffic used as CBR, two packet sizes were used as 512 and 1024 bytes.
For the simulation of the underwater sensor network, a scenario was created with 100 underwater sensor nodes, 8 mobile nodes and 1 mobile base node. The simulation area is 1.5 km × 1.5 km, and the transmission range for each node is 400m. For node mobility, random waypoint model has been used and the node speed is 10 meters (m).
To show the loss or gain of energy the unit "decibel" is used.

dB = 10log10 P2/P1 where P1 -input signal and P2 -output signal
When the experiment was carried out in the given area as shown in Table I, There has been a significant gain in signal strengths. In the simulation the situation was changed to normal, i.e. no initial energy was given and no sensors were used, it was just like a natural disaster situation. Not underwater, it was a general situation. It was seen that signal gain was remarkable and if possible the system will be able to transmit dying or depleting signals even after 3-4 hours of signal loss. In this case, initial signal strength was allocated to check the gain in signal strength as shown in Table II as signal strength gain. The energy required by the nodes to operate is high [19] regardless of any protocol used. It has been observed that the energy required is more when there is a requirement of signals and the signal strength weakens with loss of energy. It has been analysed that antenna gain is expressed in decibels. In this case 'i' means isotropic. This factor means that the change in power is referenced with respect to an isotropic radiator. dBi is the gain of an antenna system relative to an isotropic radiator at radio frequencies. Gain shown in two tables is in dBi. This gain reflects antennas ability to direct signals in a particular direction. The gain is substantial. More work is going on to find packet delivery and delay. In the present work, in the worst situations, the gain was approx. 50 percent, while in some cases when one or more powerful antennas were added, it reached a maximum of 70 percent.

V. CONCLUSION
An analysis has been done starting with the underwater problem of data depletion to general disastrous situations. A general solution has been proposed. This will take care of situations that come under the category of disaster and sudden loss of signal or communication. It has been observed in the study that proper antenna insertions are a vital matter. At times it actually can change the scenario a lot. It was observed that a gain in signal strength of more than 70% can be achieved. This process can be adopted at a mass scale in case of disasters and lives can be saved.

VI. FUTURE WORK
In maximum situations, evaluations presented in literature have been confined to only one disaster scene. While there can be various situations like an earthquake, a volcano, a tsunami, and a hurricane. So more realistic scenarios should be there for evaluations.
Simulations and system's performance have not evaluated in the re-life scenarios. Evaluation can be done with particle requirements on these systems where a disaster situation occurs and can be accessed with better clarity and advantage.
Deploying the automated WSN is the area to be researched more as manual placement of the nodes in a disaster situation can be difficult. This applies to both before or after the disaster.
This research work undergo with the static nodes, it is unclear the actual performance of the proposed work with mobile nodes. The study needs to be further done with the mobile nodes.
Existing works are there providing feasibility and other different ad hoc networks in a unique system though further research is required to find the optimal solution.