Non Cooperative Behavior Case Study

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3.3 NON-COOPERATIVE BEHAVIOUR The cooperative behaviour of bacteria is beneficial for individuals. There are various non-cooperative behaviour in bacteria they are clashes, competition in growth, cheating. Competition in Growth In limited resources, the bacteria utilize the nutrients, which affect other bacteria’s to live. The scarcity of nutrient resources leads the bacteria to act selfish Fast growth will decrease the productivity of bio-films. Cheating During QS, there exists a reduction in population growth, thus the non-cooperative behaviour will increase the level of cooperative bacteria. The entire bio-film structure will be collapse, when the non-cooperators encountered the cooperative bacteria. 4 SIMULATION AND RESULTS…show more content…
In Fig.4.4, as the density of the Chemo attractant increases, thus it increases the rate of information transfer. The bacteria reach destination successfully by which it sense the gradient if chemo attractant. However, still see the benefits of cooperative signalling, which helps to the directional movement of the bacteria toward the destination. Figure 4.4 Chemo attractant vs successful transmission The relative gain in terms of the successful transmission probability (due to cooperation) with varying chemo attractant density is illustrated. In the low-density conditions, the effect of cooperative communication, the bacteria are unable to sense the chemo attractant gradient effectively, especially when the bacteria are far from the chemo attractant source. In such cases, the cooperative signalling molecules and compensate for the low chemo attractant density, leading to higher gains.…show more content…
The communication medium transfers the bacteria containing information is virtualized in the ns2 simulator. It involves the feasibility of the BN and, additionally, allows developing a Mathematical analysis of the network based on the available information on the biological phenomena. The nano-machine (node) involve as a transceiver by transferring the bacteria (packet) and by gathering the data. In this analysis, expressions for the delay, capacity of bacteria to tumble destination and communication range of the system. Based on the analyses of the bacterial communication was done. The analyzed graph shows that, efficiency of the molecular communication using the bacteria. Using NS2 and MATLAB simulator conducts a performance evaluation based on varying time, distance between source and destination, density of chemical signalling, relation between number of bacteria and gain. Performance analysis for the single link using two nano-machines was done. It is extended for the group of nana-machines and parametric of the behaviour is analyze such as delay, capacity of bacteria to tumble destination and communication range of the

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