The bit error rate attained by is, and the packet corruption probability for is (11).
The packet corruption probability is calculated by the average bit error rate (13).
As a result, increasing the rate adaptation threshold to decrease the packet corruption probability in the channel leads to a better overall performance.
From Equation 10 we can see that τ i depends on the probability of transmission failure p i, f, which is determined with the collision probability p i, c and the corruption probability p i, e.
The packet corruption probability is calculated according to the modulation scheme used in the PHY layer, the distance between the transmitter and the receiver, and the existence of nearby interferer(s).
It embraces the properties like (a) Efficiency: data auditing with least possible computational complexity; (b) Public Verifiability: to allow data auditing process delegation to a trustworthy third-party auditor (TPA) and reducing the computational burden on the client's side; (c) Detection Probability: to check potential data corruption detection probability.
Second, individuals with greater temptation to corruption (a lower probability of getting caught) cooperate less than individuals with lesser temptation (a higher probability of getting caught) or individuals who do not participate in the corruption game.
In doing so, we also test the Beckerian prediction that at the same level of expected payoff, a low probability of detection with high fine is a stronger deterrent to corruption than a high probability of detection with low fine.
First, individuals are exogenously assigned to one of three groups: a corruption game with the probability of getting caught of 25%% (which we denote as the high-monitoring group), a corruption game with the probability of getting caught of 5%% (the low-monitoring group), and a control group not exposed to the corruption game.
Moreover, it reduced the probability that corruption in one dataset propagates to others, thus providing higher structure stability.
