As cyber physical system (CPS) is often used in safety critical areas, any failure on its components could result in a degradation of the physical state, which then causes major harm to life and/or property. Since the concept of dependence leads to that of trust, the components of the CPS should be dependable to each other to deliver the intended services as specified without failing during its operation. In this study, Markov chain is applied to model and analyze the component dependability of the CPSs. Recovery techniques are also proposed to guarantee a high level of dependability to take care of assuring the continuity of system operation.
To avoid unexpected failures of the CPS, due to degradation of its physical component, maintenance could be utilized as a recovery technique to extend its life time. In relation with maintenance as a recovery technique, the effect of involving maintenance is demonstrated during the deterioration state of the physical entity on the availability of the CPS. In addition to that, since reliability and economic factors are of equal importance in maintaining an equipment, the optimum time of the constant-interval for preventive replacement policy is computed as it is suited for complex systems in a manner that minimizes cost.
CPSs with unmanned aerial vehicles(UAVs) could be taken as mobile sensors, and are extensively used for remote sensing in various applications, such as watering plants, agricultural and environmental monitoring. In such kinds of applications, in which WSN technology is an integral component of the CPS design, prolonging the lifetime of the network by reducing sensor nodes power that might be wasted due to data transmission is a challenge as sensor nodes are battery powered and are often difficult to be recharged. Since UAVs replace the multi-hop communication among nodes, they can be utilized as a solution to prolong the life time of the WSNs. However, the network lifetime is extended in exchange for higher data acquisition latency. Heuristic algorithms, such as, Nearest Neighbor heuristic TSP algorithm (NN), have been proposed for reducing the data acquisition latency due to the NP-hardness of the TSP whose computational complexity increases exponentially with the increment of number of sensor nodes. In this study, efficient schemes that modify the previous NN scheme are proposed to gain a reduction in the data acquisition latency with no significant change in computational time. Analytical and simulation results have demonstrated that the proposed schemes outperform the previous NN scheme up to 78.64% in reducing the data acquisition latency.
Among the proposed schemes, the directional NN scheme directed to the next nearest node (DDNN) attains the shortest tour distance. However, the DDNN scheme does not consider the reliability of the system in case of node or link failures. To collect the sensing data rapidly and reliably, the DDNN scheme should be able to react to node or link failures and manage the data transmissions effectively in the network. And hence, an extension of the DDNN scheme, fault tolerable DDNN scheme (FT-DDNN) is proposed to enhance the fault tolerant capability while reducing the data acquisition latency of the UAV. The Performance analyses have demonstrated that the proposed scheme tolerates fault in case of malfunctions of sensors due to node/link failures and improves the detection rate of the DDNN scheme up to 34.93% at the cost of a little bit distance.