Low-complexity Data Collection Scheme for UAV sink nodes in Cellular IoT Networks
ABSTARCT :
Owing to the nature of battery-operated sensors, the residual energy of their battery should be considered when a sink node collects sensory data from them. If a sink attempts to collect data from a sensor that does not have sufficient residual energy to transmit data, the utilization of wireless communication resources may be degraded. However, requiring a periodic residual energy report of the sensors considerably reduces the energy efficiency of them. Consequently, the sink node must be able to estimate the residual energy of the sensors without additional information exchange before attempting to collect data. To tackle this problem, we propose a data collection scheme for mobile sinks in cellular Internet-of-things (IoT) networks. The scheme consists of two phases. In the first phase, the mobile sink estimates the residual energy of the surrounding sensors. To reduce the complexity, we design a state diagram composed of three states based on the Markov chain of the sensor. The sink node calculates the communicable likelihood of each sensor based on the state diagram and collects data from the sensor with the highest likelihood. In the second phase, a cellular base station (BS) selects the appropriate mobile sink to improve the signal-to-interference-plus-noise ratio (SINR) of the signal from a cellular user. Each sink node delivers the bidding price to the BS based on the likelihoods of the sensors. The BS determines an appropriate sink node to allocate resources based on the received bidding prices. Moreover, we show the performance of the proposed method in terms of SINR and IoT network utilization through simulation.
EXISTING SYSTEM :
? This survey focuses on the routing mechanism of WSN-aided target tracking application by presenting the strengths and drawbacks of the existing schemes.
? Instead of providing a comprehensive review of all the existing data-gathering frameworks for each category, this study selects four protocols for static sinks and three protocols for the other two categories to provide the fundamental understanding of each datagathering paradigm.
? Apart from CTP and UEWDC, all the investigated protocols consider network lifetime, and the validation is done by comparing with other existing protocols.
? The network environment is considered to be a rural area with a line-of-sight link, which means that no obstacles exist in the network.
DISADVANTAGE :
? In this way, the directional antenna limits the UAV coverage and overcomes the directional deafness problem.
? Incorporating UAV helps prolong the network lifetime and avoid the energy-hole problem faced by sensor networks.
? We can use intelligent computing methods to lessen the computation time, as discussed in the problem formulation.
? To achieve better network performances in such environments, several issues pertaining to UWSNs must be addressed.
? Considering the advantage of the PRM algorithm in obtaining the shortest collision-free map and that of the ABC in operating and converging quickly, we have addressed the issues of slow convergence and easy entrapment in the locally optimal solutions observed in other algorithms.
PROPOSED SYSTEM :
• This work presents an in-depth discussion on the distributed database management systems proposed for WSNs.
• The research work consolidates data gathering techniques proposed from a different perspective such as networking, compressive sensing, signal processing, and information theory.
• To collect WSN data, both multirotor and fixed-wing UAVs have been proposed in the literature.
• The performance evaluation for small, medium, and large network scenarios demonstrates the efficiency of the proposed method.
• To analyze the delay, we only consider the sink mobility delay of the proposed algorithm.
ADVANTAGE :
? Our performance study based on MATLAB simulations shows that the proposed hybrid path planning algorithm outperforms the conventional algorithms in terms of flight time, energy usage, accuracy, and safety.
? Among the different probabilistic sampling-based algorithms, the PRM is an extremely effective path planning approach due to its probabilistic completeness and remarkable practical performance.
? We have considered some key metrics to evaluate the proposed MAC’s performance and compared it with existing protocols.
? Therefore, in our study, we optimized the UAV velocity during data and non-data collection periods to minimize the total flight time without degrading the network performance.
? The HPP algorithm’s performance depends on the time complexity of the ABC algorithm to generate trajectory points in the dynamic environment.
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