Current Issue : January - March Volume : 2021 Issue Number : 1 Articles : 5 Articles
Leach (low energy adaptive clustering hierarchy) algorithm is a self-clustering topology algorithm. Its execution process is cyclical.\nEach cycle is divided into two phases: cluster building phase and stable data communication phase. In the stage of cluster building,\nthe adjacent nodes cluster dynamically and randomly generate cluster heads. In the data communication phase, the nodes in the\ncluster send the data to the cluster head, and the cluster head performs data fusion and sends the results to the aggregation node.\nBecause the cluster head needs to complete data fusion, communication with the convergence node and other works, the energy\nconsumption is large. Leach algorithm can ensure that each node acts as cluster head with equal probability, so that the nodes in\nthe network consume energy relatively evenly. The basic idea of Leach algorithm is to randomly select cluster head nodes in a\ncircular way. It evenly distributes the energy load of the whole network to each sensor node in the network. It can reduce network\nenergy consumption and improve network life cycle. Leach repeatedly performs cluster refactoring during its operation. This\npaper studies the parameter detection of wireless sensor network based on Leach algorithm on the on-chip embedded debugging\nsystem. Because the classical low-power adaptive clustering layered protocol (Leach) has the problem of energy imbalance and\nshort node life cycle, this paper uses embedded debugging technology based on Leach algorithm and the residual energy and\nposition of nodes in wireless sensor networks were tested for research. This Leach algorithm uses the concept of wheel. Each round\nconsists of two phases: initialization and stabilization. In the initialization stage, each node generates a random number between 0\nand 1. If the random number generated by a node is less than the set threshold T (n), the node publishes a message that it is a\ncluster head. Through the research on the parameter detection, the simulation results show that the research in this paper has good\nfeasibility and rationality....
One of the most important problems of data transmission in packet networks, in particular\nin wireless sensor networks, are periodic overflows of buffers accumulating packets directed to a\ngiven node. In the case of a buffer overflow, all new incoming packets are lost until the overflow\ncondition terminates. From the point of view of network optimization, it is very important to know the\nprobabilistic nature of this phenomenon, including the probability distribution of the duration of the\nbuffer overflow period. In this article, a mathematical model of the node of a wireless sensor network\nwith discrete time parameter is proposed. The model is governed by a finite-buffer discrete-time\nqueueing system with geometrically distributed interarrival times and general distribution of\nprocessing times. A system of equations for the tail cumulative distribution function of the first\nbuffer overflow period duration conditioned by the initial state of the accumulating buffer is\nderived. The solution of the corresponding system written for probability generating functions\nis found using the analytical approach based on the idea of embedded Markov chain and linear\nalgebra. Corresponding result for next buffer overflow periods is obtained as well. Numerical study\nillustrating theoretical results is attached....
This paper investigates a secure wireless-powered sensor network (WPSN) with the aid of a cooperative jammer (CJ). A power\nstation (PS) wirelessly charges for a user equipment (UE) and the CJ to securely transmit information to an access point (AP) in\nthe presence of multiple eavesdroppers. Also, the CJ are deployed, which can introduce more interference to degrade the\nperformance of the malicious eavesdroppers. In order to improve the secure performance, we formulate an optimization\nproblem for maximizing the secrecy rate at the AP to jointly design the secure beamformer and the energy time allocation. Since\nthe formulated problem is not convex, we first propose a global optimal solution which employs the semidefinite programming\n(SDP) relaxation. Also, the tightness of the SDP relaxed solution is evaluated. In addition, we investigate a worst-case scenario,\nwhere the energy time allocation is achieved in a closed form. Finally, numerical results are presented to confirm effectiveness of\nthe proposed scheme in comparison to the benchmark scheme....
Water quality monitoring (WQM) systems seek to ensure high data precision, data accuracy, timely reporting, easy accessibility of\ndata, and completeness. The conventional monitoring systems are inadequate when used to detect contaminants/pollutants in real\ntime and cannot meet the stringent requirements of high precision forWQMsystems. In this work, we employed the different types\nof wireless sensor nodes to monitor the water quality in real time. Our approach used an energy-efficient data transmission schedule\nand harvested energy using solar panels to prolong the node lifetime. The study took place at the Weija intake in the Greater Accra\nRegion of Ghana. The Weija dam intake serves as a significant water source to the Weija treatment plant which supplies treated\nwater to the people of Greater Accra and parts of Central regions of Ghana. Smart water sensors and smart water ion sensor\ndevices from Libelium were deployed at the intake to measure physical and chemical parameters........
Wireless sensor networks as the base support for the Internet of things have been a large number of popularity and application.\nSuch as intelligent agriculture, we have to use the sensor network to obtain the growing environment data of crops and others.\nHowever, the difficulty of power supply of wireless nodes has seriously hindered the application and development of Internet of\nthings. In order to solve this problem, people use low-power sleep scheduling and other energy-saving methods on the nodes.\nAlthough these methods can prolong the working time of nodes, they will eventually become invalid because of the exhaustion\nof energy. The use of solar energy, wind energy, and wireless signals in the environment to obtain energy is another way to solve\nthe energy problem of nodes. However, these methods are affected by weather, environment, and other factors, and they are\nunstable. Thus, the discontinuity work of the node is caused. In recent years, the development of wireless power transfer (WPT)\nhas brought another solution to this problem. In this paper, a three-layer framework is proposed for mobile station data\ncollection in rechargeable wireless sensor networks to keep the node running forever, named TLFW which includes the sensor\nlayer, cluster head layer, and mobile station layer. And the framework can minimize the total energy consumption of the system.\nThe simulation results show that the scheme can reduce the energy consumption of the entire system, compared with a Mobile\nStation in a Rechargeable Sensor Network (MSiRSN)....
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