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Directed Diffusion based on weighted Grover’s Quantum Algorithm (DWGQ)
Abstract and Figures
Wireless sensor networks (WSN) have become involved in many different areas such as military, disaster management, and many other civic uses. So, improving the overall performance of the network is very necessarily to achieve the desired aim. One of the most famous protocols that used in wireless sensor networks is the Directed Diffusion protocol. Also, Quantum computing is a new field in computer science and it tries to speed up the process of any computation by parallelizing the work using the same hardware. Therefore, in this study a comparison is conducted between the classical Directed Diffusion Protocol and the proposed protocol that based on the weighted Grover's Quantum Algorithm. An example of the proposed solution shows that our protocol is performing much better in case of end-to-end delay and power consumption.
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... This solution uses such techniques as data aggregation and congestion management in order to balance the traffic uniformly, which helps in balancing the load on sensor nodes and thus, increases the network lifetime [17]. The LEACH routing algorithm is characterized as hierarchical and is designed to gather and receive data from and to the sink node, which essentially acts as a base station for ad-hoc networks [18,19]. PEGASIS and LEACH algorithms are similar. ...
... For bottleneck prediction throughout network lifetime, sensors are controlled via monitoring buffer capacity and channel usage. On the other hand, congestion management and avoidance mechanisms can increase the performance of network and balance traffic load in multi-hop routing [18]. ...
The Wireless Sensor Networks (WSNs) consist of many sensor nodes which are vital to various applications in our daily lives. Load-balancing is a key challenge for WSNs. Improving load-balancing can help with controlling traffic, saving energy and eventually, resulting in a better lifetime. In this paper, a modification of the Energy Efficient Credit-Based (EECB) routing algorithm is proposed, which selects optimal routes based on the priority of relay nodes using Markov Decision Process (MDP). Simulation results demonstrate that the proposed algorithm achieves better load-balancing, better lifetime, and lower energy consumption, at the expense of slightly higher packet loss and lower data delivery rate. The results are presented in comparison with the commonly used Low-Energy Adaptive Clustering Hierarchy (LEACH) algorithm.
... If |Φ is equal to the superposition state, |q , after some iterations, then the success probability should be equal to one, which means ( q|Φ ) 2 = 1. The success probability can be illustrated after t Grover iterations, as follows [44]: ...
Clustering is an effective topology control approach that evenly distributes loads across sensor nodes, enhances network scalability, and increases the lifetime in wireless sensor networks. In this paper, we propose a novel energy-efficient weighted cluster head (CH) selection approach that improves the overall performance of the network and increases energy efficiency. An optimization strategy is proposed that emphasizes adjusting the transmission range with the appropriate node density, which increases energy efficiency for intra- and inter-cluster communications to 86% and 97%, respectively. In addition, the implementation of a quantum search algorithm for choosing the CH is explained. Compared to the classical method such as EECS and HEED, the proposed quantum search algorithm has a quadratic speed-up advantage. The classical search algorithm requires N steps to find a specific element in an array of N elements, but instead of using a classical algorithm, Grover’s quantum search algorithm minimizes the complexity to O ( N ). In this work, an energy-efficient cluster head selection approach is illustrated through a classical weighted clustering algorithm, and its implementation is also extended through a quantum weighted search algorithm which is demonstrated by the simulation results.
... On the other hand, in [46][47][48][49][50][51][52] are demonstrate improvements in Grover's algorithm and its applications on directed diffusion, in the distributed geometric machine, comparing two Data-Encoding Methods on Quantum Costs, in numerical Quantum Optimal Control, and Quantum Cryptanalysis. ...
Classical computing there are multiple algorithms to efficiently locate a certain element within a disorganized database; however, quantum computing can be applied more assertively in the face of problems in which it is complicated to verify a solution and at the same time to test multiple and possible solutions. Therefore, this article presents an introduction to Quantum Computing, developing some concepts of quantum formalism, and then approach Grover's algorithm which exploits the principle of superposition to the maximum. Finally, a classic simulation of this algorithm is performed, and the results obtained are compared with classical. Current position: Professor at Universidad Distrital Francisco José de Caldas, Colombia. algorithms such as sequential search and binary search method. A 95% is obtained as a result of greater effectiveness in times-when solving the same search-, revealing the potential advantages of quantum computing. Resumen: En la computación clásica existen múltiples algoritmos para localizar de manera eficiente un determinado elemento dentro de una base de datos desorganizada; sin embargo, la computación cuántica puede aplicarse de manera más asertiva frente a tales problemas cuando es complejo verificar una solución y a la vez probar múltiples y posibles soluciones. Por lo anterior, en este artículo se presenta una introducción a la Computación Cuántica-desarrollando algunos conceptos del formalismo cuántico-, y luego se aborda el algoritmo de Grover el cual explota al máximo el principio de superposición. Finalmente se realiza una simulación clásica de dicho algoritmo, y los resultados obtenidos se comparan con otros algoritmos clásicos como el método de búsqueda lineal y búsqueda binaria. Se obtiene como resultado un %95 de mayor efectividad en tiempos-a la hora de resolver la misma búsqueda-, logrando poner de manifiesto las ventajas potenciales de la computación cuántica.
Information technology has been focused to estimate growth degree of plants in agriculture. This paper focuses on leaf temperature that changes according to the activity of photosynthesis. Infrared cameras are a major method to measure leaf temperature in conventional methods. However, the expensive device price causes difficulty to install many sensors in practical fields. Infrared radiation sensors are new candidate device to estimate growth state by measuring leaf temperature. Since the price of infrared radiation sensors is inexpensive, we can install a lot of sensors into fields. Additionally, the consumed power of infrared radiation sensors is relatively small comparing to Infrared cameras. These features of infrared radiation sensors are appropriate for sensor networks working with a battery. This paper proposes a field sensor network to measure growth state of plants by infrared radiation sensors. Our goal is to realize a practical and inexpensive sensor network system with typical system on chip (SoC). Therefore, we employ a reasonable price SoC supporting IEEE 802.15.4 standard to design a unique device with various sensors. In order to realize multi-hop communication with low-power consumption, we propose a routing and media access control mechanisms for the developed system. The media access control technology realizes periodic sleep operation of all devices to enable long-term operation of the system. The routing control technology can construct a multi-hop network with the minimum number of hops. The experimental results demonstrated that the development system works in the practical fields.
Wireless sensor networks consist of small nodes with sensing, computation, and wireless communications capabilities. Many routing, power management, and data dissemination protocols have been specifically designed for WSNs where energy awareness is an essential design issue. Routing protocols in WSNs might differ depending on the application and network architecture. In this article we present a survey of state-of-the-art routing techniques in WSNs. We first outline the design challenges for routing protocols in WSNs followed by a comprehensive survey of routing techniques. Overall, the routing techniques are classified into three categories based on the underlying network structure: flit, hierarchical, and location-based routing. Furthermore, these protocols can be classified into multipath-based, query-based, negotiation-based, QoS-based, and coherent-based depending on the protocol operation. We study the design trade-offs between energy and communication overhead savings in every routing paradigm. We also highlight the advantages and performance issues of each routing technique. The article concludes with possible future research areas.
Advances in processor, memory and radio technology will enable small and cheap nodes capable of sensing, communication and computation. Networks of such nodes can coordinate to perform distributed sensing of environmental phenomena. In this paper, we explore the directed diffusion paradigm for such coordination. Directed diffusion is datacentric in that all communication is for named data. All nodes in a directed diffusion-based network are application-aware. This enables diffusion to achieve energy savings by selecting empirically good paths and by caching and processing data in-network. We explore and evaluate the use of directed diffusion for a simple remote-surveillance sensor network.
In Mobile Ad-hoc Networks (MANETs), routing protocols directly affect various indices of network Quality of Service (QoS), so they play an important role in network performance. To address the drawbacks associated with traditional routing protocols in MANETs, such as poor anti-fading performance and slow convergence rate, for basic Dynamic Source Routing (DSR), we propose a new routing model based on Grover's searching algorithm. With this new routing model, each node maintains a node vector function, and all the nodes can obtain a node probability vector using Grover's algorithm, and then select an optimal routing according to node probability. Simulation results show that compared with DSR, this new routing protocol can effectively extend the network lifetime, as well as reduce the network delay and the number of routing hops. It can also significantly improve the anti-jamming capability of the network.
The current Grover quantum searching algorithm cannot identify the difference in importance of the search targets when it is applied to an unsorted quantum database, and the probability for each search target is equal. To solve this problem, a Grover searching algorithm based on weighted targets is proposed. First, each target is endowed a weight coefficient according to its importance. Applying these different weight coefficients, the targets are represented as quantum superposition states. Second, the novel Grover searching algorithm based on the quantum superposition of the weighted targets is constructed. Using this algorithm, the probability of getting each target can be approximated to the corresponding weight coefficient, which shows the flexibility of this algorithm. Finally, the validity of the algorithm is proved by a simple searching example.
The multidisciplinary field of quantum computing strives to exploit some of the uncanny aspects of quantum mechanics to expand our computational horizons. Quantum Computing for Computer Scientists takes readers on a tour of this fascinating area of cutting-edge research. Written in an accessible yet rigorous fashion, this book employs ideas and techniques familiar to every student of computer science. The reader is not expected to have any advanced mathematics or physics background. After presenting the necessary prerequisites, the material is organized to look at different aspects of quantum computing from the specific standpoint of computer science. There are chapters on computer architecture, algorithms, programming languages, theoretical computer science, cryptography, information theory, and hardware. The text has step-by-step examples, more than two hundred exercises with solutions, and programming drills that bring the ideas of quantum computing alive for today's computer science students and researchers.
Advances in processor, memory and radio technology will enable small and cheap nodes capable of sensing, communication and computation. Networks of such nodes can coordinate to perform distributed sensing of environmental phenomena. In this paper, we explore the directed diusion paradigm for such coordination. Directed diusion is datacentric in that all communication is for named data. All nodes in a directed diusion-based network are applicationaware. This enables diusion to achieve energy savings by selecting empirically good paths and by caching and processing data in-network. We explore and evaluate the use of directed diusion for a simple remote-surveillance sensor network. 1 Introduction In the near future, advances in processor, memory and radio technology will enable small and cheap nodes capable of wireless communication and signicant computation. The addition of sensing capability to such devices will make distributed microsensing|an activity in which a collection of ...
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