Current Issue : October - December Volume : 2020 Issue Number : 4 Articles : 5 Articles
In this paper, we propose an indoor visible light communication (VLC) system which makes use of Walsh precoding and multiple\nlight-emitting diodes (LEDs) at the transmitter for multiplexing the data. The proposed VLC system is based on intensity\nmodulation and uses the notion of spatial modulation for communicating the positive and negative values of the synthesized\ntransmit signal using signal processing technique at the transmitter. We also illustrate the flexibility, ability, and easiness of the\nsystem to configure well in a multiuser environment. We have also developed a near-maximum likelihood (ML) detection\ntechnique for efficiently decoding the data bits at the receiver. The proposed near-ML reduces the search space involved in ML\ntechnique by using the initial ZF solution. The results of the simulation studies illustrate that the proposed technique offers a\nhigher data rate and good bit error rate (BER) performance in indoor VLC environments....
Pathfinding is a kind of problem widely used in daily life. It is widely used in\nnetwork games, map navigation and other fields. However, the traditional A*\nalgorithm has some shortcomings, such as heuristic function needs to be designed\naccording to different problems, path has many inflection points, and\nalgorithm stability is poor. B* algorithm also has the shortcoming of inaccurate\npathfinding. In order to solve the problems existing in A* and B* algorithms,\nobstacle avoidance regeneration mechanism, pre-exploration mechanism\nand equivalent waiting strategy are proposed. It adds a bidirectional parallel\nsearch mechanism to form an IBP-B* algorithm (Intelligent bi-directional\nparallel B* routing algorithm). The simulation results show that the speed of\nIBP-B* algorithm is 182% higher than that of A* algorithm and 366% higher\nthan that of BFS algorithm. Meanwhile, compared with B* algorithm, IBP-B*\nalgorithm improves the pathfinding accuracy of the algorithm....
Network performance is of great importance for processing Internet of Things (IoT) applications in the fifth-generation (5G)\ncommunication system. With the increasing number of the devices, how network services should be provided with better\nperformances is becoming a pressing issue. The static resource allocation of wireless networks is becoming a bottleneck for the\nemerging IoT applications. As a potential solution, network virtualization is considered a promising approach to enhancing the\nnetwork performance and solving the bottleneck issue. In this paper, the problem of wireless network virtualization is\ninvestigated where one wireless infrastructure provider (WIP), mobile virtual network operators (MVNOs), and IoT devices\ncoexist. In the system model under consideration, with the help of a software-defined network (SDN) controller, the WIP can\ndivide and reconfigure its radio frequency bands to radio frequency slices. Then, two MVNOs, MVNO1 and MVNO2, can lease\nthese frequency slices from the WIP and then provide IoT network services to IoT users under competition. We apply a twostage\nStackelberg game to investigate and analyze the relationship between the two MVNOs and IoT users, where MVNO1 and\nMVNO2\nfirstly try to maximize their profits by setting the optimal network service prices. Then, IoT users make decisions on\nwhich network service they should select according to the performances and prices of network services. Two competition cases\nbetween MVNO1 and MVNO2 are considered, namely, Stackelberg game (SG) where MVNO1 is the leader whose price of\nnetwork service is set firstly and MVNO2 is the follower whose network service price is set later and noncooperative strategic\ngame (NSG) under which the service prices of MVNO1 and MVNO2 are simultaneously set. Each IoT user decides whether and\nwhich MVNO to select on the basis of the network service prices and qualities. The numerical results are provided to show the\neffectiveness of our game model and the proposed solution method....
Sensor-cloud is a developing technology and popular paradigm for various applications. It integrates wireless sensor into a cloud\ncomputing environment. On the one hand, the cloud offers extensive data storage and analytical and processing capabilities not\navailable in sensor nodes. On the other hand, data distribution (such as time synchronization and configuration files) is always\nan important topic in such sensor-cloud systems, which leads to a rapid increase in energy consumption by sensors. In this\npaper, we aim to reduce the energy consumption of data dissemination in sensor-cloud systems and study the optimization of\nenergy consumption with time-varying channel quality when multiple nodes use the same channel to transmit data. Suppose\nthat there is a certain probability that the nodes send data for competing channel. And then, they decide to distribute data in\nterms of channel quality for saving energy after getting the channel successfully whether or not. Firstly, we construct the\nmaximization problem of average energy efficiency for distributing data with delay demand. Then, this maximization problem\ntransferred an optimal stopping problem which generates the optimal stopping rule. At last, the thresholds of the optimal\ntransmission rate in each period are solved by using the optimal stopping theory, and the optimal energy efficiency for data\ndistribution is achieved. Simulation results indicate that the strategy proposed in this paper can to some extent improve\naverage energy efficiency and delivery ratio and enhance energy optimization effect and network performance compared with\nother strategies....
To obtain precise personalized services in mobile commerce, the users have to disclose their personal information to the operator,\nwhich constitutes a potential threat to their privacy security. In this paper, a mobile commerce privacy security risk assessment\nmodel is established based on information entropy and Markov chain, and effective security risk measurement, and assessment\nmethod is put forward. Our method can provide accurate and quantitative results in assessing privacy disclosure risk to guide\nthe usersâ?? selection of safe mobile commerce applications and protect their privacy security....
Loading....