Capacity Upper Bound of Channel Assembling in Cognitive Radio Networks with Quasistationary Primary User Activities

In cognitive radio networks (CRNs) with multiple channels, various channel-assembling (ChA) strategies may be applied to secondary users (SUs), resulting in different achieved capacity. However, there is no previous work on determining the capacity upper bound (UB) of ChA for SUs under given system configurations. In this paper, we derive the maximum capacity for CRNs with ChA through Markov chain modeling, considering that primary user (PU) activities are relatively static, compared with SU services. We first deduce a closed-form expression for the maximum capacity in a dynamic ChA strategy and then demonstrate that no other ChA strategy can provide higher capacity than that achieved by this dynamic strategy. © 2012 IEEE.The work of L. Jiao and F. Y. Li was supported in part by the Research Council of Norway through the ECO-boat MOL project under Grant 210426. The work of E. Song was supported in part by the National Natural Science Foundation of China under Grant 60901037 and in part by the Foundation for Basic Research of Sichuan University for Distinguished Young Scholars under Grant 0082604132188. The work of V. Pla was supported by the Spanish Ministerio de Ciencia e Innovacion through Project TIN2010-21378-C02-02. The review of this paper was coordinated by Prof. B. Hamdaoui.Jiao, L.; Song, E.; Pla, V.; Li, FY. (2013). Capacity Upper Bound of Channel Assembling in Cognitive Radio Networks with Quasistationary Primary User Activities. IEEE Transactions on Vehicular Technology. 62(4):1849-1855. https://doi.org/10.1109/TVT.2012.2236115S1849185562

Greedy versus Dynamic Channel Aggregation Strategy in CRNs: Markov Models and Performance Evaluation

Publishes version of a paper from the book: Networking 2011 Workshops. Also available f rom the publisher on SpringLink:http://dx.doi.org/10.1007/978-3-642-23041-7_3In cognitive radio networks, channel aggregation techniques which aggregate several channels together as one channel have been proposed in many MAC protocols. In this paper, we consider elastic data traffic and spectrum adaptation for channel aggregation, and propose two new strategies named as Greedy and Dynamic respectively. The performance of channel aggregation represented by these strategies is evaluated using continuous time Markov chain models. Moreover, simulation results based on various traffic distributions are utilized in order to evaluate the validity and preciseness of the mathematical models

Job shop scheduling with artificial immune systems

The job shop scheduling is complex due to the dynamic environment. When the information of the jobs and machines are pre-defined and no unexpected events occur, the job shop is static. However, the real scheduling environment is always dynamic due to the constantly changing information and different uncertainties. This study discusses this complex job shop scheduling environment, and applies the AIS theory and switching strategy that changes the sequencing approach to the dispatching approach by taking into account the system status to solve this problem. AIS is a biological inspired computational paradigm that simulates the mechanisms of the biological immune system. Therefore, AIS presents appealing features of immune system that make AIS unique from other evolutionary intelligent algorithm, such as self-learning, long-lasting memory, cross reactive response, discrimination of self from non-self, fault tolerance, and strong adaptability to the environment. These features of AIS are successfully used in this study to solve the job shop scheduling problem. When the job shop environment is static, sequencing approach based on the clonal selection theory and immune network theory of AIS is applied. This approach achieves great performance, especially for small size problems in terms of computation time. The feature of long-lasting memory is demonstrated to be able to accelerate the convergence rate of the algorithm and reduce the computation time. When some unexpected events occasionally arrive at the job shop and disrupt the static environment, an extended deterministic dendritic cell algorithm (DCA) based on the DCA theory of AIS is proposed to arrange the rescheduling process to balance the efficiency and stability of the system. When the disturbances continuously occur, such as the continuous jobs arrival, the sequencing approach is changed to the dispatching approach that involves the priority dispatching rules (PDRs). The immune network theory of AIS is applied to propose an idiotypic network model of PDRs to arrange the application of various dispatching rules. The experiments show that the proposed network model presents strong adaptability to the dynamic job shop scheduling environment.postprin

A vision-based optical character recognition system for real-time identification of tractors in a port container terminal

Automation has been seen as a promising solution to increase the productivity of modern sea port container terminals. The potential of increase in throughput, work efficiency and reduction of labor cost have lured stick holders to strive for the introduction of automation in the overall terminal operation. A specific container handling process that is readily amenable to automation is the deployment and control of gantry cranes in the container yard of a container terminal where typical operations of truck identification, loading and unloading containers, and job management are primarily performed manually in a typical terminal. To facilitate the overall automation of the gantry crane operation, we devised an approach for the real-time identification of tractors through the recognition of the corresponding number plates that are located on top of the tractor cabin. With this crucial piece of information, remote or automated yard operations can then be performed. A machine vision-based system is introduced whereby these number plates are read and identified in real-time while the tractors are operating in the terminal. In this paper, we present the design and implementation of the system and highlight the major difficulties encountered including the recognition of character information printed on the number plates due to poor image integrity. Working solutions are proposed to address these problems which are incorporated in the overall identification system.postprin