customer premise equipment

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The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform

Hiroyo Ogawa - One of the best experts on this subject based on the ideXlab platform.

Michiaki Hayashi - One of the best experts on this subject based on the ideXlab platform.

  • optimal virtualization of functionality for customer premise equipment
    International Conference on Communications, 2015
    Co-Authors: Kalika Suksomboon, Masaki Fukushima, Michiaki Hayashi
    Abstract:

    Network function virtualization has been introduced to extend the lifetime of customer premise equipment (CPE). Some functionalities of CPE for serving new service features have been expected to be shifted to a data center. However a lack of network cost analysis causes an argument of the worthiness of this shifting.We propose a determination framework for the functionality virtualization of CPE. Firstly, all functionalities of CPE are transformed to a graph structure. Secondly, the functionality virtualization is determined based on the functionality graph in order to minimize the network cost. The determination problem is formulated as a binary quadratic programming problem; however, searching for the optimal solution is NP-complete. Thus, we propose two heuristic algorithms (i.e., modified Karger's (mKar) and virtualization-cost-based determination (VCD)) to determine which functionality should be virtualized and placed in the data center. This paper performs both theoretical analysis and simulation to evaluate the performance of our algorithms. Those evaluations show that mKar is faster than VCD while VCD provides the solutions closer to the optimum than that of mKar. Conclusive remarks of our findings provide the significant insights into the way of functionality virtualization.

  • ICC - Optimal virtualization of functionality for customer premise equipment
    2015 IEEE International Conference on Communications (ICC), 2015
    Co-Authors: Kalika Suksomboon, Masaki Fukushima, Michiaki Hayashi
    Abstract:

    Network function virtualization has been introduced to extend the lifetime of customer premise equipment (CPE). Some functionalities of CPE for serving new service features have been expected to be shifted to a data center. However a lack of network cost analysis causes an argument of the worthiness of this shifting.We propose a determination framework for the functionality virtualization of CPE. Firstly, all functionalities of CPE are transformed to a graph structure. Secondly, the functionality virtualization is determined based on the functionality graph in order to minimize the network cost. The determination problem is formulated as a binary quadratic programming problem; however, searching for the optimal solution is NP-complete. Thus, we propose two heuristic algorithms (i.e., modified Karger's (mKar) and virtualization-cost-based determination (VCD)) to determine which functionality should be virtualized and placed in the data center. This paper performs both theoretical analysis and simulation to evaluate the performance of our algorithms. Those evaluations show that mKar is faster than VCD while VCD provides the solutions closer to the optimum than that of mKar. Conclusive remarks of our findings provide the significant insights into the way of functionality virtualization.

Zenghua Zhao - One of the best experts on this subject based on the ideXlab platform.

  • design of a novel dynamic trust model for spectrum management in wrans of tv white space
    Journal of Network and Computer Applications, 2017
    Co-Authors: Cong Wang, Zenghua Zhao
    Abstract:

    Abstract The cognitive radio (CR) technique is considered as a better and more efficient answer to the predicament brought by the high demands of wireless communication services and the scarcity or low utilization of frequency spectrum resources. The IEEE 802.22 standard has regulated the wireless regional area networks (WRANs) as one example of the CR networks, which is operating in the television white space (TVWS) spectrum. In the centralized WRANs, the secondary user base station (SUBS) allocates the spectrum holes for the customer premise equipment (CPE) on the basis of the spectrum sensing information from the CPEs around. However, since the CPEs are easy compromised under the varying and uncontrollable environment, the WRANs is subjected to the primary user emulation attacks (PUEA) and the spectrum sensing data falsification (SSDF) attacks, which may lead to a wrong global spectrum decision made by SUBS. A novel dynamic trust model for the SUBS spectrum management based on the subjective logic for the centralized WRANs of TVWS is proposed in this paper. The proposed trust model has a positive impact on reducing the influence of users’ vicious behaviors and encourages the CPEs to participate in truthful actions for communications. The analysis shows that the time complexity of the proposed trust model is O ( n ) . Simulations indicate that the proposed trust model can significantly reduce the probability of the errors by the SUBS in the spectrum decision making.

Kiyoshi Hamaguchi - One of the best experts on this subject based on the ideXlab platform.

Kalika Suksomboon - One of the best experts on this subject based on the ideXlab platform.

  • optimal virtualization of functionality for customer premise equipment
    International Conference on Communications, 2015
    Co-Authors: Kalika Suksomboon, Masaki Fukushima, Michiaki Hayashi
    Abstract:

    Network function virtualization has been introduced to extend the lifetime of customer premise equipment (CPE). Some functionalities of CPE for serving new service features have been expected to be shifted to a data center. However a lack of network cost analysis causes an argument of the worthiness of this shifting.We propose a determination framework for the functionality virtualization of CPE. Firstly, all functionalities of CPE are transformed to a graph structure. Secondly, the functionality virtualization is determined based on the functionality graph in order to minimize the network cost. The determination problem is formulated as a binary quadratic programming problem; however, searching for the optimal solution is NP-complete. Thus, we propose two heuristic algorithms (i.e., modified Karger's (mKar) and virtualization-cost-based determination (VCD)) to determine which functionality should be virtualized and placed in the data center. This paper performs both theoretical analysis and simulation to evaluate the performance of our algorithms. Those evaluations show that mKar is faster than VCD while VCD provides the solutions closer to the optimum than that of mKar. Conclusive remarks of our findings provide the significant insights into the way of functionality virtualization.

  • ICC - Optimal virtualization of functionality for customer premise equipment
    2015 IEEE International Conference on Communications (ICC), 2015
    Co-Authors: Kalika Suksomboon, Masaki Fukushima, Michiaki Hayashi
    Abstract:

    Network function virtualization has been introduced to extend the lifetime of customer premise equipment (CPE). Some functionalities of CPE for serving new service features have been expected to be shifted to a data center. However a lack of network cost analysis causes an argument of the worthiness of this shifting.We propose a determination framework for the functionality virtualization of CPE. Firstly, all functionalities of CPE are transformed to a graph structure. Secondly, the functionality virtualization is determined based on the functionality graph in order to minimize the network cost. The determination problem is formulated as a binary quadratic programming problem; however, searching for the optimal solution is NP-complete. Thus, we propose two heuristic algorithms (i.e., modified Karger's (mKar) and virtualization-cost-based determination (VCD)) to determine which functionality should be virtualized and placed in the data center. This paper performs both theoretical analysis and simulation to evaluate the performance of our algorithms. Those evaluations show that mKar is faster than VCD while VCD provides the solutions closer to the optimum than that of mKar. Conclusive remarks of our findings provide the significant insights into the way of functionality virtualization.