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Resource allocation is an important problem in ubiquitous network. Most of the existing resource allocation methods considering only wireless networks are not suitable for the ubiquitous network environment, and they will harm the interest of individual users with instable resource requirements. This paper considers the multi-point video surveillance scenarios in a complex network environment with both wired and wireless networks. We introduce the utility estimated by the total costs of an individual network user. The problem is studied through mathematical modeling and we propose an improved problem-specific branch-and-cut algorithm to solve it. The algorithm follows the divide-and-conquer principle and fully considers the duality feature of network selection. The experiment is conducted by simulation through C and Lingo. And it shows that compared with a centralized random allocation scheme and a cost greed allocation scheme, the proposed scheme has better per- formance of reducing the total costs by 13.0% and 30.6% respectively for the user.
Resource allocation is an important problem in ubiquitous network. Most of the existing resource allocation methods considers only wireless networks are not suitable for the ubiquitous network environment, and they will harm the interest of individual users with instable resource requirements. This paper considers the multi- point video surveillance scenarios in a complex network environment with both wired and wireless networks. We introduce the utility estimated by the total costs of an individual network user. The problem is studied through mathematical modeling and we propose an improved problem-specific branch-and- cut algorithm to solve it. The algorithm follows the divide-and-conquer principle and fully considered the duality feature of network selection. The experiment is conducted by simulation through C and Lingo. And it shows that compared with a centralized random allocation scheme and a cost greed allocation scheme, the proposed scheme has better per-formance of reducing t he total costs by 13.0% and 30.6% respectively for the user.