This paper presents a methodology for evaluating the performance of forwarding strategies for location management in a personal communication services (PCS) mobile network. A forwarding strategy in the PCS network can be implemented by two mechanisms: a forwarding operation which follows a chain of databases to locate a mobile user and a resetting operation which updates the databases in the chain so that the current location of a mobile user can be known directly without having to follow a chain of databases. In this paper, we consider the PCS network as a server whose function is to provide services to the mobile user for 'updating the location of the user as the user moves across a database boundary' and 'locating the mobile user'. We use a Markov chain to describe the behavior of the mobile user and analyze the best time when forwarding and resetting should be performed in order to optimize the service rate of the PCS network. We demonstrate the applicability of our approach with hexagonal and mesh coverage models for the PCS network and provide a physical interpretation of the result.
In this article, we propose and analyze dynamic redundancy management of integrated intrusion detection and tolerance for lifetime maximization of homogeneous clustered wireless sensor networks (WSNs). We take a holistic approach of integrating multisource and multipath routing for intrusion tolerance with majority voting for intrusion detection in our redundancy management protocol design. By dynamically controlling the redundancy level for both multisource multipath routing and voting-based intrusion detection with energy consideration, we identify the optimal redundancy level to be applied to maximize the WSN lifetime in response to changing environment conditions including node density, radio range, and node capture rate. We demonstrate the effectiveness of our integrated redundancy management protocol by a comparative analysis with a multisource multipath routing algorithm called AFTQC that considers only fault/intrusion tolerance.
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