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To improve the end-to-end Successful Delivery Probability(SDP) of mobile nodes in opportunistic network,hybrid Opportunistic Network(OppNet) architecture using Fix Infrastructure Nodes(FINs) is proposed.As enhanced OppNet serving for special users,the network planning and design should take user’s mobility behavior into account.We adopt collected users’ mobility records,analyze users’ stay pattern,and establish Message Exchange Points(MEPs) where FINs should be installed.Our solution includes MEPs detection algorithm,Maximum end-to-end Success Delivery Probability(MSDP) detection algorithm,and simulated annealing algorithm.After data preprocessing,MEPs detection algorithm detects feasible locations from users’ trajectory records where not more than one user visit frequently.End to end SDPs of these feasible MEPs are evaluated using MSDP detection algorithm.To reduce the computation complexity,a simulated annealing algorithm to select optimal FIN locations in a large number of feasible MEPs is given.The evaluation experiments based on reallife trajectory dataset verify our proposal can achieve better E2 E SDP gain than “most visitors” strategy and “max residence probability” strategy.
To improve the end-to-end Successful Delivery Probability (SDP) of mobile nodes in opportunistic network, Hybrid Opportunistic Network (OppNet) architecture using Fix Infrastructure Nodes (FINs) is proposed. Aspect OppNet serving for special users, the network planning and design attracts user’s mobility behavior into account. We adoplected users ’mobility records, analyze users’ stay pattern, and establish Message Exchange Points (MEPs) where FINs should be installed. Our solution includes MEPs detection algorithm, Maximum end-to-end Success Delivery Probability (MSDP) detection algorithm, and simulated annealing algorithm. After data preprocessing, MEPs detection algorithm detects feasible locations from users’ trajectory records where not more than one user visit frequently. End to SDPs of these MEPs are evaluated using MSDP detection algorithm. To reduce the computation complexity, a simulated annealing algorithm to select optimal FIN locations in a large number of feasible MEPs is given. The evaluation experiments based on reallife trajectory dataset verify our proposal can achieve better E2E SDP gain than “most visitors ” strategy and “max residence probability ” strategy.