As an auxiliary facility, roadside units (RSUs) can well improve the shortcomings incurred by ad hoc networks and promote network performance in a vehicular ad hoc network (VANET). However, deploying a large number of RSUs will lead to high installation and maintenance costs. Therefore, trying to find the best locations is a key issue when deploying RSUs with the set delay and budget. In this paper, we study the delay-bounded and cost-limited RSU deployment (DBCL) problem in urban VANET. We prove it is non-deterministic polynomial-time hard (NP-hard), and a binary differential evolution scheme is proposed to maximize the number of roads covered by deploying RSUs. Opposite-based learning is introduced to initialize the first generation, and a binary differential mutation operator is designed to obtain binary coding. A random variable is added to the traditional crossover operator to increase population diversity. Also, a greedy-based individual reparation and promotion algorithm is adopted to repair infeasible solutions violating given constraints, and to gain optimal feasible solutions with the compromise of given limits. Moreover, after selection, a solution promotion algorithm is executed to promote the best solution found in generation. Simulation is performed on analog trajectories sets, and results show that our proposed algorithm has a higher road coverage ratio and lower packet loss compared with other schemes.
With the development and popularization of cloud storage technology, cloud storage has become a main method of data storage. Aiming at the problem of large delay and low availability incurred by multiple invalid nodes in cloud storage, a new type of concurrent nodes repair scheme called Distributed-Cross Repair Solution (DCRS) is proposed. In this scheme, system repair operation is performed in replacement nodes, and all of the replacement nodes cooperatively and crossly repair data to ensure that the data blocks that are required for repairing are only transmitted once within the system. This will solve the system repair bottleneck in the traditional repair scheme and resolve the problem of large internal network throughput and other problems, which can effectively reduce the repair delay of the system. At the same time, the repair trigger mechanism is adopted in order to avoid the repair failure problem caused by the coming of additional damaged nodes during the system reparation, which increases the system’s reliability. The simulation results show that the DCRS has obvious effects in reducing system repair delay and increasing system availability.
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