Hierarchical stream merging is a technique for efficiently delivering popular media on demand using multicast and client buffers. Though there has been much theoretical study around the performance of stream merging, implementation issues were rarely discussed. We argue that the frequent alterations of client behavior hinder the feasibility of traditional stream merging methods. To address this problem, we proposed a new algorithm named CIM (Client Initiated Merge). Despite a minor compronk in server throughput, the new approach greatly reduces system complexity and control overhead. Working OD an event-driven mode, it readily accommodates VCR feasuch as jump and stop. Both simulation and experimental results are given, confirming that the sacriiice in overall server cost is trivial in comparison with the advantages it introduceS.
By using WebGIS technology and designing the traceability database of the production, wholesale and sale information of agricultural product, the agricultural product traceability information system based on ArcGIS server is developed and some functions are implemented. Firstly the production place, wholesale place and sale place of the agricultural product is visualized . Then the information of agricultural product is queried and analyzed quickly. At the same time, the shortest path analysis of production place, wholesale place and sale place is implemented. Finally, by using the relationship of production, wholesale and sale of agricultural product, the traceability of agricultural product is researched and implemented.
Multi-QoS and Trusted resource management and Task Scheduling are key problem in cloud computing. This paper presented an effective Multi-QoS and Trusted resource management model and Task Scheduling algorithm in Cloud Computing Environment. By using the idea of fuzzy clustering for reference, the proposed approach can subtly schedule the Cloud tasks to appropriate resources that exactly meets its’ multi-QoS needs of resources. Considering the credibility of cloud resources, the credibility and trusty of task scheduling has been dramatically improved.
Cloud computing has been extensively focused by both industry and academia. Resource management and scheduling is a basic and important problem in cloud computing environment. This paper proposes a new and effective cloud resource management model and scheduling algorithm based on fuzzy clustering and Distributed hash Table. By introducing effective theory and technology, the proposed approach can: (1) subtly assign the appropriate resources to the requestors that exactly satisfy its’ needs of resources, while effectively avoid unreasonable scheduling of resources; (2) rapidly and effectively locate the resources that literally satisfy the needs of the resource requestor. Simulation experiments show that the proposed approach works better than similar algorithms.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.