澳洲论文代写：流媒体与实时媒体比较
正如在摘要中所提到的，第一个实验的目的是通过测量网络性能参数特征，通过测量在大多数非必要的网络应用程序被关闭时，用户可以使用的各种网络资源的范围和负载。
这对于本实验的目的是至关重要的，因为要对网络性能参数进行分析，必须在记录、记录和量化之后对某个基准进行度量。
第二次测试
第二个实验进行理解中央处理器上的负载的影响后的最终用户连接,包括建立一个安全连接的时间(尽管有问题的应用程序不需要一个安全的主机建立连接,因时不同特点举办手机)来确定网络资源消耗的程度时看YouTube视频。
这个实验的主要内容包括从客户端发送到服务器的字节数(平均)，而跟踪研究则包含在对等对话中。由于节点拥塞在本文的文献综述中也很重要，因此，基于YouTube服务器网络特性中的可用资源，可以对合适的拥塞措施进行参数化。
通过对网络资源的利用，通过对网络资源的利用，通过对网络性能参数的分析，对网络资源的利用进行了分析和分析。其中最突出的网络性能参数如下:
1 .工作交通崩溃
2.大量数据传输的应用
3 .项目交互式web应用程序
4.交通流
5.广域网络位置
澳洲论文代写：流媒体与实时媒体比较
As mentioned in the abstract, the first experiment was conducted with the aim of understanding the network performance parameter characteristics by measuring the extent and load to which various network resources available to the user were being consumed when most the non-essential network applications had been turned off.
This is essential for the purpose of this experiment since the network performance parameters to be analyzed have to be measured against a certain benchmark after they have been recorded, documented and quantified.
Second Test
The second experiment was performed to understand the impact of the load on the central processor of the end-user after the connection has been made, including the time elapsed in establishing a secure connection (though the application in question does not require a secure host for the establishment of a connection, due to which the characteristics differ when hosted over a mobile phone) to determine the extent of network resources being consumed when one is watching a YouTube video.
The major components of the scope of this experiment include the number of bytes sent per packet (on an average) from the client to the server or in the opposite direction, whereas trace studies are included for peer to peer conversations. Since the node congestion is also significant as mentioned in the literature review of this paper, suitable congestion measures will be parameterized based on the resources available within the network characteristics of the YouTube server.
From the trace study, the following inferences can be made of the utilization of network resources, by discussing the following processes and breaking down their salient features to be reflected by suitable network performance parameters. The most salient of these network performance parameters are listed as follows:
1.Traffic breakdown
2.Bulk data transfer applications
3.Interactive web applications
4.Traffic flow
5.Wide-area network locality