In this chapter, the author first outline the fundamentals of networking in Section 1.1 with different network models. Starting from small-size networks, Section 1.2 will discuss local area network (LAN) for limited geographic area with variant topologies, technologies and access mechanisms. Section 1.3 will then consider wide area network (WAN) for a large geographic area, where the author will highlight some well-known WAN devices and topologies along with relevant technologies over network media. In order to model the communications between different devices in different networks, a reference model or framework is required. Section 1.4 will provide a brief explanation of seven layers in open systems interconnection (OSI) framework. As the most widely used protocol over the Internet, Transmission Control Protocol/Internet Protocol (TCP/IP) suite with a variety of communication protocols will be presented in Section 1.5. A brief account of internetworks and internetworking units will be explained in Section 1.6 where I will show the functionalities of intermediary devices for computer networking, including repeaters/hubs, bridges/switches, and routers/gateways.

In this chapter, the author will first present in Section 3.1 an overview of IP addresses with various types and addressing mechanisms. The first version of IP addresses, namely, IP version 4 (IPv4) will be discussed in Section 3.2 followed by various mechanisms for dividing the network with subnetting in Sections 3.3 and 3.4 as well as how to group the small networks via supernetting in Section 3.5. A brief introduction of the extended version of IP addressing called IP version 6 (IPv6) will be described in Section 3.6 along with discussions for further readings.

In this chapter, the author will first introduce various network services and requirements in Section 5.1. Service characteristics and levels will be described in Section 5.2 along with discussion on requirements of service performance. Section 5.3 will provide detailed steps of requirement analysis process where user, application, host, and network requirements will be sequentially presented in Sections 5.4-5.7. A typical requirement analysis model will be developed in Section 5.8. This chapter further provides analyses of reliability, maintainability, and availability (RMA) of the network and its components in Section 5.9.

In order to validate the effectiveness of a network design, its performance needs to be evaluated. In general, there are three approaches to evaluate the network performance, including benchmarking, simulation, and analytical modeling. In this chapter, the author will sequentially discuss these three approaches along with their merits and demerits as well as their applications. Section 7.1 will first present the benchmarking technique, followed by the introduction of simulation and analytical modeling approaches in Sections 7.2 and 7.3, respectively. Also, in this chapter, a typical system and its component will be provided in Section 7.4 as illustrations of different performance-evaluation techniques.

In practical networks, most of the parameters are random and variant over time. Statistical models are crucial in network simulation to represent the real network. Specifically, queuing systems have been developed as a statistical model of the waiting lines in telecommunication networks. In this chapter, I will first introduce statistical models used for modeling queuing systems with different distribution types in Section 9.1. Section 9.2 will present Poisson point process (PPP) and its variants including homogeneous PPP and inhomogeneous PPP which have been well developed to model the number of events occurred in the statistical models. This chapter will be closed by outlining detailed steps for developing input models in Section 9.3, which include data collection, distribution identification, parameter estimation, and testing.

In network modeling and simulation, a real network can be represented via statistical models. Due to the randomness of the phenomenon, possible outcomes of the event can be assigned by a real number of random quantity which is known as a random variable. The random variable is specified by a probability distribution. Depending on the data type of the random quantity, we have two kinds of random variables including discrete and continuous random variables. In this chapter, the author will first introduce the basic concepts of random variables in Section 11.1. Discrete and continuous random variables will be sequentially presented in Sections 11.2 and 11.3. Specifically, distribution functions, mean, variance, and moments will be discussed for each random variable type.

This chapter will discuss various families of continuous random variables and their applications in modeling and validating random events. In this chapter, I will first provide a review of formulas related to continuous random variables in Section 13.1. Then, various kinds of continuous random variables, including uniform, exponential, Erlang, normal, and lognormal random variables, will be sequentially discussed in Sections 13.2-13.6. For each random variable, its probability density function (pdf), cumulative distribution function (cdf), expected value, and variance will be derived along with discussion of their properties and relevant applications.

A typical application of the statistical models can be found in queuing systems to model the waiting experiences. This statistical modeling of the waiting is well known as queuing theory. This chapter is devoted to study the queuing theory in the context of computer and communication networks. In this chapter, the author will first introduce the basic concept of queuing theory in Section 15.1. The application of queuing theory in the form of queuing systems for computer and communication networks will be presented in Section 15.2. As a background of the queuing system, the Poisson point process will be then reviewed in Section 15.3. Various performance measures and their relationship with Little's law will be discussed in Section 15.4. This chapter will be closed by introducing Kendall's notation for specifying queuing systems in Section 15.5.

Considering queuing systems with multiple servers, this chapter is devoted to present multi-server queues in which packets are served by multiple packets in parallel. There exist various models for multi-server queues depending on the system capacity and population size of the sources. In this chapter, the author will first introduce M/M/c queue with infinite system capacity and infinite population in Section 17.1. Its variant models with finite system capacity and finite population will be sequentially discussed in Sections 17.2 and 17.3. For every queuing model, its behaviors will be presented along with detailed analyses of relevant performance measures.