We have established an ambitious goal for ourselves: to understand how to build a computer network from the ground up. Our approach to accomplishing this goal will be to start from first principles and then ask the kinds of questions we would naturally ask if building an actual network. At each step, we will use today’s protocols to illustrate various design choices available to us, but we will not accept these existing artifacts as gospel. Instead, we will be asking (and answering) the question of why networks are designed the way they are. While it is tempting to settle for just understanding the way it’s done today, it is important to recognize the underlying concepts because networks are constantly changing as technology evolves and new applications are invented. It is our experience that once you understand the fundamental ideas, any new protocol that you are confronted with will be relatively easy to digest.
As we noted above, a student of networks can take several perspectives. When we wrote the first edition of this book, the majority of the population had no Internet access at all, and those who did obtained it while at work, at a university, or by a dial-up modem at home. The set of popular applications could be counted on one’s fingers. Thus, like most books at the time, ours focused on the perspective of someone who would design networking equipment and protocols. We continue to focus on this perspective, and our hope is that after reading this book you will know how to design the networking equipment and protocols of the future.
However, we also want to cover the perspectives of two additional stakeholders: those who develop networked applications and those who manage or operate networks. Let’s consider how these three stakeholders might list their requirements for a network:
An application programmer would list the services that his or her application needs: for example, a guarantee that each message the application sends will be delivered without error within a certain amount of time or the ability to switch gracefully among different connections to the network as the user moves around.
A network operator would list the characteristics of a system that is easy to administer and manage: for example, in which faults can be easily isolated, new devices can be added to the network and configured correctly, and it is easy to account for usage.
A network designer would list the properties of a cost-effective design: for example, that network resources are efficiently utilized and fairly allocated to different users. Issues of performance are also likely to be important.
This section attempts to distill the requirements of different stakeholders into a high-level introduction to the major considerations that drive network design and, in doing so, identify the challenges addressed throughout the rest of this book.
1.2.2 Scalable Connectivity
Starting with the obvious, a network must provide connectivity among a set of computers. Sometimes it is enough to build a limited network that connects only a few select machines. In fact, for reasons of privacy and security, many private (corporate) networks have the explicit goal of limiting the set of machines that are connected. In contrast, other networks (of which the Internet is the prime example) are designed to grow in a way that allows them the potential to connect all the computers in the world. A system that is designed to support growth to an arbitrarily large size is said to scale. Using the Internet as a model, this book addresses the challenge of scalability.
To understand the requirements of connectivity more fully, we need to take a closer look at how computers are connected in a network. Connectivity occurs at many different levels. At the lowest level, a network can consist of two or more computers directly connected by some physical medium, such as a coaxial cable or an optical fiber. We call such a physical medium a link, and we often refer to the computers it connects as nodes. (Sometimes a node is a more specialized piece of hardware rather than a computer, but we overlook that distinction for the purposes of this discussion.) As illustrated in Figure 2, physical links are sometimes limited to a pair of nodes (such a link is said to be point-to-point), while in other cases more than two nodes may share a single physical link (such a link is said to be multiple-access). Wireless links, such as those provided by cellular networks and Wi-Fi networks, are an important class of multiple-access links. It is always the case that multiple-access links are limited in size, in terms of both the geographical distance they can cover and the number of nodes they can connect. For this reason, they often implement the so-called last mile, connecting end users to the rest of the network.
If computer networks were limited to situations in which all nodes are directly connected to each other over a common physical medium, then either networks would be very limited in the number of computers they could connect, or the number of wires coming out of the back of each node would quickly become both unmanageable and very expensive. Fortunately, connectivity between two nodes does not necessarily imply a direct physical connection between them—indirect connectivity may be achieved among a set of cooperating nodes. Consider the following two examples of how a collection of computers can be indirectly connected.
Figure 3 shows a set of nodes, each of which is attached to one or more point-to-point links. Those nodes that are attached to at least two links run software that forwards data received on one link out on another. If organized in a systematic way, these forwarding nodes form a switched network. There are numerous types of switched networks, of which the two most common are circuit switched and packet switched. The former is most notably employed by the telephone system, while the latter is used for the overwhelming majority of computer networks and will be the focus of this book. (Circuit switching is, however, making a bit of a comeback in the optical networking realm, which turns out to be important as demand for network capacity constantly grows.) The important feature of packet-switched networks is that the nodes in such a network send discrete blocks of data to each other. Think of these blocks of data as corresponding to some piece of application data such as a file, a piece of email, or an image. We call each block of data either a packet or a message, and for now we use these terms interchangeably.
Packet-switched networks typically use a strategy called store-and-forward. As the name suggests, each node in a store-and-forward network first receives a complete packet over some link, stores the packet in its internal memory, and then forwards the complete packet to the next node. In contrast, a circuit-switched network first establishes a dedicated circuit across a sequence of links and then allows the source node to send a stream of bits across this circuit to a destination node. The major reason for using packet switching rather than circuit switching in a computer network is efficiency, discussed in the next subsection.
The cloud in Figure 3 distinguishes between the nodes on the inside that implement the network (they are commonly called switches, and their primary function is to store and forward packets) and the nodes on the outside of the cloud that use the network (they are traditionally called hosts, and they support users and run application programs). Also note that the cloud is one of the most important icons of computer networking. In general, we use a cloud to denote any type of network, whether it is a single point-to-point link, a multiple-access link, or a switched network. Thus, whenever you see a cloud used in a figure, you can think of it as a placeholder for any of the networking technologies covered in this book.1
The use of clouds to represent networks predates the term cloud computing by at least a couple of decades, but there is an increasingly rich connection between these two usages, which we explore in the Perspective discussion at the end of each chapter.
A second way in which a set of computers can be indirectly connected is shown in Figure 4. In this situation, a set of independent networks (clouds) are interconnected to form an internetwork, or internet for short. We adopt the Internet’s convention of referring to a generic internetwork of networks as a lowercase i internet, and the TCP/IP Internet we all use every day as the capital I Internet. A node that is connected to two or more networks is commonly called a router or gateway, and it plays much the same role as a switch—it forwards messages from one network to another. Note that an internet can itself be viewed as another kind of network, which means that an internet can be built from a set of internets. Thus, we can recursively build arbitrarily large networks by interconnecting clouds to form larger clouds. It can reasonably be argued that this idea of interconnecting widely differing networks was the fundamental innovation of the Internet and that the successful growth of the Internet to global size and billions of nodes was the result of some very good design decisions by the early Internet architects, which we will discuss later.
Just because a set of hosts are directly or indirectly connected to each other does not mean that we have succeeded in providing host-to-host connectivity. The final requirement is that each node must be able to say which of the other nodes on the network it wants to communicate with. This is done by assigning an address to each node. An address is a byte string that identifies a node; that is, the network can use a node’s address to distinguish it from the other nodes connected to the network. When a source node wants the network to deliver a message to a certain destination node, it specifies the address of the destination node. If the sending and receiving nodes are not directly connected, then the switches and routers of the network use this address to decide how to forward the message toward the destination. The process of determining systematically how to forward messages toward the destination node based on its address is called routing.
This brief introduction to addressing and routing has presumed that the source node wants to send a message to a single destination node (unicast). While this is the most common scenario, it is also possible that the source node might want to broadcast a message to all the nodes on the network. Or, a source node might want to send a message to some subset of the other nodes but not all of them, a situation called multicast. Thus, in addition to node-specific addresses, another requirement of a network is that it supports multicast and broadcast addresses.
The main idea to take away from this discussion is that we can define a network recursively as consisting of two or more nodes connected by a physical link, or as two or more networks connected by a node. In other words, a network can be constructed from a nesting of networks, where at the bottom level, the network is implemented by some physical medium. Among the key challenges in providing network connectivity are the definition of an address for each node that is reachable on the network (be it logical or physical), and the use of such addresses to forward messages toward the appropriate destination node(s). [Next]
1.2.3 Cost-Effective Resource Sharing
As stated above, this book focuses on packet-switched networks. This section explains the key requirement of computer networks—efficiency—that leads us to packet switching as the strategy of choice.
Given a collection of nodes indirectly connected by a nesting of networks, it is possible for any pair of hosts to send messages to each other across a sequence of links and nodes. Of course, we want to do more than support just one pair of communicating hosts—we want to provide all pairs of hosts with the ability to exchange messages. The question, then, is how do all the hosts that want to communicate share the network, especially if they want to use it at the same time? And, as if that problem isn’t hard enough, how do several hosts share the same link when they all want to use it at the same time?
To understand how hosts share a network, we need to introduce a fundamental concept, multiplexing, which means that a system resource is shared among multiple users. At an intuitive level, multiplexing can be explained by analogy to a timesharing computer system, where a single physical processor is shared (multiplexed) among multiple jobs, each of which believes it has its own private processor. Similarly, data being sent by multiple users can be multiplexed over the physical links that make up a network.
To see how this might work, consider the simple network illustrated in Figure 5, where the three hosts on the left side of the network (senders S1-S3) are sending data to the three hosts on the right (receivers R1-R3) by sharing a switched network that contains only one physical link. (For simplicity, assume that host S1 is sending data to host R1, and so on.) In this situation, three flows of data—corresponding to the three pairs of hosts—are multiplexed onto a single physical link by switch 1 and then demultiplexed back into separate flows by switch 2. Note that we are being intentionally vague about exactly what a “flow of data” corresponds to. For the purposes of this discussion, assume that each host on the left has a large supply of data that it wants to send to its counterpart on the right.
There are several different methods for multiplexing multiple flows onto one physical link. One common method is synchronous time-division multiplexing (STDM). The idea of STDM is to divide time into equal-sized quanta and, in a round-robin fashion, give each flow a chance to send its data over the physical link. In other words, during time quantum 1, data from S1 to R1 is transmitted; during time quantum 2, data from S2 to R2 is transmitted; in quantum 3, S3 sends data to R3. At this point, the first flow (S1 to R1) gets to go again, and the process repeats. Another method is frequency-division multiplexing (FDM). The idea of FDM is to transmit each flow over the physical link at a different frequency, much the same way that the signals for different TV stations are transmitted at a different frequency over the airwaves or on a coaxial cable TV link.
Although simple to understand, both STDM and FDM are limited in two ways. First, if one of the flows (host pairs) does not have any data to send, its share of the physical link—that is, its time quantum or its frequency—remains idle, even if one of the other flows has data to transmit. For example, S3 had to wait its turn behind S1 and S2 in the previous paragraph, even if S1 and S2 had nothing to send. For computer communication, the amount of time that a link is idle can be very large—for example, consider the amount of time you spend reading a web page (leaving the link idle) compared to the time you spend fetching the page. Second, both STDM and FDM are limited to situations in which the maximum number of flows is fixed and known ahead of time. It is not practical to resize the quantum or to add additional quanta in the case of STDM or to add new frequencies in the case of FDM.
The form of multiplexing that addresses these shortcomings, and of which we make most use in this book, is called statistical multiplexing. Although the name is not all that helpful for understanding the concept, statistical multiplexing is really quite simple, with two key ideas. First, it is like STDM in that the physical link is shared over time—first data from one flow is transmitted over the physical link, then data from another flow is transmitted, and so on. Unlike STDM, however, data is transmitted from each flow on demand rather than during a predetermined time slot. Thus, if only one flow has data to send, it gets to transmit that data without waiting for its quantum to come around and thus without having to watch the quanta assigned to the other flows go by unused. It is this avoidance of idle time that gives packet switching its efficiency.
As defined so far, however, statistical multiplexing has no mechanism to ensure that all the flows eventually get their turn to transmit over the physical link. That is, once a flow begins sending data, we need some way to limit the transmission, so that the other flows can have a turn. To account for this need, statistical multiplexing defines an upper bound on the size of the block of data that each flow is permitted to transmit at a given time. This limited-size block of data is typically referred to as a packet, to distinguish it from the arbitrarily large message that an application program might want to transmit. Because a packet-switched network limits the maximum size of packets, a host may not be able to send a complete message in one packet. The source may need to fragment the message into several packets, with the receiver reassembling the packets back into the original message.
In other words, each flow sends a sequence of packets over the physical link, with a decision made on a packet-by-packet basis as to which flow’s packet to send next. Notice that, if only one flow has data to send, then it can send a sequence of packets back-to-back; however, should more than one of the flows have data to send, then their packets are interleaved on the link. Figure 6 depicts a switch multiplexing packets from multiple sources onto a single shared link.
The decision as to which packet to send next on a shared link can be made in a number of different ways. For example, in a network consisting of switches interconnected by links such as the one in Figure 5, the decision would be made by the switch that transmits packets onto the shared link. (As we will see later, not all packet-switched networks actually involve switches, and they may use other mechanisms to determine whose packet goes onto the link next.) Each switch in a packet-switched network makes this decision independently, on a packet-by-packet basis. One of the issues that faces a network designer is how to make this decision in a fair manner. For example, a switch could be designed to service packets on a first-in, first-out (FIFO) basis. Another approach would be to transmit the packets from each of the different flows that are currently sending data through the switch in a round-robin manner. This might be done to ensure that certain flows receive a particular share of the link’s bandwidth or that they never have their packets delayed in the switch for more than a certain length of time. A network that attempts to allocate bandwidth to particular flows is sometimes said to support quality of service (QoS).
Also, notice in Figure 6 that since the switch has to multiplex three incoming packet streams onto one outgoing link, it is possible that the switch will receive packets faster than the shared link can accommodate. In this case, the switch is forced to buffer these packets in its memory. Should a switch receive packets faster than it can send them for an extended period of time, then the switch will eventually run out of buffer space, and some packets will have to be dropped. When a switch is operating in this state, it is said to be congested.
The bottom line is that statistical multiplexing defines a cost-effective way for multiple users (e.g., host-to-host flows of data) to share network resources (links and nodes) in a fine-grained manner. It defines the packet as the granularity with which the links of the network are allocated to different flows, with each switch able to schedule the use of the physical links it is connected to on a per-packet basis. Fairly allocating link capacity to different flows and dealing with congestion when it occurs are the key challenges of statistical multiplexing. [Next]
1.2.4 Support for Common Services
The previous discussion focused on the challenges involved in providing cost-effective connectivity among a group of hosts, but it is overly simplistic to view a computer network as simply delivering packets among a collection of computers. It is more accurate to think of a network as providing the means for a set of application processes that are distributed over those computers to communicate. In other words, the next requirement of a computer network is that the application programs running on the hosts connected to the network must be able to communicate in a meaningful way. From the application developer’s perspective, the network needs to make his or her life easier.
When two application programs need to communicate with each other, a lot of complicated things must happen beyond simply sending a message from one host to another. One option would be for application designers to build all that complicated functionality into each application program. However, since many applications need common services, it is much more logical to implement those common services once and then to let the application designer build the application using those services. The challenge for a network designer is to identify the right set of common services. The goal is to hide the complexity of the network from the application without overly constraining the application designer.
Intuitively, we view the network as providing logical channels over which application-level processes can communicate with each other; each channel provides the set of services required by that application. In other words, just as we use a cloud to abstractly represent connectivity among a set of computers, we now think of a channel as connecting one process to another. Figure 7 shows a pair of application-level processes communicating over a logical channel that is, in turn, implemented on top of a cloud that connects a set of hosts. We can think of the channel as being like a pipe connecting two applications, so that a sending application can put data in one end and expect that data to be delivered by the network to the application at the other end of the pipe.
Like any abstraction, logical process-to-process channels are implemented on top of a collection of physical host-to-host channels. This is the essense of layering, the cornerstone of network architectures discussed in the next section.
The challenge is to recognize what functionality the channels should provide to application programs. For example, does the application require a guarantee that messages sent over the channel are delivered, or is it acceptable if some messages fail to arrive? Is it necessary that messages arrive at the recipient process in the same order in which they are sent, or does the recipient not care about the order in which messages arrive? Does the network need to ensure that no third parties are able to eavesdrop on the channel, or is privacy not a concern? In general, a network provides a variety of different types of channels, with each application selecting the type that best meets its needs. The rest of this section illustrates the thinking involved in defining useful channels.
Identify Common Communication Patterns
Designing abstract channels involves first understanding the communication needs of a representative collection of applications, then extracting their common communication requirements, and finally incorporating the functionality that meets these requirements in the network.
One of the earliest applications supported on any network is a file access program like the File Transfer Protocol (FTP) or Network File System (NFS). Although many details vary—for example, whether whole files are transferred across the network or only single blocks of the file are read/written at a given time—the communication component of remote file access is characterized by a pair of processes, one that requests that a file be read or written and a second process that honors this request. The process that requests access to the file is called the client, and the process that supports access to the file is called the server.
Reading a file involves the client sending a small request message to a server and the server responding with a large message that contains the data in the file. Writing works in the opposite way—the client sends a large message containing the data to be written to the server, and the server responds with a small message confirming that the write to disk has taken place.
A digital library is a more sophisticated application than file transfer, but it requires similar communication services. For example, the Association for Computing Machinery (ACM) operates a large digital library of computer science literature at
This library has a wide range of searching and browsing features to help users find the articles they want, but ultimately much of what it does is respond to user requests for files, such as electronic copies of journal articles.
Using file access, a digital library, and the two video applications described in the introduction (videoconferencing and video on demand) as a representative sample, we might decide to provide the following two types of channels: request/reply channels and message stream channels. The request/reply channel would be used by the file transfer and digital library applications. It would guarantee that every message sent by one side is received by the other side and that only one copy of each message is delivered. The request/reply channel might also protect the privacy and integrity of the data that flows over it, so that unauthorized parties cannot read or modify the data being exchanged between the client and server processes.
The message stream channel could be used by both the video on demand and videoconferencing applications, provided it is parameterized to support both one-way and two-way traffic and to support different delay properties. The message stream channel might not need to guarantee that all messages are delivered, since a video application can operate adequately even if some video frames are not received. It would, however, need to ensure that those messages that are delivered arrive in the same order in which they were sent, to avoid displaying frames out of sequence. Like the request/reply channel, the message stream channel might want to ensure the privacy and integrity of the video data. Finally, the message stream channel might need to support multicast, so that multiple parties can participate in the teleconference or view the video.
While it is common for a network designer to strive for the smallest number of abstract channel types that can serve the largest number of applications, there is a danger in trying to get away with too few channel abstractions. Simply stated, if you have a hammer, then everything looks like a nail. For example, if all you have are message stream and request/reply channels, then it is tempting to use them for the next application that comes along, even if neither type provides exactly the semantics needed by the application. Thus, network designers will probably be inventing new types of channels—and adding options to existing channels—for as long as application programmers are inventing new applications.
Also note that independent of exactly what functionality a given channel provides, there is the question of where that functionality is implemented. In many cases, it is easiest to view the host-to-host connectivity of the underlying network as simply providing a bit pipe, with any high-level communication semantics provided at the end hosts. The advantage of this approach is that it keeps the switches in the middle of the network as simple as possible—they simply forward packets—but it requires the end hosts to take on much of the burden of supporting semantically rich process-to-process channels. The alternative is to push additional functionality onto the switches, thereby allowing the end hosts to be “dumb” devices (e.g., telephone handsets). We will see this question of how various network services are partitioned between the packet switches and the end hosts (devices) as a recurring issue in network design.
Reliable Message Delivery
As suggested by the examples just considered, reliable message delivery is one of the most important functions that a network can provide. It is difficult to determine how to provide this reliability, however, without first understanding how networks can fail. The first thing to recognize is that computer networks do not exist in a perfect world. Machines crash and later are rebooted, fibers are cut, electrical interference corrupts bits in the data being transmitted, switches run out of buffer space, and, as if these sorts of physical problems aren’t enough to worry about, the software that manages the hardware may contain bugs and sometimes forwards packets into oblivion. Thus, a major requirement of a network is to recover from certain kinds of failures, so that application programs don’t have to deal with them or even be aware of them.
There are three general classes of failure that network designers have to worry about. First, as a packet is transmitted over a physical link, bit errors may be introduced into the data; that is, a 1 is turned into a 0 or vice versa. Sometimes single bits are corrupted, but more often than not a burst error occurs—several consecutive bits are corrupted. Bit errors typically occur because outside forces, such as lightning strikes, power surges, and microwave ovens, interfere with the transmission of data. The good news is that such bit errors are fairly rare, affecting on average only one out of every 106 to 107 bits on a typical copper-based cable and one out of every 1012 to 1014 bits on a typical optical fiber. As we will see, there are techniques that detect these bit errors with high probability. Once detected, it is sometimes possible to correct for such errors—if we know which bit or bits are corrupted, we can simply flip them—while in other cases the damage is so bad that it is necessary to discard the entire packet. In such a case, the sender may be expected to retransmit the packet.
The second class of failure is at the packet, rather than the bit, level; that is, a complete packet is lost by the network. One reason this can happen is that the packet contains an uncorrectable bit error and therefore has to be discarded. A more likely reason, however, is that one of the nodes that has to handle the packet—for example, a switch that is forwarding it from one link to another—is so overloaded that it has no place to store the packet and therefore is forced to drop it. This is the problem of congestion just discussed. Less commonly, the software running on one of the nodes that handles the packet makes a mistake. For example, it might incorrectly forward a packet out on the wrong link, so that the packet never finds its way to the ultimate destination. As we will see, one of the main difficulties in dealing with lost packets is distinguishing between a packet that is indeed lost and one that is merely late in arriving at the destination.
The third class of failure is at the node and link level; that is, a physical link is cut, or the computer it is connected to crashes. This can be caused by software that crashes, a power failure, or a reckless backhoe operator. Failures due to misconfiguration of a network device are also common. While any of these failures can eventually be corrected, they can have a dramatic effect on the network for an extended period of time. However, they need not totally disable the network. In a packet-switched network, for example, it is sometimes possible to route around a failed node or link. One of the difficulties in dealing with this third class of failure is distinguishing between a failed computer and one that is merely slow or, in the case of a link, between one that has been cut and one that is very flaky and therefore introducing a high number of bit errors.
The key idea to take away from this discussion is that defining useful channels involves both understanding the applications’ requirements and recognizing the limitations of the underlying technology. The challenge is to fill in the gap between what the application expects and what the underlying technology can provide. This is sometimes called the semantic gap. [Next]
A final requirement, which seems to be neglected or left till last all too often (as we do here), is that networks need to be managed. Managing a network includes upgrading equipment as the network grows to carry more traffic or reach more users, troubleshooting the network when things go wrong or performance isn’t as desired, and adding new features in support of new applications. Network management has historically been a human-intensive aspect of networking, and while it is unlikely we’ll get people entirely out of the loop, it is increasingly being addressed by automation and self-healing designs.
This requirement is partly related to the issue of scalability discussed above—as the Internet has scaled up to support billions of users and at least hundreds of millions of hosts, the challenges of keeping the whole thing running correctly and correctly configuring new devices as they are added have become increasingly problematic. Configuring a single router in a network is often a task for a trained expert; configuring thousands of routers and figuring out why a network of such a size is not behaving as expected can become a task beyond any single human. This is why automation is becoming so important.
One way to make a network easier to manage is to avoid change. Once the network is working, simply do not touch it! This mindset exposes the fundamental tension between stability and feature velocity: the rate at which new capabilities are introduced into the network. Favoring stability is the approach the telecommunications industry (not to mention University system administrators and corporate IT departments) adopted for many years, making it one of the most slow moving and risk averse industries you will find anywhere. But the recent explosion of the cloud has changed that dynamic, making it necessary to bring stability and feature velocity more into balance. The impact of the cloud on the network is a topic that comes up over and over throughout the book, and one we pay particular attention to in the Perspectives section at the end of each chapter. For now, suffice it to say that managing a rapidly evolving network is arguably the central challenge in networking today.