I M A G E B Y Y U R I H O Y D A

types are marked with the name of the content. A user interested in specific content creates an interest packet and sends it into the network. The NDN routing protocol is based on a name-prefix strategy, which, in some ways, is similar to prefix aggregation in IP routing. An NDN router, however, differs from IP routers in two important ways: it maintains a temporary cache of data that it has seen so far, so that any new interests from downstream nodes can be responded to directly without going to an upstream router; and only one request is sent to the upstream router for multiple interests to the same name by a number of downstream nodes. Multiple paths for the same content are also supported.

The security in NDN is also data-centric. The producer of the data cryptographically signs each data packet, and a consumer can reason about data integrity and provenance from such signatures. In addition, encryption of data packets can be used to control access to information.

Using human-readable names allows for the creation of predictable names for content, which is useful for a certain class of applications. The paper also describes how applications would look with NDN by using a number of examples such as video streaming, real-time conferencing, building automation systems, and vehicular networking.

NDN is not the first ICN, and it isn’t the last. Earlier ICNs were based on flat cryptographic identifiers for addresses, compared to NDN’s hierarchical human-readable names. A more detailed overview of ICNs, their challenges, commonalities, and differences can be found in a 2011 survey paper by Ghodsi et al. ( https://dl.acm.org/cita- tion.cfm?id=2070563).

To provide a little historical context, NDN was one of several future Internet architectures (FIAs) funded by the National Science Foundation. It is instructive to look at a few other projects, such as XIA ( https://dl.acm. org/ citation.cfm?id=2070564) and MobilityFirst ( https://dl.acm.org/cita- tion.cfm?id=2089017), which share the goals of cleaner architectures for the future Internet.

The key lesson for practitioners is
that choosing the right level of abstrac-
cloud, and everywhere in between
form a continuum. Thus, for power
users such as factory floors, city infra-
structures, corporations, small busi-
nesses, and even some individuals,
edge computing means making ap-
propriate use of on-premises resourc-
es together with their current reliance
on the cloud. In addition to existing
cloud providers, a large number of
smaller but more optimally located
service providers, that handle the
overflow demand from power users as
well as support novice users, are likely
to flourish.

Creating edge computing infrastructures and applications encompasses quite a breadth of systems research. Let’s take a look at the academic view of edge computing and a sample of existing research that will be relevant in the coming years.

 

A Vision For Edge Computing: Opportunities And Challenges Let’s start with an excellent paper that introduced the term fog computing and highlights why practitioners should care about it:

 

Fog Computing and Its Role in the Internet of Things

F. Bonomi, R. Milito, J. Zhu, and S. Addepalli In Proceedings of the First Edition of the ACM Workshop on Mobile Cloud Computing, (2012) 3–16; https://dl.acm.org/citation. cfm?id=2342513

Although short, this paper provides a clear characterization of fog computing and a concise list of the opportunities it provides. It then goes deeper into the discussion of richer applications and services enabled by fog computing, such as connected vehicles, smart grid, and wireless sensor/actua-tor networks. The key takeaway is that the stricter performance/QoS requirements of these rich applications and services need: better architectures for compute, storage, and networking; and appropriate orchestration and management of resources.

While this paper is specifically about
the Internet of Things and fog com-
puting, the same ideas apply to edge
computing in the broader sense. Un-
surprisingly, the opportunities of edge
computing also come with a number of
challenges. An in-depth case study of
some of these challenges and possible
workarounds is illustrated in the Farm-
Beats project that was discussed in the
RfP “Toward a Network of Connected
Things” featured in the July 2018 issue
of Communications, p. 52–54.

A World Full of Information:
Why Naming Matters

One of the hurdles in using resources at the edge is the complexity they bring with them. What can be done to ease the management complexity? Are existing architectures an attempt to find workarounds for some more fundamental problems?

Information-centric networks (ICNs) postulate that most applications care only about information, but the current Internet architecture involves shoehorning these applications into a message-oriented, host-to-host network. While a number of ICNs have been proposed in the past, a recent notable paper addresses named data networking (NDN).

 

Named Data Networking

L. Zhang et al.

ACM SIGCOMM Computer Communication Rev. 44, 3 (2014), 66–63; https://dl.acm.org/citation. cfm?id=2656887

NDN, like many other ICNs, considers named information as a first-class citizen. Information is named with human-readable identifiers in a hierarchical manner, and the information can be directly accessed by its name instead of through a host-based URL scheme.

As for the architecture of the routing network itself, NDN has two types of packets: interest and data. Both