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The Emergence of Edge Computing COVER FEATURE OUTLOOK The Emergence of Edge Computing Mahadev Satyanarayanan, Carnegie Mellon University Industry investment and research interest in edge computing, in which computing and storage nodes are placed at the Internet’s edge in close proximity to mobile devices or sensors, have grown dramatically in recent years. This emerging technology promises to deliver highly responsive cloud services for mobile computing, scalability and privacy-policy enforcement for the Internet of Things, and the ability to mask transient cloud outages. loud computing, which has dominated IT new paradigm in which substantial computing and storage discourse in the past decade, has a twofold resources—variously referred to as cloudlets,1 micro value proposition. First, centralization exploits datacenters, or fog nodes2—are placed at the Internet’s economies of scale to lower the marginal edge in close proximity to mobile devices or sensors. Ccost of system administration and operations. Second, Industry investment and research interest in edge organizations can avoid the capital expenditure of computing have grown dramatically in recent years. creating a datacenter by consuming computing resources Nokia and IBM jointly introduced the Radio Applications over the Internet from a large service provider. These Cloud Server (RACS), an edge computing platform for considerations have led to the consolidation of computing 4G/LTE networks, in early 2013.3 The following year, a capacity into multiple large datacenters spread across the mobile edge computing standardization effort began globe. The proven economic benefits of cloud computing under the auspices of the European Telecommunications make it likely to remain a permanent feature of the future Standards Institute (ETSI).4 The Open Edge Computing computing landscape. initiative (OEC; openedgecomputing.org) was launched in However, the forces driving centralization are not the June 2015 by Vodafone, Intel, and Huawei in partnership only ones at work. Nascent technologies and applications with Carnegie Mellon University (CMU) and expanded for mobile computing and the Internet of Things (IoT) are a year later to include Verizon, Deutsche Telekom, driving computing toward dispersion. Edge computing is a T-Mobile, Nokia, and Crown Castle. This collaboration 30 COMPUTER PUBLISHED BY THE IEEE COMPUTER SOCIETY 0018-9162/17/$33.00 © 2017 IEEE includes creation of a Living Edge container for isolation, safety, resource Clearly, reliance on a cloud datacenter Lab in Pittsburgh, Pennsylvania, to management, and metering. is not advisable for applications that gain hands-on experience with a live In 1997, Brian Noble and his require end-to-end delays to be tightly deployment of proof-of-concept cloudlet- colleagues first demonstrated edge controlled to less than a few tens of based applications. Organized by the computing’s potential value to mobile milliseconds. As will be discussed later, telecom industry, the first Mobile Edge computing.6 They showed how speech tight control of latency is necessary Computing Congress (tmt.knect365.com /mobile-edge-computing) convened in London in September 2015 and again in Munich a year later. The Open Fog USING PERSISTENT CACHING SIMPLIFIES Consortium (www.openfogconsortium .org) was created by Cisco, Microsoft, THE MANAGEMENT OF CLOUDLETS Intel, Dell, and ARM in partnership DESPITE THEIR PHYSICAL DISPERSAL AT with Princeton University in November THE INTERNET EDGE. 2015, and has since expanded to include many other companies. The First IEEE/ ACM Symposium on Edge Computing (conferences.computer.org/SEC) was held recognition could be implemented for emerging applications such as in October 2016 in Washington, DC. with acceptable performance on a augmented reality (AR). These developments raise several resource-limited mobile device by These observations about end-to- questions: why has edge computing offloading computation to a nearby end latency and cloud computing emerged, what new capabilities does it server. Two years later, Jason Flinn were first articulated in a 2009 article enable, and where is it headed? and I extended this approach to I coauthored with Paramvir Bahl, improve battery life.7 In a 2001 article Rámon Cáceres, and Nigel Davies ORIGIN AND BACKGROUND that generalized these concepts, I that laid the conceptual foundation The roots of edge computing reach introduced the term cyber foraging for for edge computing.1 We advocated back to the late 1990s, when Akamai the amplification of a mobile device’s a two-level architecture: the first introduced content delivery networks computing capabilities by leveraging level is today’s unmodified cloud (CDNs) to accelerate web performance.5 nearby infrastructure.8 infrastructure; the second level A CDN uses nodes at the edge close to Cloud computing’s emergence in the consists of dispersed elements called users to prefetch and cache web content. mid-2000s led to the cloud becoming the cloudlets with state cached from the These edge nodes can also perform some most obvious infrastructure to leverage first level. Using persistent caching content customization, such as adding from a mobile device. Today, Apple’s instead of hard state simplifies the location-relevant advertising. CDNs are Siri and Google’s speech-recognition management of cloudlets despite their especially valuable for video content, services both offload computation to physical dispersal at the Internet edge. because the bandwidth savings from the cloud. Unfortunately, consolidation The cloudlet concept can, of course, caching can be substantial. implies large average separation be expanded to a multilevel cloudlet Edge computing generalizes and between a mobile device and its optimal hierarchy. extends the CDN concept by leveraging cloud datacenter. Ang Li and his In 2012, Flavio Bonomi and his cloud computing infrastructure. As colleagues reported that the average colleagues introduced the term fog with CDNs, the proximity of cloudlets round-trip time from 260 global computing to refer to this dispersed to end users is crucial. However, vantage points to their optimal Amazon cloud infrastructure.2 However, their instead of being limited to caching web Elastic Compute Cloud (EC2) instances motivation for decentralization is content, a cloudlet can run arbitrary is 74 ms.9 To this must be added the IoT infrastructure scalability rather code just as in cloud computing. This latency of a wireless first hop. In terms than mobile applications’ interactive code is typically encapsulated in a of jitter, the variance inherent in a performance. The researchers envision virtual machine (VM) or a lighter-weight multihop network must be included. a multilevel hierarchy of fog nodes JANUARY 2017 31 OUTLOOK 1.0 1.0 0.8 3.3 J Mobile only 16.4 J 0.8 1.1 J Cloudlet 5.4 J 0.6 3.1 J AWS-East 6.6 J 0.6 0.4 5.1 J AWS-West 8.5 J 0.4 0.2 5.2 J AWS-EU 9.5 J 0.2 0 9.4 J AWS-Asia 14.3 J 0 0 200 400 600 800 1,000 0 200 400 600 800 1,000 Milliseconds Milliseconds (a) (b) FIGURE 1. Response time distribution and per-operation energy cost of an (a) augmented reality and (b) face recognition application on a mobile device, in which an image from the device is transmitted over a Wi-Fi first hop to a cloudlet or an Amazon Web Services (AWS) datacenter. The ideal is best approximated by a cloudlet, demonstrating the importance of low-latency offload services. Figure adapted from K. Ha et al., “The Impact of Mobile Multimedia Applications on Data Center Consolidation,” Proc. 2013 IEEE Int’l Conf. Cloud Eng. (IC2E 13), 2013, pp. 166–176. stretching from the cloud to IoT edge need to use a multihop networking to network failure, cloud failure, devices. strategy to cover a large geographic or a denial-of-service attack, area with many access points imposes a fallback service on a nearby WHY PROXIMITY MATTERS an economic limit on both latency cloudlet can temporarily mask As we explore new applications and and bandwidth. Each hop introduces the failure. use cases for both mobile computing queuing and routing delay, as well as and the IoT, the virtues of proximity buffer bloat.10 I now discuss each of these advan- are becoming increasingly apparent. The proximity of cloudlets helps in tages in detail. In the physical world, the importance at least four distinct ways: of proximity has never been in HIGHLY RESPONSIVE doubt. The old axiom about the › Highly responsive cloud services. CLOUD SERVICES three top determinants of real estate A cloudlet’s physical proxim- Humans are acutely sensitive to delays value being “location, location, and ity to a mobile device makes it in the critical path of interaction, and location” captures this observation easier to achieve low end-to-end their performance on cognitive tasks well. In the cyber world, the seamless latency, high bandwidth, and is remarkably fast and accurate.11 connectivity offered by the Internet low jitter to services located on For example, under normal lighting has lulled us into a false sense of the cloudlet. This is valuable for conditions, face recognition takes disregard for physical proximity. applications such as AR and vir- 370–620 ms, depending on familiarity. Because logical network proximity is tual reality that offload compu- Speech recognition takes 300–450 ms entirely characterized by low latency, tation to the cloudlet. for short phrases, and it requires only low jitter, and high bandwidth, the › Scalability via edge analytics. The 4 ms to tell that a sound is a human question “How close is physically cumulative ingress bandwidth voice. VR applications that use head- close enough?” cannot be answered in demand into the cloud from a tracked systems require latencies of the abstract. It is dependent on factors large collection of high-band- less than 16 ms to achieve perceptual such as the networking technologies width IoT sensors, such as video stability. End-to-end latency of a few used, network contention, application cameras, is considerably lower tens of milliseconds is a safe but characteristics, and user tolerance for if the raw data is analyzed achievable goal.
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