The proliferation of Internet of Things (IoT) and the success of rich cloud services have pushed the horizon of a new computing paradigm, edge computing, which calls for processing the data at the edge of the network. Edge computing has the potential to address the concerns of response time requirement, battery life constraint, bandwidth cost saving, as well as data safety and privacy. In this paper, we introduce the definition of edge computing, followed by several case studies, ranging from cloud offloading to smart home and city, as well as collaborative edge to materialize the concept of edge computing. Finally, we present several challenges and opportunities in the field of edge computing, and hope this paper will gain attention from the community and inspire more research in this direction.

Edge Computing: Vision and Challenges

物件導向軟體之架構(Object-Oriented Software Construction)探討

Driven by the visions of Internet of Things and 5G communications, recent years have seen a paradigm shift in mobile computing, from the centralized mobile cloud computing toward mobile edge computing (MEC). The main feature of MEC is to push mobile computing, network control and storage to the network edges (e.g., base stations and access points) so as to enable computation-intensive and latency-critical applications at the resource-limited mobile devices. MEC promises dramatic reduction in latency and mobile energy consumption, tackling the key challenges for materializing 5G vision. The promised gains of MEC have motivated extensive efforts in both academia and industry on developing the technology. A main thrust of MEC research is to seamlessly merge the two disciplines of wireless communications and mobile computing, resulting in a wide-range of new designs ranging from techniques for computation offloading to network architectures. This paper provides a comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management. We also discuss a set of issues, challenges, and future research directions for MEC research, including MEC system deployment, cache-enabled MEC, mobility management for MEC, green MEC, as well as privacy-aware MEC. Advancements in these directions will facilitate the transformation of MEC from theory to practice. Finally, we introduce recent standardization efforts on MEC as well as some typical MEC application scenarios.

A Survey on Mobile Edge Computing: The Communication Perspective

Mobile phones or smartphones are rapidly becoming the central computer and communication device in people's lives. Application delivery channels such as the Apple AppStore are transforming mobile phones into App Phones, capable of downloading a myriad of applications in an instant. Importantly, today's smartphones are programmable and come with a growing set of cheap powerful embedded sensors, such as an accelerometer, digital compass, gyroscope, GPS, microphone, and camera, which are enabling the emergence of personal, group, and communityscale sensing applications. We believe that sensor-equipped mobile phones will revolutionize many sectors of our economy, including business, healthcare, social networks, environmental monitoring, and transportation. In this article we survey existing mobile phone sensing algorithms, applications, and systems. We discuss the emerging sensing paradigms, and formulate an architectural framework for discussing a number of the open issues and challenges emerging in the new area of mobile phone sensing research.

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A survey of mobile phone sensing

Driven by the visions of Internet of Things and 5G communications, recent years have seen a paradigm shift in mobile computing, from the centralized Mobile Cloud Computing towards Mobile Edge Computing (MEC). The main feature of MEC is to push mobile computing, network control and storage to the network edges (e.g., base stations and access points) so as to enable computation-intensive and latency-critical applications at the resource-limited mobile devices. MEC promises dramatic reduction in latency and mobile energy consumption, tackling the key challenges for materializing 5G vision. The promised gains of MEC have motivated extensive efforts in both academia and industry on developing the technology. A main thrust of MEC research is to seamlessly merge the two disciplines of wireless communications and mobile computing, resulting in a wide-range of new designs ranging from techniques for computation offloading to network architectures. This paper provides a comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management. We also present a research outlook consisting of a set of promising directions for MEC research, including MEC system deployment, cache-enabled MEC, mobility management for MEC, green MEC, as well as privacy-aware MEC. Advancements in these directions will facilitate the transformation of MEC from theory to practice. Finally, we introduce recent standardization efforts on MEC as well as some typical MEC application scenarios.

Web page load time is a key performance metric that many techniques aim to reduce. Unfortunately, the complexity of modern Web pages makes it difficult to identify performance bottlenecks. We present WProf, a lightweight in-browser profiler that produces a detailed dependency graph of the activities that make up a page load. WProf is based on a model we developed to capture the constraints between network load, page parsing, JavaScript/CSS evaluation, and rendering activity in popular browsers. We combine WProf reports with critical path analysis to study the page load time of 350 Web pages under a variety of settings including the use of end-host caching, SPDY instead of HTTP, and the mod pagespeed server extension. We find that computation is a significant factor that makes up as much as 35% of the critical path, and that synchronous JavaScript plays a significant role in page load time by blocking HTML parsing. Caching reduces page load time, but the reduction is not proportional to the number of cached objects, because most object loads are not on the critical path. SPDY reduces page load time only for networks with high RTTs and mod pagespeed helps little on an average page.

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Demystifying page load performance with WProf

Routing protocols for disruption-tolerant networks (DTNs) use a variety of mechanisms, including discovering the meeting probabilities among nodes, packet replication, and network coding. The primary focus of these mechanisms is to increase the likelihood of finding a path with limited information, and so these approaches have only an incidental effect on such routing metrics as maximum or average delivery delay. In this paper, we present rapid, an intentional DTN routing protocol that can optimize a specific routing metric such as the worst-case delivery delay or the fraction of packets that are delivered within a deadline. The key insight is to treat DTN routing as a resource allocation problem that translates the routing metric into per-packet utilities that determine how packets should be replicated in the system. We evaluate rapid rigorously through a prototype deployed over a vehicular DTN testbed of 40 buses and simulations based on real traces. To our knowledge, this is the first paper to report on a routing protocol deployed on a real outdoor DTN. Our results suggest that rapid significantly outperforms existing routing protocols for several metrics. We also show empirically that for small loads, RAPID is within 10% of the optimal performance.

/pdf/replication-routing-in-dtns-a-resource-allocation-approach-7cw4tud51t.pdf

Replication routing in DTNs: a resource allocation approach

SPDY is increasingly being used as an enhancement to HTTP/11 To understand its impact on performance, we conduct a systematic study of Web page load time (PLT) under SPDY and compare it to HTTP To identify the factors that affect PLT, we proceed from simple, synthetic pages to complete page loads based on the top 200 Alexa sites We find that SPDY provides a significant improvement over HTTP when we ignore dependencies in the page load process and the effects of browser computation Most SPDY benefits stem from the use of a single TCP connection, but the same feature is also detrimental under high packet loss Unfortunately, the benefits can be easily overwhelmed by dependencies and computation, reducing the improvements with SPDY to 7% for our lower bandwidth and higher RTT scenarios We also find that request prioritization is of little help, while server push has good potential; we present a push policy based on dependencies that gives comparable performance to mod_spdy while sending much less data

How speedy is SPDY

Opportunistic connections to the Internet from open wireless access points is now commonly possible in urban areas. Vehicular networks can opportunistically connect to the Internet for several seconds via open access points. In this paper, we adapt the interactive process of web search and retrieval to vehicular networks with intermittent Internet access. Our system, called Thedu, has mobile nodes use an Internet proxy to collect search engine results and prefetch result pages. The mobile nodes download the pre-fetched web pages from the proxy. Our contribution is a novel set of techniques to make aggressive but selective prefetching practical, resulting in a significantly greater number of relevant web results returned to mobile users. In particular, we prioritize responses in the order of the usefulness of the response to the query, that allows the mobile node to download the most useful response first. To evaluate our scheme, we deployed Thedu on DieselNet, our vehicular testbed operating in a micro-urban area around Amherst, MA. Using a simulated workload, we find that users can expect four times as many useful responses to web search queries compared to not using Thedu's mechanisms. Moreover, the mean latency in receiving the first relevant response for a query is 2.7 minutes for our deployment; we expect Thedu to have even better performance in larger cities that have densely populated open APs.

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Web search from a bus

Mobile page load times are an order of magnitude slower compared to non-mobile pages. It is not clear what causes the poor performance: the slower network, the slower computational speeds, or other reasons. Further, most Web optimizations are designed for non-mobile browsers and do not translate well to the mobile browser. Towards understanding mobile Web page load times, in this paper we: (1) perform an in-depth pairwise comparison of loading a page on a mobile versus a non-mobile browser, and (2) characterize the bottlenecks in the mobile browser {\em vis-a-vis} non-mobile browsers. To this end, we build a testbed that allows us to directly compare the low-level page load activities and bottlenecks when loading a page on a mobile versus a non-mobile browser. We find that computation is the main bottleneck when loading a page on mobile browsers. This is in contrast to non-mobile browsers where networking is the main bottleneck. We also find that the composition of the critical path during page load is different when loading pages on the mobile versus the non-mobile browser. A key takeaway of our work is that we need to fundamentally rethink optimizations for mobile browsers.

https://dl.acm.org/doi/pdf/10.1145/2872427.2883014

Aruna Balasubramanian

Papers

Demystifying page load performance with WProf

Replication routing in DTNs: a resource allocation approach

How speedy is SPDY

Web search from a bus

An In-depth Study of Mobile Browser Performance