{"id":595,"date":"2019-11-09T21:00:08","date_gmt":"2019-11-09T18:00:08","guid":{"rendered":"http:\/\/nawab.me\/blog\/?p=595"},"modified":"2019-11-09T21:10:09","modified_gmt":"2019-11-09T18:10:09","slug":"whats-hot-in-systemsnetworking-research","status":"publish","type":"post","link":"http:\/\/nawab.me\/blog\/2019\/11\/09\/whats-hot-in-systemsnetworking-research\/","title":{"rendered":"What’s hot in systems\/networking research?"},"content":{"rendered":"

What is the future of computer systems and networking research? This\u00a0is what the joint NSF CSR\/NeTS PI meeting<\/a> helped me answer earlier this\u00a0week. And the answer might surprise you! This meeting is\u00a0hosted by the National Science Foundation (NSF) where more than 300\u00a0professors were invited to discuss what the next exciting challenges\u00a0would be in the broad areas of computer systems and networking research.<\/p>\n

\"csrnetsmeeting\"<\/a><\/p>\n

The PI meeting was organized by holding parallel\u00a0break-out sessions. Each break-out session has a topic of discussion\u00a0and a lead. These topics of discussions were sampled from attendees\u00a0and the organizers aggregated all the answers and came up with the program. The dominating topic in these break-out sessions was a\u00a0surprise to me! Many would expect that the dominating topics would be\u00a0machine learning and\/or blockchain. (Machine learning DID come second\u00a0in the aggregated answer.) Blockchain, however, was second to last and did not\u00a0have a dedicated break-out session! The topic of discussion that was most requested in the PI meeting\u00a0was edge computing systems! This translated into having most of the break-out sessions be about or around edge computing topics (9 out of the 23 break-out sessions\u00a0here<\/a>) and many of the rest of the sessions have edge computing and related topics as one of the points of discussions.<\/p>\n

“The topic of discussion that was most requested in the PI meeting is edge computing systems!”<\/h1>\n

Seeing this was delightful to me, as I have started a couple of years\u00a0ago working in data management for edge-cloud systems, and seeing that this area is\u00a0recognized as an important area by my peers (and ultimately NSF\u00a0reviewers!) validates my area choice. Nonetheless, I was surprised as\u00a0I knew that there are overwhelming interest and opportunities in both\u00a0ML and blockchain. But attending the break-out sessions helped me realize\u00a0what is happening.<\/p>\n

Unfortunately, all break-out sessions were in parallel for two\u00a0sessions only, so we can only attend two! The choice was hard. I knew\u00a0I wanted to go to an edge session — but there were so many! I ended\u00a0up choosing to go to the session about “Computer Architecture for\u00a0Edge Computing”, in which we discussed the challenges and\u00a0opportunities in computer architecture for edge computing. In that\u00a0session, I quickly realized why many PIs viewed the edge as one of the main\u00a0areas of future research. A lot of them were already tackling problems\u00a0in ML, blockchain, cloud computing, and others. And what many PIs realize is that utilizing the edge infrastructure can be a frontier to\u00a0overcome the fundamental limits of today’s computing paradigms. Their view of the edge is as an extension to the\u00a0cloud or to as a new infrastructure for their applications that would enable doing more compute and storage closer to\u00a0users.<\/p>\n

“what many PIs\u00a0realize is that utilizing the edge infrastructure can be a frontier to overcome the fundamental limits of today’s computing paradigms.”<\/h1>\n

The edge seems to be the infrastructure that would enable many\u00a0of the exciting emerging applications in ML and video-based social\u00a0networks. These applications that deal with rich multimedia data and\u00a0require real-time performance can only be realized by removing the\u00a0gap between the users and the cloud, which is a natural role for the\u00a0edge.<\/p>\n

The second session I attended was the “Internet-Scale Distributed\u00a0Systems” session, which asked questions about how to support emerging\u00a0data-intensive applications such as 360-degree video streaming, and\u00a0real-time analytics in applications like Industrial IoT (IIoT). The\u00a0conclusion of that session was similar to the first one — the\u00a0enabler of these technologies is an edge infrastructure.<\/p>\n

The sentiment about the edge and how it can enable future\u00a0technologies was clear. However, there are challenges\u00a0in its way, as recognized by many in the audience. After all, the\u00a0edge is not a new idea — it has been there for many decades and it\u00a0has been already successful for streaming and content delivery\u00a0applications. The reason for this renewed excitement about the edge\u00a0is that it seems to have the potential to bring together a lot of the\u00a0foreseen applications in ML, and cloud computing and making them a\u00a0reality. From various discussions in both sessions, the main\u00a0challenges standing in the way of this happening are the following:<\/p>\n

“The reason for this renewed excitement about the edge\u00a0is that it seems to have the potential to bring together a lot of the\u00a0foreseen applications in ML, and cloud computing and making them a\u00a0reality.”<\/h1>\n

From what was discussed, the main challenge, in my opinion, is a chicken and egg problem. Edge\u00a0applications cannot be deployed without an accessible edge\u00a0infrastructure. But, an edge infrastructure would not be built\u00a0without a proven business model and business case for it. The edge\u00a0infrastructure can be built by a big telecommunication company that\u00a0already has the infrastructure around the country, by say placing\u00a0accessible compute and storage service providers on their\u00a0infrastructure. However, why would they make this investment? Would\u00a0there be a return? If we do not want to rely on these big players and\u00a0wait until they take the step forward, another approach to realize\u00a0the edge infrastructure is to start at a small scale. Various small\u00a0players (maybe universities!) could start building edge sites that\u00a0collectively would be a playground for researchers and practitioners\u00a0to prove the case for the edge from both a practical and a business perspective. This bottom-up academic edge infrastructure can be for\u00a0the future global edge infrastructure what ARPANET was for the\u00a0Internet.<\/p>\n

“Various small\u00a0players (maybe universities!) could start building edge sites that\u00a0collectively would be a playground for researchers and practitioners\u00a0to prove the case for the edge from both a practical and a business perspective.”<\/h1>\n

The other challenge deals with the right abstraction for the edge. It\u00a0turned out that different communities have different definitions of\u00a0what constitutes an edge environment and whether there is a need to\u00a0draw a line between edge datacenters, telecommunication\u00a0infrastructure, user’s stationary devices and mobile computing. The\u00a0conclusion to this is to be aware of the differences between these\u00a0abstractions and to be clear which one is considered in one’s work (and grant proposals!). Many shared the view that these represent natural tiering starting from the source of data until the cloud. An area of\u00a0suggested research in one of the sessions is to build data\u00a0management systems as a hierarchical design that adapts to the tiers\u00a0of the users’ infrastructure.<\/p>\n

Another concern that I had pertains to my interest in extending cloud\u00a0applications to leverage edge locations. There are still many\u00a0colleagues who have a traditional view of what an edge application is\u00a0— video analytics in applications like surveillance, smart homes,\u00a0cars, etc. These are definitely great applications that we should\u00a0continue working on. However, there are more opportunities and\u00a0applications that can benefit from the edge. In particular, many of\u00a0the traditional web and cloud applications continue to increase their\u00a0demands on data processing and communication. This includes\u00a0video-based online social networks and VR\/AR\/MR applications. These\u00a0applications are not only about detecting objects in images and\u00a0rendering. Eventually, these applications are going to be tied up\u00a0with a data application that would require real-time retrieval of\u00a0data to be part of the experience of the video-based social network\u00a0or VR\/AR\/MR application. Without this support, many of these\u00a0applications are going to be stuck as single-user applications with\u00a0simple functionality.<\/p>\n

“There is something for\u00a0everyone in edge computing. It is worth it to consider how your research\u00a0problem\/solution would be different if deployed on the edge. The\u00a0reward could be great if (when?) the edge materializes globally.”<\/h1>\n

There were many other discussed challenges and concerns that I won’t describe in detail, such as security, privacy, policy, and\u00a0education. We were told that the reports of all break-out sessions\u00a0will be available online soon! I recommend to look out for them.\u00a0My feelings coming out of the meeting is that there is something for\u00a0everyone in edge computing. It is worth it to consider how your research\u00a0problem\/solution would be different if deployed on the edge. The\u00a0reward could be great if (when?) the edge materialized globally.<\/p>\n


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What is the future of computer systems and networking research? This\u00a0is what the joint NSF CSR\/NeTS PI meeting helped me answer earlier this\u00a0week. And the answer might surprise you! 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