An official website of the United States government
The goal of this short document is to explain why recent developments in the Internet's infrastructure are problematic. As context, we note that the Internet was originally designed to provide a simple universal service - global end-to-end packet delivery - on which a wide variety of end-user applications could be built. The early Internet supported this packet-delivery service via an interconnected collection of commercial Internet Service Providers (ISPs) that we will refer to collectively as the public Internet. The Internet has fulfilled its packet-delivery mission far beyond all expectations and is now the dominant global communications infrastructure. By providing a level playing field on which new applications could be deployed, the Internet has enabled a degree of innovation that no one could have foreseen. To improve performance for some common applications, enhancements such as caching (as in content-delivery networks) have been gradually added to the Internet. The resulting performance improvements are so significant that such enhancements are now effectively necessary to meet current content delivery demands. Despite these tangible benefits, this document argues that the way these enhancements are currently deployed seriously undermines the sustainability of the public Internet and could lead to an Internet infrastructure that reaches fewer people and is largely concentrated among only a few large-scale providers. We wrote this document because we fear that these developments are now decidedly tipping the Internet's playing field towards those who can deploy these enhancements at massive scale, which in turn will limit the degree to which the future Internet can support unfettered innovation. This document begins by explaining our concerns but goes on to articulate how this unfortunate fate can be avoided. To provide more depth for those who seek it, we provide a separate addendum with further detail.
more »
« less
Disease, disaster and the internet: Reconceptualizing environmental hazards in the time of coronavirus
The internet is made from a vast physical system of cables that stretch unseen across prairies, mountains, oceans, under streets and within buildings. Our online information rapidly flows through this global lattice of equipment every time we send e-mails, play online games, stream Netflix or teleconference with co-workers. With a global society that has recently shifted to living, working and entertaining almost entirely online – to the point of pushing our internet’s capacity to its brink – it is worth considering the threat of disease to an industry that has traditionally prepared for a different set of environmental risks. Disasters such as earthquakes, tsunami, power outages and fishermen’s anchors have long been considered the leading environmental threats to the internet. But what about a pandemic? This article builds on a visit I took to a Seattle data centre in March 2020, when the city was beginning to go on coronavirus lockdown. As I toured the data centre’s earthquake-preparedness equipment, back-up batteries and servers sheltered within protective cages, I could not help but consider if the internet, and the thousands of employees who keep it in operation, were equipped to handle this type of ecological invader?
more »
« less
- Award ID(s):
- 1947134
- PAR ID:
- 10469981
- Publisher / Repository:
- Intellect Books
- Date Published:
- Journal Name:
- Journal of Environmental Media
- Volume:
- 1
- Issue:
- Supplement 1
- ISSN:
- 2632-2463
- Page Range / eLocation ID:
- 10.1 to 10.8
- Subject(s) / Keyword(s):
- internet, environment, disease, COVID-19, infrastructure, telecommunications, ocean
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
With the proliferation of data movement across the Internet, global data traffic per year has already exceeded the Zettabyte scale. The network infrastructure and end-systems facilitating the vast data movement consume an extensive amount of electricity, measured in terawatt-hours per year. This massive energy footprint costs the world economy billions of dollars partially due to energy consumed at the network end-systems. Although extensive research has been done on managing power consumption within the core networking infrastructure, there is little research on reducing the power consumption at the end-systems during active data transfers. This paper presents a novel cross-layer optimization framework, called Cross-LayerHLA, to minimize energy consumption at the end-systems by applying machine learning techniques to historical transfer logs and extracting the hidden relationships between different parameters affecting both the performance and resource utilization. It utilizes offline analysis to improve online learning and dynamic tuning of application-level and kernel-level parameters with minimal overhead. This approach minimizes end-system energy consumption and maximizes data transfer throughput. Our experimental results show that Cross-LayerHLA outperforms other state-of-the-art solutions in this area.more » « less
-
null (Ed.)With the popularity of the Internet, traditional offline resource allocation has evolved into a new form, called online resource allocation. It features the online arrivals of agents in the system and the real-time decision-making requirement upon the arrival of each online agent. Both offline and online resource allocation have wide applications in various real-world matching markets ranging from ridesharing to crowdsourcing. There are some emerging applications such as rebalancing in bike sharing and trip-vehicle dispatching in ridesharing, which involve a two-stage resource allocation process. The process consists of an offline phase and another sequential online phase, and both phases compete for the same set of resources. In this paper, we propose a unified model which incorporates both offline and online resource allocation into a single framework. Our model assumes non-uniform and known arrival distributions for online agents in the second online phase, which can be learned from historical data. We propose a parameterized linear programming (LP)-based algorithm, which is shown to be at most a constant factor of 1/4 from the optimal. Experimental results on the real dataset show that our LP-based approaches outperform the LP-agnostic heuristics in terms of robustness and effectiveness.more » « less
-
null (Ed.)Smart city projects have the potential to improve the management of environmental and public infrastructure. However, the operational and capital expenditures of smart cities can prevent cities from becoming smarter. A notable factor that influences the cost is providing cellular Internet connectivity to IoT devices. 5G has been proposed as a possible solution, but projections show that 5G will not be able to support the load of billions of IoT devices coming online. To mitigate this, people, vehicles, and other nodes in transportation networks can be exploited to transmit non-urgent data by leveraging device-to-device communication in order to reduce cellular connectivity costs associated with smart city sensors. Hence, this paper addresses cost-effective edge node placement in smart cities that opportunistically leverage public transit networks. We introduce an algorithm that selects a set of edge nodes that provide minimal delivery delay within a budget. The algorithm is evaluated for two public transit network data-sets: Chapel Hill, North Carolina and Louisville, Kentucky and results show that our algorithm outperforms betweeness and in-degree centrality metrics with a reduction in latency of over 20 minutes.more » « less
-
Direct exploitation, which includes the trade of wild animals for their parts, is a major driver of extinction. Digital communication tools, particularly the internet, have facilitated the trade in endangered species. Here, we automatically collected data to analyze online sales of threatened animals across 148 English-text online mar- ketplaces. We created a tool that searched for online sales of 13,267 animal species at risk of global extinction, as classified by the International Union for Conservation of Nature (IUCN), as well as 706 animal species on Ap- pendix I of the Convention for International Trade in Endangered Species (CITES), for which international commercial trade is prohibited. Examining a period of 15 weeks in 2018, we identified 10,699 unique listings selling body parts or eggs of threatened species, of which 4131 contained a full species name (common or sci- entific). These 4131 results were then filtered by keywords and, finally, manually vetted, which yielded 546 sale listings for 83 species. Of these 546 listings, 61 % advertised shark trophies (mainly jaws), 73 % of which were taken from species listed as endangered or critically endangered. Just four websites hosted >95 % of listings. We identified 18 species for sale that are included on CITES Appendix I. We also identified 13 species for which the IUCN had not identified intentional use as a threat. This work expands current understanding about the dealing of endangered and potentially illegal species online, specifies taxa threatened by online trade, and highlights emerging opportunities and persistent challenges to preventing the trafficking of threatened species.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1386/jem_00031_1
