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Record W2413962607

Next-generation networking technologies from Bell labs

2009· article· en· W2413962607 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Symposium on Wireless Communication Systems · 2009
Typearticle
Languageen
FieldComputer Science
TopicMobile Agent-Based Network Management
Canadian institutionsBell (Canada)
Fundersnot available
KeywordsComputer scienceComputer networkRouterThe InternetTelecommunicationsVoice over IPHost (biology)Next-generation networkWorld Wide Web
DOInot available

Abstract

fetched live from OpenAlex

The telecom industry has an aspiration of moving to an Internet core for all of its services. Even cellular networks, with billions of end points, are moving to an Internet core. This poses a number of challenges, especially with ever-increasing content traffic. This talk will present these challenges and some efforts at Bell Labs to deal with them. Some of these challenges are issues with Mobile IP, increased complexity of routers, and the need to deal with increasing opex expenses. Here are some solutions Bell labs is working on to enable migration of telecom networks to an Internet core. • Making Mobility a core part of the Internet: Mobile IP is a patch on the original IP design. Traffic sent to a mobile client is first sent to a home agent, which in turn tunnels it to the client in its current location. This design should be fixed to avoid triangulation. Bell Labs has designed a new protocol to deal with this issue. In our new approach, a mobile host gets an address locally (using a lightweight DHCP). Then this address, along with the host's unique ID, gets advertised on the network. • Router designs: The networking community is looking at approaches to open up routers so that third parties can add new features. Bell Labs has developed an approach called softrouter in which routers are disaggregated into simple forwarding elements and shared control elements. This approach enables the easy addition of new functions to the IP networks. • Self-management: Opex is beginning to dominate the total cost of ownership of networks, resulting in a high cost of service to the end-user. This is getting worse with the deployment of femto cells in homes and increasingly complex services. To change this trend, we need extensive automation of the deployment, configuration and optimization of networks. Scalability requires decentralized solutions where discovery and network integration tasks are performed with locally available information under local control. This is in contrast to the mostly centralized network management systems used today. Bell Labs has an extensive program in this area. This research uses various mathematical approaches such as linear programming and genetic programming.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.836
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.040
GPT teacher head0.258
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it