Emerging Networking Technologies

Information-Centric Networking (ICN) / Named Data Networking (NDN)

ICN shifts the network paradigm from host-centric (where is it?) to content-centric (what do I want?).

NDN Architecture

NDN (the leading ICN architecture) uses two packet types and three data structures.

Packets:

• Interest: Consumer requests data by name (e.g., /com/example/video/segment-42).
• Data: Producer (or cache) returns signed data matching the Interest name.

Per-node data structures:

NDN Forwarding Process

Interest arrives:
  1. Check CS → if match, return Data (cache hit)
  2. Check PIT → if existing entry for same name, add incoming face (aggregate)
  3. Check FIB → forward Interest toward producer; create PIT entry

Data arrives:
  1. Match against PIT → forward Data to all recorded incoming faces
  2. Optionally cache in CS
  3. Remove PIT entry

NDN Properties

Challenges

• Name-based routing does not scale like IP prefix aggregation.
• PIT state per pending request introduces DoS vulnerability (Interest flooding attack).
• Cache privacy: timing attacks can reveal cached content.
• Incremental deployment over existing IP infrastructure.

LEO Satellite Networks

Low Earth Orbit (LEO) satellite constellations provide global broadband connectivity with lower latency than GEO satellites.

Orbital Parameters

Starlink Architecture

User Terminal (phased-array antenna)
    ↕ Ka/Ku-band
Starlink Satellite (LEO, ~550 km)
    ↕ Optical inter-satellite links (ISLs)
Adjacent Satellites
    ↕ Ka/Ku-band
Ground Station (gateway to Internet)

• Constellation: ~6,000+ satellites in multiple orbital shells (as of 2025).
• Inter-satellite links (ISLs): Laser links between satellites enable traffic to traverse the constellation without touching the ground. In vacuum, light travels ~1.47x faster than in fiber, making satellite paths potentially faster than terrestrial fiber for long distances.
• Handover: As satellites move (7.5 km/s), user terminals must switch between satellites frequently (~15-second intervals).

Networking Challenges

Routing Approaches

• Snapshot-based: Precompute routes for discrete time intervals; topology is quasi-periodic.
• Geographic routing: Forward toward the satellite closest to the destination ground station.
• Contact graph routing: Model satellite contacts as a time-evolving graph; compute time-dependent shortest paths.

Time-Sensitive Networking (TSN)

IEEE 802.1 TSN standards enable deterministic, bounded-latency communication over Ethernet.

Key TSN Standards

Time-Aware Shaper (TAS)

Time axis divided into repeating cycles:

Cycle: |  Slot A  |  Slot B  | Slot C | Guard |
       | Critical | Scheduled|  Best  | Band  |
       | traffic  | traffic  | effort |       |

Gate states per queue: OPEN or CLOSED
Only queues with open gates can transmit in each slot.

• Provides deterministic, bounded latency for critical traffic.
• Requires precise time synchronization (802.1AS).
• Schedule computed offline by a Central Network Controller (CNC).

TSN Applications

Network Slicing (5G)

Network slicing creates multiple logical networks on shared physical infrastructure, each tailored to specific service requirements.

5G Slice Types (3GPP)

Slicing Architecture

                   Shared Physical Infrastructure
                  /            |              \
        +--------+    +-------+     +---------+
        | Slice 1 |    | Slice 2|    | Slice 3  |
        | eMBB    |    | URLLC  |    | MIoT     |
        | (video) |    | (auto) |    | (sensor) |
        +--------+    +-------+     +---------+
        Each slice has its own:
          - RAN configuration (scheduling, numerology)
          - Core network functions (SMF, UPF)
          - SLA guarantees (bandwidth, latency, reliability)

Implementation Technologies

Slice Isolation

• Resource isolation: Dedicated spectrum, compute, and network resources per slice.
• Performance isolation: One slice's traffic surge does not degrade another slice's SLA.
• Security isolation: Separate authentication, encryption, and policy domains.

In-Network Computing

Processing data within the network (at switches, SmartNICs) rather than only at endpoints.

Programmable Switch Applications

Using P4-programmable switches (e.g., Intel Tofino) for computation.

In-Network Aggregation for ML

Traditional AllReduce:
  Worker 1 ──→ Parameter Server ──→ Worker 1
  Worker 2 ──→ (aggregates all)  ──→ Worker 2
  Worker 3 ──→                   ──→ Worker 3

In-network aggregation:
  Worker 1 ──→ Switch (aggregates ──→ Worker 1
  Worker 2 ──→ gradients in      ──→ Worker 2
  Worker 3 ──→ data plane)       ──→ Worker 3

• Reduces network traffic by aggregating at the switch.
• SwitchML achieves near-ideal speedup for distributed training.
• Challenges: limited switch memory, fixed-point arithmetic, fault tolerance.

Computational Storage and Processing

• SmartNIC computing: Run application logic (e.g., consensus, encryption, compression) on DPU/IPU processors.
• Computational storage: Process queries at the storage device (e.g., filtering in NVMe SSDs).
• In-network databases: Push selection and aggregation to network switches.

Quantum Networking Fundamentals

Quantum networking uses quantum mechanical properties (superposition, entanglement) to enable communication capabilities impossible with classical networks.

Key Concepts

Quantum Key Distribution (QKD)

The most mature quantum networking application. Uses quantum mechanics to establish provably secure encryption keys.

BB84 Protocol:

1. Alice sends qubits in random bases (rectilinear + or diagonal x)
2. Bob measures in random bases
3. Public comparison of bases (not values); keep only matching-basis bits
4. Error rate check: if too high, eavesdropper detected (discard)
5. Privacy amplification → shared secret key

• Security guaranteed by physics (measurement disturbs quantum states).
• Limited by distance (photon loss in fiber ~0.2 dB/km; ~100 km practical limit without repeaters).
• Commercial QKD systems exist (ID Quantique, Toshiba).

Quantum Repeaters

Classical amplifiers cannot be used (no-cloning theorem). Quantum repeaters use entanglement swapping.

Node A ←entangle→ Repeater ←entangle→ Node B
         (segment 1)         (segment 2)

Repeater performs Bell measurement on its two qubits:
  → A and B become entangled (entanglement swapping)
  → Extends entanglement distance

• First generation: Entanglement swapping + purification; requires quantum memory.
• Second generation: Adds quantum error correction.
• Third generation: Full quantum error correction (fault-tolerant); enables arbitrary-distance quantum communication.
• Current status: experimental demonstrations at lab scale; practical repeaters remain a major research challenge.

Quantum Internet Architecture

End nodes (quantum processors)
    ↕ quantum channels (fiber / free-space optical)
Quantum repeaters (extend entanglement)
    ↕
Quantum switches/routers (entanglement routing)
    ↕
Classical control plane (manages quantum resources)

Development Stages (Wehner et al.)

Current State and Challenges

• QKD networks operational in China (Beijing-Shanghai backbone, 2000 km), EU (EuroQCI), and other regions.
• Satellite-based QKD demonstrated (Micius satellite, China).
• Quantum memories with sufficient coherence times remain a primary hardware bottleneck.
• Entanglement routing and resource management are open research problems.
• Integration with classical Internet infrastructure requires new protocol stacks.