Beaconless Geocast Protocols

• Beaconless geocast protocols are routing frameworks that use local geographic coordinates to forward messages without periodic beacons, minimizing control overhead.
• They employ zones of relevance and delay-based backoff mechanisms to ensure efficient one-to-many communication in dynamic environments like vehicular networks.
• Empirical and theoretical studies show these protocols achieve scalable, robust performance by optimizing redundancy suppression and adaptive retransmissions.

Beaconless geocast protocols are routing frameworks for mobile ad-hoc wireless networks that enable one-to-many communication without reliance on periodic beacon exchange. Instead, message forwarding and suppression rely purely on local geographic coordinates and embedded packet information, significantly reducing control-plane overhead and adapting more robustly to mobility, radio range fluctuations, and network fragmentation. These protocols have been extensively studied both in vehicular networking scenarios and formal theoretical models (Joshi et al., 2022, Gudmundsson et al., 2 Dec 2025).

1. System Model and Beaconless Fundamentals

Beaconless geocast operates under the premise that each node is aware only of its own GPS position and does not possess or maintain periodic neighbor information. The forwarding region is typically specified via two zones:

• Zone of Relevance (ZOR): The geographic region that constitutes the intended recipients.
• Zone of Forwarding (ZOF): Slight expansion of ZOR to include nodes capable of forwarding into ZOR.

Each packet carries essential metadata: unique identifier, last sender position, hop count, and zone-entry flags. The radio coverage is modeled as a nominal disk of radius $R_{tx}$, with symmetric reception assumed. This design contrasts with beacon-based routing, which utilizes periodic HELLO packets for neighbor discovery and route maintenance, incurring significant overhead and instability under mobility (Joshi et al., 2022, Gudmundsson et al., 2 Dec 2025).

2. Heuristics and Protocol Taxonomy

Six representative beaconless geocast protocols have been systematically analyzed in theoretical and simulation studies (Gudmundsson et al., 2 Dec 2025). Their heuristics are summarized below.

Protocol	Key Mechanism	Notes
Simple Flooding	Broadcast once per node per ID	Max redundancy, poor scalability
M-heuristic	Rebroadcast up to $M$ times per node/ID	Adjustable redundancy cap
T-heuristic	Rebroadcast if min-dist $\geq T$	Forces wavefront advance, risks gaps
CD (Center-Distance)	Forward if strictly closer to center	Monotonic region progress
CD-P (Priority Enhancement)	Forward message yielding greatest center reduction	Achieves low maximal node load
Delay-Based	Timer inversely proportional to progress	Powerful in practice, analytically complex

Delay-based mechanisms, including those in practical protocols such as BLR, GeRaF, and greedy beaconless geocast, instantiate contention windows (timers) as monotonic functions of position; upon hearing a more advanced transmission, nodes cancel their own scheduled forwarding (Gudmundsson et al., 2 Dec 2025, Joshi et al., 2022).

3. Forwarding Discipline, Redundancy Suppression, and Operation

The distance-based backoff discipline is central to scalability and throughput. In the DRG protocol (Joshi et al., 2022), each node schedules rebroadcast with

$$BO_d(R_{tx}, d) = MaxBO_d \cdot S_d \left( \frac{R_{tx} - d}{R_{tx}} \right)$$

Nodes geographically furthest from the previous sender select the shortest backoff, thus promoting forward progress per hop and minimizing unnecessary transmissions. Redundant broadcasts are suppressed using an angular criterion: if the angle subtended between two prior transmitters at the candidate node exceeds a threshold $\theta_{min}$ (for instance, $180^\circ$ for $CR_{th}=0.78$), the node cancels its pending retransmission, as the coverage area is already well covered.

Protocol operation is event-driven: upon receiving a packet that has not been seen, the node checks for ZOR/ZOF inclusion and, if eligible, participates in contention, subject to redundancy suppression and implicit acknowledgment rules.

4. Delivery Guarantees, Fragmentation Recovery, and Time Persistence

DRG and related beaconless protocols incorporate multi-tiered mechanisms for message reliability:

• Implicit acknowledgment: Lower-priority rebroadcasts are canceled upon reception of a copy from a node farther from the previous sender.
• Rapid retransmission bursts: After each broadcast, nodes re-enter contention at maximum backoff, ensuring coverage recovery when a "winning" node is absent.
• Long-backoff retransmissions: If a node detects fragmentation (no progress after several rapid attempts), it schedules a retransmission after $LongBO_d$, approximated by the time for a vehicle to traverse a radio range at maximal velocity.
• Time-persistence: Within ZOR, nodes periodically rebroadcast forwarded messages for a persistence interval $T_{Rp}$, ensuring late-arriving nodes can still receive critical information (Joshi et al., 2022).

5. Theoretical Network-Load Analysis

A central metric for protocol efficiency is the worst-case and typical maximum number of times any node receives a given message ("RecMess"). Analytical bounds have been rigorously established for 1D models (Gudmundsson et al., 2 Dec 2025):

Protocol	Unbounded-range RecMess	Bounded-range RecMess
Flooding	$(n-2)k$	$2r k$
M-heuristic	$M k$	$[\min(M/2,2r) k,\min(M,2r)k]$
T-heuristic	$[\lceil n/2T\rceil k, \lceil n/T\rceil k]$	$[\lceil r/T\rceil k, \lceil 2r/T\rceil k]$
CD	$[k, n k]$	$[2k, 2r k]$
CD-P	$[k, n k]$	$[2k, 2r k]$

Probabilistically, under random activation (fair access), CD-P achieves best scaling:

Protocol	Unbounded-range RecMess	Bounded-range RecMess
CD	$\Theta(k^2 \log(n/k+1)),\; k \le n$; $\Theta(n k),\; k>n$	$O(k^{3/2})$
CD-P	$\Theta(k \log n)$	$\Theta(k)$

Simple flooding's unbounded growth makes it unsuitable for dense networks. The CD heuristic, while enforcing monotonic progress, may still induce heavy per-node load. CD-P and delay-based approaches asymptotically minimize maximal node burden (Gudmundsson et al., 2 Dec 2025).

6. Empirical Performance and Comparative Evaluation

Simulations of DRG (Joshi et al., 2022), employing JiST/SWANS with STRAW mobility, demonstrate reliable performance under both dense and sparse conditions:

• Highway scenarios: Both flooding and DRG achieve near-100% Packet Delivery Ratio (PDR) across all densities. Crucially, DRG's overhead scales with number of hops ($O(k)$) and remains invariant as density increases, whereas flooding’s overhead scales with total nodes ($O(n)$), growing rapidly with density.
• City grid scenarios: DRG maintains high PDR even in fragmentation-prone, sparse conditions due to persistent rebroadcasts. Flooding’s delivery sharply deteriorates as node density drops.
• Delay: DRG yields low and density-insensitive end-to-end delay; in extremely sparse scenarios, delay is determined chiefly by physical mobility, aligning with safety timing requirements.
• Redundancy suppression: Angular coverage criteria and backoff scheduling optimize protocol overhead and coverage.

Contrasts with explicit-route geocast and pure flooding are pronounced: explicit paths fail under VANET mobility due to route fragility; flooding overloads the network in all but the most sparse regimes (Joshi et al., 2022).

7. Practical Implications and Protocol Selection

Analysis confirms several practical guidelines (Gudmundsson et al., 2 Dec 2025):

• Beaconless operation obviates neighbor-table maintenance, minimizes energy and bandwidth consumption, and supports rapid topology change.
• Protocols combining monotonic geographic progress (e.g., CD heuristic) with queue-based priority (CD-P) or delay functions (as in DRG) yield optimal per-node load and delivery resilience.
• Adjustable flooding schemes (M-heuristic, T-heuristic) provide a parameterized trade-off between coverage reliability and overhead, suitable for tuning protocol aggressiveness in application-specific deployments.
• For large, dense, or obstacle-rich ad-hoc networks, strict flooding should be avoided; event-driven forwarding with spatial suppression ensures scalability.
• The mathematical and simulation results obtained in 1D and 2D inform the design and deployment of robust protocols for urban vehicular, sensor, and inter-vehicle communication domains (Joshi et al., 2022, Gudmundsson et al., 2 Dec 2025).

8. Open Problems and Theoretical Directions

While delay-based beaconless geocast protocols achieve empirical success, their worst-case analytical characterization remains challenging outside 1D settings. The formal paper of coverage bounds, contention orderings, and suppression rules in higher dimensions and under realistic MAC contention is an active area. Techniques including coupling, stochastic domination, and large deviations underpin current results for CD and CD-P, but further quantitative analyses for delay-based heuristics in dynamic, heterogeneous networks are warranted (Gudmundsson et al., 2 Dec 2025).

A plausible implication is that the integration of event-driven state, geometric suppression, and distributed activation may extend optimal scaling properties to complex spatial topologies and intermittent connectivity regimes. Continued synthesis of theoretical and empirical methodology will shape future network protocol developments.