Asterisk Call Center: Queue Strategies (ringall, leastrecent, fewestcalls, linear) (Latest Versions)

In an Asterisk call-center environment, the queue strategy determines how incoming calls are distributed among available agents.

While queues may appear simple, the chosen distribution algorithm directly affects:

• Customer wait time
• Agent workload balance
• Service-level agreement (SLA) compliance
• Overall call-center efficiency

Selecting the correct queue strategy is therefore a business-critical architectural decision, not just a configuration detail.

How Queue Distribution Works Internally

When a caller enters a queue:

1. Asterisk checks which agents are logged in and not paused
2. The selected strategy algorithm chooses the next agent
3. The call is delivered according to penalties, timeouts, and retry rules

Different strategies optimize for different goals such as fairness, speed, or simplicity.

Common Queue Strategies in Asterisk

• linear → fixed order routing
• leastrecent → agent idle longest gets call
• fewestcalls → agent with lowest call count gets call
• random → random distribution
• rrmemory → round-robin with memory

This article focuses on the three most widely used enterprise production strategies: linear, leastrecent, and fewestcalls.

Linear Strategy (Predictable but Unbalanced)

The linear strategy always calls agents in the same order.

strategy=linear

Behavior

• Agent 1 rings first
• If busy → Agent 2 rings
• Order never changes

Advantages

• Simple and predictable
• Useful for small teams or priority routing

Disadvantages

• First agents receive most calls
• Uneven workload distribution
• Poor scalability in real call centers

Leastrecent Strategy (Fair Idle-Time Distribution)

The leastrecent strategy sends the next call to the agent who has been idle for the longest time.

strategy=leastrecent

Behavior

• Tracks last call completion time for each agent
• Selects the longest-idle agent

Advantages

• Balanced idle time across agents
• Improves fairness in workload
• Common in customer support centers

Disadvantages

• Does not account for total call count
• Agents with shorter calls may still receive more calls

FewestCalls Strategy (Balanced by Volume)

The fewestcalls strategy routes calls to the agent who has handled the lowest total number of calls.

strategy=fewestcalls

Behavior

• Maintains cumulative call counters per agent
• Chooses the lowest count first

Advantages

• Best long-term workload balance
• Prevents agent burnout
• Common in sales or outbound teams

Disadvantages

• May ignore real-time idle duration
• Slightly higher computational overhead

Real-World Strategy Selection Guide

Queue Configuration Example

[support]
strategy=leastrecent
timeout=15
retry=5
wrapuptime=10
maxlen=0

Strategy tuning must always be combined with:

• Agent penalties
• Wrap-up time
• Retry intervals
• Queue length limits

Common Production Problems

• Agents receiving uneven call volume due to wrong strategy
• Idle agents not getting calls because of pause state
• Service levels dropping from poor timeout tuning
• Queue appearing “stuck” when strategy conflicts with penalties

Debugging Queue Behavior

queue show support

This reveals:

• Agent status and pause state
• Call distribution order
• Total calls handled per agent

MYLINEHUB Architecture Insight

In MYLINEHUB call-center deployments:

• Queue strategy is selected per campaign or organization
• Dynamic agent state is stored in database
• Real-time analytics track fairness and SLA performance
• AI-driven routing may override classical strategies when needed

This enables scalable, multi-tenant, enterprise-grade telecom distribution logic.

Final Takeaway

Queue strategies define how fairly and efficiently customers are connected to agents.

The correct choice depends on:

• Team size
• Business objective (speed vs fairness)
• Operational metrics and SLA goals

Understanding and tuning queue strategies is essential for building a high-performance, enterprise-ready Asterisk call center.