State of the Network: January

In our latest monthly report, we examine the performance of the Swarm network for January, continuing our ongoing analysis of the network's dynamics. This month, we again report on key metrics such as total network rewards, win values, active staking nodes, and geographic distribution of nodes to understand the network's current state and trends.

Network Total Monthly Rewards

This metric shows the total rewards paid out across the entire network for each month.

Month	Total Network Rewards (xBZZ)
August	135,927
September	147,825
October	152,868
November	148,617
December	159,865
January	157,596

In January, the Swarm network distributed a total of 157,596 xBZZ in rewards to its node operators. This slight decrease from December's record of 159,865 xBZZ perhaps indicates a stabilisation in network utilisation after the recent growth spurts. This metric remains a critical indicator of the network's health and its capacity to incentivise participation.

Monthly Median Win Values

This metric is the median win amount for each win event.

Month	Median Win Values (xBZZ)
August	43.97
September	44.62
October	46.84
November	46.83
December	48.06
January	47.43

The median win value experienced a very slight decrease to 47.43 xBZZ in January from 48.06 xBZZ in December, falling into the range of values from recent months.

Monthly Average Win Values

This metric is the average win amount for each win event.

Month	Average Win Values (xBZZ)
August	41.45
September	46.52
October	62.09
November	47.41
December	57.75
January	51.20

January saw the average win value adjust to 51.20 xBZZ, down from 57.75 xBZZ in December.

Active Staking Node Monthly Average Earnings

This metric shows the average monthly earnings for an active staking node.

Month	Avg Total Earnings per Node (xBZZ)
August	31.11
September	32.31
October	14.73
November	8.12
December	12.40
January	13.89

The average earnings per active staking node increased to 13.89 xBZZ in January. This rise, against a backdrop of a slight decrease in the total number of active staking nodes, illustrates the network's dynamic self-adjusting economic model.

Total Active Staking Nodes by Month

This metric shows the total active staking nodes by month. "Active nodes" are nodes which have submitted a commit transaction at least once within the month (this metric does not measure nodes which have been actively participating in neighbourhoods not chosen within the month).

Month	Total Active Staking Nodes
August	4,368
September	4,574
October	10,367
November	20,868
December	12,891
January	11,350

January's active staking nodes decreased to 11,350 from December's 12,891. This reduction possibly indicates tighter competition among node operators.

Total Winning Nodes by Month

This metric shows the total number of unique active staking nodes which have won at least once within the month.

Month	Total Winning Nodes
August	1,993
September	2,125
October	2,462
November	2,787
December	2,308
January	2,474

The total number of unique active staking nodes that won at least once rose to 2,474 in January from 2,308 in December.

Total Active Staking Nodes by Country

This metric shows the total number of active staking nodes across the top four countries and all other countries aggregated into the "Other" category, as well as the remaining nodes in the "Unknown" category.

	China	Germany	Finland	Unknown	United States	Other
August	855	1,481	1,611	267	7	147
September	574	2,046	1,607	217	8	123
October	6,242	2,042	1,543	175	282	91
November	16,145	2,225	1,961	37	363	137
December	8,333	2,001	1,919	265	312	61
January	6,696	1,937	1,769	701	181	66

January showed a slight reshuffling in the geographic distribution of active staking nodes, with a decrease in nodes from China and adjustments in other regions.

Conclusion

January's data for the Swarm network perhaps indicates a period of stabilisation and maturation, with trends in rewards, node participation, and geographical distribution showing subtle adjustments rather than dramatic shifts. The slight decrease in total rewards and active nodes, alongside an increase in average earnings per node, suggests a more efficient allocation of resources within a competitive ecosystem. Moreover, the evolving geographic distribution of nodes highlights Swarm's continuing global reach.