Load Balancing with Minimal Deviation in Switch Memories

Yaniv Sadeh, Ori Rottenstreich, Haim Kaplan

Research output: Contribution to journalArticlepeer-review


Traffic splitting is a required functionality in networks, for example for load balancing over multiple paths or among different servers. The capacities of the servers determine the partition by which traffic should be split. A recent approach implements traffic splitting within the ternary content addressable memory (TCAM), which is often available in switches. It is important to reduce the amount of memory allocated for this task since TCAMs are power consuming and are also required for other tasks such as classification and routing. Previous work showed how to compute the smallest prefix-matching TCAM necessary to implement a given partition exactly. In this paper we solve the more practical case, where at most n prefix-matching TCAM rules are available, restricting the ability to implement exactly the desired partition. We consider the L1 distance between partitions, which is of interest when overloaded requests are simply dropped, and we want to minimize the total loss. We prove that the Niagara algorithm 2 can be used to find the closest partition in L1 to the desired partition, that can be realized with n TCAM rules. Moreover, we prove it for arbitrary partitions, with (possibly) non-integer parts. We also include a short discussion on similarities and differences to previous work which studies the same problem but for L∞ distances.

Original languageEnglish
Pages (from-to)1
Number of pages1
JournalIEEE Transactions on Network and Service Management
StateAccepted/In press - 2023


  • Costs
  • Load Balancing
  • Load management
  • Memory management
  • Partitioning algorithms
  • Servers
  • Switches
  • TCAM
  • Task analysis
  • Traffic Splitting


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