Ginseng: Market-driven memory allocation

Orna Agmon Ben-Yehuda, Eyal Posener, Muli Ben-Yehuda, Assaf Schuster, Ahuva Mu'alem

Research output: Contribution to conferencePaperpeer-review


Physical memory is the scarcest resource in today's cloud computing platforms. Cloud providers would like to maximize their clients' satisfaction by renting precious physical memory to those clients who value it the most. But real-world cloud clients are selfish: they will only tell their providers the truth about how much they value memory when it is in their own best interest to do so. How can real- world cloud providers allocate memory efficiently to those (selfish) clients who value it the most? We present Ginseng, the first market-driven cloud system that allocates memory efficiently to selfish cloud clients. Ginseng incentivizes selfish clients to bid their true value for the memory they need when they need it. Ginseng continuously collects client bids, finds an efficient memory allocation, and re-allocates physical memory to the clients that value it the most. Ginseng achieves a 6:2 × -15:8 × improvement (83%-100% of the optimum) in aggregate client satisfaction when compared with state-of-the-art approaches for cloud memory allocation. Copyright is held by the owner/author(s).

Original languageEnglish
Number of pages12
StatePublished - 2014
Externally publishedYes
Event10th ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments, VEE 2014 - Salt Lake City, UT, United States
Duration: 1 Mar 20142 Mar 2014


Conference10th ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments, VEE 2014
Country/TerritoryUnited States
CitySalt Lake City, UT


  • KVM
  • Memory Overcommitment

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software


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