Founded on the recognition that the ideas and technology of computing and information science are relevant to every academic discipline, CIS capitalizes on interdisciplinary collaboration to accelerate knowledge creation and discovery. At the center of Cornell's Information Campus, Computing and Information Science (CIS) bridges information and innovation.

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  • Shoal: A Lossless Network for High-density and Disaggregated Racks 

    Shrivastav, Vishal; Valadarsky, Asaf; Ballani, Hitesh; Costa, Paolo; Lee, Ki Suh; Wang, Han; Agarwal, Rachit; Weatherspoon, Hakim (2017-04-30)
    Rack-scale computers comprise hundreds of micro-servers connected to internal storage and memory through an internal network. However, their density and disaggregated nature pose a problem for existing packet-switched ...
  • Full-Processor Timing Channel Protection with Applications to Secure Hardware Compartments 

    Ferraiuolo, Andrew; Wang, Yao; Xu, Rui; Zhang, Danfeng; Myers, Andrew; Suh, Edward (2017-04-25)
    This paper presents timing compartments, a hardware architecture abstraction that eliminates microarchitectural timing channels between groups of processes of VMs running on shared hardware. When coupled ...
  • Unrestricted Stone Duality for Markov Processes 

    Furber, Robert; Kozen, Dexter; Larsen, Kim; Mardare, Radu; Panangaden, Prakash (2017-02-23)
    Stone duality relates logic, in the form of Boolean algebra, to spaces. Stone-type dualities abound in computer science and have been of great use in understanding the relationship between computational models and the ...
  • Election Verifiability: Cryptographic Definitions and an Analysis of Helios and JCJ 

    Smyth, Ben; Frink, Steven; Clarkson, Michael R. (2017-02-13)
    Definitions of election verifiability in the computational model of cryptography are proposed. The definitions formalize notions of voters verifying their own votes, auditors verifying the tally of votes, and auditors ...
  • Mixing Consistency in Geodistributed Transactions: Technical Report 

    Milano, Matthew P.; Myers, Andrew C. (2016-10-07)
    Weakly consistent data stores have become popular because they enable highly available, scalable distributed applications. However, some data needs strong consistency. For applications that mix accesses to strongly and ...

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