California Institute of Technology

Northeastern University

Derek Leong

Tracey Ho

Yunkai Wei

Asma Qureshi

Edmund Meng Yeh

Hongyi Yao

Ran Liu

Michael Burd

Ying Cui

Zhao Li

A system and method for joint dynamic interest request forwarding and dynamic cache placement and eviction and provided within the context of the Named Data Networking (NDN) architecture. The system and method employ a virtual control plane that operates on the user demand rate for data objects in the network, and an actual plane that handles Interest Packets and Data Packets. Distributed algorithms within the virtual plane achieve network load balancing through dynamic forwarding and caching, thereby maximizing the user demand rate that the NDN network can satisfy. A method of congestion control is also provided to achieve optimal network fairness using the VIP framework.

System and method for joint dynamic forwarding and caching in content distribution networks

A computer-based real-time streaming system under packet erasures wherein created messages can be decoded within a fixed delay form their creation is presented. Various code construction methods and corresponding hardware implementation for different cases of erasure link models are also presented.

Coding for real-time streaming under packet erasures

Allocation of storage budget in a computer-based distributed storage system is described, where associated computer-based storage nodes have heterogeneous access probabilities. The problem is to allocate a given storage budget across the available computer-based nodes so as to store a unit-size data object (e.g. file) with a higher reliability (e.g. increased probability for the storage budget to be recovered). Efficient algorithms for optimizing over one or more classes of allocations are presented. A basic one-level symmetric allocation is presented, where the storage budget is spread evenly over an appropriately chosen subset of nodes. Furthermore, a two-level symmetric allocation is presented, where the budget is divided into two parts, each spread evenly over a different subset of computer-based storage nodes, such that the amount allocated to each node in the first subset is twice that of the second subset. Further expansion of the two-level symmetric allocation is provided with a three-level and a generic k-level symmetric allocation.

Distributed storage allocation for heterogeneous systems

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Pasadena, CA, United States of America

Derek Leong