A simple on-line bin-packing algorithm
Journal of the ACM (JACM)
Static scheduling of synchronous data flow programs for digital signal processing
IEEE Transactions on Computers
On-line bin packing in linear time
Journal of Algorithms
Static Rate-Optimal Scheduling of Iterative Data-Flow Programs Via Optimum Unfolding
IEEE Transactions on Computers
Improved bounds for harmonic-based bin packing algorithms
Discrete Applied Mathematics - Special volume: combinatorics and theoretical computer science
Improved space for bounded-space, on-line bin-packing
SIAM Journal on Discrete Mathematics
Multidimensional on-line bin-packing: an algorithm and its average-case analysis
Information Processing Letters
Delivering voice over IP networks
Delivering voice over IP networks
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
CloudOpt: multi-goal optimization of application deployments across a cloud
Proceedings of the 7th International Conference on Network and Services Management
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New and proposed communication systems are entirely digital, including Voice over Internet Protocol tasks as well as traditional data packets, fax, etc. Numerous digital signal processing (DSP) algorithms are available to encode and decode these signals, each having different requirements for data memory, program memory, and processor speed. A DSP multiprocessor having numerous DSP cores receives a stream of requests for encoding and decoding tasks. A service request is "blocked" if no DSP core can handle the task when it arrives. We present algorithms for assigning DSP tasks to cores in order to minimize the number of blocked tasks. This is similar to an online bin-packing problem with the important difference that the program memory can be shared between simultaneous service requests for the same DSP algorithm. Since bin-packing is known to be NP-complete, we develop fast heuristic online methods for this problem.