2017/11/06 by Anupam Gupta, Guru Guruganesh, Gupta, Anupam +5
Computer Science · Engineering · #Advanced Manufacturing and Logistics Optimization #Data Structures and Algorithms (cs.DS) #F.2.3 #FOS: Computer and information sciences #Optimization and Packing Problems #Optimization and Search Problems
paper · pdf · doi:10.48550/arxiv.1711.02078
openalex publication_date 2017/11/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We study the classic Bin Packing problem in a fully-dynamic setting, where new items can arrive and old items may depart. We want algorithms with low asymptotic competitive ratio while repacking items sparingly between updates. Formally, each item i has a movement cost ci≥ 0, and we want to use α⋅ OPT bins and incur a movement cost γ⋅ ci, either in the worst case, or in an amortized sense, for α, γ as small as possible. We call γ the recourse of the algorithm. This is motivated by cloud storage applications, where fully-dynamic Bin Packing models the problem of data backup to minimize the number of disks used, as well as communication incurred in moving file backups between disks. Since the set of files changes over time, we could recompute a solution periodically from scratch, but this would give a high number of disk rewrites, incurring a high energy cost and possible wear and tear of the disks. In this work, we present optimal tradeoffs between number of bins used and number of items repacked, as well as natural extensions of the latter measure.