Bin Packing With Fragile Objects Nikhil Bansal (CMU) Joint with Zhen Liu (IBM) & Arvind Sankar(MIT)
Motivation Many Users Limited Frequency channels Question: How to share channels?
Sharing Channels Limit on users/channel: Signal to Noise Ratio (SNR, ) Users 1,2 and 3 : Signals s 1, s 2 and s 3 Eg: Signals 5,5,10,10 N 0 =0 =2/3 (5,5) or (10,10) fine but (5,10) not possible
A Special kind of Bin Packing Users = Objects, Freq. Channels = Bins, Signals = Weights, Packing where objects are Fragile Each object limits total weight of the bin it lies in s 1 +s 2 +s 3 · (1+1/ ) s 1 –N 0 s1+s2+s3 · min{(1+1/ )s 1 – N 0, (1+1/ )s 2 -N 0,(1+1/ )s 3 -N 0 }
Fragile Bin Packing Problem Problem: Object i: Weight w i, Fragility f i Object i in Bin j => Total weight in Bin j · f i Classical Bin Packing: Bins of unit capacity. f i =1 Clearly, N P-Complete Channel Assignment: w i =s i and f i =(1+1/ )s i – N 0
Approximation Results 1) Minimize number of bins used: Obtain 2 approximation Cannot be better than 3/2 unless P=NP 2) Approximation with respect to Fragility: i.e. Solution uses Opt # of bins, but total bin weight violated up to c times. Obtain 2 approximation
Number of bins Inapproximability: 3/2 Even in the asymptotic case (Unlike Bin Packing [De La Vega][Karmarkar]) Take Partition instance (sum = s, wts 2 [1,s/2]) FBP Instance I 0, Fragility = s/2 I= I 0 [ I 1 [ I 2 [ … [ I k-1 where I j = s j I 0 Fragility(I j )=s j+1 /2 < s j+1. I j and I k (j<k) cannot share a bin <3k bins implies some I j partitioned into 2.
Approx. for Bins f n ¸ f n-1 ¸ … ¸ f 2 ¸ f 1 N N-1 … B1B1 B2B2 B3B3 Optimum Idea : 9 “banded” solution, not too worse, find it N N-1 … H1H1 H2H2 H3H3 Banded
Fractional Version N N-1 … B1B1 B2B2 B3B3 Optimum N N-1 … B’ 1 B’ 2 B’ 3 Fractional version W’ 1 =W 1 W’ 2 =W 2 … W 1, W 2 … is total weight of B 1 B 2... Lies Fractionally in 1 st and 2 nd bin
Fractional Version Observations: 1) No B’ i begins sooner than B i 2) · Opt fractionally covered objects 3) Uses Opt # of bins B1B1 B2B2 B3B3 B’ 1 B’ 2 B’ 3 OptimumFractional
Rounding Step B’ 1 B’ 2 B’ B’’ 1 B’’ 2 B’’ 3 Fractionally covered objects -> own bins Add · Opt bins Each bin B’’_i is valid 9 assignment with · 2 Opt bins and is “banded” (Individual Bin)
Algorithm Starting from 1, keep packing objects until no possible Open another bin Continue packing until all objects packed … Easy to show: gives optimal “banded” solution 9 some “banded” · 2 Opt Gives a 2 approximation
Approx. for fragility Rounding: Include fractionally covered objects, in higher bin. N N B’ 1 B’ 2 B’ 3 Fractional version N N B’’ 1 B’’ 2 B’’ 3 After Rounding
Algorithm 1) Assignment banded 2) # bins used = Opt 3) Can show: fragility violated at most 2 times. Algorithm: Start from 1, pack objects until fragility has to be violated ¸ 2 times Open another bin Continue packing until all packed Produces a 2 approximation wrt Fragility
Conclusions and Extensions Closing gap between 3/2 and 2 Online version Dynamic case Other extensions similar to classical bin packing 1.Generalization of Bin Packing, motivated by frequency assignment 2.offline case, approximation results for various measures
Thank You!
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Motivation Share channels C1C1 C1C1 C1C1 C2C Question: How to share channels?