TY - JOUR
T1 - Distributed fractional local ratio and independent set approximation
AU - Halldórsson, Magnús M.
AU - Rawitz, Dror
N1 - Publisher Copyright:
© 2024 Elsevier Inc.
PY - 2025/3
Y1 - 2025/3
N2 - We consider the MAXIMUM WEIGHT INDEPENDENT SET problem, with a focus on obtaining good approximations for graphs of small maximum degree Δ. We give deterministic local algorithms running in time poly(Δ,logn) that come close to matching the best centralized results known and improve the previous distributed approximations by a factor of about 2. More precisely, we obtain approximations below [Formula presented], and a further improvement to 8/5+ε when Δ=3. Technically, this is achieved by leveraging the fractional local ratio technique, for a first application in a distributed setting.
AB - We consider the MAXIMUM WEIGHT INDEPENDENT SET problem, with a focus on obtaining good approximations for graphs of small maximum degree Δ. We give deterministic local algorithms running in time poly(Δ,logn) that come close to matching the best centralized results known and improve the previous distributed approximations by a factor of about 2. More precisely, we obtain approximations below [Formula presented], and a further improvement to 8/5+ε when Δ=3. Technically, this is achieved by leveraging the fractional local ratio technique, for a first application in a distributed setting.
KW - Approximation algorithms
KW - Distributed algorithms
KW - Fractional local ratio
KW - Maximum weight independent set
UR - http://www.scopus.com/inward/record.url?scp=85210114702&partnerID=8YFLogxK
U2 - 10.1016/j.ic.2024.105238
DO - 10.1016/j.ic.2024.105238
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AN - SCOPUS:85210114702
SN - 0890-5401
VL - 303
JO - Information and Computation
JF - Information and Computation
M1 - 105238
ER -