A simple parallel algorithm for the maximal independent set problem
SIAM Journal on Computing
PODC '87 Proceedings of the sixth annual ACM Symposium on Principles of distributed computing
A lower bound for radio broadcast
Journal of Computer and System Sciences
An Ω(D log(N/D)) lower bound for broadcast in radio networks
PODC '93 Proceedings of the twelfth annual ACM symposium on Principles of distributed computing
Probabilistic Algorithms for the Wakeup Problem in Single-Hop Radio Networks
ISAAC '02 Proceedings of the 13th International Symposium on Algorithms and Computation
Improved Inapproximability Results for MaxClique, Chromatic Number and Approximate Graph Coloring
FOCS '01 Proceedings of the 42nd IEEE symposium on Foundations of Computer Science
Broadcasting Algorithms in Radio Networks with Unknown Topology
FOCS '03 Proceedings of the 44th Annual IEEE Symposium on Foundations of Computer Science
Initializing newly deployed ad hoc and sensor networks
Proceedings of the 10th annual international conference on Mobile computing and networking
Some simple distributed algorithms for sparse networks
Distributed Computing
Maximal independent sets in radio networks
Proceedings of the twenty-fourth annual ACM symposium on Principles of distributed computing
Coloring unstructured radio networks
Proceedings of the seventeenth annual ACM symposium on Parallelism in algorithms and architectures
Local approximation schemes for ad hoc and sensor networks
DIALM-POMC '05 Proceedings of the 2005 joint workshop on Foundations of mobile computing
Broadcasting in undirected ad hoc radio networks
Distributed Computing - Special issue: PODC 02
A log-star distributed maximal independent set algorithm for growth-bounded graphs
Proceedings of the twenty-seventh ACM symposium on Principles of distributed computing
Distributed (δ+1)-coloring in linear (in δ) time
Proceedings of the forty-first annual ACM symposium on Theory of computing
Bounds on Contention Management Algorithms
ISAAC '09 Proceedings of the 20th International Symposium on Algorithms and Computation
What is the use of collision detection (in wireless networks)?
DISC'10 Proceedings of the 24th international conference on Distributed computing
Deploying wireless networks with beeps
DISC'10 Proceedings of the 24th international conference on Distributed computing
Chameleon-MAC: adaptive and self-algorithms for media access control in mobile ad hoc networks
SSS'10 Proceedings of the 12th international conference on Stabilization, safety, and security of distributed systems
Distributed game-theoretic vertex coloring
OPODIS'10 Proceedings of the 14th international conference on Principles of distributed systems
Bounds on contention management algorithms
Theoretical Computer Science
Radio network distributed algorithms in the unknown neighborhood model
ICDCN'10 Proceedings of the 11th international conference on Distributed computing and networking
Distributed ($#916;+1)-coloring in the physical model
ALGOSENSORS'11 Proceedings of the 7th international conference on Algorithms for Sensor Systems, Wireless Ad Hoc Networks and Autonomous Mobile Entities
Survey: Distributed algorithm engineering for networks of tiny artifacts
Computer Science Review
Leader election in shared spectrum radio networks
PODC '12 Proceedings of the 2012 ACM symposium on Principles of distributed computing
VCM: the vector-based coloring method for grid wireless ad hoc and sensor networks
Proceedings of the 15th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems
Operations Research
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We present a randomized coloring algorithm for the unstructured radio network model, a model comprising autonomous nodes, asynchronous wake-up, no collision detection and an unknown but geometric network topology. The current state-of-the-art coloring algorithm needs with high probability O(Δ ∙ log n) time and uses O(Δ) colors, where n and Δ are the number of nodes in the network and the maximum degree, respectively; this algorithm requires knowledge of a linear bound on n and Δ. We improve this result in three ways: Firstly, we improve the time complexity, instead of the logarithmic factor we just need a polylogarithmic additive term; more specifically, our time complexity is O(Δ + log Δ ∙ log n) given an estimate of n and Δ, and O(Δ + log2 n) without knowledge of Δ. Secondly, our vertex coloring algorithm needs Δ + 1 colors only. Thirdly, our algorithm manages to do a distance-d coloring with asymptotically optimal O(Δ) colors for a constant d.