
doi: 10.1007/11945529_29
Ad hoc networks consist of wireless hosts that communicate with each other in the absence of a fixed infrastructure. Such networks cannot rely on centralized and organized network management. The clustering problem consists in partitioning network nodes into groups called clusters, giving a hierarchical organization of the network. A self-stabilizing algorithm, regardless of the initial system configuration, converges to legitimates configurations without external intervention. Due to this property, self-stabilizing algorithms tolerate transient faults. In this paper we present a robust self-stabilizing clustering algorithm for ad hoc network. The robustness property guarantees that, starting from an arbitrary configuration, in one round, network is partitioned into clusters. After that, the network stays partitioned during the convergence phase toward a legitimate configuration where the clusters partition ensures that any neighborhood has at most k clusterheads (k is a given parameter).
Distributed algorithm, [INFO.INFO-MC] Computer Science [cs]/Mobile Computing, [INFO.INFO-NI] Computer Science [cs]/Networking and Internet Architecture [cs.NI], Ad hoc networking, [INFO.INFO-DC] Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], Self-stabilization, Clustering
Distributed algorithm, [INFO.INFO-MC] Computer Science [cs]/Mobile Computing, [INFO.INFO-NI] Computer Science [cs]/Networking and Internet Architecture [cs.NI], Ad hoc networking, [INFO.INFO-DC] Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], Self-stabilization, Clustering
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 5 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
