Finding influential nodes reshuffles the very notion of linear paths in business processes and replaces it with networks of business value within a smart enterprise system. There are many existing algorithms for identifying influential nodes with certain limitations for applying in large-scale networks. In this article, we propose a community structure with integrated features ranking (CIFR) algorithm to find influential nodes in the network. First, we use the community detection algorithm to find communities in the system, and then we rank the nodes of network based on three factors, namely local ranking, gateway ranking, and community ranking, collectively termed as integrated features. Our algorithm intends to select influential nodes, which are both globally and locally optimal, leading to overall high information propagation. We perform the experimental results on total eight networks using various evaluation parameters. The obtained results validate superior performance against contemporary algorithms adding value to smart enterprises.

The authors propose three variants of distributed and stateless forwarding strategies for wireless sensor networks, namely greedy minimum energy consumption forwarding protocol (GMFP), lifetime maximising GMFP (LM-GMFP) and variance minimising GMFP (VAR-GMFP), which aim at maximising the network lifetime while achieving a high forwarding success rate. GMFP selects a forwarding node that minimises per-packet energy consumption while maximising the forwarding progress. LM-GMFP extends the GMFP algorithm by also taking into account the remaining energy at the prospective one-hop forwarding nodes. In VAR-GMFP, on the other hand, the packet is forwarded to the next node that ensures a locally high mean and low variance of nodal remaining energy. Through simple probabilistic analysis the authors prove the intuition behind the optimum forwarding node selection for network lifetime maximisation. They then model the lifetime maximisation of a sensor network as an optimisation problem and compare the practical protocol-dependent network lifetime with the theoretical upper bound. Through extensive simulations the author demonstrate that the proposed protocols outperform the existing energy-aware protocols in terms of network lifetime and end-to-end delay.

In a wireless sensor network, as the sensor nodes have limited energy, it is important to minimize nodal energy consumption due to message communication to extend the network lifetime. Existing forwarding protocols either do not consider network performance and energy saving jointly, or they are not distributed. In this paper, we propose a hybrid approach, called minimum consumption maximum remaining energy (MIN-MAX-E) forwarding, which combines minimum energy consumption of transmitter-receiver pair along with maximum remaining energy of the receiver in making a relay node selection decision. Extensive simulation studies show that the proposed algorithm offers a significantly improved energy saving performance with respect to the existing energy-aware approaches.

Abstract A spanning tree T of a graph G is said to be a tree t‐spanner if the distance between any two vertices in T is at most t times their distance in G. While the complexity of the problem of recognizing whether a graph has a tree t‐spanner is known for any fixed t≠3, the case t = 3 is still open. H.‐O. Le and V. B. Le (1999, Networks, 34(2), 81‐87) have shown that every directed path graph admits a tree 3‐spanner by proposing an algorithm to construct a tree 3‐spanner of a given directed path graph. In this paper, we point out a flaw in their algorithm by producing a directed path graph for which their algorithm fails to produce a tree 3‐spanner although the graph admits a tree 3‐spanner. Furthermore, we show that directed path graphs need not admit tree 3‐spanners in general. Next, we show that directed path graphs of diameter two always admit tree 2‐spanners and hence tree 3‐spanners. Finally, we show that a tree 2‐spanner of a diameter two directed path graph can be constructed in linear time. © 2007 Wiley Periodicals, Inc. NETWORKS, Vol. 50(3), 203–210 2007

In this paper we propose a parallel algorithm to construct a one-sided monotone polygon from a Hamiltonian 2-sep chordal graph which takes O(log n) time and uses O(n) processors on a CREW PRAM model. We also propose parallel algorithms to recognize Hamiltonian 2-sep chordal graphs and to construct a Hamiltonian cycle in such a graph, which run in O(log/sup 2/ n) time using O(mn) processors on a CRCW PRAM model and O(log/sup 2/ n) time using O(m) processors on a CREW PRAM model, respectively.