35676657
On skolem graceful graphs
Abstract A Skolem graceful labelling of graphs is introduced. It is shown that a tree is Skolem graceful iff it is graceful. The Skolem deficiency of a graph is defined and Skolem deficiencies of some well-known graphs are calculated. The class of Skolem graceful graphs is shown to be finite universal.
5645473
On Magic Strength of Graph
5672921
Mobility prediction and routing in ad hoc wireless networks
By exploiting non-random behaviors for the mobility patterns that mobile users exhibit, we can predict the future state of network topology and perform route reconstruction proactively in a timely manner. Moreover, by using the predicted information on the network topology, we can eliminate transmissions of control packets otherwise needed to reconstruct the route and thus reduce overhead. In this paper, we propose various schemes to improve routing protocol performances by using mobility prediction. We then evaluate the effectiveness of using mobility prediction via simulation. Copyright © 2001 John Wiley & Sons, Ltd.
14022203
An arbitration look-ahead scheme for reducing end-to-end latency in networks on chip
With the increasing complexity of system-on-chips, networks on chip (NoC) using multi-hop switching require low end-to-end latency for QoS guarantees. An arbitration look-ahead scheme is proposed to reduce the end-to-end packet latency in the NoC. Its packet arbitration at each switch is completed a few cycles in advance of the packet arrival. As a result, a packet bypasses the switch without the latency of input queuing and arbitration. This scheme is analyzed on a 4/spl times/4 mesh topology. A maximum 65% and average 26% latency reduction are obtained under random traffic. Latency reduction up to 36% is achieved under multimedia traffic.
2001028
Optimal Transmission Schedules in TWDM Optical Passive Star Networks
Abstract This paper is concerned with optimal transmission schedules in the TWDM (time and wavelength division multiplexed) optical passive star network. Our model of the network consists of a set V of N nodes with N tunable transmitters and N fixed-tuned receivers (where each node is assigned a transmitter-receiver pair), k wavelengths (each wavelength is shared by N k receivers where N k is an integer), and tuning time δ > 0 (in units of time slot, for transmitters to tune from one wavelength to another). We assume that at any given time slot, at most one transmission can be done per wavelength. An optimal transmission schedule is defined to be the one that schedules transmissions such that for each node v in V, the transmitter in v transmits once to every receiver in V — {v} within a repeating cycle of minimum length. We present an optimal transmission schedule for each tuning time, and show that the cycle length of any optimal transmission schedule is max {N(N — 1)/k, kδ + N — 1}.
11234364
Robust routing in wireless ad hoc networks
A wireless ad hoc network is a collection of mobile nodes with no fixed infrastructure. The absence of a central authorization facility in dynamic and distributed environments requires collaboration among nodes. When a source searches for a route to a destination, an intermediate node can reply with its cached entry. To strengthen correctness of such a routing discovery process, we propose a method in which the intermediate node requests its next hop to send a confirmation message to the source. After receiving both a route reply and confirmation message, the source determines the validity of a path according to its policy. As a result, this strategy discourages malicious nodes from intercepting packets. Simulation results show a remarkable improvement in throughput (30% higher delivery ratio and 10% less data transmission overhead) with a moderate increase of control messages.
39604886
Drug risk assessment with determining the number of sub-populations under finite mixture normal models
Abstract In some biological experiments, it is quite common that laboratory subjects may be different in their patterns of susceptibility to a treatment. In these situations, finite mixture model analysis becomes a useful tool. Under a finite mixture normal model, drug risk assessment problems are studied under the assumption that the population at risk consists of multiple sub-types of different susceptibilities. The EM algorithm and its extension are utilized to obtain the maximum likelihood estimates of the model. Particular discussion is given to the model selection problem based on Bayes factor, which is approximated by the Schwarz criterion. Meantime, the practical significance of the proposed method is illustrated with an actual dose–response data set.