We comment on the paper “Extremal Cayley digraphs of finite Abelian groups” [Intercon. Networks 12 (2011), no. 1-2, 125–135]. In particular, we give some counterexamples to the results presented there, and provide a correct result for degree two.
Barolli, A.; Oda, T.; Xhafa, F.; Barolli, L.; Takizawa, M.; Uchida, K. Journal of interconnection networks Vol. 12, num. 3, p. 205-219 DOI: 10.1142/S0219265911002952 Data de publicació: 2011-09 Article en revista
In this paper, we consider the behavior of a wireless ad-hoc sensor network for different radio models. By means of simulations, we analyze the performance of three protocols: AODV, DSR, and DSDV considering two radio models TwoRayGround and Shadowing.
In difference with other works, we generalize the type of radio model by allowing the path loss randomnesses to be present in the service environment of the network. We study the perceived Goodput and Depletion of the ad-hoc sensor network and compare the performance of three protocols for different scenarios. The simulation results confirm the fact that the shadowing phenomena, by destroying the regularity of the network, reduce the mean distance among nodes and at the same time increase the interference level and the latency of packet transmission. In particular, we found a maximum relative difference of 70%. On the other hand, for the proactive DSDV routing protocol the energy consumption rate seems to be independent of the radio model, at least for moderate size of the network (256 nodes). Also, we found that the packet delivery ratio of AODV and DSR routing protocols are more stable than DSDV protocol.
Computational Grid (CG) is an emerging paradigm in which geographically distributed resources are logically unified as a computational unit. A challenging problem in such systems is the allocation of jobs to resources that minimizes both makespan and flowtime parameters. In this paper, we present an experimental study on Genetic Algorithms (GAs) for scheduling independents jobs to Grid resources based on two replacement strategies: Steady-State GA (SSGA) and Struggle GA (SGA). SSGA distinguishes for its accentuated convergence of the population that rapidly reaches good solutions though it is soon stagnated. The SGA is based on struggle replacement and adaptively maintains diverse population, reducing thus convergence rapidity. The experimental results, based on a benchmark simulation model, showed that SGA outperforms SSGA for moderate size instances. On the other hand, the time needed by the SGA to reach makespan values obtained by the SSGA rapidly increases as more jobs and machines are added to the Grid. Thus, for larger size instances, SGA is not able to improve the results of the SSGA. Finally, we also report and analyze flowtime values for the considered benchmark.
In this paper we present a study on the requirements for the design and implementation of simulation packages for Grid systems. Grids are emerging as new distributed computing systems whose main objective is to manage and allocate geographically distributed computing resources to applications and users in an efficient and transparent manner. Grid systems are at present very difficult and complex to use for experimental studies of large-scale distributed applications. Although the field of simulation of distributed computing systems is mature, recent developments in large-scale distributed systems are raising needs not present in the simulation of the traditional distributed systems. Motivated by this, we present in this work a set of basic requirements that any simulation package for Grid computing should offer. This set of functionalities is obtained after a careful review of most important existing Grid simulation packages and includes new requirements not considered in such simulation packages. Based on the identified set of requirements, a Grid simulator is developed and exemplified for the Grid scheduling problem.