Fat or thin? Is the verdict in?

ABSTRACT Thin client or network computing is a hot topic. The hype claims lower total cost of ownership, faster applications deployment and reduced management pain, compared to traditional computing architectures. Early in 1998 the Flinders University Library installed network computers in the Central and branch libraries for student access to the Internet. This paper is a review of network computers in the light of our experience over the past two years. Do network computers offer all that is claimed in the hype? Are there hidden costs? What are the issues of configuration, server scaling, network performance and fault diagnosis? Do they have a future in the Library arena

Evolutionary computation for quality of service internet routing optimization

In this work, the main goal is to develop and evaluate a number of optimization algorithms in the task of improving Quality of Service levels in TCP/IP based networks, by configuring the routing weights of link-state protocols such as OSPF. Since this is a complex problem, some meta-heuristics from the Evolutionary Computation arena were considered, working over a mathematical model that allows for flexible cost functions, taking into account several measures of the network behavior such as network congestion and end-to-end delays. A number of experiments were performed, resorting to a large set of network topologies, where Evolutionary Algorithms (EAs), Differential Evolution and some common heuristic methods including local search were compared. EAs make the most promising alternative leading to solutions with an effective network performance even under unfavorable scenarios

Simulation modeling for integrated e-supply chain management

E-supply chain management is an emerging area of interest as companies begin to explore the Internet\u27s potential to restructure supply chain relationships. The environmental impact of e-supply chain management is a critical issue towards sustainability. This thesis discusses and models an integrated e-supply chain network accounting for material and information flows throughout the supply chain in order to analyze the environmental implications and tradeoffis with other system characteristics. The network structure has complex interactions between various entities. In order to understand and analyze dynamic performance, a discrete-event simulation approach is utilized. An integrated tool was developed using the Arena simulation software to simulate the e-business supply chain including lifecycle stages. The modules capture general supply chain process and ebusiness concepts. Consequently, it can be used in wide range of applications. A case study based upon a desktop computer was modeled to illustrate the application of the simulation model, evaluate environmental performance and examine the stochastic behavior of the network

Kerja Sama G20 dalam Pemulihan Ekonomi Global dari COVID-19

This study reveals the institutional performance of the G20 in order to help global economy recovery because of COVID-19. This study uses qualitative methods, providing in-depth descriptions through internet-based research as data-based techniques. This study indicates that G20 has proven its performance in carrying out a multilateral cooperation system through collective responses, which contain six dimensions, namely yaitu domestic political management; deliberation; direction setting; decision making; and development of global governance. G20's coordination creates a global network that includes interactions between international institutions, namely the IMF, WTO, and World Bank, as well as regional organizations and informal partnerships in the arena of international cooperation

Performance Study of Round Robin and Proportional Fair Scheduling Algorithms by Emulation for Video Traffic in LTE Networks

Video communication over mobile broadband is gaining popularity due to the increased demand for applications such as Video on Demand (VoD), IPTV, video conferencing etc. In order to support these video applications over mobile broadband, efficient video streaming within the limited bandwidth environment is essential. Further, Long Term Evolution (LTE) network incorporates advanced Radio Resource Management (RRM) mechanism such as scheduling to realize efficient video streaming over limited bandwidth arena. Scheduling does the task of dividing and allocating radio resources in order to maximize system throughput and enhance Quality of Experience (QoE) of the end user. Hence, in this paper an attempt has been made to evaluate the performance of Round Robin (RR) and Proportional Fair (PF) scheduling algorithms using EXata network emulator for real video traffic generated by Video LAN (VLC) media player. Packet Delivery Ratio (PDR) and throughput are considered as performance metrics for the emulation studies

A neural circuit for navigation inspired by C. elegans Chemotaxis

We develop an artificial neural circuit for contour tracking and navigation inspired by the chemotaxis of the nematode Caenorhabditis elegans. In order to harness the computational advantages spiking neural networks promise over their non-spiking counterparts, we develop a network comprising 7-spiking neurons with non-plastic synapses which we show is extremely robust in tracking a range of concentrations. Our worm uses information regarding local temporal gradients in sodium chloride concentration to decide the instantaneous path for foraging, exploration and tracking. A key neuron pair in the C. elegans chemotaxis network is the ASEL & ASER neuron pair, which capture the gradient of concentration sensed by the worm in their graded membrane potentials. The primary sensory neurons for our network are a pair of artificial spiking neurons that function as gradient detectors whose design is adapted from a computational model of the ASE neuron pair in C. elegans. Simulations show that our worm is able to detect the set-point with approximately four times higher probability than the optimal memoryless Levy foraging model. We also show that our spiking neural network is much more efficient and noise-resilient while navigating and tracking a contour, as compared to an equivalent non-spiking network. We demonstrate that our model is extremely robust to noise and with slight modifications can be used for other practical applications such as obstacle avoidance. Our network model could also be extended for use in three-dimensional contour tracking or obstacle avoidance