Distributed Network

This paper reports on an Australian project that is developing an online system to deliver researcher-driven national-scale infrastructure for the humanities, focused on mapping, time series, and data integration. Australian scholars and scholars of Australia worldwide are well served with digital resources and tools to deepen the understanding of Australia and its historical and cultural heritage. There are, however, significant barriers to use. The Time Layered Cultural Map of Australia (TLCMap) will provide an umbrella infrastructure related to time and space, helping to activate and draw together existing high-quality resources. TLCMap expands the use of Australian cultural and historical data for research through sharply defined and powerful discovery mechanisms. See https://tlcmap.newcastle.edu.au/.

This paper reports on an Australian project that is developing an online system to deliver researcher-driven national-scale infrastructure for the humanities, focused on mapping, time series, and data integration. Australian scholars and scholars of Australia worldwide are well served with digital resources and tools to deepen the understanding of Australia and its historical and cultural heritage. There are, however, significant barriers to use. The Time Layered Cultural Map of Australia (TLCMap) will provide an umbrella infrastructure related to time and space, helping to activate and draw together existing high-quality resources. TLCMap expands the use of Australian cultural and historical data for research through sharply defined and powerful discovery mechanisms. See https://tlcmap.newcastle.edu.au/.

Verification of the geographic location of a moving device is vital. This verification is important in terms of ensuring that the flying systems moving in the swarm are in orbit and that they are able to task completion and manage their energy efficiency. Cyber-attacks on unmanned aerial vehicles (UAV) in a swarm can affect their position and cause various damages. In order to avoid this challenge, it is necessary to share with each other the positions of UAV in the swarm and to increase their accuracy. In this study, it is aimed to increase position accuracy and data integrity of UAV by using blockchain technology in swarm. Experiments were conducted on a virtual UAV network (UAVNet). Successful results were obtained from this proposed study.

This paper reports on an Australian project that is developing an online system to deliver researcher-driven national-scale infrastructure for the humanities, focused on mapping, time series, and data integration. Australian scholars and scholars of Australia worldwide are well served with digital resources and tools to deepen the understanding of Australia and its historical and cultural heritage. There are, however, significant barriers to use. The Time Layered Cultural Map of Australia (TLCMap) will provide an umbrella infrastructure related to time and space, helping to activate and draw together existing high-quality resources. TLCMap expands the use of Australian cultural and historical data for research through sharply defined and powerful discovery mechanisms. See https://tlcmap.newcastle.edu.au/.

This letter proposes a fast retry limit adaptation algorithm for 802.11e distributed networks. Differently from existing solutions, which manage a unique access category, the presented method jointly estimates the retry limits associated to both voice and video packets. The algorithm, which operates in saturated and non-saturated traffic conditions, is validated adopting an 802.11n physical layer and comparing its performance with a proper extension of an existing solution.

It by and large acknowledged that the trouble of system congestion control stays a basic issue and a high need, particularly given the developing size, request, and speed (transfer speed) of the inexorably coordinated administrations systems. In spite of the examination endeavors spreading over several decades and accordingly the sizable measure of different plans proposed, there are no generally worthy control arrangements. Current arrangements in existing systems are progressively getting insufficient, and it's commonly acknowledged that these arrangements can only with significant effort extent even with different proposed "fixes". In this paper, a Fuzzy based congestion control is talked about to manage the congestion control issue. The exhibition of the controlled framework is assessed by means of reenactment.

We introduce the new Masked Interval Routing Scheme, MIRS for short, where a mask is added to each interval to indicate particular subsets of "consecutive" labels. Interval routing becomes more exible, with the classical IRS scheme being a special case of MIRS. We then take two directions. First we show that the interval information stored in the network may be drastically reduced in the hard cases, proving that in globe graphs of O(n 2) vertices the number of intervals per edge goes down from (n) to O(log n). The technique is then extended to globe graphs of arbitrary dimensions. Second we show that MIRS may be advantageously used in fault-tolerant networks, proving that optimal routing with one interval per edge is still possible in hypercubes with a "harmless" subset of faulty vertices. This work is aimed to introducing a new technique. Further research is needed in both the directions taken here. Still, the examples provided show that MIRS may be useful in practical applications.

Cloud computing is a growing industry and it has already dominated many IT markets segments. Cloud providers offer numerous equivalent IaaS services aiming to fulfill clients' requirements. In addition, cloud clients need to choose solutions that minimize costs without compromising efficiency though. However, not only the confusion due to the large variety of cloud services but also the uncertainty about the efficiency specifications that their cloud services should have, can make cloud computing services selection a difficult task for the users. Into this context, this paper presents an approach to a multi-attribute decision-making problem that focuses on the calculation of efficiency of IaaS cloud services as a measurable driver for both clients and providers. A DEA input-oriented model is described, which estimates efficiency of cloud services based on functional and nonfunctional parameters. Furthermore, the contribution of functional and non-functional features to the overall performance is examined. This innovative model urges providers to optimize the efficiency of their services aiming to increase their market share and, at the same time, assists clients in choosing a cost-effective cloud solution.

Leveraging the traditional virtual network concept, some recent research works have proposed the Virtual Data Center (VDC) as an abstraction to capture both bandwidth and compute/storage resource requirements for an application. However a virtual node in a VDC is limited to a virtual machine (VM), which can only be embedded onto a single physical machine. This condition limits the applicability of the VDC abstraction and the potential of deploying parallel computing. In this paper, we propose a new abstraction based on our Application Centric Network Virtualization (ACNV) approach. Specifically, we model a service application offered by a service provider as a virtual network of service function nodes, which closely matches the service provider's view on the architecture of the application. An infrastructure provider that hosts the application decides how to map the virtual network to the substrate network. Different from the VDC abstraction, each virtual node in our proposed abstraction can be split and mapped onto multiple physical machines, which allows the infrastructure provider to provide auto scaling for the application with variable number of physical machines for exploring the full benefits of parallel computing. We also allow multiple virtual nodes to be mapped and colocated in the same physical machine to minimize resource fragmentation and communication overhead. Extensive simulation results show that the proposed ACNV abstraction outperforms existing VDC-like approaches in achieving optimal resource usage.

This paper reports on an Australian project that is developing an online system to deliver researcher-driven national-scale infrastructure for the humanities, focused on mapping, time series, and data integration. Australian scholars and scholars of Australia worldwide are well served with digital resources and tools to deepen the understanding of Australia and its historical and cultural heritage. There are, however, significant barriers to use. The Time Layered Cultural Map of Australia (TLCMap) will provide an umbrella infrastructure related to time and space, helping to activate and draw together existing high-quality resources. TLCMap expands the use of Australian cultural and historical data for research through sharply defined and powerful discovery mechanisms. See https://tlcmap.newcastle.edu.au/.

Wireless computing, because of the limited memory capacity of the palmtops, forces to separate data (stored on a remote server) from the application (running on the palmtops) that uses them. In applications working on data that frequently change, several kilobytes of data are ...

With the rapid growth of both information and users on the Internet, how to effectively improve the quality of network service becomes an urgent problem to be addressed. Load balancing is a solution to this problem in an effective way. Different ...

The main objective of this paper is to provide a global architectural and decision support solution built on the requirements for a reaction after alert detection mechanisms in the frame of information systems security and more particularly applied to telecom infrastructures security. These infrastructures are distributed in nature, therefore the targeted architecture is developed in a distributed perspective and is composed of three basic layers: low level, intermediate level and high level. The low level constitutes the interface between the main architecture and the targeted infrastructure. The intermediate level is responsible of correlating the alerts coming from different domains of the infrastructure and to smartly deploy the reaction actions. The architecture is elaborated using the multi-agents system that provides the advantages of autonomous and interaction facilities, and has been associated to the OntoBayes model for decision support mechanism. This model helps agents to make decisions according to preference values and is built upon ontology based knowledge sharing, Bayesian networks based uncertainty management and influence diagram based decision support. The major novelty of this Decision Support System is the layered view of the infrastructure thanks to MAS architecture, which enables the decision making with different levels of knowledge. The proposed approach has been successfully experimented for data access control mechanism.

With the rapid growth of both information and users on the Internet, how to effectively improve the quality of network service becomes an urgent problem to be addressed. Load balancing is a solution to this problem in an effective way. Different adaptive load balancing methods have been developed to estimate servers load performance. However, they suffer from either increased processing load on the servers, or additional traffic on the network and the servers, or are impractical in real time scenario. In this paper, we used the concept of content based queues, and have used RTT passive measurement technique to get an adaptive load balancing algorithm inside the cluster and used the round robin load balancing algorithm outside the cluster. Using the same queue for each type of request results into overload on server, so we use the concept of different queue for different type of request. The whole load balancing task is performed by a webproxy, a proxy that has access to all servers so it also removes the drawback of dynamic algorithm in which most of the load balancing task is performed by server itself.