Advanced Information Networking and Applications 

About: Advanced Information Networking and Applications is an academic conference. The conference publishes majorly in the area(s): Wireless sensor network & Quality of service. Over the lifetime, 5708 publications have been published by the conference receiving 61276 citations.

Cloud Computing: Issues and Challenges

Abstract: Many believe that Cloud will reshape the entire ICT industry as a revolution. In this paper, we aim to pinpoint the challenges and issues of Cloud computing. We first discuss two related computing paradigms - Service-Oriented Computing and Grid computing, and their relationships with Cloud computing We then identify several challenges from the Cloud computing adoption perspective. Last, we will highlight the Cloud interoperability issue that deserves substantial further research and development.

A Particle Swarm Optimization-Based Heuristic for Scheduling Workflow Applications in Cloud Computing Environments

Abstract: Cloud computing environments facilitate applications by providing virtualized resources that can be provisioned dynamically. However, users are charged on a pay-per-use basis. User applications may incur large data retrieval and execution costs when they are scheduled taking into account only the ‘execution time’. In addition to optimizing execution time, the cost arising from data transfers between resources as well as execution costs must also be taken into account. In this paper, we present a particle swarm optimization (PSO) based heuristic to schedule applications to cloud resources that takes into account both computation cost and data transmission cost. We experiment with a workflow application by varying its computation and communication costs. We compare the cost savings when using PSO and existing ‘Best Resource Selection’ (BRS) algorithm. Our results show that PSO can achieve: a) as much as 3 times cost savings as compared to BRS, and b) good distribution of workload onto resources.

CloudAnalyst: A CloudSim-Based Visual Modeller for Analysing Cloud Computing Environments and Applications

Abstract: Advances in Cloud computing opens up many new possibilities for Internet applications developers. Previously, a main concern of Internet applications developers was deployment and hosting of applications, because it required acquisition of a server with a fixed capacity able to handle the expected application peak demand and the installation and maintenance of the whole software infrastructure of the platform supporting the application. Furthermore, server was underutilized because peak traffic happens only at specific times. With the advent of the Cloud, deployment and hosting became cheaper and easier with the use of pay-peruse flexible elastic infrastructure services offered by Cloud providers. Because several Cloud providers are available, each one offering different pricing models and located in different geographic regions, a new concern of application developers is selecting providers and data center locations for applications. However, there is a lack of tools that enable developers to evaluate requirements of large-scale Cloud applications in terms of geographic distribution of both computing servers and user workloads. To fill this gap in tools for evaluation and modeling of Cloud environments and applications, we propose CloudAnalyst. It was developed to simulate large-scale Cloud applications with the purpose of studying the behavior of such applications under various deployment configurations. CloudAnalyst helps developers with insights in how to distribute applications among Cloud infrastructures and value added services such as optimization of applications performance and providers incoming with the use of Service Brokers.

A Comparative Study into Distributed Load Balancing Algorithms for Cloud Computing

Abstract: The anticipated uptake of Cloud computing, built on well-established research in Web Services, networks, utility computing, distributed computing and virtualisation, will bring many advantages in cost, flexibility and availability for service users. These benefits are expected to further drive the demand for Cloud services, increasing both the Cloud's customer base and the scale of Cloud installations. This has implications for many technical issues in Service Oriented Architectures and Internet of Services (IoS)-type applications; including fault tolerance, high availability and scalability. Central to these issues is the establishment of effective load balancing techniques. It is clear the scale and complexity of these systems makes centralized assignment of jobs to specific servers infeasible; requiring an effective distributed solution. This paper investigates three possible distributed solutions proposed for load balancing; approaches inspired by Honeybee Foraging Behaviour, Biased Random Sampling and Active Clustering.

Fall Detection from Human Shape and Motion History Using Video Surveillance

Abstract: Nowadays, Western countries have to face the growing population of seniors. New technologies can help people stay at home by providing a secure environment and improving their quality of life. The use of computer vision systems offers a new promising solution to analyze people behavior and detect some unusual events. In this paper, we propose a new method to detect falls, which are one of the greatest risk for seniors living alone. Our approach is based on a combination of motion history and human shape variation. Our algorithm provides promising results on video sequences of daily activities and simulated falls.