Abstract The concept of the Cloud computing has significantly changed the field of parallel and distributed computing systems today. Cloud computing enables a wide range of users to access distributed, scalable, virtualized hardware and/or software infrastructure over the Internet. Load balancing is the process of distributing the load among various nodes of a distributed system to improve resource utilization, minimum response time and maximize... The concept of the Cloud computing has significantly changed the field of parallel and distributed computing systems today. Cloud computing enables a wide range of users to access distributed, scalable, virtualized hardware and/or software infrastructure over the Internet. Load balancing is the process of distributing the load among various nodes of a distributed system to improve resource utilization, minimum response time and maximize throughput while also avoiding a situation where some of the nodes are heavily loaded while other nodes are idle or doing very little work. Load balancing ensures that all the processor in the system or every node in the network does approximately the equal amount of work at any instant of time. In this paper, we propose a new two level fuzzy approach for dynamic load balancing in cloud computing. This approach characterizes the uncertainty in a distributed system by using the fuzzy logic. The processor speed and queue length of nodes are used to balance the load of the nodes in cluster level and processing power and average queue length of clusters are used to balance the load of the clusters in cloud level through fuzzy logic. In comparative study, proposed algorithm shows better average of response time and throughput than Round Robin and Randomize algorithms. Read More Read Less

Abstract In wireless sensor networks, the database consists of data collected by the different network nodes. This database can be accessed by relational queries, such as: selections, projections and joins. Joins are queries that use a lot of energy, which is a determining factor for network lifetime. In this paper, a new technique for n-way join queries is suggested, using an in-network processing and... In wireless sensor networks, the database consists of data collected by the different network nodes. This database can be accessed by relational queries, such as: selections, projections and joins. Joins are queries that use a lot of energy, which is a determining factor for network lifetime. In this paper, a new technique for n-way join queries is suggested, using an in-network processing and adopting the filtering approach. Simulation results showed very good performances of the proposed technique compared with a central processing of those queries at the sink. Read More Read Less

Abstract Currently there are a lot of electronic learning media are developed to support the learning environment and improving the quality of learning outcomes. Learning is the process of how we perceive and understand the real world around us. Thus in the process of learning requires learning media that can support quality learning outcomes. With the development of information technology we can develop learning... Currently there are a lot of electronic learning media are developed to support the learning environment and improving the quality of learning outcomes. Learning is the process of how we perceive and understand the real world around us. Thus in the process of learning requires learning media that can support quality learning outcomes. With the development of information technology we can develop learning media application framework that can be used to build a learning atmosphere simulation-based medical records. The purpose of this research is to design a prototype for simulation of the administration of the hospital medical record (ProSIARS). ProSIARS will be used as a media laboratory practice simulation clinic medical records I (PKRM I). Simulation is a technique for practice and learning that can be applied to various disciplines. Simulation can strengthen in depth experience with real-world substance imitate aspects fully interactive. With ProSIARS can wake simulation-based learning environment that is dynamic and visualizations that represent the atmosphere of the time and the behaviour of real work. ProSIARS can be combined with teaching materials, guidance materials and tools supporting software, can even be combined with interrelated disciplines such as education of nurses and doctors. Traditionally the procedural PKRM I education and knowledge gained through theoretical concepts and models of apprenticeship. Software architecture contributes independently developed to represent the educational content of medical records (e.g. simulation models, guidance materials) and software engineering (e.g. interface). We provide a template interface and set of application modules to be arranged into administration education simulation framework needs medical records. Prototype design is done with the stages of the SDLC (system development life cycle), then followed up with the study to determine the level of benefit ProSIARS against behavioural (cognitive, affective and psychomotor) students. The approach uses quasi-experimental research with methods of non-equivalent control group design. Read More Read Less