Distributed Information Management with Mobile Agents

With more users taking advantage of publicly accessible networks, such as corporate intranets and the Internet, larger amounts of information is becoming electronically distributed and disseminated. Distributed information management is an emerging technology for dealing with the problems of managing information that is spread across networks, users and applications. We present four categories that we consider being necessary to developing tools to undertake distributed information management tasks. To help model the dynamic and heterogeneous nature of a user's distributed information, we advocate the use of agents and agent technologies when building distributed information management applications. We present an agent-oriented architecture which is based around a concept of mobile agents, since they provide a convenient abstraction for modelling distributed applications

Priori information and sliding window based prediction algorithm for energy-efficient storage systems in cloud

One of the major challenges in cloud computing and data centers is the energy conservation and emission reduction. Accurate prediction algorithms are essential for building energy efficient storage systems in cloud computing. In this paper, we first propose a Three-State Disk Model (3SDM), which can describe the service quality and energy consumption states of a storage system accurately. Based on this model, we develop a method for achieving energy conservation without losing quality by skewing the workload among the disks to transmit the disk states of a storage system. The efficiency of this method is highly dependent on the accuracy of the information predicting the blocks to be accessed and the blocks not be accessed in the near future. We develop a priori information and sliding window based prediction (PISWP) algorithm by taking advantage of the priori information about human behavior and selecting suitable size of sliding window. The PISWP method targets at streaming media applications, but we also check its efficiency on other two applications, news in webpage and new tool released. Disksim, an established storage system simulator, is applied in our experiments to verify the effect of our method for various users’ traces. The results show that this prediction method can bring a high degree energy saving for storage systems in cloud computing environment