The Object Replication Method for the Efficient Migration of Agent
نویسندگان
چکیده
The migration method of a mobile agent affects the entire performance of the distributed system. Most of the existing migration methods have the slow-witted structures due to the fixed order migration that cause the subsequent accumulation of the task results. They can induce various problems such as the failure of host, network obstacles, service absence, and increased traffic resulting in the inefficient operation of the mobile agent. In this paper, we propose the new migration method using the object replication to solve these problems. The proposed model is simply composed of only three components: the Mobile Agent Client, Naming Agent Server, and Mobile Agent Server. The Mobile Agent Client performs the object replication according to the acquired object information (the number of replications) from the Naming Service Management Module. The main function of the naming service given by the naming agent is to provide information regarding the object replication and the location transparency of servers in the distributed network environment. We also suggest the replication algorithm and the migration model of the replicated mobile agent object using the naming service. The experiments analyzing the performance of our method and the sequential migration method are performed and the results are compared to guarantee the effectiveness of our approach
منابع مشابه
Urban Vegetation Recognition Based on the Decision Level Fusion of Hyperspectral and Lidar Data
Introduction: Information about vegetation cover and their health has always been interesting to ecologists due to its importance in terms of habitat, energy production and other important characteristics of plants on the earth planet. Nowadays, developments in remote sensing technologies caused more remotely sensed data accessible to researchers. The combination of these data improves the obje...
متن کاملE2DR: Energy Efficient Data Replication in Data Grid
Abstract— Data grids are an important branch of gird computing which provide mechanisms for the management of large volumes of distributed data. Energy efficiency has recently emerged as a hot topic in large distributed systems. The development of computing systems is traditionally focused on performance improvements driven by the demand of client's applications in scientific and business domai...
متن کاملFisher Discriminant Analysis (FDA), a supervised feature reduction method in seismic object detection
Automatic processes on seismic data using pattern recognition is one of the interesting fields in geophysical data interpretation. One part is the seismic object detection using different supervised classification methods that finally has an output as a probability cube. Object detection process starts with generating a pickset of two classes labeled as object and non-object and then selecting ...
متن کاملA version numbering scheme for informational objects used in VM live migration
Various numbering schemes are used to track different versions and revisions of files, software packages, and documents. One major challenge in this regard is the lack of an all-purpose, adaptive, comprehensive and efficient standard. To resolve the challenge, this article presents Quadruple Adaptive Version Numbering Scheme. In the proposed scheme, the version identifier consists of four integ...
متن کاملA Versioning Approach to VM Live Migration
In the context of virtual machines live migration, two strategies called “pre-copy” and “post-copy” have already been presented; but each of these strategies works well only in some circumstances. In this paper, we have a brief presentation of QAVNS and then introduce a new approach which is based on the concept of "informational object", assigning QAVNS-scheme-revision number, and observing th...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- AISS
دوره 2 شماره
صفحات -
تاریخ انتشار 2010