The Experts below are selected from a list of 105042 Experts worldwide ranked by ideXlab platform
Lee, Hee C. - One of the best experts on this subject based on the ideXlab platform.
-
Optimization of Paging Cost in Mobile Switching System by Genetic Algorithm
NSUWorks, 1997Co-Authors: Lee, Hee C.Abstract:The maximum bandwidth capacity of radio frequency channels such as the forward control channel (FOCC) used in the mobile switching systems is fixed. The FOCC has been experiencing severe congestion because of the inefficiency of conventional mobile paging methods. A bottleneck is caused in the FOCC due to constraints of both the bandwidth and the limited number of radio frequency channels in the mobile telecommunication systems. In this dissertation, an approach that minimizes the paging cost of FOCC in order to locate a mobile station in the mobile switching system is presented. In order to minimize the paging cost and to maximize the bandwidth utilization of the FOCC, a new paging schema with the optimal partition of paging zones is developed. By using the refined mobile\u27s probability pattern stored in the Statistical Profile, the approach employs the genetic algorithm and the derived fitness function to generate the optimal partition of paging zones, such that the paging cost to locate a mobile station as well as the bandwidth consumption in FOCC is minimized
-
Optimal Mobile Location Tracking by Multilayered Model Strategy
NSUWorks, 1997Co-Authors: Sun Junping, Lee, Hee C.Abstract:We developed a multilayered model for the purposes such as mobility management, mobile activity modeling, and optimal paging and mobile location tracking. A bottleneck in the forward control channel (FOCC) is caused due to constraints such as the limited bandwidth and number of radio frequency channels, and inefficiency of conventional mobile paging methods in mobile telecommunication systems. In order to minimize the paging cost and to maximize utilization of the bandwidth in the FOCC, we develop a new paging schema, based on the multilayered model, with the optimal partition of paging zones. By using the refined mobile\u27s probability pattern stored in a Statistical Profile, we employ the genetic algorithm and the probabilistic cost function to generate the optimal partition of paging zones such that the paging cost to locate a mobile station as well as the bandwidth consumption in the FOCC is minimized
Shuchi Sethi - One of the best experts on this subject based on the ideXlab platform.
-
analysis and clustering of workload in google cluster trace based on resource usage
Computational Science and Engineering, 2016Co-Authors: Mansaf Alam, Kashish Ara Shakil, Shuchi SethiAbstract:Cloud computing has gained interest amongst commercial organizations, research communities, developers and other individuals during the past few years. In order to move ahead with research in field of data management and to enable processing of such data, we need benchmark datasets and freely available data which are publicly accessible. Google in May 2011 released a trace of a cluster of 11k machines referred as "Google Cluster Trace". This trace contains cell information of about 29 days. This paper provides analysis of resource usage and requirements in this trace and is an attempt to give an insight about such kind of production trace similar to the ones in cloud environment. The major contributions of this paper include Statistical Profile of jobs based on resource usage, clustering of workload patterns and classification of jobs into different types based on k-means clustering. Though there have been earlier works for analysis of this trace, but our analysis provides several new findings such as jobs in a production trace are trimodal and there occurs symmetry in the tasks within a long job type.
-
analysis and clustering of workload in google cluster trace based on resource usage
arXiv: Distributed Parallel and Cluster Computing, 2015Co-Authors: Mansaf Alam, Kashish Ara Shakil, Shuchi SethiAbstract:Cloud computing has gained interest amongst commercial organizations, research communities, developers and other individuals during the past few this http URL order to move ahead with research in field of data management and processing of such data, we need benchmark datasets and freely available data which are publicly accessible. Google in May 2011 released a trace of a cluster of 11k machines referred as Google Cluster Trace.This trace contains cell information of about 29 days.This paper provides analysis of resource usage and requirements in this trace and is an attempt to give an insight into such kind of production trace similar to the ones in cloud environment.The major contributions of this paper include Statistical Profile of Jobs based on resource usage, clustering of Workload Patterns and Classification of jobs into different types based on k-means clustering.Though there have been earlier works for analysis of this trace, but our analysis provides several new findings such as jobs in a production trace are trimodal and there occurs symmetry in the tasks within a long job type
Junping Sun - One of the best experts on this subject based on the ideXlab platform.
-
Optimal Mobile Locat ion Tracking by Multilayered Model Strategy
2009Co-Authors: Junping SunAbstract:We developed a multilayered model for the purposes such as mobility management, mobile activity modeling, and optimal paging and mobile location tracking. A bot-tleneck in the forward control channel (FOCC) is caused due to constraints such as the limited bandwidth and number of radio frequency channels, and ineficiency of conventional mobile paging methods in mobile telecom-munication systems. In order to minimize the paging cost and to maximize utilization of the bandwidth in the FOCC, we develop a new paging schema, based on the multilayered model, with the optimal partition of paging zones. By using the refined mobile’s probability pattern stored in a Statistical Profile, we employ the genetic algo-rithm and the probabilistic cost function to generate the optimal partition of paging zones such that the paging cost to locate a mobile station as well as the bandwidth consumption in the FOCC is minimized.
Mansaf Alam - One of the best experts on this subject based on the ideXlab platform.
-
analysis and clustering of workload in google cluster trace based on resource usage
Computational Science and Engineering, 2016Co-Authors: Mansaf Alam, Kashish Ara Shakil, Shuchi SethiAbstract:Cloud computing has gained interest amongst commercial organizations, research communities, developers and other individuals during the past few years. In order to move ahead with research in field of data management and to enable processing of such data, we need benchmark datasets and freely available data which are publicly accessible. Google in May 2011 released a trace of a cluster of 11k machines referred as "Google Cluster Trace". This trace contains cell information of about 29 days. This paper provides analysis of resource usage and requirements in this trace and is an attempt to give an insight about such kind of production trace similar to the ones in cloud environment. The major contributions of this paper include Statistical Profile of jobs based on resource usage, clustering of workload patterns and classification of jobs into different types based on k-means clustering. Though there have been earlier works for analysis of this trace, but our analysis provides several new findings such as jobs in a production trace are trimodal and there occurs symmetry in the tasks within a long job type.
-
analysis and clustering of workload in google cluster trace based on resource usage
arXiv: Distributed Parallel and Cluster Computing, 2015Co-Authors: Mansaf Alam, Kashish Ara Shakil, Shuchi SethiAbstract:Cloud computing has gained interest amongst commercial organizations, research communities, developers and other individuals during the past few this http URL order to move ahead with research in field of data management and processing of such data, we need benchmark datasets and freely available data which are publicly accessible. Google in May 2011 released a trace of a cluster of 11k machines referred as Google Cluster Trace.This trace contains cell information of about 29 days.This paper provides analysis of resource usage and requirements in this trace and is an attempt to give an insight into such kind of production trace similar to the ones in cloud environment.The major contributions of this paper include Statistical Profile of Jobs based on resource usage, clustering of Workload Patterns and Classification of jobs into different types based on k-means clustering.Though there have been earlier works for analysis of this trace, but our analysis provides several new findings such as jobs in a production trace are trimodal and there occurs symmetry in the tasks within a long job type
Antonio Francisco - One of the best experts on this subject based on the ideXlab platform.
-
land markets employment and resource use in the peri urban green zones of maputo mozambique a case study of land market rigidities and institutional constraints to economic growth
Research Papers, 1995Co-Authors: Michael J Roth, Stephen R Boucher, Antonio FranciscoAbstract:Beginning in January 1991, the U.S. Agency for International Development funded a series of studies on land, employment, and financial markets in the peri-urban areas of Maputo. Beginning in September 1991, a land-market survey involving 121 households and 162 plots of land was administered in two peri-urban green zones of Maputo-districts 4 and 6. Households were queried about their land-settlement histories, mode of land acquisition, terms and conditions of transfer, land rights, size of holdings, perceptions of tenure security, land-use practices, commercial input use, hired labor, agricultural sales and revenues, nonfarm employment and earnings, and general demographic characteristics. The present study reports findings from the land-market survey along with numerous other interviews with producers, buyers and sellers of land, local authorities, and district and national officials in Maputo and its surrounding peri-urban green zones. Section 1 is introductory while section 2 covers the legal foundation of land tenure and describes the various authorities and agencies responsible for setting and enforcing land policy in the peri-urban zone. Section 3 explains the research design and sampling frame used to select households and landholdings for the study, choice of strata, survey instruments, research questions, and data limitations. Section 4 provides a Statistical Profile of the household economy while section 5 examines processes of land settlement, land acquisition, types and sources of land dispute, and registration benefits. In section 6, economic and political factors are linked with land prices to explain the determination of "reservation" and "offer" prices of land and to evaluate the influence of market factors and Possible asymmetries in information and bargaining position on land-price perceptions.