Top PDF Demand re-registration for PCS database restoration

Demand re-registration for PCS database restoration

Demand re-registration for PCS database restoration

Observation 1. Effect of α. Figures 3–5 indicate that both p 1,d and θ d first increase and then decrease as α (the probability that an MS issues re-registration at a times- lot) increases. When α is very small, an MS does not issue/re-issue a re-registration message until a long wait- ing period has elapsed. It is likely that a normal regis- tration, call origination, or call termination occurs be- fore a successful demand re-registration operation is per- formed, which results in poor θ d performance. This sit- uation is improved as α increases. For a large α, in- creasing α implies a large number of re-try, which re- sults in many collisions and thus poor θ d performance.
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Registration area planning for PCS networks using genetic algorithms

Registration area planning for PCS networks using genetic algorithms

Useless location updating [10] refers to the case of subse- quent LU’s without using the updated information as shown in Fig. 11. In this example, the LU in RA2 is a useless location updating since no calls arrive for portable A during the time period that the portable A was in RA2. As we mentioned in Section I, the reason for updating location information is to make the network be able to locate a portable whenever this portable is called. Thus, useless location updating indicates the waste of signaling and database access. It is not necessary for a portable to perform LU’s much more frequently than the portable receives calls. To improve the network perfor- mance, we should minimize the probability of useless location updating.
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Implicit deregistration with forced registration for PCS mobility management

Implicit deregistration with forced registration for PCS mobility management

Department of Computer Science and Information Engineering, National Chiao Tung University, Hsinchu, Taiwan, ROC YUGUANG FANG Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL 32611, USA Abstract. Registration/deregistration with a mobility database called Visitor Location Registers (VLRs) is required in a PCS network when a mobile phone moves between registration areas. Several schemes were proposed to deregister a mobile phone after it moves out of a registration area. A simple scheme, called implicit deregistration, is studied in this paper, which does not specifically deregister any obsolete record in the VLR. If the VLR is full when a mobile phone arrives, a record in the VLR is deleted and the reclaimed storage is reassigned to the incoming mobile phone. It is possible that a valid record will be deleted. If so, the VLR record of a mobile phone may be deleted before a call to the mobile phone arrives. Our previous work assumed that the incoming call setup would be lost. In this paper, we propose forced registration to restore the VLR record before the call setup operation can proceed.
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Per-user checkpointing for mobility, database failure restoration

Per-user checkpointing for mobility, database failure restoration

Based on (37), Fig. 6a plots  II against  1 = 2 . When 1 = 2 increases, the variance of interregistration interval increases. Therefore, we will observe a small number of checkpoint intervals that experience many registrations and a large number of checkpoint intervals that experience no registration. From the description of Algorithm II, it is also clear that the checkpoint intervals without registration are longer than the intervals with registrations. Since a failure is a random observer of the checkpoint intervals, the failure time is more likely to fall in a checkpoint interval without any registration. Therefore,  II decreases as  1 = 2 increases (this phenomenon is also true for Algorithm I). Based on (39), Fig. 6b indicates that Algorithm II provides 20- 55 percent improvement over Algorithm I in terms of  performance.
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An analysis of location record checkpointing interval for mobility database in PCS networks

An analysis of location record checkpointing interval for mobility database in PCS networks

Published online: 31 January 2008 Springer Science+Business Media, LLC 2008 Abstract Mobility database that stores the users’ location records is very important to connect calls to mobile users on personal communication networks. If the mobility database fails, calls to mobile users may not be set up in time. This paper studies failure restoration of mobility database. We study per-user location record checkpointing schemes that checkpoint a user’s record into a non-volatile storage from time to time on a per-user basis. When the mobility database fails, the user location records can be restored from the backup storage. Numeric analysis has been used to choose the optimum checkpointing interval so that the overall cost is minimized. The cost function that we consider includes the cost of checkpointing a user’s location record and the cost of paging a user due to an invalid location record. Our results indicate that when user registration intervals are exponen- tially distributed, the user record should never be checkpointed if checkpointing costs more than paging.
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Modeling mobility database failure restoration using checkpoint schemes

Modeling mobility database failure restoration using checkpoint schemes

Scheme II [7]. If no registration has occurred before the t p timer expires, the backup record is the same as that in the HLR. Therefore, checkpoint is postponed until the next registration occurs. To implement Scheme II, a tri- state Finite State Machine (FSM) is implemented for every HLR record (see Fig. 1 (a)). State 0 represents that neither registration event nor t p timeout event occurs after the previous checkpoint. State 1 represents that after the previous checkpoint, the first registration event occurs before a t p timeout event does. Note that the backup record is obsolete in this state. State 2 represents that after the previous checkpoint, a t p timeout event occurs before a registration event does. Initially, the FSM is in State 0, and the t p timer starts to decrement. If a registration event occurs before the t p timer expires, the FSM moves to State 1, and remains in State 1 until the t p timeout event occurs. At this point, the HLR record is checkpointed into the backup, the t p timer is restarted, and the FSM moves back to State 0. If the timeout event occurs at State 0, the FSM moves to State 2 and the t p
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Deregistration strategies for PCS networks

Deregistration strategies for PCS networks

II. E XPLICIT D EREGISTRATION In the explicit scheme, a registration record is deleted when the corresponding portable moves out of the RA. Thus, the database is full if and only if the number of portables in the RA is larger than the size of the database. To derive the probability that a portable cannot register at a particular RA, we first derive the distribution for the number of portables in an RA. Let be the expected number of portables in an RA. Suppose that the residence time of a portable in an RA has a general distribution with the density function and mean 1 In the steady state, the rate at which portables move into an RA equals the rate at which portables move out of the RA. In other words, the rate at which portables move into an RA is The arrival of portables can be viewed as being generated from input streams, which have the same general distribution with arrival rate If is reasonably large in an RA, the net input stream is approximated as a Poisson process with arrival rate Thus, the distribution for the portable population can be modeled by an queue with arrival rate and mean residence time 1 Let be the steady-state probability that there are portables in the RA. This model was validated against simulation experiments by Lin and Chen [6]. By the standard technique [4]
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Portable movement modeling for PCS networks

Portable movement modeling for PCS networks

Index Terms—Call holding time, cell residence times, location modeling, mobility, personal communications services (PCS). I. I NTRODUCTION P ERSONAL Communications Services (PCS) networks are poised to provide integrated services such as voice, data and multimedia to mobile users anywhere, anytime [1], [11], in an uninterrupted and seamless way, using advanced micro- cellular and handoff concepts [8]. In such a network, the ser- vice area is populated with base stations which provide the radio links for communications. The radio coverage of each base sta- tion is called a cell. The base station is responsible for locating a mobile user or a portable through paging or some other loca- tion tracking strategies [17], [21], and delivers calls from and to the portable. The service of a PCS network is also divided into registration areas (RAs), each of which consists of an aggrega- tion of cells, forming a contiguous geographical region. For a call from or to a roaming user, the location of the roaming user has to be determined for the call delivery. Two-level hierarchies which maintain a system of a home database (called home loca- tion register or HLR) and a visited database (called visitor loca- tion register or VLR) are commonly used for mobility manage- ment. When a user subscribes to a service from a PCS network, the user will first register at HLR where the user’s information profile is stored. When the user requests a service in a visited RA, it will contact the VLR associated with the RA, the VLR will contact the HLR of the user for authentication, the user’s record will be temporarily stored in the VLR. The VLR acts as an agent for the roaming user in the RA it is visiting.
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Demand-driven, iterative capacity allocation and cycle time estimation for re-entrant lines

Demand-driven, iterative capacity allocation and cycle time estimation for re-entrant lines

MPS-day-demandi,(t): total demanded type-i moves of day t, including the planned number of moves of day t and the delayed number of moves up to the end of day t-1.. After the PULL pr[r]

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Demand-Driven, Iterative Capacity Allocation and Cycle Time Estimation for Re-entrant Lines

Demand-Driven, Iterative Capacity Allocation and Cycle Time Estimation for Re-entrant Lines

Wafers revisit machines at different stages of production => Re-entrant nature.. => Resource competition among - product types..[r]

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Polling deregistration for unlicensed PCS

Polling deregistration for unlicensed PCS

A fast polling algorithm is described in this paper for both PACS and PACS-UB to facilitate interoperability between public and local (private) wireless access systems by e[r]

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Call performance for a PCS network

Call performance for a PCS network

new call-blocking and forced termination, these default values may be used as the reference input parameters for second- level modeling. However, the call-completion probability and the expected effective call-holding times cannot be derived directly from these two parameters. Both the cell-residence time and the call-holding time distributions must carefully be chosen to reflect the real systems. In our model, a general cell- residence time distribution is considered, which can be used to accommodate any real PCS system. The selection of the call-holding times was in the past typically assumed to be ex- ponentially distributed. Such an assumption may be reasonable when the calls are charged based on the lengths of the call- holding times. The assumption is no longer valid, however, for the modern telephone services which apply flat-rate billing programs. Flat-rate billing encourages people to make long calls (for example, people may log on from their PC’s at home to main computers in the companies through local telephone calls, and sometimes keep the connections for several days).
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Handover management for a PCS network

Handover management for a PCS network

To initiate handover, the portable temporarily suspends the voice con- versation by sending a link suspend message to the old R P (message 1, Fig. 4) and sends a handover r[r]

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Performance analysis for dual band PCS networks

Performance analysis for dual band PCS networks

Performance Analysis for Dual Band PCS Networks Yi-Bing Lin, Senior Member, IEEE, Wei-Ru Lai, and Rong-Jaye Chen, Member, IEEE AbstractÐIn a dual band personal communications services (PCS) network, heavy traffic areas are covered by microcells which overlay macrocells. In such a network, microcells and macrocells utilize different frequency bands. We propose an analytic model to study the performance of a dual band PCS architecture. Our model assumes that a PCS subscriber has a general residence time distribution in a microcell and the macrocell residence time distribution is derived from the microcell residence time distribution. An iterative algorithm is used to compute the overflow traffic from a microcell to its overlaid macrocell. Then, the call incompletion probability is computed by a macrocell model based on the overflow traffic. Our study indicates that the variance of the microcell residence time distribution and the number of microcells covered by a macrocell have significant effects on the call incompletion probability.
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Revisiting Demand for Insurance

Revisiting Demand for Insurance

Key Words: Demand for Insurance, Wealth Effect, Substitution Effect. 摘 要 本篇論文首先推導保險的 Marsharllian 需求與 Hicksian 需求,並利用 Slutsky 定理重新檢視保險市場中的所得效果與替代效果,論文進一步討論本文在理論與 實證上可能的應用,最後我們提供應用的實例,並說明此一實例在責任保險上可 能的意涵。

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Video Inpainting for Object Removal and Video Restoration

Video Inpainting for Object Removal and Video Restoration

2.1 Background Construction Method The basic idea of this rough and reliable background construction algorithm is bases on change detection. In paper [10], the change detection approach separated the difference frame into the changed region and the unchanged region, according to a threshold obtained from background estimation. The difference between two consecutive input frames is the basic concept of change detection. Rough and consistent object information is very difficult to obtain because the behavior and characteristics of the moving objects differ significantly. The quality of segmentation result depends strongly on the background noise, object motion, and the contrast between the object and the background. While the algorithm, which are based on inter-frame change detection, enable automatic detection of objects and allow larger non-grid motion compared to object tracking methods and object boundaries tend to be irregular in some critical image areas due to the lack of spatial edge information. Instead of trying to obtain more information from the moving objects of the video sequence, the focus is on the rough background. The long-term behavior of the object motion accumulated from the several frames instead of relying on frame difference of two consecutive frames that causes the final result more rough. The block diagram of rough background construction is display in Figure 1. The first step is to calculate the frame difference mask by thresholding frame difference that comes from two consecutive frames and ten frame difference masks are generated. The information of ten frame difference masks is counted in the background buffer. According the frame difference masks of past several frames, pixels that are not moving for a long time are considered as rough background.
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An Improved GGSN Failure Restoration Mechanism for UMTS

An Improved GGSN Failure Restoration Mechanism for UMTS

Abstract. Universal mobile telecommunications system (UMTS) provides packet-switched data services for mobile users. To efficiently deliver packets in the UMTS core network, the PDP contexts (i.e., the routing information) are maintained in the volatile storage (e.g., memory) of SGSN, GGSN, and UE. The GGSN routes packets between the UMTS core network and external data networks, and thus has heavy traffic and computation loading, which may result in PDP contexts lost or corrupted, and the QoS of the UMTS network may degrade significantly. To resolve this issue, 3GPP 23.007 proposes a mechanism for GGSN failure restoration. In this mechanism, the corrupted PDP contexts can be restored through the PDP Context Activation procedure. However, this incurs extra signaling cost to the network. To reduce the network signaling cost and delay for restoration of the corrupted PDP contexts, this paper proposes an improved mechanism
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Modeling estuarine hydrodynamics and salinity for wetland restoration

Modeling estuarine hydrodynamics and salinity for wetland restoration

To cite this Article Hsu, Ming-Hsi, Kuo, Albert Y., Kuo, Jan-Tai and Liu, Wen-Cheng'Modeling estuarine hydrodynamics and salinity for wetland restoration', Journal of Environmental Science and Health, Part A, 33: 5, 891 — 921 To link to this Article: DOI: 10.1080/10934529809376768 URL: http://dx.doi.org/10.1080/10934529809376768

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Classifier-augmented median filters for image restoration

Classifier-augmented median filters for image restoration

window and/or 5 5 selection, Fig. 2(b)–(h) were the resulting images of Fig. 2(a) by the median, CWM, SD-ROM, and the proposed methods. It can be observed from these simulated im- ages that the 3 3 CWM cannot remove noisy pixels effec- tively, even when the noise rate is as low as 10%. Moreover, 3 3 median-based filtering needed to be implemented recur- sively to enhance its limited noise suppression capability caused by such a small window size being adopted. Although recursive implementation canceled more noise at the price of excessive annoying blurring of the image details and textures. 5 5 me- dian and CWM filters generally demonstrated better noise can- cellation capability than their 3 3 counterparts, but they de- graded the image details and signal structure seriously. CWM filters improve median filters in detail preservation at the cost of a reduced noise suppression ability. Qualitative assessment SD-ROM approach visually, it demonstrated good noise can- cellation and edge-preserving, which is in compliance with the brilliant quantitative figures displayed in the table. As can be seen from these images, our proposed method has been found to largely outperform the other methods both in impulse noise suppression and edge and finer details preservation. It is also to be noted that the new method, SD-ROM as well, avoided very annoying blurring in the output image’s edge and details, which was observed in recursive median and CWM filters. We have re- peated the simulations on “Baboon” and “Peppers” images cor- rupted by varying percentages of impulse noise, our new tech- nique yielded superior restoration results, similar to the “Lena”
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Billing strategies and performance analysis for PCS networks

Billing strategies and performance analysis for PCS networks

From 1987 to 1988, he held research and teaching positions in both the Department of Mathematics and the Institute of Automation at Qufu Normal University. From September 1989 to December 1993, he was a Teaching and a Research Assistant in the Department of Systems, Control and Industrial Engineering, Case Western Reserve University, where he held a research associate position from January 1994 to May 1994. He held a post-doctoral position in the Department of Electrical Engineering, Boston University, from June 1994 to August 1995. From September 1995 to May 1997, he was a Research Assistant in the Department of Electrical and Computer Engineering, Boston University. From June 1997 to July 1998, he was a Visiting Assistant Professor in the Department of Electrical Engineering, University of Texas at Dallas, Richardson. Since July 1998, he has been an Assistant Professor in the Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark. He has published more than 30 papers in professional journals and refereed conferences. He is the Area Editor for ACM Mobile Computing and Communications Review. His research interests include wireless networks and mobile communications, personal communication services, stochastic and adaptive systems, hybrid systems in integrated communications and controls, robust stability and controls, nonlinear dynamical systems, and neural networks.
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