Load sharing with buffering over heterogeneous networks
Bibliographic record
Abstract
By most predictions, fourth-generation (4G) wireless systems will be composed of heterogeneous networks. Two important constituent networks will be Wireless LAN (WLAN) and cellular mobile radio systems (e.g., UMTS). WLAN is designed for low-range, high/medium-data-rate access and can be used as a complement to the larger cellular systems. In this paper, a general analytical model for load sharing in heterogeneous networks is proposed. Both networks have the capability of buffering call request. This model provides more insights of the behavior of the heterogeneous networks and allows an accurate examination on the effects of various system parameters on performance. In addition, three load sharing schemes are proposed for the integrated UMTS/WLAN system. Numerical results are provided to verify the usefulness of the proposed model and to compare the three sharing schemes in terms of performance. I. INTRODUCTION Establishing unified heterogeneous wireless networks including a set of different technologies and standards is a main feature of the fourth-generation (4G) mobile radio systems (1)(2). Conceptually, a 4G wireless network architecture can be viewed as many overlapping wireless Internet access domains. Different radio access networks have their own properties. High-tier systems such as Universal Mobile Telecommunication System (UMTS) provide high mobility but with less data transmission bandwidth (3). Low-tier systems such as wireless local area network (WLAN) provide high/medium data rate, in general, low mobility. Hot-spot areas are normally covered by both high-tier and low-tier systems, in which low-tier systems are complement to high-tier systems. In the heterogeneous networking environment considered in this paper, low-tier systems are built to provide additional bandwidth at a hot area and shares the traffic load of high-tier systems. Beside this, low-tier systems have their own traffic load. UMTS and WLAN will be taken as the examples for high- and low-tier systems. Various interworking strategies of the heterogeneous networks have been presented in the literature (4)-(6). To date, the main research attention has been given to the interworking functionalities, the architecture and signaling, etc. In order to efficiently utilize radio resource, a practical radio resource management of the heterogeneous networks, e.g., a load sharing scheme, has to be considered and optimized. However, the optimization of the support of the quality of service (QoS) over such infrastructures are either largely ignored or carried out by simulations only due to the lack of an analytical model. In order to gain deeper understanding of the system behavior and to analyze and compare the performance of using different load sharing schemes, an analytical model is necessary. In this paper, we first propose a general analytical model to quantify the performance of a load sharing heterogeneous networking environment. The traffic loads and QoS's of both of the systems are taken into account. To accommodate more users' call requests, both systems have the capability of buffering congested call request. Based on this general analytical model, the performance metrics including the call blocking probabilities, buffering probabilities and bandwidth usages, etc., of both systems with various load sharing schemes applied can be obtained. The effects of the system parameters, such as the traffic intensity and buffer size of each system, on the overall performance of the heterogeneous networks can be found analytically. In this paper, the objective of the load sharing in the heterogeneous networks is to improve the capacity of the UMTS network while maintaining the QoS of WLAN users. Three load sharing schemes, i.e., block balancing (BB), fully sharing (FS) and reserved sharing (RS), are proposed. The overall performance of the UMTS/WLAN networks for each load sharing scheme is investigated. Numerical results demonstrate that BB and RS provide better overall performance than FS. When both of the two networks are heavily loaded, BB is a better choice. Increasing the buffer size in UMTS can effectively improve the overall performance if the call blocking probability is the main concern. The effects of additional system parameters, such as maximum allowed sharing channels, and the WLAN coverage, will be studied. II. SYSTEM OVERVIEW A. Interworking architecture In this paper, we consider real-time traffics that require dedicated radio resource. A WLAN acts as a cooperating system and is built to provide additional radio resource at a hot spot area. The analysis of WLAN involved in this study will be focused on Point Coordinator Function (PCF) in the infrastructure IEEE 802.11 WLAN. A mobile host (MH) requiring performance guarantees from WLAN is required to set up a logical channel (LCH) with the point coordinator (PC). The maximum number of LCH is calculated and kept by the PC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".