Performance evaluation and comparison of fuzzy-based intelligent CAC Systems for wireless cellular networks

The mobile cellular systems are expected to support multiple services with guaranteed Quality of Service(QoS). But, the ability of wireless systems to accommodate expected growth of traffic load and broadband services is limited by available radio frequency spectrum. Call Admission Control (CAC) is one of the resource management functions, which regulates network access to ensure QoS provisioning. However, the decision for CAC is very challenging issue due to user mobility, limited radio spectrum, and multimedia traffic characteristics. To deal with these problems, we implemented a Fuzzy Admission Control System (FACS). We compared the performance of FACS with Shadow Cluster Concept (SCC). In another work, we extended FACS by considering the priority of the on-going connections. We called this system FACS-P. As priority parameter, we considered only one parameter (service request). In this work, we improve our previous system by adding different priorities. We call this system FACS-MP. We evaluate and compare the performance of implemented systems by simulations. From the simulations results, we conclude that the FACS-MP can differentiate better different services compared with previous systems.Peer ReviewedPostprint (published version

Resource reservation in wireless networks based on pattern recognition

Resource reservation is very important for handoff control in wireless networks. Many researches have aimed to predict the user's destination cell based on its movement pattern for efficient resource reservation. In the future networks with small size cells, handoffs will occur more frequently and the user's movement will be more like a random process, so it is not practical to predict the accurate destination of a user. We propose a statistical strategy for resource reservation through the estimation of a user's transfer probabilities, which represent the possibilities of the user leaving the current cell and entering the neighboring cells. The resources reserved for a user in each base station are proportional to the user's transfer probabilities. A mathematical model is proposed to obtain the transfer probabilities of a user from the initial states (position, velocity and direction) through simulation of the user's movement. Neural networks are developed to predict the transfer probabilities of a user from the initial states and facilitate efficient resource reservation.published_or_final_versio

A fuzzy-based call admission control system for wireless cellular networks

The mobile cellular systems are expected to support multiple services with guaranteed quality of service (QoS). However, the ability of wireless systems to accommodate expected growth of traffic load and broadband services is limited by available radio frequency spectrum. Call admission control (CAC) is one of the resource management functions, which regulates network access to ensure QoS provisioning. However, the decision for CAC is very challenging issue due to user mobility, limited radio spectrum, and multimedia traffic characteristics. To deal with these problems, in this paper, we propose a fuzzy CAC system. We compare the performance of the proposed system with shadow cluster concept (SCC). We evaluate by simulation the performance of the proposed system. The proposed system has a good behavior on deciding the number of accepted connections while keeping the QoS for serving connections.Peer ReviewedPostprint (published version

A fuzzy-based CAC scheme for wireless cellular networks considering different priorities

The mobile cellular systems are expected to support multiple services with guaranteed Quality of Service(QoS). But, the ability of wireless systems to accommodate expected growth of traffic load and broadband services is limited by available radio frequency spectrum. Call Admission Control (CAC) is one of the resource management functions, which regulates network access to ensure QoS provisioning. However, the decision for CAC is very challenging issue due to user mobility, limited radio spectrum, and multimedia traffic characteristics. In our previous work, we proposed a fuzzy-based CAC system by considering the priority of the on-going connections. As priority parameter, we considered only one parameter (service request). In this work, we extend our work by adding different priorities. We call this system FACS-MP. We evaluate by simulations the performance of the proposed system. From the simulations results, we conclude that the FACS-MP can differentiate better different services compared with previous system.Peer ReviewedPostprint (published version

A fuzzy based call admission control scheme for wireless cellular networks considering priority of on-going connections

The mobile cellular systems are expected to support multiple services with guaranteed Quality of Service (QoS).But, the ability of wireless systems to accommodate expected growth of traffic load and broadband services is limited by available radio frequency spectrum. Call Admission Control (CAC) is one of the resource management functions, which regulates network access to ensure QoS provisioning. However, the decision for CAC is very challenging issue due to user mobility, limited radio spectrum, and multimedia traffic characteristics. In our previous work, we proposed a fuzzy-based CAC system and compared the performance of the proposed system with Shadow Cluster Concept (SCC). In this work, we extend our work by considering the priority of the on-going connections. We evaluate by simulations the performance of the proposed system and compare its performance with our previous work. The performance evaluation shows that the proposed system has a good behavior in keeping the QoS of on-going connectionsPeer ReviewedPostprint (published version

Efficient resource allocation and call admission control in high capacity wireless networks

Resource Allocation (RA) and Call Admission Control (CAC) in wireless networks are processes that control the allocation of the limited radio resources to mobile stations (MS) in order to maximize the utilization efficiency of radio resources and guarantee the Quality of Service (QoS) requirements of mobile users. In this dissertation, several distributed, adaptive and efficient RA/CAC schemes are proposed and analyzed, in order to improve the system utilization while maintaining the required QoS. Since the most salient feature of the mobile wireless network is that users are moving, a Mobility Based Channel Reservation (MBCR) scheme is proposed which takes the user mobility into consideration. The MBCR scheme is further developed into PMBBR scheme by using the user location information in the reservation making process. Through traffic composition analysis, the commonly used assumption is challenged in this dissertation, and a New Call Bounding (NCB) scheme, which uses the number of channels that are currently occupied by new calls as a decision variable for the CAC, is proposed. This dissertation also investigates the pricing as another dimension for RA/CAC. It is proven that for a given wireless network there exists a new call arrival rate which can maximize the total utility of users, while maintaining the required QoS. Based on this conclusion, an integrated pricing and CAC scheme is proposed to alleviate the system congestion

Performance analysis of handoff resource allocation strategies through the state-dependent rejection scheme

The state-dependent rejection scheme (SRS) provides a common framework for analysing existing handoff schemes and for designing new ones easily. Designing new schemes is made simple by determining the appropriate set of state-dependent probabilities. The Markov analysis of SRS is simple and useful for drawing initial conclusions on handoff strategies. The analysis and simulations carried out here demonstrate the capability of SRS to adapt to different mobility and load scenarios and to achieve good performance while targeting quality of service performance metrics.Peer Reviewe

QoS Provisioning for Multi-Class Traffic in Wireless Networks

Physical constraints, bandwidth constraints and host mobility all contribute to the difficulty of providing Quality of Service (QoS) guarantees in wireless networks. There is a growing demand for wireless networks to support all the services that are available on wired networks. These diverse services, such as email, instant messaging, web browsing, video conferencing, telephony and paging all place different demands on the network, making QoS provisioning for wireless networks that carry multiple classes of traffic a complex problem. We have developed a set of admission control and resource reservation schemes for QoS provisioning in multi-class wireless networks. We present three variations of a novel resource borrowing scheme for cellular networks that exploits the ability of some multimedia applications to adapt to transient fluctuations in the supplied resources. The first of the schemes is shown to be proportionally fair: the second scheme is max-min fair. The third scheme for cellular networks uses knowledge about the relationship between streams that together comprise a multimedia session in order to further improve performance. We also present a predictive resource reservation scheme for LEO satellite networks that exploits the regularity of the movement patterns of mobile hosts in LEO satellite networks. We have developed the cellular network simulator (CNS) for evaluating call-level QoS provisioning schemes. QoS at the call-level is concerned with call blocking probability (CBP), call dropping probability (CDP), and supplied bandwidth. We introduce two novel QoS parameters that relate to supplied bandwidth—the average percent of desired bandwidth supplied (DBS), and the percent of time spent operating at the desired bandwidth level (DBT)

Predictability of Wlan Mobility and Its Effects on Bandwidth Provisioning

Wireless local area networks (WLANs) are emerging as a popular technology for access to the Internet and enterprise networks. In the long term, the success of WLANs depends on services that support mobile network clients. \par Although other researchers have explored mobility prediction in hypothetical scenarios, evaluating their predictors analytically or with synthetic data, few studies have been able to evaluate their predictors with real user mobility data. As a first step towards filling this fundamental gap, we work with a large data set collected from the Dartmouth College campus-wide wireless network that hosts more than 500 access points and 6,000 users. Extending our earlier work that focuses on predicting the next-visited access point (i.e., location), in this work we explore the predictability of the time of user mobility. Indeed, our contributions are two-fold. First, we evaluate a series of predictors that reflect possible dependencies across time and space while benefiting from either individual or group mobility behaviors. Second, as a case study we examine voice applications and the use of handoff prediction for advance bandwidth reservation. Using application-specific performance metrics such as call drop and call block rates, we provide a picture of the potential gains of prediction. \par Our results indicate that it is difficult to predict handoff time accurately, when applied to real campus WLAN data. However, the findings of our case study also suggest that application performance can be improved significantly even with predictors that are only moderately accurate. The gains depend on the applications\u27 ability to use predictions and tolerate inaccurate predictions. In the case study, we combine the real mobility data with synthesized traffic data. The results show that intelligent prediction can lead to significant reductions in the rate at which active calls are dropped due to handoffs with marginal increments in the rate at which new calls are blocked