P. S. Satyanarayana

Performability Model of Vertical Handoff in Wireless Data Network

The integration of different wireless technologies is the emerging trend in providing ubiquitous access to the high data rate wireless network. In such system user will be roaming among different radio access technologies (RATs) and this is known as vertical handover/handoff. In order to understand the practical behavior of the system, the Performability model is found to be essential. In wireless network the available bandwidth (ABW) of network is divided into set of logical channels[1] and these set of channels are shared among a set of network users. The network users are divided into new users and handoff users. The handoff users are further classified into vertical handoff users and horizontal handoff users. In a wireless network, the priority is given to handoff users. In order to provide better service to the wireless users the quality of service (QoS) parameters were defined[2]. One of the QoS parameter for the wireless network is handoff dropping probability. For better QoS it is desirable to reduce the handoff dropping probability hence separate set of guard channels were reserved for handoff[3][4]. In this prevailing scenario it is highly desirable to obtain analytic performability model. The stochastic Petri net (SPN) based performability model has been developed to verify the efficiency and accuracy of analytic performability model. The results obtained from both the performability models are promising.

Call Admission Control Approaches in Beyond 3G Networks Using Multi Criteria Decision Making

The next generation wireless networks (NGWN) should cater the varied requirements of the user and applications. The Call admission Control (CAC) is one of the radio resource management (RRM) technique used in the wireless networks. Unlike the CAC in homogeneous wireless networks the CAC in next generation wireless networks is very complex. In the next generation heterogeneous wireless networks, a user with a multi-interface terminal may have network access to different service providers using various technologies. This makes call admission control a challenging task where single criteria based CAC algorithms may not be able handle the decision making process efficiently, to address the heterogeneous architectures which characterize next generation wireless network, it is apparent that the call admission control algorithms should be based on multiple criteria. Various approaches have been proposed to solve the call admission control decision problem using multi criteria decision making (MCDM). This article provides a comprehensive survey of the different approaches for Call admission control using multi criteria decision making (MCDM) for incoming calls in heterogeneous wireless networks. The advantages and disadvantages of each approach are discussed.

Call Admission Control Mechanism for Optimal QoS in Next Generation Wireless Networks

The Next generation wireless network (NGWN) will be heterogeneous in nature where different radio access technologies (RATs) operate together .The mobile terminals operating in this heterogeneous environment will have different quality of service requirements to be handled by the system. The radio resource management is one of the key challenge in NGWN.Call admission control is one of the radio resource management technique plays instrumental role in ensure the desired Quality of Service (QoS) to the users working on different applications which have diversified nature of QoS requirements from the wireless networks . The call blocking probability is one such QoS parameter for the wireless network. For better QoS it is desirable to reduce the call blocking probability. In this customary scenario it is highly desirable to obtain analytic Performance model. In this paper we propose a higher order Markov chain based performance model for call admission control in a heterogeneous wireless network environment. In the proposed algorithm we have considered three classes of traffic having different QoS requirements and we have considered the heterogeneous network environment which includes that can effectively handle applications like voice calls, Web browsing and file transfer applications which are with varied QoS parameters. The paper presents the call blocking probabilities for all the three types of traffic both for fixed and varied traffic scenario.

A Perspective on Traffic Measurement Tools in Wireless Networks

To understand the characteristics of the wireless networks, the network usage data from wireless measurement tools are essential. The data collection is a process of collecting the network time-varying information in standardized format and from standard interfaces. The characteristics include signal propagation, received signal quality, network traffic, active applications and mobility of the mobile terminal (MT). The purpose of the measurement is to collect vital data of the wireless network. There are several tools available for this purpose. The most widely used network measurement tools are client side measurement tool, Syslog, Simple Network Management protocol (SNMP), network sniffing, wireless sniffing. This paper discusses the different wireless measurement tools and their benefits and limitation these tools.

Soft Computing Technique Based Call Admission Control Decision Mechanism

The decision Mechanism is the concluding phase of any decision making process. This paper discusses on the different methodologies available for implementing the decision mechanisms. The paper preambles with a brief description on set of conventional Multi criteria Decision Mechanisms (MCDM) like Analytical Hierarchy Process (AHP), Simple Additive weighting Method (SAW) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Grey Rational Analysis (GRA) along with benefits and limitations of each technique. The different intelligent/soft computing techniques that are widely used in decision making processes like fuzzy logic, neural networks are discussed and finally confines the discussions to the different neural network (NN) based decision support systems. The paper proposes a fuzzy neural network based architecture for call admission control decision mechanism in a heterogeneous wireless network environment.

A Perspective on Estimation of Available Capacity in Wireless Networks

To understand the characteristics of the wireless networks, the network usage data from wireless measurement tools are essential. The data collection is a process of collecting the network time-varying information in standardized formats and from standard interfaces. The characteristics of the wireless networks include, signal propagation, received signal quality, network traffic, active applications and mobility of the MT. The purpose of the measurement is to collect vital data of the wireless network. There are several tools available for this purpose. The most widely used network measurement tools are client side measurement tool, Syslog, Simple Network Management protocol(SNMP), network sniffing, wireless sniffing. This paper discusses the different wireless measurement tools like Syslog, Simple Network Management protocol, network sniffing, wireless sniffing and their benefits and limitations.