With the rapid increase of new and diverse cellular mobile services, the overlapping of cells has become typical in the majority of the coverage area of the network. Vertical handovers occur between two layers of cells when a user is switched from one layer to the other. In this paper we investigate the influence of network parameters on vertical hard handover performance in a cell environment. The work considers two layers of cells: a layer of macrocells and a layer of microcells. Handover requests enter the macrocell from neighbor macrocells and from microcells that belong to a different layer. Using Markov chain analysis and simulation we calculate network performance parameters such as mean queue delay, handover dropping probability and channel utilization. We also compare the handover performance for the macrocell and macrocell traffic separately. Our results show the influence of total channels, maximum queue size and handover request arrival rate on handover performance. They also show that when the traffic from each layer is treated with equal priority in the system, the performance of each layer is comparable.
HANDOVER NECESSITY ESTIMATION FOR 4G HETEROGENEOUS NETWORKSijistjournal
One of the most challenges of 4G network is to have a unified network of heterogeneous wireless networks. To achieve seamless mobility in such a diverse environment, vertical hand off is still a challenging problem. In many situations handover failures and unnecessary handoffs are triggered causing degradation of services, reduction in throughput and increase the blocking probability and packet loss. In this paper a new vertical handoff decision algorithm handover necessity estimation (HNE), is proposed to minimize the number of handover failure and unnecessary handover in heterogeneous wireless networks. we have proposed a multi criteria vertical handoff decision algorithm based on two parts: traveling time estimation and time threshold calculation. Our proposed methods are compared against two other methods: (a) the fixed RSS threshold based method, in which handovers between the cellular network and the WLAN are initiated when the RSS from the WLAN reaches a fixed threshold, and (b) the hysteresis based method, in which a hysteresis is introduced to prevent the ping-pong effect. Simulation results show that, this method reduced the number of handover failures and unnecessary handovers up to 80% and 70%, respectively.
HANDOVER NECESSITY ESTIMATION FOR 4G HETEROGENEOUS NETWORKSijistjournal
One of the most challenges of 4G network is to have a unified network of heterogeneous wireless networks. To achieve seamless mobility in such a diverse environment, vertical hand off is still a challenging problem. In many situations handover failures and unnecessary handoffs are triggered causing degradation of services, reduction in throughput and increase the blocking probability and packet loss. In this paper a new vertical handoff decision algorithm handover necessity estimation (HNE), is proposed to minimize the number of handover failure and unnecessary handover in heterogeneous wireless networks. we have proposed a multi criteria vertical handoff decision algorithm based on two parts: traveling time estimation and time threshold calculation. Our proposed methods are compared against two other methods: (a) the fixed RSS threshold based method, in which handovers between the cellular network and the WLAN are initiated when the RSS from the WLAN reaches a fixed threshold, and (b) the hysteresis based method, in which a hysteresis is introduced to prevent the ping-pong effect. Simulation results show that, this method reduced the number of handover failures and unnecessary handovers up to 80% and 70%, respectively.
This document discusses vertical handover decision algorithms for heterogeneous wireless networks. It analyzes existing vertical handover decision algorithms and proposes a new prediction-based approach. Specifically:
1. Existing algorithms do not consider mobility prediction methods to take proactive measures when deciding vertical handovers.
2. The proposed algorithm uses a Hidden Markov Model predictor to accurately estimate a user's next location based on current and historical movement data.
3. This allows the algorithm to make more informed vertical handover decisions by anticipating future movements and network conditions.
An Intelligent Approach for Handover Decision in Heterogeneous Wireless Envir...CSCJournals
Vertical handoff is the basic requirement of the convergence of different access technologies. It is also the key characteristic and technology of overlay wireless network with appropriate network interfaces. The integration of diverse but complementary cellular and wireless technologies in the next generation wireless networks requires the design of intelligent vertical handoff decision algorithms to enable mobile users equipped with contemporary multi-interfaced mobile terminals to seamlessly switch network access and experience uninterrupted service continuity anywhere and anytime. Most existing vertical handoff decision strategies are designed to meet individual needs that may not achieve a good system performance. In this paper an intelligent approach is used for vertical handover decision. The intelligence is based on the fuzzy logic approach. So here, fuzzy logic is used for network selection and decision making for vertical handover.
Research Inventy : International Journal of Engineering and Scienceinventy
Research Inventy : International Journal of Engineering and Science
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed
This document discusses decision strategies for vertical handovers in heterogeneous wireless networks. It begins by introducing the concepts of vertical handovers and heterogeneous networks. It then discusses some key aspects of handover management including the three phase process (information gathering, decision, execution), types of handovers, and control mechanisms. Several vertical handover decision strategies are then summarized, including those based on decision functions, user-centric approaches, and multiple attribute decision making. The strategies aim to select the optimal network by evaluating different criteria like network conditions, user preferences, quality of service, and applying weighting and algorithms. The document provides an overview of recent research on improving handover decisions between different wireless technologies.
This document discusses vertical handover in heterogeneous wireless networks. It begins by introducing the concept of vertical handover which allows seamless switching between different wireless technologies like 3G cellular networks and WiFi networks. It then discusses some of the challenges in managing vertical handovers, particularly achieving seamlessness and automation. Several decision strategies for vertical handover are proposed to address these challenges and achieve the goal of always providing users with the best available connection. The document goes on to describe the typical phases of the vertical handover process - information gathering, decision, and execution. It also discusses factors that influence the handover decision like network conditions, user preferences, and quality of service requirements.
ADHOCFTSIM: A Simulator of Fault Tolerence In the AD-HOC Networksijwmn
The flexibility and diversity of Wireless Mobile Networks offer many opportunities that are not always taken into account by existing distributed systems. In particular, the proliferation of mobile users and the use of mobile Ad-Hoc promote the formation of collaborative groups to share resources. We propose a solution for the management of fault tolerance in the Ad-Hoc networks, combining the functions needed to better availability of data. Our contribution takes into account the characteristics of mobile terminals in order to reduce the consumption of resources critical that energy, and to minimize the loss of information. Our solution is based on the formation of clusters, where each is managed by a node leader. This solution is mainly composed of four sub-services, namely: prediction, replication, management of nodes in the cluster and supervision. We have shown, using several sets of simulation, that our solution is twofold: minimizing the
HANDOVER NECESSITY ESTIMATION FOR 4G HETEROGENEOUS NETWORKSijistjournal
One of the most challenges of 4G network is to have a unified network of heterogeneous wireless networks. To achieve seamless mobility in such a diverse environment, vertical hand off is still a challenging problem. In many situations handover failures and unnecessary handoffs are triggered causing degradation of services, reduction in throughput and increase the blocking probability and packet loss. In this paper a new vertical handoff decision algorithm handover necessity estimation (HNE), is proposed to minimize the number of handover failure and unnecessary handover in heterogeneous wireless networks. we have proposed a multi criteria vertical handoff decision algorithm based on two parts: traveling time estimation and time threshold calculation. Our proposed methods are compared against two other methods: (a) the fixed RSS threshold based method, in which handovers between the cellular network and the WLAN are initiated when the RSS from the WLAN reaches a fixed threshold, and (b) the hysteresis based method, in which a hysteresis is introduced to prevent the ping-pong effect. Simulation results show that, this method reduced the number of handover failures and unnecessary handovers up to 80% and 70%, respectively.
HANDOVER NECESSITY ESTIMATION FOR 4G HETEROGENEOUS NETWORKSijistjournal
One of the most challenges of 4G network is to have a unified network of heterogeneous wireless networks. To achieve seamless mobility in such a diverse environment, vertical hand off is still a challenging problem. In many situations handover failures and unnecessary handoffs are triggered causing degradation of services, reduction in throughput and increase the blocking probability and packet loss. In this paper a new vertical handoff decision algorithm handover necessity estimation (HNE), is proposed to minimize the number of handover failure and unnecessary handover in heterogeneous wireless networks. we have proposed a multi criteria vertical handoff decision algorithm based on two parts: traveling time estimation and time threshold calculation. Our proposed methods are compared against two other methods: (a) the fixed RSS threshold based method, in which handovers between the cellular network and the WLAN are initiated when the RSS from the WLAN reaches a fixed threshold, and (b) the hysteresis based method, in which a hysteresis is introduced to prevent the ping-pong effect. Simulation results show that, this method reduced the number of handover failures and unnecessary handovers up to 80% and 70%, respectively.
This document discusses vertical handover decision algorithms for heterogeneous wireless networks. It analyzes existing vertical handover decision algorithms and proposes a new prediction-based approach. Specifically:
1. Existing algorithms do not consider mobility prediction methods to take proactive measures when deciding vertical handovers.
2. The proposed algorithm uses a Hidden Markov Model predictor to accurately estimate a user's next location based on current and historical movement data.
3. This allows the algorithm to make more informed vertical handover decisions by anticipating future movements and network conditions.
An Intelligent Approach for Handover Decision in Heterogeneous Wireless Envir...CSCJournals
Vertical handoff is the basic requirement of the convergence of different access technologies. It is also the key characteristic and technology of overlay wireless network with appropriate network interfaces. The integration of diverse but complementary cellular and wireless technologies in the next generation wireless networks requires the design of intelligent vertical handoff decision algorithms to enable mobile users equipped with contemporary multi-interfaced mobile terminals to seamlessly switch network access and experience uninterrupted service continuity anywhere and anytime. Most existing vertical handoff decision strategies are designed to meet individual needs that may not achieve a good system performance. In this paper an intelligent approach is used for vertical handover decision. The intelligence is based on the fuzzy logic approach. So here, fuzzy logic is used for network selection and decision making for vertical handover.
Research Inventy : International Journal of Engineering and Scienceinventy
Research Inventy : International Journal of Engineering and Science
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed
This document discusses decision strategies for vertical handovers in heterogeneous wireless networks. It begins by introducing the concepts of vertical handovers and heterogeneous networks. It then discusses some key aspects of handover management including the three phase process (information gathering, decision, execution), types of handovers, and control mechanisms. Several vertical handover decision strategies are then summarized, including those based on decision functions, user-centric approaches, and multiple attribute decision making. The strategies aim to select the optimal network by evaluating different criteria like network conditions, user preferences, quality of service, and applying weighting and algorithms. The document provides an overview of recent research on improving handover decisions between different wireless technologies.
This document discusses vertical handover in heterogeneous wireless networks. It begins by introducing the concept of vertical handover which allows seamless switching between different wireless technologies like 3G cellular networks and WiFi networks. It then discusses some of the challenges in managing vertical handovers, particularly achieving seamlessness and automation. Several decision strategies for vertical handover are proposed to address these challenges and achieve the goal of always providing users with the best available connection. The document goes on to describe the typical phases of the vertical handover process - information gathering, decision, and execution. It also discusses factors that influence the handover decision like network conditions, user preferences, and quality of service requirements.
ADHOCFTSIM: A Simulator of Fault Tolerence In the AD-HOC Networksijwmn
The flexibility and diversity of Wireless Mobile Networks offer many opportunities that are not always taken into account by existing distributed systems. In particular, the proliferation of mobile users and the use of mobile Ad-Hoc promote the formation of collaborative groups to share resources. We propose a solution for the management of fault tolerance in the Ad-Hoc networks, combining the functions needed to better availability of data. Our contribution takes into account the characteristics of mobile terminals in order to reduce the consumption of resources critical that energy, and to minimize the loss of information. Our solution is based on the formation of clusters, where each is managed by a node leader. This solution is mainly composed of four sub-services, namely: prediction, replication, management of nodes in the cluster and supervision. We have shown, using several sets of simulation, that our solution is twofold: minimizing the
BIO-INSPIRED SEAMLESS VERTICAL HANDOVER ALGORITHM FOR VEHICULAR AD HOC NETWORKSijwmn
One of the most important factors to implement VANET is by considering the variety of wireless networks available around the city as well as the vehicles traffic scenarios. However, by providing a diverse range of wireless access technologies, it is necessary to provide continuous network connectivity as well as selecting the most suitable network technology and performance. Many researchers have worked on building algorithms for selecting the best network to improve the handover process. However, with high-speed vehicles mobility, the vertical handover process became the most challenging task in order to achieve realtime network selection. This paper proposes a bio-inspired network selection algorithm influenced by insect's behaviour which combines Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO). The proposed algorithm is applied to process multi-criteria parameters to evaluate the best available network and then execute the handover process seamlessly. The results demonstrate the benefits of the proposed Multi-Criteria ABC-PSO method by reducing the handover decision delays by 25%. It gives the optimum performance in terms of network selections and reduces the handover latency by 14.5%. The proposed algorithm also reduces the number of unnecessary handovers by 48% for three different mobility scenarios based on traffic environments (highway, urban and traffic jam).
Handover management scheme in LTE FEMTOCELL networksijcsit
This document discusses handover management in LTE femtocell networks. It presents the architecture of LTE femtocell networks and investigates different handover scenarios, particularly macrocell to femtocell handover which is difficult due to the large number of candidate femtocells. The document proposes using the HeNB Policy Function entity to optimize handover decision making by selecting the target femtocell based on constraints to make the optimal decision and reduce unnecessary handovers. An analytical model is also presented to evaluate handover signalling costs.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
The advancement in mobile technology and wireless network increase the using of mobile device in database
driven application, these application require high reliability and availability due to nature inheritance of
mobile environment, transaction is the center component in database systems, In this paper we present
useful work done in mobile transaction, we show the mobile database environment and overview a lot of
proposed model of mobile transaction and show many techniques used to enhance transaction execution.
MOVEMENT ASSISTED COMPONENT BASED SCALABLE FRAMEWORK FOR DISTRIBUTED WIRELESS...ijcsa
Intelligent networks are becoming more enveloping and dwelling a new generation of applications are
deployed over the peer-to-peer networks. Intelligent networks are very attractive because of their role in
improving the scalability and enhancing performance by enabling direct and real-time communication
among the participating network stations. A suitable solution for resource management in distributed wireless systems is required which should support fault-tolerant operations, requested resources (at shortest path), minimize overhead generation during network management, balancing the load distribution between the participating stations and high probability of lookup success and many more. This article
presents a Movement Assisted Component Based Scalable Framework (MAC-SF) for the distributed
network which manages the distributed wireless resources and applications; monitors the behavior of the
distributed wireless applications transparently and attains accurate resource projections, manages the
connections between the participating network stations and distributes the active objects in response to the
user requests and changing processing and network conditions. This system is also compared with some
exiting systems. Results shows that MAC-SF is a better system and can be used in any wireless network.
This document summarizes research on vertical handover between UMTS and WLAN networks. It describes the architectures, algorithms and procedures involved in vertical handover. The key points are:
1. Vertical handover allows seamless switching between cellular (UMTS) and wireless local area (WLAN) networks. This provides benefits like reduced power consumption and lower costs when using WLAN connections.
2. The Universal Seamless Handover Architecture (USHA) is proposed to support both horizontal and vertical handovers with small infrastructure changes. It uses IP tunneling techniques.
3. The Smart Decision Model is used for reliable network selection. It gathers information to choose the best network interface based on factors
Analysis of Neighbor Knowledge Based Bcast Protocol Performance For Multihop ...pijans
This document analyzes the performance of a neighbor knowledge based broadcast protocol called BCAST in mobile ad hoc networks using network simulator NS-2. It varies the number of data senders (multicast group size) and data sending rate to analyze packet delivery ratio, end-to-end delay, packet loss probability, and network control overhead. The simulation results show that BCAST generally performs well and provides robust performance even with high traffic loads.
Analysis of Neighbor Knowledge Based Bcast Protocol Performance For Multihop ...pijans
Reliable group communication is a challenging issue for most Mobile Ad-hoc Networks (MANETs) due to
dynamic nature of wireless mobile nodes, group key establishment and management, ensuring secure
information exchange and Quality of Service (QoS) in data transfer. Recently multicast and broadcast
routing protocols are emerging for supporting QoS aware group communication. In MANETs QoS
requirements can be quantified by a set of measurable pre-specified service attributes such as packet
delivery ratio, end-to-end delay, packet loss probability, network control overhead, throughput,
bandwidth, power consumption, service coverage area etc. In this paper, the performance of a neighbor
knowledge based broadcast protocol is analyzed using different QoS metrics (packet delivery ratio, end-toend delay, packet loss probability and network control overhead). BCAST is used as broadcast protocol.
The performance differentials are analyzed using NS-2 network simulator for varying number of data
senders (multicast group size) and data sending rate (offered traffic to the network) over QoS aware group
communication. Simulation results show that BCAST performs well in most cases and provides robust
performance even with high traffic environments.
This document presents a comparative analysis of vertical handoff in IEEE 802.11 WLAN and CDMA networks. It discusses vertical handoff strategies and methods, and related work on handoff performance analysis in 802.11 networks. The paper then presents an existing vertical handoff algorithm between WLAN and CDMA networks, and defines variables used to determine handoff delay and throughput. Simulation results are shown comparing throughput and handoff delay for real-time and non-real-time services under different conditions in a network modeled based on WLAN and CDMA technologies.
A Comparative Analysis of Vertical Handover Decision Process Algorithms for N...Editor IJMTER
This document summarizes a research paper that analyzes algorithms for vertical handover decision processes in heterogeneous wireless networks. It begins with an abstract that outlines the goal of selecting the best network for a user based on various parameters. It then provides background on heterogeneous networks and the need for vertical handoff algorithms. The document categorizes different types of vertical handoffs and discusses key parameters considered in decision algorithms like bandwidth, speed, signal strength, power consumption and cost. Finally, it examines example algorithms like SAW, TOPSIS, GRA and MEW that make network selection decisions based on weighting and ranking these parameters.
This document summarizes research on parameters for vertical handoff in heterogeneous wireless networks. It discusses several key parameters that influence vertical handoff decisions, including available bandwidth, received signal strength, cost, latency, and quality of service. The document reviews several existing approaches for vertical handoff that consider parameters like bandwidth, RSS, access fee, packet delay, available bandwidth, and network load. Overall, the document analyzes parameters that are important for designing efficient vertical handoff mechanisms in next-generation heterogeneous wireless networks.
Spectrum Sensing with VSS-NLMS Process in Femto/Macrocell EnvironmentsIJECEIAES
Handover is a process that allows a mobile node to change its attachment point. A mobile node connected to a network can, in order to improve the quality of service, have the need to leave it to connect to a cell either of the same network or of a new network. The present paper introduce three techniques using adaptive Variable Step-Size Least Mean Square (VSSLMS) filter combined with spectrum sensing probability method to detect the triggering of handover in heterogeneous LTE networks. These techniques are Normalized LMS (NLMS), Kwong-NLMS and Li-NLMS. The simulation environment is composed of two femtocells belonging to a macrocell. Five User Equipements (UEs) are positioned in one femtocell and are assumed closest to its circumference. Simulation results show that sensing probability with Li-NLMS algorithm has a better performance compared with classical NLMS and Kwong-NLMS
An Enhanced Algorithm for Load-based Handover Decision-making in 5G Wireless ...IRJET Journal
This paper proposes an enhanced algorithm for load-based handover decision making in 5G wireless networks. The current handover decision making process does not consider the load of potential target cells, which can lead to handover failures if a user is handed over to an overloaded cell. The proposed algorithm uses fuzzy logic to determine if a candidate cell is suitable for handover based on its current load. Simulation results show the new algorithm improves network load balancing and reduces handover failures compared to existing methods.
Teletraffic Analysis of Overflowed Traffic with Voice only in Multilayer 3G W...IRJET Journal
This document presents a study analyzing the traffic overflow performance of a three-layered wireless mobile network with microcells, macrocells and satellite cells handling voice-only traffic. The three-layered hierarchical network structure is described, with microcells overlaid by macrocells and macrocells overlaid by satellite cells. An existing call admission control scheme is evaluated that prioritizes voice calls, including handling call blocking probabilities, channel utilization, and call dropping probabilities across the different cell layers under varying traffic parameters. Analytical models are developed and numerical calculations are performed to analyze the performance of the call admission control scheme in the three-layered network handling overflowed voice traffic.
Performance and handoff evaluation of heterogeneous wireless networks 2IAEME Publication
This document discusses performance evaluations of heterogeneous wireless networks (HWNs) using the OPNET simulator. It implemented WLAN, WiMAX, and UMTS networks with applications like FTP, video conferencing, and VoIP. Handoff management between the networks was also evaluated. Simulation results showed WiMAX throughput was over 30% higher than WLAN and UMTS. Vertical handoff between WLAN-WiMAX and WLAN-UMTS was difficult without carefully engineering the WLAN network due to differences between the networks. Key metrics like delay, throughput, and received traffic were analyzed and WiMAX generally had superior performance.
Handover is the process of switching among the
available services without any interruption. Vertical handover is
a technique of switching from one type of a network to another
type of network (e.g., from WiFi to WiMAX). Seamless handover
between different access technologies is a great challenge as it
needs to obey different performance of QoS and security
constraints. Service users are becoming more demanding
regarding roaming capabilities across different networking
technologies such as WiFi, WiMAX, and CDMA as they claim
service continuity with QoS requirement and good security
features. Vertical Handover Decision (VHD) algorithms need to
be designed to provide the required Quality of Service (QoS) to a
wide range of applications while allowing seamless roaming
among a number of access network technologies. This paper is
about the implementation of the VHD algorithms designed to
satisfy these requirements. A combination of 3 parameters i.e.
Data Rate, SINR and RSS are evaluated to take decision of the
best network among available.
QOS ROUTING AND PERFORMANCE EVALUATION FOR MOBILE AD HOC NETWORKS USING OLSR ...ijasuc
Mobile Ad-Hoc network is a collection of mobile nodes in communication without using infrastructure.
As the real-time applications used in today’s wireless network grow, we need some schemes to provide
more suitable service for them. We know that most of actual schemes do not perform well on traffic which
is not strictly CBR. Therefore, in this paper we have studied the impact, respectively, of mobility models
and the density of nodes on the performances (End-to-End Delay, Throughput and Packet Delivery ratio)
of routing protocol (Optimized Link State Routing) OLSR by using in the first a real-time VBR (MPEG-4)
and secondly the Constant Bit Rate (CBR) traffic. Finally we compare the performance on both cases.
Experimentally, we considered the three mobility models as follows Random Waypoint, Random
Direction and Mobgen Steady State. The experimental results illustrate that the behavior of OLSR change
according to the model and the used traffics.
This document provides a tutorial on self-optimization of the random access procedure in 3G Long Term Evolution (LTE) networks. It describes the key components and steps of the random access procedure, including random access preambles, formats, opportunities, and the contention-based procedure. It also addresses relevant performance metrics like access probability, detection miss probability, and contention probability. The paper discusses modeling radio network simulations and collecting performance data to enable self-optimization of random access parameters to meet specified requirements. The goal is to present relevant self-optimization problems rather than complete solutions.
The document discusses wireless network technologies and vertical handoffs. It introduces the motivation for intelligent vertical handoff techniques using artificial intelligence. Key points include:
1) Heterogeneous wireless networks integrate different technologies like WiFi, WiMAX and UMTS to provide seamless mobility but handoff decision making is challenging due to many parameters.
2) The document proposes using fuzzy logic for intelligent handoff necessity estimation and target network selection to maximize user satisfaction based on multiple criteria.
3) IEEE 802.16 standards including 802.16m, 802.16e, and 802.16j are discussed which focus on data rates up to 100Mbps for mobile and 1Gbps for fixed
A vertical handover decision approaches in next generation wireless networks ...ijmnct
In next generation wireless network the most desirable feature is its ability to move seamlessly over various
access network regardless of the network infrastructure is used. The handover between these dissimilar
networks can be explored by using vertical handover algorithms. This paper focuses on the vertical
handover decision methods and algorithms effectiveness. Most of the algorithms which are based on RSS
values provide vertical handover with small delay at a lower rate of throughput. There are such algorithms
which provide significant improvements in throughput but at a cost of higher delays. As per the need for the
real time applications in next generation wireless networks there is a requirement of developing new
optimized algorithms that are able to produce high throughput and minimizing signalling cost and delay.
Call for Papers - 10th International Conference on Computer Science and Infor...josephjonse
10th International Conference on Computer Science and Information Technology (CSTY 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Computer Science, Engineering and Information Technology. The Conference looks for significant contributions to all major fields of the Computer Science, Engineering and Information Technology in theoretical and practical aspects.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to.
8th International Conference on Soft Computing, Mathematics and Control (SMC ...josephjonse
8th International Conference on Soft Computing, Mathematics and Control (SMC 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications impacts and challenges of Soft Computing, Mathematics and Control. The conference documents practical and theoretical results which make a fundamental contribution for the development of Soft Computing, Mathematics and Control. The aim of the conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.
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BIO-INSPIRED SEAMLESS VERTICAL HANDOVER ALGORITHM FOR VEHICULAR AD HOC NETWORKSijwmn
One of the most important factors to implement VANET is by considering the variety of wireless networks available around the city as well as the vehicles traffic scenarios. However, by providing a diverse range of wireless access technologies, it is necessary to provide continuous network connectivity as well as selecting the most suitable network technology and performance. Many researchers have worked on building algorithms for selecting the best network to improve the handover process. However, with high-speed vehicles mobility, the vertical handover process became the most challenging task in order to achieve realtime network selection. This paper proposes a bio-inspired network selection algorithm influenced by insect's behaviour which combines Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO). The proposed algorithm is applied to process multi-criteria parameters to evaluate the best available network and then execute the handover process seamlessly. The results demonstrate the benefits of the proposed Multi-Criteria ABC-PSO method by reducing the handover decision delays by 25%. It gives the optimum performance in terms of network selections and reduces the handover latency by 14.5%. The proposed algorithm also reduces the number of unnecessary handovers by 48% for three different mobility scenarios based on traffic environments (highway, urban and traffic jam).
Handover management scheme in LTE FEMTOCELL networksijcsit
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International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
The advancement in mobile technology and wireless network increase the using of mobile device in database
driven application, these application require high reliability and availability due to nature inheritance of
mobile environment, transaction is the center component in database systems, In this paper we present
useful work done in mobile transaction, we show the mobile database environment and overview a lot of
proposed model of mobile transaction and show many techniques used to enhance transaction execution.
MOVEMENT ASSISTED COMPONENT BASED SCALABLE FRAMEWORK FOR DISTRIBUTED WIRELESS...ijcsa
Intelligent networks are becoming more enveloping and dwelling a new generation of applications are
deployed over the peer-to-peer networks. Intelligent networks are very attractive because of their role in
improving the scalability and enhancing performance by enabling direct and real-time communication
among the participating network stations. A suitable solution for resource management in distributed wireless systems is required which should support fault-tolerant operations, requested resources (at shortest path), minimize overhead generation during network management, balancing the load distribution between the participating stations and high probability of lookup success and many more. This article
presents a Movement Assisted Component Based Scalable Framework (MAC-SF) for the distributed
network which manages the distributed wireless resources and applications; monitors the behavior of the
distributed wireless applications transparently and attains accurate resource projections, manages the
connections between the participating network stations and distributes the active objects in response to the
user requests and changing processing and network conditions. This system is also compared with some
exiting systems. Results shows that MAC-SF is a better system and can be used in any wireless network.
This document summarizes research on vertical handover between UMTS and WLAN networks. It describes the architectures, algorithms and procedures involved in vertical handover. The key points are:
1. Vertical handover allows seamless switching between cellular (UMTS) and wireless local area (WLAN) networks. This provides benefits like reduced power consumption and lower costs when using WLAN connections.
2. The Universal Seamless Handover Architecture (USHA) is proposed to support both horizontal and vertical handovers with small infrastructure changes. It uses IP tunneling techniques.
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Analysis of Neighbor Knowledge Based Bcast Protocol Performance For Multihop ...pijans
This document analyzes the performance of a neighbor knowledge based broadcast protocol called BCAST in mobile ad hoc networks using network simulator NS-2. It varies the number of data senders (multicast group size) and data sending rate to analyze packet delivery ratio, end-to-end delay, packet loss probability, and network control overhead. The simulation results show that BCAST generally performs well and provides robust performance even with high traffic loads.
Analysis of Neighbor Knowledge Based Bcast Protocol Performance For Multihop ...pijans
Reliable group communication is a challenging issue for most Mobile Ad-hoc Networks (MANETs) due to
dynamic nature of wireless mobile nodes, group key establishment and management, ensuring secure
information exchange and Quality of Service (QoS) in data transfer. Recently multicast and broadcast
routing protocols are emerging for supporting QoS aware group communication. In MANETs QoS
requirements can be quantified by a set of measurable pre-specified service attributes such as packet
delivery ratio, end-to-end delay, packet loss probability, network control overhead, throughput,
bandwidth, power consumption, service coverage area etc. In this paper, the performance of a neighbor
knowledge based broadcast protocol is analyzed using different QoS metrics (packet delivery ratio, end-toend delay, packet loss probability and network control overhead). BCAST is used as broadcast protocol.
The performance differentials are analyzed using NS-2 network simulator for varying number of data
senders (multicast group size) and data sending rate (offered traffic to the network) over QoS aware group
communication. Simulation results show that BCAST performs well in most cases and provides robust
performance even with high traffic environments.
This document presents a comparative analysis of vertical handoff in IEEE 802.11 WLAN and CDMA networks. It discusses vertical handoff strategies and methods, and related work on handoff performance analysis in 802.11 networks. The paper then presents an existing vertical handoff algorithm between WLAN and CDMA networks, and defines variables used to determine handoff delay and throughput. Simulation results are shown comparing throughput and handoff delay for real-time and non-real-time services under different conditions in a network modeled based on WLAN and CDMA technologies.
A Comparative Analysis of Vertical Handover Decision Process Algorithms for N...Editor IJMTER
This document summarizes a research paper that analyzes algorithms for vertical handover decision processes in heterogeneous wireless networks. It begins with an abstract that outlines the goal of selecting the best network for a user based on various parameters. It then provides background on heterogeneous networks and the need for vertical handoff algorithms. The document categorizes different types of vertical handoffs and discusses key parameters considered in decision algorithms like bandwidth, speed, signal strength, power consumption and cost. Finally, it examines example algorithms like SAW, TOPSIS, GRA and MEW that make network selection decisions based on weighting and ranking these parameters.
This document summarizes research on parameters for vertical handoff in heterogeneous wireless networks. It discusses several key parameters that influence vertical handoff decisions, including available bandwidth, received signal strength, cost, latency, and quality of service. The document reviews several existing approaches for vertical handoff that consider parameters like bandwidth, RSS, access fee, packet delay, available bandwidth, and network load. Overall, the document analyzes parameters that are important for designing efficient vertical handoff mechanisms in next-generation heterogeneous wireless networks.
Spectrum Sensing with VSS-NLMS Process in Femto/Macrocell EnvironmentsIJECEIAES
Handover is a process that allows a mobile node to change its attachment point. A mobile node connected to a network can, in order to improve the quality of service, have the need to leave it to connect to a cell either of the same network or of a new network. The present paper introduce three techniques using adaptive Variable Step-Size Least Mean Square (VSSLMS) filter combined with spectrum sensing probability method to detect the triggering of handover in heterogeneous LTE networks. These techniques are Normalized LMS (NLMS), Kwong-NLMS and Li-NLMS. The simulation environment is composed of two femtocells belonging to a macrocell. Five User Equipements (UEs) are positioned in one femtocell and are assumed closest to its circumference. Simulation results show that sensing probability with Li-NLMS algorithm has a better performance compared with classical NLMS and Kwong-NLMS
An Enhanced Algorithm for Load-based Handover Decision-making in 5G Wireless ...IRJET Journal
This paper proposes an enhanced algorithm for load-based handover decision making in 5G wireless networks. The current handover decision making process does not consider the load of potential target cells, which can lead to handover failures if a user is handed over to an overloaded cell. The proposed algorithm uses fuzzy logic to determine if a candidate cell is suitable for handover based on its current load. Simulation results show the new algorithm improves network load balancing and reduces handover failures compared to existing methods.
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This document presents a study analyzing the traffic overflow performance of a three-layered wireless mobile network with microcells, macrocells and satellite cells handling voice-only traffic. The three-layered hierarchical network structure is described, with microcells overlaid by macrocells and macrocells overlaid by satellite cells. An existing call admission control scheme is evaluated that prioritizes voice calls, including handling call blocking probabilities, channel utilization, and call dropping probabilities across the different cell layers under varying traffic parameters. Analytical models are developed and numerical calculations are performed to analyze the performance of the call admission control scheme in the three-layered network handling overflowed voice traffic.
Performance and handoff evaluation of heterogeneous wireless networks 2IAEME Publication
This document discusses performance evaluations of heterogeneous wireless networks (HWNs) using the OPNET simulator. It implemented WLAN, WiMAX, and UMTS networks with applications like FTP, video conferencing, and VoIP. Handoff management between the networks was also evaluated. Simulation results showed WiMAX throughput was over 30% higher than WLAN and UMTS. Vertical handoff between WLAN-WiMAX and WLAN-UMTS was difficult without carefully engineering the WLAN network due to differences between the networks. Key metrics like delay, throughput, and received traffic were analyzed and WiMAX generally had superior performance.
Handover is the process of switching among the
available services without any interruption. Vertical handover is
a technique of switching from one type of a network to another
type of network (e.g., from WiFi to WiMAX). Seamless handover
between different access technologies is a great challenge as it
needs to obey different performance of QoS and security
constraints. Service users are becoming more demanding
regarding roaming capabilities across different networking
technologies such as WiFi, WiMAX, and CDMA as they claim
service continuity with QoS requirement and good security
features. Vertical Handover Decision (VHD) algorithms need to
be designed to provide the required Quality of Service (QoS) to a
wide range of applications while allowing seamless roaming
among a number of access network technologies. This paper is
about the implementation of the VHD algorithms designed to
satisfy these requirements. A combination of 3 parameters i.e.
Data Rate, SINR and RSS are evaluated to take decision of the
best network among available.
QOS ROUTING AND PERFORMANCE EVALUATION FOR MOBILE AD HOC NETWORKS USING OLSR ...ijasuc
Mobile Ad-Hoc network is a collection of mobile nodes in communication without using infrastructure.
As the real-time applications used in today’s wireless network grow, we need some schemes to provide
more suitable service for them. We know that most of actual schemes do not perform well on traffic which
is not strictly CBR. Therefore, in this paper we have studied the impact, respectively, of mobility models
and the density of nodes on the performances (End-to-End Delay, Throughput and Packet Delivery ratio)
of routing protocol (Optimized Link State Routing) OLSR by using in the first a real-time VBR (MPEG-4)
and secondly the Constant Bit Rate (CBR) traffic. Finally we compare the performance on both cases.
Experimentally, we considered the three mobility models as follows Random Waypoint, Random
Direction and Mobgen Steady State. The experimental results illustrate that the behavior of OLSR change
according to the model and the used traffics.
This document provides a tutorial on self-optimization of the random access procedure in 3G Long Term Evolution (LTE) networks. It describes the key components and steps of the random access procedure, including random access preambles, formats, opportunities, and the contention-based procedure. It also addresses relevant performance metrics like access probability, detection miss probability, and contention probability. The paper discusses modeling radio network simulations and collecting performance data to enable self-optimization of random access parameters to meet specified requirements. The goal is to present relevant self-optimization problems rather than complete solutions.
The document discusses wireless network technologies and vertical handoffs. It introduces the motivation for intelligent vertical handoff techniques using artificial intelligence. Key points include:
1) Heterogeneous wireless networks integrate different technologies like WiFi, WiMAX and UMTS to provide seamless mobility but handoff decision making is challenging due to many parameters.
2) The document proposes using fuzzy logic for intelligent handoff necessity estimation and target network selection to maximize user satisfaction based on multiple criteria.
3) IEEE 802.16 standards including 802.16m, 802.16e, and 802.16j are discussed which focus on data rates up to 100Mbps for mobile and 1Gbps for fixed
A vertical handover decision approaches in next generation wireless networks ...ijmnct
In next generation wireless network the most desirable feature is its ability to move seamlessly over various
access network regardless of the network infrastructure is used. The handover between these dissimilar
networks can be explored by using vertical handover algorithms. This paper focuses on the vertical
handover decision methods and algorithms effectiveness. Most of the algorithms which are based on RSS
values provide vertical handover with small delay at a lower rate of throughput. There are such algorithms
which provide significant improvements in throughput but at a cost of higher delays. As per the need for the
real time applications in next generation wireless networks there is a requirement of developing new
optimized algorithms that are able to produce high throughput and minimizing signalling cost and delay.
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PERFORMANCE EVALUATION OF VERTICAL HARD HANDOVERS IN CELLULAR MOBILE SYSTEMS
1. International Journal of Next-Generation Networks (IJNGN) Vol.10, No.1/2, June 2018
DOI : 10.5121/ijngn.2018.10201 1
PERFORMANCE EVALUATION OF VERTICAL HARD
HANDOVERS IN CELLULAR MOBILE SYSTEMS
Sahar Bashir Abass, Samah Fageer Ahmed, Shimaa Hyder Makki and Niemah
Izzeldin Osman
Department of Computer Systems and Networks, College of Computer Science and
Information Technology, Sudan University of Science and Technology,
Khartoum, Sudan
ABSTRACT
With the rapid increase of new and diverse cellular mobile services, the overlapping of cells has become
typical in the majority of the coverage area of the network. Vertical handovers occur between two layers of
cells when a user is switched from one layer to the other. In this paper we investigate the influence of
network parameters on vertical hard handover performance in a cell environment. The work considers two
layers of cells: a layer of macrocells and a layer of microcells. Handover requests enter the macrocell from
neighbor macrocells and from microcells that belong to a different layer. Using Markov chain analysis and
simulation we calculate network performance parameters such as mean queue delay, handover dropping
probability and channel utilization. We also compare the handover performance for the macrocell and
macrocell traffic separately. Our results show the influence of total channels, maximum queue size and
handover request arrival rate on handover performance. They also show that when the traffic from each
layer is treated with equal priority in the system, the performance of each layer is comparable.
KEYWORDS
Handover Queue Delay, Markov Chain, Performance Evaluation, Vertical Handover
1. INTRODUCTION
The goal of Fourth Generation Systems (4G) is to provide high quality services to the increasing
number of users at a reduced cost [1]. Cell overlapping was introduced in mobile cellular systems
since 2G systems and is used for many reasons. Using a base station that covers a large area of
land is considered an optimum solution for high mobility communication, as is reduces the
number of required handovers to maintain communication. In addition, segregating high mobility
and low mobility traffic reduces network overhead in terms of channel allocation and handover
management. Moreover, the intersection of different mobile generations provides coverage for
more recent system (4G and beyond) users where these services are not available yet, ensuring
continuous communication.
In a system where macrocells and micro cells overlap, each layer serves users according to some
parameter (mobile speed, requested service or channel availability). Handovers occur between the
two layers in what is known as vertical handovers. The problem with vertical handovers is not
having sufficient resource for users. In some cases, the traffic entering a cell from a different
layer might consume all the resources, with the expense of Quality of Service (QoS) for users
entering the cell from the same layer.
A number of studies have considered vertical handovers in cellular systems. A few works on
handovers in femtocell overlaid macrocell have been described in [2]. The considered handover
objectives include throughput, energy efficiency, and reduction in unnecessary handovers,
2. International Journal of Next-Generation Networks (IJNGN) Vol.10, No.1/2, June 2018
2
network load balancing, interference management and network security. The work compares
existing handover techniques against the stated objectives. A speed based handover algorithm for
macro-femto scenario is proposed in [3]. This study focused on different types of handovers and
compared the performance of different handover decision algorithms using simulation. The study
showed the mathematical complexity of the most famous approaches for handover techniques and
compared them to simulation result.
The survey in [4] discussed various existing handover decision algorithms for the integrated
macrocell-femtocell network. A number of handover management algorithms are studied and
advantages, disadvantages of proposed algorithms are discussed. The study in [5] simulates
femtocell scenarios with features and models compliant with 3GPP specifications using LTE-sim
framework. Results show that the increase in the number of femtocells in the system decreases
overall performance.
A study, explained in [6] analyzed the performance of handover strategies in femtocell networks
under hybrid access mode with the aim of minimizing unnecessary handovers. The evaluation is
based on the specific stay time interval ‘T’ and user equipment velocity. The simulation results
showed that the proposed algorithm minimized unnecessary handovers decreasing handover
probability compared to the traditional strategy.
All of the previous studies consider femtocells, which are indoor miniature cells that serve
stationary mobiles. Therefore the mobile speed or the requested service does not play an
influential parameter in the handover decision. The main reason for a handover to occur is the
mobile exiting the coverage area of the femtocell.
In this paper, we evaluate the performance of hard handover requests that experience a vertical
handover between two cellular layers. We consider a two-layer cell environment having a layer of
macrocells overlapping a layer of microcells. The handover from a macrocell to a microcell
happens due to the change in the speed of the mobile, the limitation of requested resource or the
absence of service in the cell. In our work in [7] we show preliminary results for the simulation.
Here we consider a more generic model, where overlapping of different cell sizes can be
evaluated and therefore exemplifying different mobile generations (2G, 2.5G, 4G, etc). We
consider hard handover where each user is connected to at most one base station at all times.
Therefore the work does not consider 3G CDMA-based systems that employ soft handover,
which requires further investigation. We develop a Markov model and derive analytical equations
for different performance parameters. The paper explores the influence of multi-layer traffic on
network performance. We compare and validate results from both methods. We consider a more
generic model, where hard handover between two overlapped cells is investigated.
The remainder of this paper is organized as follows: Section 2 describes handovers in mobile
systems. Section 3 explains the design of the simulation, the input and output parameters and
considered system scenarios. Section 4 describes the Markov chain analytical model. In Section 5
we demonstrate by results the vertical handover performance evaluation. Section 6 is a
conclusion.
2. HORIZONTAL AND VERTICAL HANDOVERS
In cellular mobile telecommunications, the term handover (or handoff) refers to the process of
transferring an ongoing call or data session from one channel connected to the core network to
another channel [8]. Handovers occur in general when the signal strength between the mobile and
the serving Base Station (BS) falls below a certain level due to the mobile distance from the base
station or the level of interference. Handovers are classified with respect to systems, frequencies,
connections and other criteria. There are two types of handover in general: horizontal handover
and vertical handovers.
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2.1 HORIZONTAL HANDOVER
These include all handovers happening between a pair of adjacent cells which may or may not
belong to the same system or have the same properties. There are two types of handovers with
respect to the number of connections associated with the mobile during the handover process [9]:
2.1.1 HARD HANDOVER
In hard handover the channel in the source cell is released and only then the channel in the target
cell is engaged. Thus the connection to the source is broken before the connection to the target is
made. For this reason such handovers are also known as “break-before-make”.
2.1.2 SOFT HANDOVER
In soft handover the channel in the source cell is retained and used for a while in parallel with the
channel in the target cell. In this case the connection to the target is established before the
connection to the source is broken, hence this handover is called “make-before-break”. Soft
handovers may involve using connections to more than two cells.
2.1.3 SOFTER HANDOVER
When the soft handover is performed both in the downlink (forward link) and the uplink (reverse
link), the handover is called softer. Softer handovers are possible when the cells involved in the
handover have a single cell site. In 4G systems the type of handover is hard handover [8], and
therefore it is the handover type considered in this work.
2.2 VERTICAL HANDOVER (VHO)
Vertical handover is a network node that automatically changes its connection type to access a
supporting infrastructure. When a computing device could connect to the Internet via two
different network technologies, it is automatically connected to the available network. This
switching from one network to the other is called vertical handover. Vertical handover enable the
phone to select the higher bandwidth at lower costs for networks like wide local area networks. It
also provides extended coverage for cellular networks [10]. However, a vertical handover suffers
from drawbacks. First, it handles all connections in the same manner. In other words, when all
connections are transferred from one interface to another, only one wireless interface (the best
one) is used at that moment. In addition, an incorrect handover decision may degrade the QoS or
break off the current call.
There are a number of possible handovers in a mobile network, both horizontal and vertical,
shown in Figure.1
1. Handovers moving out of the current macrocell into a neighbor macrocell.
2. Handovers moving from a neighbor macrocell into the current macrocell.
3. Handovers from a microcell into the macrocell.
4. Handovers from the macrocell into a microcell.
5. Handovers moving out of the current microcell into a neighbor microcell.
6. Handovers moving from a neighbor microcell into the current microcell.
In this paper, we consider the handovers labelled 2 and 3 in Figure 1, since they are incoming
traffic handled by the resources of the cell of interest (labelled macrocell in Figure 1). As for
other handover types, they are handled by resources from other cells.
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Figure.1: Horizontal and vertical handovers in a mobile cellular system
3. SIMULATION ENVIRONMENT
Following we explain in details the simulation modeling strategy used in the evaluation including
the simulation environment, inputs and outputs.
3.1 SIMULATION MODELING
In this paper, we use a discrete event driven simulation to evaluate the vertical handover system
[11]. The model of the system evolves over time by an ‘arrive’ or ‘depart’ event and the state
variables change instantaneously at separated points in time.
The basic entities in the queuing network model are channels, which represent servers, and
handover requests, which represent customers. We use a M/M/c/c+N queue where M describes
the Poisson arrival and service process, c are the total cannels and N is the size of the handover
queue. The queue is employed to hold handover requests when no channels are available to
handle the requests immediately (from the c total channels). ‘Arrive’ and ‘depart’ events are
randomly generated and the arrival and service rates follow an exponential distribution. The c
channels serve calls from the front of the queue. If there are less than c active calls in the cell,
some of the cannels will be idle. If there are more than c calls, additional requests are placed in
the queue. The queue is of size N, so all requests that exceed the system capacity (c+N) are
dropped.
3.2 SIMULATION INPUT PARAMETERS
The inputs of the model are:
3.2.1 REQUEST ARRIVAL RATE
A call request in the system is a handover call moving from a neighbor cell into the current
macrocell. This call can be entering from a macrocell in the same layer with an arrival rate ⅄a, or
from a microcell in a different layer with an arrival rate ⅄i.
3.2.2 TOTAL CHANNELS
A server here is a channel, which is the resource provided by the cell for the mobile user to send
and receive signals for a service (a call for example). There is a total of c available channels in the
cell which are fairly granted to macrocell and microcell users.
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3.2.3 SERVICE RATE
The service rate of a customer at the server μ is the number of served customers per unit time.
The average service time 1/µ, is the average call duration, which is the average amount of time a
caller holds a channel.
3.2.4 QUEUE LENGTH
The queue length N is the maximum number of callers the queue can accommodate.
3.3 SIMULATION OUTPUTS
The outputs of the model are:
3.3.1 CHANNEL UTILIZATION
The utilization of a channel is the proportion of time the cannel is busy, or, equivalently, the
average number of customers in service there.
3.3.2 THROUGHPUT
The throughput is the average number of served customers per unit time.
3.3.3 MEAN QUEUE DELAY
This is the average time a call request waits in the queue.
3.3.4 DROPPING PROBABILITY
This is the probability that the call is dropped due to the system reaching its full capacity. (The
system capacity is calculated from the queue size N plus the total channels c).
3.4 SYSTEM SCENARIOS
The system considers two layers of overlapped cells:
1. A layer of macrocells that provides service to mobile users who are moving at a high speed.
2. A layer of microcells that accommodates slow moving and stationary mobile users.
The system considers two types of customers:
1. Handover requests from neighboring macrocells.
2. Handover requests from microcells in a different layer.
There are three possible scenarios in the system:
1. a user request is immediately served
If there is an available channel, the caller is immediately provided with the channel for
continuous communication.
2. a user request is held in the queue
If all channels are busy, the user request is delayed and placed in the queue until there is an
available channel.
3. a user request is dropped
If all channels are busy and the handover queue is full the user request is dropped.
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3.5 SIMULATION FLOWCHART
The flow of events in the simulation is shown in the flowchart in Figure. 2. The simulation starts
by initializing the parameters and enter them into the simulation. The next step is accepting a
handover requests. The queue is checked weather it is full or not. If the queue is full, then the
request will be dropped. In case the queue is empty or not full, the simulation checks if there is an
available channel in the cell. If no channel is available, the request will be placed in the queue
until a channel is available. Otherwise, the request will immediately be granted a channel. In all
cases, statistics are calculated to evaluate the performance of the current request as well as the
system in whole, and system state variables are updated. After that, the simulation checks if the
end of simulation is reached. If not, it accepts a new request, otherwise, the simulation terminates.
Start
Initialize & Input
Accept Request
Queue Full ?
Drop Request
Channel
Available ?
Serve Request
Put request in
queue until
channel is
available
Calculate
Request
Statistics
Max No. of
Request ?
Calculate evaluation results
End
Yes
No
No
Yes
Yes
No
Figure.2 Simulation flowchart
4. MARKOV CHAIN ANALYTICAL MODEL
A Markov chain is a state representation of a system. Each state indicates the number of users in
the system. A transition is the rate to move from one state to the next. Figure. 3 below shows the
Markov chain of the vertical handover cellular system.
An ‘arrive’ process increases the number of handover requests in the system, and it is equally
likely to be caused by a request from a macro cell or a microcell. The number of occupied
channels is the cell is the number of active callers until all channels c are occupied. Additional
requests result in increasing the number of users in the system, while the total service rate does
not exceed the maximum cμ. The final state indicates that the maximum capacity of the system is
c+N.
Figure.3 Markov chain
λa + λi λa + λi
μ 2μ
0 1 2
λa + λi λa + λi
cμ cμ
c-1 c c+1
… …
λa + λi λa + λi
cμ cμ
N+c-2 N+c-1 N+c
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The Markov chain in Figure.3 is solved and a mathematical model is derived for different
performance evaluation parameters. Here we show the equations for P(0), P(n) and the Dq which
are the probability of no requests in the system, the probability of having n customers in the
system and the queue delay, respectively. For the remaining parameters we refer the reader to.
Equations (1) – (3) are used to evaluate the system performance using different input values.
5. VERTICAL HANDOVER PERFORMANCE EVALUATION
In this section, we show input values for the model and simulation, and present the outcomes of
the performance evaluation.
5.1 INPUT VALUES
The input values of both the model and simulation parameters are set as listed in Table 1. These
values are used in the Markov model to calculate the values of parameters derived by the model.
The simulation uses these values as initial values to run the simulation. Different runs of the
simulation use different input values for analysis and comparison. For example, Figure 4. uses a
range of values for the number of channels (5 – 40). Also, Figure 5. uses a range of values for the
queue size (1 – 100). All results demonstrated in figures are found by the simulation unless stated.
It is worth mentioning that a Markov model generally states that when the arrival rate is increased
such that it exceeds the service rate, the QoS of the system deteriorates. Nevertheless, the exact
influance on QoS depends on factors such as the number of channels, the queue size and the
average holding time (average call duration). The results that we present here attempt to show
expected QoS for different inputs and the influance of each parameter on QoS.
Table 1 Input Values
Parameter Input
value
Macrocell arrival rate 10 Call/sec
Microcell arrival rate 20 Call/sec
Service rate 15 Call/sec
Total number of channels 15
Queue size 50
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5.2 MEAN QUEUE DELAY MEASUREMENTS
Figure.4 Mean queue delay having different number of channels obtained from the simulation and math
model
Figure.5 Mean queue delay (s) having different queue sizes obtained from the math model
5 10 15 20 25 30 40
Delay
(ms)
Number of Channels
Simulation
Math Model
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Figure.6 Mean queue delay having different arrival rates obtained by the math model
We evaluate the mean queue delay with respect to three parameters: number of channels, queue
size and arrival rate.
5.2.1 MEAN DELAY HAVING DIFFERENT NUMBER OF CHANNELS:
When the number of channels increases, more requests are served immediately reducing the
delay, as shown in Figure.4. The results also compare the simulation and the analytical model. As
Figure. 4 shows, the results are comparable, which proves the validity of the two approaches.
5.2.2 MEAN DELAY HAVING DIFFERENT QUEUE SIZE:
A longer queue implies storing more requests in the queue increasing the number of requests
awaiting service. This results in increasing the average queue delay, as can be seen in Figure. 5.
5.2.3 MEAN DELAY HAVING DIFFERENT ARRIVAL RATES:
The average queue delay increases with increasing the request arrival rate as more requests result
in a longer queue. This continues until the queue is full, where any additional arrivals are dropped
resulting in the saturation of the value of delay. Figure.6 shows the queue delay considering
different arrival rates. It also shows the delay for queue sizes 10, 20 and 40. As can be seen in
Figure. 6, the delay for longer queues saturates at a higher value for the delay, consistent with
findings shown in Figure. 5.
5.3 DROPPING PROBABILITY MEASUREMENTS
Figure.7 Dropping probability having different number of channels when increasing the traffic
(request/second)
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Figure.8 Dropping probability having different queue sizes when increasing the traffic (request/second)
The dropping probability is calculated using Equation (2) where n is substituted with the system
maximum capacity, as a handover request is dropped when the queue is full. Similar to the queue
delay, the dropping probability is evaluated with respect to three parameters: the number of
channels, the queue size and arrival rate.
5.3.1 DROPPING PROBABILITY HAVING DIFFERENT NUMBER OF CHANNELS:
When increasing the number of channels, more requests are served, reducing the number of
rejected calls due to unavailable resources. The dropping probability decreases by increasing the
number of channels as shows in Figure. 7.
5.3.2 DROPPING PROBABILITY HAVING DIFFERENT QUEUE SIZES:
The dropping probability is reduced by increasing the queue size, because the queue can handle a
larger number of arrivals as can be seen in Figure. 8.
5.3.3 DROPPING PROBABILITY HAVING DIFFERENT ARRIVAL RATES:
The Dropping probability increases with increasing the arrival rate. The queue reaches its
maximum capacity faster and the remaining requests are dropped. Both Figure. 7 and Figure .8
show this increase.
5.4 MACROCELL-MICROCELL EVALUATION
To evaluate the influence of different-layer traffic on same-layer traffic, we consider three cases:
1. Case one: where macrocell and microcell traffic are the same.
2. Case two: macrocell arrival rate is 20 requests/second and microcell arrival rate is 10
requests/second.
3. Case three: macrocell and microcell request arrival rates are 10 and 20 requests/second,
respectively.
For these cases, we evaluate the mean queue delay, the dropping probability and channel
utilization. Channel utilization is found by calculating the fraction of time system channels are
busy over total simulation time.
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5.4.1 MACROCELL AND MICROCELL TRAFFIC IS SIMILAR
Figure.9 Macrocell-Microcell mean queue delay
Figure.10 Macrocell-Microcell dropping probability
Figure.11 Macrocell-Microcell channel utilization
In this case, traffic from both layers is the same. Macrocell and microcell requests experience the
same delay as can be seen in Figure. 9. The dropping probability and channel utilization are also
the same for both layers as Figure. 10 and Figure.11 confirm, respectively.
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5.4.2 MACROCELL TRAFFIC IS DOUBLE THE MICROCELL TRAFFIC
Figure.12 Macrocell-Microcell mean queue delay
Figure.13 Macrocell-Microcell dropping probability
Figure.14 Macrocell-Microcell channel utilization
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Here, the traffic of the macrocell is double that of the microcell. Observing Figure.12, the mean
queue delay is similar for both layers as the queue treats requests from both layers equally.
However, as requests generated at the macrocell are more, the dropping rate is more. Figure. 13
indicates that the dropping rate for macrocell traffic is double, consistent with the difference in
traffic. Figure. 14 shows that the channel utilization is similar for both layers.
5.4.3 MACROCELL TRAFFIC IS HALF THE MICROCELL TRAFFIC
In this scenario, the traffic of the macrocell is half the microcell traffic. The difference in mean
queue delay is marginal as can be seen in Figure.15. The dropping rate follows the traffic ratio, as
dropping rate for the macrocell is half of that of the microcell. Figure.16 shows this result. Similar
to the previous case, the channel utilization is similar for both layers, as Figure.17 illustrates.
Figure.15 Macrocell-Microcell mean queue delay
Figure.16 Macrocell-Microcell dropping probability
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Figure.17 Macrocell-Microcell channel utilization
6. CONCLUSIONS
This paper has investigated the performance of hard handovers in cellular mobile systems. It has
evaluated a system consisting of a layer of macrocells overlapping a layer of microcells, where
vertical hard handovers occur between the two layers. The evaluation is carried out using a
simulation and a Markov model.
From the results it has been proven that when increasing the number of channels the mean queue
delay and handover dropping rate are decreased. Yet this increase is restricted to the limitations in
bandwidth. Increasing the queue size decreases the dropping rate at the expense of increasing the
mean queue delay. Therefore an optimum queue size should be selected that results in an
acceptable level of delay to maintain the guaranteed QoS and that is tolerated by the type of
service. Finally, by increasing the arrival rate, the mean delay and the dropping rate increase.
When traffic is expected to increase, resources should be provisioned to accommodate user
traffic. The influence of traffic entering a cell from a different layer depends on the ratio of traffic
between these layers. This statement is true when the two traffic types are treated with equal
priority in the cell. In our future work, we plan to investigate applying different priorities to calls
of each layer and draw results for different scenarios. We also plan to expand the work to cover
soft handovers where more than one channel is allocated to the user during the handover process.
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Authors
Sahar Bashir Abass received the B.Sc. degree in Computer Systems and Networks from Sudan University
of Science and Technology, Khartoum, Sudan, in 2016. She is currently a network engineer. Her current
research interests include modelling cloud-based storage networks and 4G networks.
Samah Fageer Ahmed received the B.Sc. degree in Computer Systems and Networks from Sudan
University of Science and Technology, Khartoum, Sudan, in 2016. Her current research interests include
modelling of inter system handovers and queuing networks.
Shimaa Hyder Makki received the B.Sc. degree in Computer Systems and Networks from Sudan
University of Science and Technology, Khartoum, Sudan, in 2016. Her current research interests include
wireless communication systems and network performance modelling.
Niemah Izzeldin Osman received the B.Sc. degree (first class honours) in Computer Science from Sudan
University of Science and Technology, Khartoum, Sudan, in 2002 and the M.Sc. degree (with distinction)
in Mobile Computing from the University of Bradford, U.K., in 2006 and the Ph.D. degree in
Communication Networks from the University of Leeds, U.K in 2015. She is currently an Assistant
Professor at the Department of Computer Systems and Networks, Sudan University of Science and
Technology, Sudan. Her current research interests include performance evaluation of 4G LTE networks,
Internet of Things and QoE of video services.