Performance Analysis of Algorithms with Multiple Attributes for Adaptive Call Admission Control in Heterogeneous Wireless Networks

Despite recent interests in developing vertical handoff decision algorithms, an essential component of the architecture of the next generation heterogeneous wireless networks, very few studies have so far reported any meaningful comparative performance analysis. This paper attempts to fill this gap in the literature by presenting a comprehensive study on the performance of three vertical handoff decision algorithms, namely, SAW (Simple Additive Weighting), TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), and MDP (Markov Decision Process). We have used both analytical and simulation tools (ns-2.29) to evaluate and compare expected total QoS offerings in the mean duration of a service under different state transition probability distributions, user perception models on the importance of QoS parameters, and network switching costs. To our surprise, we have observed TOPSIS achieving the best performance despite MDP’s using the optimal policy. We suspect that the user satisfiability model used in MDP to estimate link rewards might have contradicted the underlying user perception model used to estimate normalised weight of each QoS parameter, which will be investigated in future.

Next generation wireless networks will support a diverse set of access technologies. And the demanding breed of multimedia applications will even more considerably require Quality of Service (QoS) support. This paper proposes an optimal prority-based Call Admission Control (CAC) scheme in heterogeneous wireless networks, i.e., the generalized semi-Markov Decision Process based CAC (GCAC). Considering the limitations of the traditional Markov decision process for optimal CAC policy, we characterize the CAC problem through a GSMDP formulation that characterize s the network behaviors in the heterogeneous system more exactly. And the proposed scheme can guarantee the QoS constrains both in the physical and network layer. Numerical examples illustrate that the performance in the GCAC scheme is significantly better than that in the conventioinal GC scheme and an optimal CAC schme based on MDP.

PurposeThis paper aims to optimize the process parameters of the fused deposition modelling (FDM) process using the Grey-based Taguchi method and the results to be verified based on a technique for order preference by similarity to ideal solution (TOPSIS) and analytical hierarchy process (AHP) calculation.Design/methodology/approachThe optimization of process parameters is gaining a potential role to develop robust products. In this context, this paper presents the parametric optimization of the FDM process using Grey-based Taguchi, TOPSIS and AHP method. The effect of slice height (SH), part fill style (PFS) and build orientation (BO) are investigated with the response parameters machining time, surface roughness and hardness (HD). Multiple objective optimizations were performed with weights of w1 = 60%, w2 = 20% and w3 = 20%. The significance of the process parameters over response parameters is identified through analysis of variance (ANOVA). Comparisons are made in terms of rank order with respect to grey relation grade (GRG), relative closeness and AHP index values. Response table, percentage contributions of process parameters for both GRG and TOPSIS evaluation are done.FindingsThe optimum factor levels are identified using GRG via the Grey Taguchi method and TOPSIS via relative closeness values. The optimized factor levels are SH (0.013 in), PFS (solid) and BO (45°) using GRG and SH (0.013 in), PFS (sparse-low density) and BO (45°) using TOPSIS relative closeness value. SH has higher significance in both Grey relational analysis and TOPSIS which were analysed using ANOVA.Research limitations/implicationsIn this research, the multiple objective optimizations were done on an automotive component using GRG, TOPSIS and AHP which showed a 27% similarity in their ranking order among the experiments. In the future, other advanced optimization techniques will be applied to further improve the similarity in ranking order.Practical implicationsThe study presents the case of an automotive component, which illustrates practical relevance.Originality/valueIn several research studies, optimization was done on the standard test specimens but not on a real-time component. Here, the multiple objective optimizations were applied to a case automotive component using Grey-based Taguchi and verified with TOPSIS. Hence, an effort has been taken to find optimum process parameters on FDM, for achieving smooth, hardened automotive components with enhanced printing time. The component can be explored as a replacement for the existing product.

The wireless network environment in the future is going to include various heterogeneous wireless networks. In a heterogeneous wireless network environment, vertical handoff processes caused by the movement of users are inevitable. However, the research related to how to achieve seamless vertical handoff and improve QoS guarantees in today's heterogeneous wireless networks is still something to work on. Therefore, this paper proposed the Advanced Vertical Handoff Translation Center (Advanced VHTC) architecture for Wi-Fi/WiMAX heterogeneous wireless networks, aiming to improve the quality of services in heterogeneous wireless networks by means of packet formats translation between heterogeneous wireless networks and the MIH-based seamless vertical handoff mechanism, which cut down the time for vertical handoff and obtain high quality and persistent connection service. Lastly, with the brilliant results of a complete simulation, this paper will show the performance in terms of delay, jitter, packets loss and throughput to prove that the Advanced VHTC for next generation heterogeneous wireless networks can provide good QoS guarantees and obtain persistent transmission with high performance while performing seamless vertical handoff.

The Analytical Hierarchy Process (AHP) approach and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method are two methods that are commonly used to handle multicriteria problems. The AHP technique uses a matrix of pairwise comparisons and a hierarchical approach to criteria in order to obtain the final criteria weights. In contrast, the TOPSIS approach incorporates the concepts of proximity to the ideal solution and preference. Next, TOPSIS uses the previously established criterion weights to compute each option's relative closeness score to the ideal answer. In order to determine how effectively the AHP and TOPSIS methodologies complement one another, this study aims to assess the protocols and underlying assumptions of the two approaches. When decision makers are aware of the benefits and drawbacks of each approach, they may choose the best course of action from a mix of the two. The results of the study indicate that the process may be streamlined, subjectivity can be reduced, and criterion weights can be stabilized by combining the AHP and TOPSIS approaches.The Analytical Hierarchy Process (AHP) approach and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method are two methods that are commonly used to handle multicriteria problems. The AHP technique uses a matrix of pairwise comparisons and a hierarchical approach to criteria in order to obtain the final criteria weights. In contrast, the TOPSIS approach incorporates the concepts of proximity to the ideal solution and preference. Next, TOPSIS uses the previously established criterion weights to compute each option's relative closeness score to the ideal answer. In order to determine how effectively the AHP and TOPSIS methodologies complement one another, this study aims to assess the protocols and underlying assumptions of the two approaches. When decision makers are aware of the benefits and drawbacks of each approach, they may choose the best course of action from a mix of the two. The results of the study indicate that the process may be streamlined, subjectivity can be reduced, and criterion weights can be stabilized by combining the AHP and TOPSIS approaches.

TOPSIS-based dynamic approach for mobile network interface selection

The advancement of computing capabilities and increase of available network bandwidths have resulted in an emergency telemedicine services which can provide high quality medical services. However, existing telemedicine systems mainly have offered a one to one communication configuration instead of a multi-connection configuration. Therefore, we suggested a hybrid multimedia telemedicine system to support the multi-patients services in wired and wireless (heterogeneous) network environments. Methods: We designed the hybrid multimedia telemedicine system consisting of 4 sub-systems, a patient system, a doctor system, a emergency monitoring system, and a multi-control server system. The patient system could deliver multimedia data of a patient to the emergency monitoring system or to the doctor system according to link configuration. The link configuration was decided as 'Flowing', or 'By-passing' in accordance the connection type of patient systems or doctor systems. At this time, as the multi-control server system considers the hybrid network, it monitored the patient's multimedia data and the state of emergency telemedicine services. Results: The hybrid multimedia telemedicine system including the multi-control server system performed the best communication configuration over heterogeneous networks. This system achieved high quality emergency telemedicine services through dynamic wired and wireless networks at real-time. Conclusion: This study represented a hybrid multimedia telemedicine system over heterogeneous networks in emergency cases. We expected that the designed system could provide not only the high quality services, tele-diagnosis and tele-consultation, but also the effective emergency telemedicine services to multi-patients in the heterogeneous network environments.239

In mobile cloud computing, employing computation offloading enables mobile devices to considerably augment their capability in emerging resource-hungry applications. However, studies on realistic offloading handoff mechanisms are still lacking. In the current work, a cross-layer collaboration handoff mechanism based on improved multi-attribute decision (CCHMD) is proposed to make reasonable, effective and efficient handoff decisions by considering the frequent movement of intelligent terminals and the heterogeneity of wireless networks. Cross-layer collaboration refers to the cooperation between communication handoff and computation handoff. The former mainly depends on received signal strength of mobile terminals, the minimum equality parameter and the minimum improvement parameter of all network attributes. By contrast, the latter hinges on several important attributes of candidate networks. To objectively evaluate the performance of each candidate network, we first apply the improved normalization and information entropy method (EM) to automatically calculate the weight value of each attribute, and employ the improved multi-attribute decision algorithm to assess all candidate networks. We then arrange these networks in descending order and select the first network as the optimal handoff network. Experimental results have proved that CCHMD exhibits better adaptability and performance than EM, simple additive weight and technique for order preference by similarity to ideal solution in terms of several indicators such as task execution time, handoff frequency, energy consumption and task execution efficiency.

In a heterogeneous wireless network, where many different wireless networks interwork together, call admission control is an important issue to distribute user traffic among different access networks in order to provide quality of service (QoS). In this paper, we present and analyze the performance of a call admission control (CAC) policy for voice and data calls, which is based on one-hop cooperation among the mobile nodes, in a cellular-WLAN interworking scenario. For call-level queueing analysis of the CAC scheme, we use a more general phase-type distribution to model the characteristics of the system. Based on the analytical model, we illustrate the effect of one-hop cooperation on call-level QoS performance (e.g., call blocking probability, call dropping probability).

The evolution of cellular networks from one generation to another has led to the deployment of multiple radio access technologies (such as 2G/2.5G/3G/4G) in the same geographical area. This scenario is termed heterogeneous cellular networks. In heterogeneous cellular networks, radio resources can be jointly or independently managed. When radio resources are jointly managed, joint call admission control algorithms are needed for making radio access technology selection decisions. This chapter gives an overview of joint call admission control in heterogeneous cellular networks. It then presents a model of load-based joint call admission control algorithm. Four different scenarios of call admission control in heterogeneous cellular networks are analyzed and compared. Simulations results are given to show the effectiveness of call admission control in the different scenarios. The coexistence of different cellular networks in the same geographical area necessitates joint radio resource management (JRRM) for enhanced QoS provisioning and efficient radio resource utilization. The concept of JRRM arises in order to efficiently manage the common pool of radio resources that are available in each of the existing radio access technologies (RATs) (Perez-Romero et al, 2005). In heterogeneous cellular networks, the radio resource pool consists of resources that are available in a set of cells, typically under the control of a radio network controller or a base station controller. There are a number of motivations for heterogeneous wireless networks. These motivations are (1) limitation of a single radio access technology (RAT), (2) users’ demand for advanced services and complementary features of different RATs, and (3) evolution of wireless technology. Every RAT is limited in one or more of the following: data rate, coverage, security-level, type of services, and quality of service it can provide, etc. (Vidales et al, 2005). A motivation for heterogeneous cellular networks arises from the fact that no single RAT can provide ubiquitous coverage and continuous high QoS levels across multiple smart spaces, e.g. home, office, public smart spaces, etc. Moreover, increasing users’ demand for advanced services that consume a lot of network resources has made network researchers developed more and more spectrally efficient multiple access and modulation schemes to support these services. Consequently, wireless networks have evolved from one generation to another. However, due to huge investment in existing RATs, operators do not readily discard their existing RATs when they acquire new ones. This situation has led to coexistence of multiple RATs in the same geographical area.

Over the last couple of years, the recent pandemic rendered work operations to be mobile and relied heavily on real-time and traffic-intensive applications such as online classrooms and meetings. Since our working life requires seamless mobility and stable wireless connectivity, heterogeneous wireless networks gain more attention as key infrastructures to fulfill communication needs. Intelligent handover decision deems necessary to select the appropriate wireless network. An intelligent mechanism such as fuzzy logic proves to enhance such decision-making. Different membership functions used in a fuzzy inference system contribute to different network selection performances. This work evaluates different fuzzy membership functions, hence appropriate membership functions can be used in the design of fuzzy-based network selection mechanisms for heterogeneous wireless networks.

PurposeThis paper aims to focus on the application of multi-attribute decision-making methods (MADMs) to ascertain the optimal machining parameters while turning Ti-6Al-4V alloy under minimum quantity lubrication (MQL) conditions using Jatropha-curcas oil (JCO) bio-based lubricant.Design/methodology/approachThe experiments were designed and performed using Taguchi L27 design of experiments methodology. A total of 27 experiments were performed under MQL conditions using textured carbide cutting tools on which different MADMs like Analytic hierarchy process (AHP), Technique for order preference by similarity to ideal solution (TOPSIS) and Simple additive weighting (SAW) were implemented in an empirical manner to extract optimize machining parameters for turning of Ti-6Al-4V alloy under set of constrained conditions.FindingsThe results evaluated through MADMs exhibit the optimized set of machining parameters (cutting speedVc= 80 m/min, feed ratef = 0.05 mm/rev. and depth of cutap= 0.10 mm) for minimizing the average surface roughness (Ra), maximum flank wear (Vbmax), tangential cutting force (Fc) and cutting temperature (T). Further, analysis of variance (ANOVA) and traditional desirability function approach was applied and results of TOPSIS and SAW methods having optimal setting of parameters were compared as well as confirmation experiments were conducted to verify the results. A SEM analysis at lowest and highest cutting speeds was performed to investigate the tool wear patterns. At the highest speed, large cutting temperature generated, thereby resulted in chipping as well as notching and fracturing of the textured insert.Originality/valueThe research paper attempted in exploring the optimized machining parameters during turning of difficult-to-cut titanium alloy (Ti-6AL-4V) with textured carbide cutting tool under MQL environment through combined approach of MADMs techniques. Ti-6Al-4V alloy has been extensively used in important aerospace components like fuselage, hydraulic tubing, bulk head, wing spar, landing gear, as well as bio-medical applications.

The aim of this research was to apply MCTs, Analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS), to reduce the EsSense25 and MemVOC vocabularies and evaluate them with coffee consumers in remote and sensory laboratory contexts. In the first stage, coffee experts evaluated both vocabularies to generate reduced lists. In the second stage, the response time for complete and reduced lists was analyzed using a pilot group of consumers. Finally, in the third stage, the complete and reduced lists were applied to coffee consumers in remote and laboratory contexts using the check-all-that-apply (CATA) technique, and their correlation was evaluated through Multiple factor analysis (MFA). The results showed that with AHP, the EsSense25 and MemVOC lists were reduced to 10 emotions and 11 memories, while TOPSIS yielded 16 emotions and 15 memories. Significant differences were found in response times between contexts and lists. In the remote context, the evaluation of the complete list took 340 s, while the reduced lists by TOPSIS and AHP required 244 and 160 s, respectively. In the sensory laboratory, the response time for the complete list was 485.8 s, while the reduced lists required 236.3 s for TOPSIS and 131.4 s for AHP, respectively. The correlation between complete and reduced lists ranged from 0.63 to 0.76 in the remote context and from 0.81 to 0.87 in the sensory laboratory. It is concluded that MCTs are an efficient alternative to reduce extensive lists of emotions and memories based on expert opinions, facilitating rapid and effective evaluations with consumers.

The prime requirements of vertical handoff in the heterogeneous vehicular network are to ensure the quality of service requirements and to provide seamless connectivity to all mobile stations. In this research paper, Multiple Attribute Decision Making (MADM) classical methods are used like the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to make the handoff decisions process quickly and efficiently. Our method called ‘MADM-TOPSIS Scheme’ is the fusing of TOPSIS method with Fuzzy Logic Sets and Rules, in order to lessen the Blocking Probability. Performance results are thus compared with the classical fuzzy TOPSIS and with an approach of the base paper. Our work is able to determine properly that by reducing the blocking probability, the handoff probability will increase that will improve the network performance in the heterogeneous vehicular system. After differentiating to classical Fuzzy TOPSIS, our work scheme shows an upgrade of 0.10 and 20% with base paper.

Quality of experience (QoE) has been a user-centric performance metric for multimedia communications. Existing communication protocols over heterogeneous networks are mostly based on quality of service, which ignores the user satisfaction and subjective evaluation. In this paper, the authors propose a novel QoE-aware multimedia communication framework for heterogeneous wireless networks. Specifically, the authors make three main contributions in this paper: (i) a general QoE model has been established by jointly characterising the multimedia applications and heterogeneous networks, (ii) the issue of multimedia communications over heterogeneous networks has been transformed as a stochastic optimisation problem, and (iii) the optimal solution is provided by designing a QoE-aware multimedia scheduling scheme. Importantly, the proposed scheme is simply enough for online implementation. Numerical simulations have demonstrated the efficiency and robustness of the proposed scheme.