A fuzzy queue-aware routing approach for wireless mesh networks

The scope of this work is to present a holistic approach in quality of service (QoS) and quality of experience (QoE) characterization and prediction in modern mobile communication networks. Analytically, multi radio access technologies have been deployed in order to deliver mobile services to quality demanded consumers. Quality of Experience (QoE) parameters describe the End-to-End (E2E) quality as experienced by the mobile users. These parameters are difficult to be measured and quantified. System Quality of Service (SQoS) parameters are metrics that are closely related to the network status, and defined from the viewpoint of the service provider rather than the service user. Moreover, E2E Service Quality of Service (ESQoS) parameters describe the QoS of the services and they are obtained directly from the QoE parameters by mapping them into parameters more relevant to network operators, service providers and mobile users. A useful technique for mobile network planning and optimization is to build reliable quality estimation models for mobile voice and video telephony service.

In this paper, we propose a new approach for video quality control for multimedia networks. Our new approach is based on video quality measure that combines both the network quality of service (QoS) as well as the user quality of experience (QoE). The proposed approach improves the end-to-end traditional video quality control for multimedia network by including the human perception of video data, which is major concern for the video client, along with the network quality of service (QoS) measurements. We will show that the proposed QoS-QoE based video quality control algorithm can reflect both the condition of the network environment and the human perception of the received networked video data stream. According to both QoS and QoE parameters, rather than using only QoS parameter, video quality control action will satisfy the user needs more than relying only on the network conditions. Since our proposed QoE parameter Self-Reference Complex Wavelet Video Structural Similarity Index (SRCW-VSSIM) can be obtained with no reference (NF) video data, it satisfies the requirement of real-time video transmission.

Recently, the evaluation on quality of the air interface in a wireless network has shifted from emphasis on QoS (quality of service) only to incorporation of QoE (quality of experience). However, it seems that QoE metrics have not been related to the surroundings of the served users so far, which may have a great influence on users' expected QoE. For instance, with a high level of QoS, a user's expectation of QoE could still be terrible because of the serious interference from the surroundings such as noise, ambient light or shaking of terminals due to mobility. From another perspective, it means that in such a case a high level of QoS may be helpless to enhance users' QoE and the requirement could be relaxed accordingly. In this paper, an approach called surrounding-adaptive QoE adjustment (SAQA) is proposed to optimize the capacity and the quality of air interface with voice service as an example. The basic idea of the approach is that user equipment (UE) detects the surroundings interference which may impact users' QoE and then adjusts QoS according to the detected results: a lower level of QoS is chosen in a bad environment to enhance the capacity, while a higher level of QoS is selected to guarantee the users' QoE in a better circumstance. Simulation results show that this method can remarkably enhance the voice capacity of the communication systems as well as guarantee users' QoE.

WMN (wireless mesh network) is a useful wireless multihop network with tremendous research value. The routing strategy decides the performance of network and the quality of transmission. A good routing algorithm will use the whole bandwidth of network and assure the quality of service of traffic. Since the routing metric ETX (expected transmission count) does not assure good quality of wireless links, to improve the routing performance, an opportunistic routing mechanism combined with long-term and short-term metrics for WMN based on OLSR (optimized link state routing) and ETX is proposed in this paper. This mechanism always chooses the highest throughput links to improve the performance of routing over WMN and then reduces the energy consumption of mesh routers. The simulations and analyses show that the opportunistic routing mechanism is better than the mechanism with the metric of ETX.

Background and Objective: Random Black Hole (BH) attack significantly degrades MANET’s performance. For strategic applications, the performance parameters like Packet Delivery Ratio, Routing Overheads, etc. are important. The objectives are: (a) To model random BH attack, (b) To propose a routing strategy for the protocol to mitigate random BH attack, (c) To evaluate and compare the network performance of modified protocol with the standard protocol. Methods: The random BH attack is modelled probabilistically. The analysis is carried out by varying Black Hole Attack (BHA) time as Early, Median, Late occurrences and mix of these three categories. The blocking performance is also analysed by varying the percentages of malicious presence in the network. Normal Optimized Link State Routing (OLSR) protocol is used to simulate the MANET performance using a typical medium size network. The protocol has then been modified using Trust- Confidence aware routing strategy, named as TCAOLSR, with a view to combat the degradations due to the random BH attack. Results: The random behavior of Black Hole attack is analyzed with all the possible random parameters, like deployment of mobile nodes, number of malicious nodes and timing instances at which these nodes change their state. From the results of individual type- Early, Median and Late, it is observed that the TCAOLSR protocol gives stable performance for Packet Delivery Ratio (PDR) and Routing Overheads (RO), whereas for OLSR protocol PDR gradually reduces and RO increases. For individual and mix type, Average Energy Consumption (AEC) per node increases marginally for TCAOLSR protocol. For the mix type, PDR for TCAOLSR is 40-60% better whereas RO for TCAOLSR is very less compared to OLSR protocol. The efficacy of the TCAOLSR protocol remains stable for different categories of BH attack with various percentages of malicious nodes compared to OLSR with the same environment. Conclusion: Simulations reveal that the modified protocol TCAOLSR, effectively mitigates the network degradation for Packet Delivery Ratio and Routing Overheads considerably, at the cost of a slight increase in Average Energy Consumption per node of the network. Efficacy of the OLSR and TCAOLSR protocols has also been defined and compared to prove robustness of the TCAOLSR protocol.

In a near future, wireless mesh networks (WMNs) and multimedia content will be abundant technologies/applications in the Internet. Hence, in order to keep and attract new customers, as well as, reduce operational costs, the development of new quality level control schemes are needed and it is one of the key requirements for the success of next generation wireless multimedia systems. With this goal in mind, this paper presents a new routing metric with focused on estimation error on wireless links, named ETXMULT (Expected Transmission Count for Multimedia Content), to assure high-quality paths on multi-hop wireless networks for multimedia traffic. Simulations were carried out, by using Network Simulator 2 (NS-2), to demonstrate the behavior and benefits of the proposed metric with Optimized Link State Routing (OLSR) routing protocol. The results presented improvements in the distribution of multimedia content compared to the original Expected Transmission Count (ETX) metric, by analyzing well-know QoS and QoE metrics.

The relationship between the user perceived Quality of Experience (QoE) with Internet applications and the Quality of Service (QoS) of the underlying network and applications is complex. Unveiling statistical relations between QoE and QoS can boost the prediction and diagnosis of QoE. In this paper, we shed light on the relationship between QoE and QoS for a popular application: YouTube video streaming. We conducted a controlled study where we asked users to rate their perceived quality of YouTube videos under different network conditions. During this experiments, we also captured network QoS and application QoS. We then analyze the resulting dataset with SES, a feature selection algorithm that identifies multiple, minimal-size, statistically-equivalent signatures with maximal predictive power for a target variable (e.g., QoE). We found that we can build optimal QoE predictors using a minimal signature of only three features from application or network QoS metrics compared to four when we consider features from both layers.

The quality perceived by the user, a concept known as Quality of user Experience (QoE), is gaining momentum. Together with the efforts of providing appropriate architectures able to deliver the expected level of Quality of Service (QoS), users' perception of the level of quality could play a key role in making a VoIP multimedia application to succeed or to fail. QoE can be measured from different approaches; subjective ones are based on polls while objective ones are mainly based on QoS network performance parameters. Although a subjective evaluation could be costly and time consuming, it gives the most accurate results. Moreover, wireless environments incorporate new challenges in terms of QoS and QoE because of inherent wireless communication characteristics. In this way, our contribution is twofold. First, we carry out a subjective QoE assessment for VoIP applications in a real wireless environment. Skype, Gizmo5, ooVoo, and Damaka are the selected VoIP applications under study. Next, we contrast QoE results with QoS evaluation from the captured video calls made during the poll. Results show that there is no precise match on both assessments, because of QoE parameters that cannot be inferred from QoS analysis, because of the different effect of some QoS parameters which prevail, or even because of the popularity of the VoIP application.

The rapid development and spread of communication technologies is now becoming a global information revolution. Customers have a need for communication services, which could be flexibly configured in accordance with their Quality of Experience (QoE) requirements. Realizing the close connection between customer experience and profitability, the service provider has been placing more and more attention on customer experience and QoE. The traditional quality of service management method based on SLA (Service Level Agreement) is not sufficient as a means to provide QoE-related contracts between service providers and customers. The current SLA method is mostly limited and focused on technical aspects of QoS (Quality of Service). Furthermore, they do not follow on the network the principles and semantic approach to the QoS specification for a communication service using QoE parameters. In this paper, we propose a customer-oriented quality of service management method for future IBN (Intent-Based Networking). It is based on a new QoE metric on a scale from 1 to 5, which allows one to take into account the commercial value of e-services for customers. Based on this approach, the network configuration and functionality of network equipment automatically changes depending on customer requirements. To implement the new method of service quality management, an algorithm for routing data packets in the network was developed, taking into account the current load of the forecast path. The algorithm of billing system functioning in conditions of customer-oriented quality management in telecommunication networks has been created. To investigate the effectiveness of the proposed method of service quality management with the traditional SLA method, we developed a simulation network model with the implementation of two approaches. By conducting a simulation, it was determined that the proposed method gives an average gain of 2–5 times for the criterion of the number of customers who require high quality of experience of the service.

As the demand for mobile services grows exponentially, the focus on wireless network optimization has been changed from Quality of Service (QoS) for the network to Quality of Experience (QoE) for users. The network optimization research about QoS in the past cannot surely meet the requirements of the users' QoE. Therefore, in this paper, a handover solution is proposed to improve the QoE while considering the QoE balance for a LTE network that provides different services. Compared with other optimization of QoE nowadays, the proposed solution balances and improves the QoE of users. The proposed solution controls handover parameter by running a handover optimization algorithm based on the dynamic particle swarm optimization (DPSO) in a central controller, which finally optimizes the overall QoE and reduces the proportion of users with extremely poor QoE. The simulation results show that the DPSO algorithm ensures the quality of the solution and increases the speed of convergence by nearly twice that of the standard particle swarm optimization algorithm (SPSO). After adopting the DPSO handover solution, the overall QoE of users is increased by 6.22 % and 4.59 % while the variance of users' QoE is decreased by 14.2 % and 22.6 %, compared with the full handover solution and the traditional handover solution respectively. The number of users with QoE less than 1.9 is reduced to 0 with the proposed solution.

With the coming of the 5G network era, Quality of Experience (QoE), which is used to describe experience quality of customers in the Direct Connect (DC) network, is critical to operators and hence has been widely studied. The existing evaluation method for QoE is unable to dynamically adjust QoE parameters so there will be deviations to reflect the real experience of customers when complaint events occur. In this paper, a novel progressive QoE evaluation model for network products is formulated. Subsequently, considering the customer complaints occurrences which represent that the real customer experience and previously calculated QoE may mismatch, the rules based on application types to judge whether QoE parameters needs to be adjusted are made. Then, a dynamic adjustment model of QoE parameters is further developed to reflect complaint customer experience. Finally, the obtained experimental result verified that the proposed dynamic perception method for QoE can accurately characterize the real customer experience. The evaluation result for QoE model based on customer satisfaction questionnaires proves the effectiveness of the QoE-aware model. The evaluation result for adjusted QoE model based on business complaints shows that the adjusted QoE calculation variance reduction rate exceeds more than 50%, which indicates that the proposed method has better ability to reflect the real customer experience.

Optimized Link State Routing (OLSR) is known for its potential features for leveraging the communication requirement in mobile ad-hoc network. However, there is less number of investigations to confirm its sustainability as well as resiliency against potential threats in mobile ad-hoc network. Hence, this paper presents a modeling of misbehaved nodes to compliment intrusion detection system for mobile nodes using OLSR using the strategic construction of secure routing decision in OLSR protocol. The technique allows each communicating mobile nodes to monitor reputation, suspicion factor, and contingency of threat to compute the degree of its vulnerability. The modeling is quite capable of truly exploring the latent adversaries within the network in the form of normal nodes. The study outcome shows proposed algorithm on OLSR to possess reduced delay, reduced algorithm processing time and maximized throughput in contrast to conventional OLSR.

Introduction and penetration of high-speed and innovative mobile data services including social media and video services have been increasing significantly across the globe. This growth is driven by deployment and availability of capable and affordable mobile networks and smartphones. These trends have also been observed in Ethiopia as the country’s sole incumbent operator ethio telecom has expanded coverage and capacity of its mobile data network, especially for universal mobile telecommunications system (UMTS) network. The successful provision of these innovative services requires mobile operators to have continuous monitoring of the quality of their networks and customer satisfaction. To that end, this monitoring allows the operator to make timely network optimization, marketing and other relevant decisions that enhance service quality. Traditionally measurement and analysis of network quality of service (QoS) is performed using data from network management system (NMS) and drive/walk test (DT/WT). In recent times, the usage QoS data from crowdsourcing (CS) is also emerging as useful monitoring tool. However, all these methods do not fully capture users’ quality of experience (QoE), which is a function of not only network QoS but also other factors including subjective users’ technical literacy and opinion. As a result, operators have recently provided attention not only for QoS but also QoE. Yet, most quality related analyses are performed using data from only subjective survey, NMS, DT/WT, or CS. It is not straightforward to find quality investigation based on data from all the methods. More importantly, such quality investigation has not been made in the context of Ethiopia’s mobile market. In this paper, we perform QoS and QoE evaluation for UMTS mobile data service based on quality data from all NMS, WT, CS and subjective survey for a business area in Addis Ababa. The evaluation is made using downlink user throughput and mean opinion score (MOS) metrics. The obtained 50th percentile throughput results from NMS, WT and CS are good enough for web browsing and offline video streaming but not for high definition (HD) video calls and live HD video streaming. Furthermore, CS provides optimistic results compared to NMS and WT and its 90th percentile throughput is very good even for live HD video streaming. Moreover, the obtained MOS results from subjective survey almost fit to the QoS results, thus indicating that the network QoS is a significant contributor to users’ perceived QoE.

Appropriate routing strategies are necessary for mobile ad hoc networks (MANETs) in order to facilitate effective data transfer. In order to counter the prevailing problems, the correct routing schemes will need to be selected as the default configurations are used. In this paper, a special optimal link state routing (OLSR) protocol is proposed to incorporate a deep learning methodology to facilitate efficient video streaming in MANETs. This study presents a new improved variant of the OLSR protocol, which is specially tailored to achieve efficient video streaming in MANETs. It is a radical approach that combines a deep‐learning model with blockchain technology to overcome security and reliability issues. It starts with the gathering of video content that is available publicly. In order to detect black‐hole nodes, a special twin‐attention‐based Elman spiking neural network model is applied. The reliability of the neighboring nodes is then measured by means of trust values. The pufferfish optimization algorithm, or the accuracy‐aware energy‐efficient multipath routing algorithm (AEMRAP), which takes into account node‐ and link‐stability degrees, is used in making routing decisions. Interplanetary file system (IPFS) technology is used to store the data on blockchain and increase its security. The authentication of the blockchain architecture is conducted via the delegated proof‐of‐stake (DPoS) method that also delivers an extra protection of MANETs against unauthorized access. The study demonstrates superior performance in securing and optimizing video transmission, confirming that the extended OLSR protocol is highly effective for MANET video streaming applications. The proposed model exceeds the current approaches with a throughput of 2100 Kbps, an average end latency of 20.2 s, and a packet‐delivery ratio of 92.3%.

The massive growth of data consumption and the variety of wireless technology emergence has made the handover (HO) an attractive research topic nowadays, mainly due to the popularity of Wireless Local Area Networks (WLANs), which allow users to reach high-speed data communication while they are in movement. Moreover, mobile devices such as tablets and smartphones have also become increasingly popular due to their low cost and ease of use, and an increase in mobile device use is expected to accelerate in the coming years, along with the availability and use of applications such as real-time services and online gaming. The traditional HO methods will likely not meet the requirements of mobile devices for modern applications due to the lack of intelligence, lack of awareness Quality of Service (QoS) and Quality of Experience (QoE) requirements of mobile users. We, therefore, introduce a novel architecture that supports horizontal HO in homogenous networks. This architecture is based on the Software-Defined Wireless Networking (SDWN) concept, where the wireless network is controlled centrally and the wireless Access Points (APs) are programmable. In this architecture, HO algorithms will assist wireless users to find the network that could best support the application requirements through Quality of Service (QoS) and Quality of Experience (QoE) management policies. The first HO algorithm proposed in this thesis is called Quality of Experience Oriented Handover Algorithm. This algorithm will guarantee the best possible connectivity to the users in terms of their QoE and QoS requirements and outperforms the traditional methods in a sparse network environment. The second contribution is called Optimised Handover Algorithm for Dense WLAN Environments. This algorithm has been designed to address dense network environments via taking into consideration the Adaptive Hysteresis Value (AHV). The AHV will help the Optimised Handover Algorithm via reducing the so-called ping-pong effect. This contribution shows promising performance results by selecting the best candidate AP, decreasing the number of redundant HO and avoiding the ping-pong effect. The final contribution is called Priority Based Handover Algorithm. We extended our proposed SDWN architecture in order to include the concept of prioritising users and make a smart decision during the process of HO. This algorithm will prioritise a certain class of users to avoid the effect of the over-congestion. The results show that the approach based on priority outperforms the state of the art and provides better QoE to the high priority users despite the over-congestion situation.