Toward Efficient Service-Level QoS Provisioning in Large-Scale 802.11-Based Networks

In ultra dense WiFi networks, access points are deployed with high density in order to support Internet access for large amount of mobile users at the same time. Since the mobile users may not be uniformly distributed in the network, the heavy loaded access points and the interference among different access points would cause the network throughput degradation. Further, although increasing transmission power levels of access points could enhance network throughput, the energy efficiency would be low. Energy consumption is an increasingly important issue today so that the network performance needs to be improved in an energy efficient manner. Under this condition, we propose a distributed power adjustment scheme to intelligently maximize the throughput of the entire network without increasing transmission power in the presence of dynamic distributed mobile users. To validate the performance of our proposed scheme, we simulate various network conditions and the results show that our proposed scheme can sustain throughput with less energy consumption with less than 200 iterations.

Internet videoconferencing has emerged as a viable medium for communication and entertainment. However, its widespread use is being challenged. This is because videoconference end-users frequently experience perceptual quality impairments such as video frame freezing and voice dropouts due to changes in network conditions on the Internet. These impairments cause extra end-user interaction effortand correspondingly lead to unwanted network bandwidth consumptionthat affects user Quality of Experience (QoE) and Internet congestion. Hence, it is important to measure and subsequently minimize the extra end-user interaction effort in a videoconferencing system. In this paper, we describe a novel active measurement scheme that considers end-user interaction effort and the corresponding network bandwidth consumption to provide videoconferencing interaction QoE measurements. The scheme involves a Multi-Activity Packet-Trains (MAPTs) methodology to dynamically emulate a videoconference session's participant interaction patterns and corresponding video activity levels that are affected by transient changes in network conditions. Also, we describe the implementation and validation of the Vperftool we have developed to measure the videoconferencing interaction QoE on a network path using our proposed scheme.

The usage of voice over IP (VoIP) traffic in IEEE 802.11 wireless networks is expected to increase in the near future due to widely deployed 802.11 wireless networks and VoIP services on fixed lines. However, the quality of service (QoS) of VoIP traffic in wireless networks is still unsatisfactory. In this thesis, I identify several sources for the QoS problems of VoIP traffic in IEEE 802.11 wireless networks and propose solutions for these problems. The QoS problems discussed can be divided into three categories, namely, user mobility, VoIP capacity, and call admission control. User mobility causes network disruptions during handoffs. In order to reduce the handoff time between Access Points (APs), I propose a new handoff algorithm, Selective Scanning and Caching, which finds available APs by scanning a minimum number of channels and furthermore allows clients to perform handoffs without scanning, by caching AP information. I also describe a new architecture for the client and server side for seamless IP layer handoffs, which are caused when mobile clients change the subnet due to layer 2 handoffs. I also present two methods to improve VoIP capacity for 802.11 networks, Adaptive Priority Control (APC) and Dynamic Point Coordination Function (DPCF). APC is a new packet scheduling algorithm at the AP and improves the capacity by balancing the uplink and downlink delay of VoIP traffic, and DPCF uses a polling based protocol and minimizes the bandwidth wasted from unnecessary polling, using a dynamic polling list. Additionally, I estimated the capacity for VoIP traffic in IEEE 802.11 wireless networks via theoretical analysis, simulations, and experiments in a wireless test-bed and show how to avoid mistakes in the measurements and comparisons. Finally, to protect the QoS for existing VoIP calls while maximizing the channel utilization, I propose a novel admission control algorithm called QP-CAT (Queue size Prediction using Computation of Additional Transmission), which accurately predicts the impact of new voice calls by virtually transmitting virtual new VoIP traffic.

Level of service (LOS) classifications of traffic operational conditions play a large role in roadway-improvement funding decisions. Consequently, it is essential that traveler perception of LOS is consistent with the values determined through a traffic analysis. Otherwise, the public confidence in appropriate transportation agency funding decisions may be undermined. Research to measure travelers\\' perceptions of traffic operational conditions is a relatively immature field and methods to obtain such data are still evolving. Methods used to collect data on the travelers\\' perception in previous studies include driver interviews at rest stops, focus groups, and rating video clips recorded from the driver\\'s field-of-view. These videos are recorded on real roadways for greater realism but the capture of the full range of operational conditions in a timely manner is its greatest problem. Another significant challenge that all the methods in the literature face is collecting a sufficiently large sample of responses. This dissertation describes an approach to incorporate travelers\\' perception of trip quality that addresses the limitations of the previous studies by the use of a combination of realistic looking 3-dimensional traffic stream visualizations and an online survey to reach a large number of people. The use of traffic simulation software provides full control of the traffic and roadway characteristics, and allows for the creation of realistic computer generated animations over the full range of operating conditions in a fast, efficient and economical manner. Furthermore, modern microsimulation software is able to record video clips from the driver\\'s viewpoint, which is likely to elicit more accurate rankings from the study participants than an overhead view. The creation of the roadway environment to produce a realistic view from the vehicle\\'s cabin interior and an automated method for choosing a representative vehicle from the traffic stream are presented. Data on drivers\\' perception of the quality of the trips depicted in the video clips are obtained inviting participants to respond to a web-based survey. In the web survey, participants watched a set of freeway trips under the desired range of roadway and traffic conditions and rate each trip using a visual analog scale that varies from 0 to 100. The travelers\\' ratings are then discretized into the desired number of service levels using cluster analysis and the service level boundaries and the associate confidence intervals are estimated using logistic regression. The feasibility of the proposed approach was demonstrated with a case study with 977 participants that rated 10,228 trips depicting 128 different combinations of traffic density, truck percentage, posted speed limit, grade steepness, and number of lanes, chosen according to a fractional factorial design. After a series of filters, the final sample consisted in 6231 ratings by 554 participants. A statistically significant correlation between traffic density and rating was found (ρ = –0.532, N = 6231). The case study results indicate that the HCM-7 freeway LOS boundaries are within the confidence intervals estimated using the proposed approach, in the exception of the threshold between LOS D and E. This suggests that, at least for the participants in the study, that drivers perceive LOS D and E as very similar. The effect of sociodemographic, traffic and roadway factors on the participants\\' perception of trip quality was investigated using a fractional factorial design. The sample consisted of 7,004 ratings by 625 participants. A total of 16 factors were analyzed using bivariate correlation and traffic density was the only factor that showed a significant, strong correlation with rating (ρ = 0.520, p < 0.001). Truck percent was also correlated with rankings, at a much lower level (ρ = –0.116, p < 0.001) and no significant influence from sociodemographic factors was found. These results were confirmed by a stepwise multiple linear regression model calibrated to the data. A CART decision tree model indicated that participants\\' perception of the trip quality tend to be affected by the presence of trucks in the stream when traffic density is greater than 7 veh/km/ln.

Enhanced Adaptive SLA-aware Algorithms for Provisioning Shared Mesh Optical Networks

Differentiated services (DiffServ) has been proposed as a scalable solution for Internet QoS. Within the DiffServ architecture, premium services is a service class which is proposed for interactive real-time applications such as real-time voice and video over the Internet. In order to ensure the service quality of premium services, each DiffServ domain need to appropriately negotiate a service level agreement (SLA) with its customers and neighboring domains. Because the resources for premium service are usually a small part of the total network bandwidth, dynamic SLA negotiation is preferred to maximize the resource utilization. However, a completely dynamic SLA negotiation scheme introduces a scalability problem for the bandwidth broker (BB). We introduce the concept of the as a viable solution that avoids the scalability problem while managing the Internet bandwidth efficiently. A threshold-based updating scheme for the pipe is used which minimizes the updating overhead for the BB while maintaining a high utilization for the pipe.

The energy demands of modern mobile devices are outstripping their battery lives. As a result, energy efficiency—fitting an energy budget and maximizing the utility of applications under given battery constraints—has become an important system design consideration. Because network communication incurs high energy costs in mobile applications, middleware presents a promising target for energy optimizations. Unfortunately, mainstream middleware mechanisms are oblivious to the highly volatile nature of mobile networks, operating over which energy efficiently requires aligning the middleware communication patterns with the network conditions in place. In this paper, we present a novel middleware architecture that optimizes energy consumption by adapting various facets of middleware functionality (e.g., data communication, encoding, and compression) dynamically in response to fluctuations in network conditions. By means of a simple configuration file, the programmer can specify the policies to follow for various parts of the communication functionality and how policies should be triggered by changes in network conditions. As compared to mainstream middleware mechanisms, our reference implementation improves the energy efficiency of mobile applications. Specifically, our benchmarks and case studies demonstrate that the new middleware architecture can reduce the energy budget of a typical third-party mobile application by as much as 30%.

This paper presents a QoS management architecture for VoIP networks. Voice quality, specifically MOS (mean opinion score), is continuously and automatically monitored by using an objective voice quality evaluation tool for periodically generated test calls carrying artificial voice signals. Edge-to-edge measurement based admission control is used to maintain packet loss rates for both directional voice flows below a predetermined value under various traffic conditions. A network design method is given to meet target blocking probability and packet loss rate. Simulation is used to evaluate network performance such as blocking probabilities and packet loss rates for the network with edge-to-edge measurement based admission control. It is shown that admission control works well to control packet loss rate under various network conditions.

Continuity and operational safety of interconnections, including HVDC connections, may be exposed to disturbance related to a network conditions and operating devices, including unstable sources such as onshore, offshore or photovoltaic farms. These interactions can lead to deterioration of voltage quality parameters. That occurs as a result for instance, source switching processes, disturbances in the internal farm network, in particular on the power export line. Considering phenomena above, this article presents an analysis of HVDC voltage harmonics in changing network conditions, including the resolution of measurement results.

In the fifth generation (5G) networks, isolated logical slices are formed by the same infrastructure, and spectrum resource. In the coverage regions of the sharing access points (APs), device to device (D2D) communication can occur among different slices, i.e., one mobile terminal (MT) acts as a D2D relay for another MT serving by a different slice. Since the slices, and the MTs are selfish who will not help others voluntarily, this paper proposes a two-layered incentive scheme to stimulate cooperation. To achieve this, two resource allocating problems of the proposed incentive scheme are formulated which introducing the slices,' and the MTs' cooperative activities, thus more resources will be allocated to the cooperative slices, and MTs as reward. Since the slices,' and the MTs' instantaneous resource allocations can not be obtained by the two optimal problems, the incentive scheduling algorithms of the slices, and the MTs are designed. Finally, we define the isolation indexes to evaluate slice isolation when carrying out cooperation. By simulating, it is proved that the proposed incentive scheme can stimulate cooperation efficiently, since the throughputs of the cooperative slices, and MTs are both improved. And the proposed incentive scheme is helpful for the slices, and the MTs to meet the statistical service quality requirements, and brings the bad effect to the instantaneous service quality requirements.

Hyper-responsive mobile applications}, such as augmented reality and online games, require ultra-low latency access to back-end services and data at runtime. While fog computing tries to meet such latency requirements by placing corresponding back-end services and data closer to clients, for e.g., within an access network, assuming a fixed back-end server throughout execution is problematic due to user mobility. A more flexible approach is thus required to allow for adapting to changes in network conditions when users roam, by relocating back-end services and data to closer available infrastructure. Support for real-time migration of software services exists, however, migrating associated disk state remains a bottleneck. This paper presents FOGFS, a fog file system that employs intelligent snapshotting, migration and synchronization mechanisms to speed up the migration of an application‘s disk state between different edge locations at runtime. The experimental evaluation of our prototype implementation reveals that the attainable speed-up is as much as 3. 3 x compared to conventional migration approaches.

As broadband connection capacities increase, residential network users can experience performance degradation when multiple applications run concurrently over bottlenecked wireless access points (APs). This paper presents Classification and Treatment iN an AP (CATNAP), a plug-and-play solution, that automatically classifies and treats flows passing through an AP without any user intervention. Implemented in NS-2 and evaluated against DropTail and Strict Priority Queuing under various network and traffic conditions, CATNAP provides better QoS support for VoIP, games and streaming video applications.

A lot of access points (APs) in wireless mesh networks (WMNs) are battery powered. In order to minimize their energy consumption, the APs can adaptively adjust their transmission power and time based on various network conditions. In this paper, the problem of minimizing the AP energy consumption is formulated as an optimization problem with the constraint to satisfy the throughput requirements of associated mobile stations (MSs). Balancing the energy consumption of the APs can be important to prolong the network lifetime, particularly in a network with high and random user mobility, which can easily result in unbalanced traffic load and energy consumption among the APs. Two distributed handoff schemes are proposed for a WMN with adaptive transmission power and rate. One scheme attempts to achieve balanced energy consumption among the APs during each scheduling interval, and the other scheme balances the AP energy consumption over a longer term. Numerical results show that both schemes achieve much longer network lifetime than the traditional distance-based handoff scheme, while the long-term based handoff scheme can achieve the objective with approximately the same number of handoffs as the distance-based handoff.

In recent years, there has been a growing demand in 3G data services, leading to deteriorating 3G service quality. Noting that Wireless Local Area Networks (WLANs) as well as 3G cellular networks are widely available today, WLANs could be effectively utilized to relieve the overload in the 3G networks. On the other hand, use of IEEE 802.11 WLAN Access Points (APs) has proliferated tremendously, resulting in a communication device inside a mobile vehicle to access the Internet. However, using Internet through APs in moving vehicles is challenging since WLAN APs have a short range and are typically not deployed to cover all roads. Several studies have investigated the performance of using intermittently available WLAN connectivity from moving vehicles for data transfers and predictive offloading in WLAN/3G networks. However, these works have not addressed mobility pattern from the viewpoint that drivers' mobility is generally known to have a daily routine. Therefore, in this paper, we consider the user's historical mobility to decide to offload data to WLAN instead of switching to 3G network. The user's application usage pattern is also considered into predicting available WLANs. To evaluate the performance of our offloading algorithm, we analyze the prediction error and conduct simulations. The simulation results show that the proposed algorithm achieves shorter transmission time than the existing schemes that do not consider user's mobility pattern by delivering more data to the WLANs.

This paper presents a theoretic framework of optimal resource allocation and admission control for peer-to-peer networks. Peer's behavioral rankings are incorporated into the resource allocation and admission control to provide differentiated services and even to block peers with bad rankings. These peers may be free-riders or suspicious attackers. A peer improves her ranking by contributing resources to the P2P system or deteriorates her ranking by consuming services. Therefore, the ranking-based resource allocation provides necessary incentives for peers to contribute their resources to the P2P systems. We define a utility function which captures the best wish for the source peer to serve competing peers, who request services from the source peer. Although the utility function is convex, Harsanyi-type social welfare functions are devised to obtain a unique optimal resource allocation that achieves max-min fairness. The parameters used in our model can be derived from the nature of the services or chosen by the source peer. No private information is required to reveal from individual peers. This prevents selfish peers to play the system strategically and cheat the resource allocation mechanism for their own benefits. The resource allocation and admission control are fully distributed and linearly scalable.