Recent studies have shown that the traffic load is often distributed unevenly among the access points. Such load imbalance results in an ineffective bandwidth utilization. The load imbalance and the consequent ineffective bandwidth utilization could be alleviated via intelligently selecting user-AP associations. In this paper, the diversity in users' utilities is sufficiently taken into account, and a Stackelberg leader-follower game is formulated to obtain the optimal user-AP association. The effectiveness of the proposed algorithm on improving the degree of load balance is evaluated via simulations. Simulation results show that the performance of the proposed algorithm is superior to or at least comparable with the best existing algorithms.

Cloud computing is an emerging computing paradigm that may have a significant impact on various aspects of the development of information infrastructure. In a Cloud environment, different types of network resources need to be virtualized as a series of service components by network virtualization, and these service components should be further composed into Cloud services provided to end users. Therefore Quality of Service (QoS) aware service composition plays a crucial role in Cloud service provisioning. This paper addresses the problem on how to compose a sequence of service components for QoS guaranteed service provisioning in a virtualization-based Cloud computing environment. The contributions of this paper include a system model for Cloud service provisioning and two approximation algorithms for QoS-aware service composition. Specifically, a system model is first developed to characterize service provisioning behavior in virtualization-based Cloud computing, then a novel approximation algorithm and a variant of a well-known QoS routing procedure are presented to resolve QoS-aware service composition. Theoretical analysis shows that these two algorithms have the same level of time complexity. Comparison study conducted based on simulation experiments indicates that the proposed novel algorithm achieves better performance in time efficiency and scalability without compromising quality of solution. The modeling technique and algorithms developed in this paper are general and effective; thus are applicable to practical Cloud computing systems.

In recent years, there has been an increasing demand with regard to available elemental services provided by independent firms for compositing new services. Currently, however, whenever it is difficult to maintain the required level of quality of a new composite web service, assignment of the new computer's resources as provisioning at the data center is not always effective, especially in the area of performance for composite web service providers. Thus, a new approach might be required. This paper presents a new control method aiming to maintain the performance requirements for composite web services. There are three aspects of our method that are applied: first of all, the theory of constraints (TOC) proposed by E.M. Goldratt ; secondly, an evaluation process in the non-linear feed forward controlling method: and finally multiple trials in applying policies with verification. In particular, we will discuss the architectural and theoretical aspects of the method in detail, and will show the insufficiency of combining the feedback controlling approach with TOC as a result of our evaluation.

In wireless single-hop networks, IEEE 802.11e Enhanced Distributed Channel Access (EDCA) is the standard for Quality of Service (QoS) control. However, it is necessary for controlling QoS to modify the currently used IEEE 802.11 Distributed Coordination Function (DCF)-compliant terminals as well as Access Points (APs). In addition, it is necessary to modify the parameter of IEEE 802.11e EDCA when the traffic is heavy. This paper proposes a novel scheme to guarantee QoS of high-priority flow with Receiving Opportunity Control in MAC Frame (ROC) employed adaptive flow control in wireless multi-hop network. In the proposed scheme, the edge APs which are directly connected to user terminals estimate the network capacity, and calculate appropriate ACK prevention probability against low-priority flow according to traffic load. Simulation evaluation results show that the proposed scheme guarantees QoS.

We propose a primary traffic based multihop relaying algorithm with cooperative transmission (PTBMR-CT). It enlarges the hop transmission distances to reduce the number of cognitive relays on the route from the cognitive source (CS) to the cognitive destination (CD). In each hop, from the cognitive nodes in a specified area depending on whether the primary source (PS) transmits data to the primary destination (PD), the cognitive node that is farthest away from the cognitive relay that sends data is selected as the other one that receives data. However, when the PS is transmitting data to the PD, from the cognitive nodes in a specified area, another cognitive node is also selected and prepared to be the cognitive relay that receives data of cooperative transmission. Cooperative transmission is performed if the PS is still transmitting data to the PD when the cognitive relay that receives data of the next hop transmission is being searched. Simulation results show that the average number of cognitive relays is reduced by PTBMR-CT compared to conventional primary traffic based farthest neighbor relaying (PTBFNR), and PTBMR-CT outperforms conventional PTBFNR in terms of the average end-to-end reliability, the average end-to-end throughput, the average required transmission power of transmitting data from the CS to the CD, and the average end-to-end transmission latency.

In this letter, we apply dynamic software updating to long-lived applications on the DDS middleware while minimizing service interruption and satisfying Quality of Service (QoS) requirements. We dynamically updated applications which run on a commercial DDS implementation to demonstrate the applicability of our approach to dynamic updating. The results show that our update system does not impose an undue performance overhead–all patches could be injected in less than 350 ms and the maximum CPU usage is less than 17%. In addition, the overhead on application throughput due to dynamic updates ranged from 0 to at most 8% and the deadline QoS of the application was satisfied while updating.

Optical code-division multiple-access (OCDMA) is a promising technique for multimedia transmission in fiber-optic local-area networks (LANs). Variable-weight optical orthogonal codes (OOCs) can be used for OCDMA networks supporting multiple quality of services (QoS). Most constructions for optimal variable-weight OOCs have focused on the case where the number of distinct Hamming weights of all codewords is equal to two, and the codewords of weight 3 are normally included. In this letter, four explicit constructions of optimal (υ,{4,5,6},1,Q)-OOCs are presented, and more new optimal (υ,{4,5,6},1,Q)-OOCs are obtained via recursive constructions. These improve the existing results on optimal variable-weight OOCs with at least three distinct Hamming weights and minimum Hamming weight 4.

In this paper a novel and effective two phase admission control (TPAC) for QoS mobile ad hoc networks is proposed that satisfies the real-time traffic requirements in mobile ad hoc networks. With a limited amount of extra overhead, TPAC can avoid network congestions by a simple and precise admission control which blocks most of the overloading flow-requests in the route discovery process. When compared with previous QoS routing schemes such as QoS-aware routing protocol and CACP protocols, it is shown from system simulations that the proposed scheme can increase the system throughput and reduce both the dropping rate and the end-to-end delay. Therefore, TPAC is surely an effective QoS-guarantee protocol to provide for real-time traffic.

This paper proposes new scheduling algorithms for best effort (BE) traffic classification in business femtocell networks. The purpose of traffic classification is to provide differentiated services to BE users depending on their traffic classes, and the concept of traffic classification is called Inter User Best Effort (IUBE) in CDMA2000 1x Evolution Data Optimized (EVDO) standard. Traffic differentiation is achieved by introducing Grade of Service (GoS) as a quality of service (QoS) parameter into the scheduler's decision metric (DM). New scheduling algorithms are called QoS Round Robin (QoS-RR), QoS Proportionally Fair (QoS-PF), QoS maximum data rate control (DRC) (QoS-maxDRC), QoS average DRC (QoS-aveDRC), QoS exponent DRC (QoS-expDRC), QoS maxDRC-PF (QoS-maxDRC-PF). Two different femtocell throughput experiments are performed using real femtocell devices in order to collect real DRC values. The first experiment examines 4, 8, 12 and 16 IUBE users, while second experiment examines 4 IUBE + 2 Voice over IP (VoIP), 8 IUBE + 2 VoIP, 12 IUBE + 2 VoIP, 16 IUBE + 2 (VoIP) users. Average sector throughput, IUBE traffic differentiation, VoIP delay bound error values are investigated to compare the performance of the proposed scheduling algorithms. In conclusion, QoS-maxDRC-PF scheduler is proposed for business femtocell environment.

Providing seamless QoS guarantees for multimedia services is one of the most critical requirements in the mobile Internet. However, the effects of host mobility make it difficult to provide such services. The next steps in signaling (NSIS) was proposed by the IETF as a new signaling protocol, but it fails to address some mobility issues. This paper proposes a new QoS NSIS signaling layer protocol (QoS NSLP) using a cross-layer design that supports mobility. Our approach is based on the advance discovery of a crossover node (CRN) located at the crossing point between a current and a new signaling path. The CRN then proactively reserves network resources along the new path that will be used after handoff. This proactive reservation significantly reduces the session reestablishment delay and resolves the related mobility issues in NSIS. Only a few amendments to the current NSIS protocol are needed to realize our approach. The experimental results and simulation study demonstrate that our approach considerably enhances the current NSIS in terms of QoS performance factors and network resource usage.

In cellular networks, maximizing the energy efficiency (EE) while satisfying certain QoS requirements is challenging. In this article, we utilize effective capacity (EC) theory as an effective means of meeting these challenges. Based on EC and taking a realistic base station (BS) power consumption model into account, we develop a novel energy efficiency (EE) metric: effective energy efficiency (EEE), to represent the delivered service bit per energy consumption at the upper layer with QoS constraints. Maximizing the EEE problem with EC constraints is addressed and then an optimal power control scheme is proposed to solve it. After that, the EEE and EC tradeoff is discussed and the effects of diverse QoS parameters on EEE are investigated through simulations, which provides insights into the quality of service (QoS) provision, and helps the system power consumption optimization.

Providing quality-of service (QoS) guarantees in VoIP applications has become an urgent demand in wireless and mobile networks. One of the important issues is to find a simple quality metric fitted to low power mobile devices such as smart phones. This paper considers the gap ratio (the proportion of the accumulated gap periods over the whole call session) as a simple quality metric. Our study aims to find the optimum packet count threshold between two adjacent lost packets (referred to as Gmin in RTCP-XR), which is needed for the purpose of identifying whether the current packet at the receiver belongs to the gap state or the burst state, because quality prediction errors depend on the Gmin value when the gap ratio is used as a simple quality metric. Based on this metric, we propose an accounting model that can be a candidate accounting metric useful for a quality-based accounting mechanism.

We consider a queuing model with applications to electric vehicle (EV) charging systems in smart grids. We adopt a scheme where an Electric Service Company (ESCo) broadcasts a one bit signal to EVs, possibly indicating 'on-peak' periods during which electricity cost is high. EVs randomly suspend/resume charging based on the signal. To model the dynamics of EVs we propose an M/M/∞ queue with random interruptions, and analyze the dynamics using time-scale decomposition. There exists a trade-off: one may postpone charging activity to 'off-peak' periods during which electricity cost is cheaper, however this incurs extra delay in completion of charging. Using our model we characterize achievable trade-offs between the mean cost and delay perceived by users. Next we consider a scenario where EVs respond to the signal based on the individual loads. Simulation results show that peak electricity demand can be reduced if EVs carrying higher loads are less sensitive to the signal.

We analyze subjective assessments by comparative evaluations of bulk data transmission by using two psychological methods (the method of successive categories and the constant method). From the results of the first experiment, the thresholds at which participants downloading a data file began to feel dissatisfaction with service degradation are 15.7 Mbps and 11.6 Mbps obtained by the two different methods when the throughput without the service degradation is approximately 22 Mbps. In the second experiment, we investigate the threshold of user satisfaction for various network environments. The threshold is 63% of the throughput of the user's usual network environment. Moreover, from the viewpoint of download time, users feel dissatisfaction with the quality when download time becomes 1.5 times longer. These values can be used to more effectively allocate network resources and thereby achieve higher service quality.

Most existing works on resource allocation in cooperative OFDMA systems have focused on homogeneous users with same service and demand. In this paper, we focus on resource allocation in a service differentiated cooperative OFDMA system where each user has a different QoS requirement. We investigate joint power allocation, relay selection and subcarrier assignment to maximize overall system rates with consideration of QoS guarantees and service support. By introducing QoS price, this combinatorial problem with exponential complexity is converted into a convex one, and a two-level dual-primal decomposition based QoS-aware resource allocation (QARA) algorithm is proposed to tackle the problem. Simulation results reveal that our proposed algorithm significantly outperforms previous works in terms of both services support and QoS satisfaction.

When a link or node fails in a network, the affected flows are automatically rerouted. This increases the hop counts of the flows, which can drastically degrade network performance. Keeping the hop lengths as stable as possible, i.e., minimizing the difference in hop length between the original flow and the rerouted flow is important for network reliability. Therefore, network service providers need a method for designing networks that stabilizes the flow hop length and maintains connectivity during a link or node failure with limited investment cost. First, we formulate the network design problem used for determining the set of links to be added that satisfies the required constraints on flow hop length stability, connectivity, and node degree. Next, we prove that this problem is NP-complete and present two approximation algorithms for the optimization problem so as to minimize the number of links added. Evaluation of the performance of these algorithms by using 39 backbone networks of commercial ISPs and networks generated by two well-known models showed that the proposed algorithms provide effective solutions in sufficiently short computation time.

Bandwidth is an extremely valuable and scarce resource in multimedia networks. Therefore, efficient bandwidth management is necessary in order to provide high Quality of Service (QoS) to users. In this paper, a new QoS-aware bandwidth allocation algorithm is proposed for the efficient use of available bandwidth. By using the multi-objective optimization technique and Talmud allocation rule, the bandwidth is adaptively controlled to maximize network efficiency while ensuring QoS provisioning. In addition, we adopt the online feedback strategy to dynamically respond to current network conditions. With a simulation study, we demonstrate that the proposed algorithm can adaptively approximate an optimized solution under widely diverse traffic load intensities.

The distribution of streaming multicast and real time audio/video applications in the Internet has been quickly increased in the Internet. Commonly, these applications rarely use congestion control and do not fairly share provided network capacity with TCP-based applications such as HTTP, FTP and emails. Therefore, Internet communities will be threatened by the increase of non-TCP-based applications that likely cause a significant increase of traffics congestion and starvation. This paper proposes a set of mechanisms, such as providing various data rates, background traffics, and various scenarios, to act friendly with TCP when sending multicast traffics. By using 8 scenarios of simulations, we use 6 layered multicast transmissions with background traffic Pareto with the shape factor 1.5 to evaluate performance metrics such as throughput, delay/latency, jitter, TCP friendliness, packet loss ratio, and convergence time. Our study shows that non TCP traffics behave fairly and respectful of the co-existent TCP-based applications that run on shared link transmissions even with background traffic. Another result shows that the simulation has low values on throughput, vary in jitter (0-10 ms), and packet loss ratio > 3%. It was also difficult to reach convergence time quickly when involving only non TCP traffics.

In this paper, we study an opportunistic scheduling scheme for the TDMA wireless network with relay stations. We model the time-varying channel condition of a wireless link as a stochastic process. Based on this model, we formulate an optimization problem for the opportunistic scheduling scheme that maximizes the expected system throughput while satisfying the QoS constraint of each user. In the opportunistic scheduling scheme for the system without relay stations, each user has only one communication path between the base station and itself, and thus only user selection is considered. However, in our opportunistic scheduling scheme for the system with relay stations, since there may exist multiple paths between the base station and a user, not only user selection but also path selection for the scheduled user is considered. In addition, we also propose an opportunistic time-sharing method for time-slot sharing between base station and relay stations. With the opportunistic time-sharing method, our opportunistic scheduling provides opportunistic resource sharing in three places in the system: user selection in a time-slot, path selection for the selected user, and time-slot sharing between base station and relay stations. Simulation results show that as the number of places that opportunistic resource sharing is applied to increases, the performance improvement also increases.

Broadband wireless access networks are promising technology for providing better end user services. For such networks, designing a scheduling algorithm that fairly allocates the available bandwidth to the end users and maximizes the overall network throughput is a challenging task. In this paper, we develop a centralized fair scheduling algorithm for IEEE 802.16 mesh networks that exploits the spatio-temporal bandwidth reuse to further enhance the network throughput. The proposed mechanism reduces the length of a transmission round by increasing the number of non-contending links that can be scheduled simultaneously. We also propose a greedy algorithm that runs in polynomial time. Performance of the proposed algorithms is evaluated by extensive simulations. Results show that our algorithms achieve higher throughput than that of the existing ones and reduce the computational complexity.