Conventional mechanisms proposed for enhancing quality of service (QoS) in 802.11 networks suffer from a lack of backward compatibility and fairness with and to legacy devices. In this paper, we present a cooperative mechanism, called TXOP (transmission opportunity) Exchange, that provides a legacy-neutral solution in which only stations (STAs) participating in TXOP Exchange cooperatively use their available bandwidth to satisfy their required throughputs, while other legacy devices continue to get the same throughput performance as before. Specifically, we discuss the implementation of TXOP Exchange in legacy 802.11 networks. We show that this mechanism can be realized with minor modifications to the RTS (request-to-send) frames of only the STAs participating in TXOP Exchange and without any replacement of legacy access points or STAs. We show an example of a proportional fair algorithm for fair and efficient MAC cooperation using a Nash bargaining solution (NBS). A simulation study using a realistic simulator verifies that the TXOP Exchange mechanism ensures legacy neutrality and fair and efficient cooperation even when a large number of legacy STAs coexist.

The market growths of smart-phones and thin clients have been significantly increasing communication traffic in mobile networks. To handle the increased traffic, network operators should consider how to leverage distributed wireless resources such as distributed spots of wireless local access networks. In this paper, we consider the system where multiple moving users share distributed wireless access points on their traveling routes between their start and goal points and formulate as an optimization problem. Then, we come up with three algorithms as a solution for the problem. The key idea here is 'longcut route instruction', in which users are instructed to choose a traveling route where less congested access points are available; even if the moving distance increases, the throughput for users in the system would improve. In this paper, we define the gain function. Moreover, we analyze the basic characteristics of the system using as a simple model as possible.

In heterogeneous mobile networks, infrastructure multihop techniques enable mobile stations (MSs) with only a single wireless interface to connect with other networks via multiple-interface MSs (MMSs). That is, MMSs can become gateways between two different mobile networks. Cooperation between different mobile networks linked by MMSs can yield many benefits, including coverage expansion, load balancing, and throughput improvement. We studied how to control these cooperative benefits. We developed a network control mechanism, Cooperative Networking, which controls the cooperative benefits in heterogeneous infra-multihop networks. The proposed mechanism assigns a cooperation rule to MSs. By following the rule, every MS chooses a path to a base station, such as direct connection to 3G networks or infra-multihop connection to wireless local area networks (WLANs). Cooperation rules are designed according to the cooperative benefits, which are selected based on the needs of network operators or users. We call a selected cooperative benefit a networking policy. In our proposed cooperative networking mechanism, network operators can adaptively select a networking policy appropriate for network conditions and the needs of users. Computer simulation results validated our proposed mechanism.

The demand for data/audio streaming/video streaming multicast services in large scale networks has been increasing. Moreover, the improved transmission speed and mobile-device capability in wireless access networks enable people to use such services via their personal mobile devices. Peer-to-peer (P2P) architecture ensures scalability and robustness more easily and more economically than server-client architecture; as the number of nodes in a P2P network increases, the amount of workload per node decreases and lessens the impact of node failure. However, mobile users feel much larger psychological cost due to strict limitations on bandwidth, processing power, memory capacity, and battery life, and they want to minimize their contributions to these services. Therefore, the issue of how we can reduce this psychological cost remains. In this paper, we consider how effective a social networking service is as a platform for mobile P2P multicast. We model users' cooperative behaviors in mobile P2P multicast streaming, and propose a social-network based P2P streaming architecture for mobile networks. We also measured the psychological forwarding cost of real users in mobile P2P multicast streaming through an emulation experiment, and verify that our social-network based mobile P2P multicast streaming improves service quality by reducing the psychological forwarding cost using multi-agent simulation.

In road-vehicle communication systems, the transmission rate between user terminals in the vehicle and the access points degrades due to changing path-loss and time-varying fading. In this paper, we used an inter-vehicle packet relay technique to improve channel quality in road-vehicle communication systems. We evaluated this method using numerical analysis to validate our method.

Multihop techniques in CDMA radio access networks, enable dead-spot mobile stations, which cannot communicate with base stations directly, to send data to them via other mobile stations. In this paper, we propose a mechanism for establishing connections and relaying packets between mobile stations. In this mechanism, the mobile stations are connected to one another and relay packets through a random access channel, which is an uplink common channel. In addition, our mechanism satisfies the requirements for applying multihop techniques to third generation radio access networks. Moreover, we also discuss our evaluation of the performance of the mechanism through computer simulations. The results we obtained reveal that it is capable of reducing dead-spot mobile stations and improving throughput with only limited modifications to conventional systems. Furthermore, we propose an adaptive transmission power control to enhance our mechanism and also evaluate this method through computer simulations.

In peer-to-peer (P2P) content sharing, users can share their content by contributing their own resources to one another. However, since there is no incentive for contributing contents or resources to others, users may attempt to obtain content without any contribution. To motivate users to contribute their resources to the service, incentive-rewarding mechanisms have been proposed. On the other hand, emerging wireless technologies, such as IEEE 802.11 wireless local area networks, beyond third generation (B3G) cellular networks and mobile WiMAX, provide high-speed Internet access for wireless users. Using these high-speed wireless access, wireless users can use P2P services and share their content with other wireless users and with fixed users. However, this diversification of access networks makes it difficult to appropriately assign rewards to each user according to their contributions. This is because the cost necessary for contribution is different in different access networks. In this paper, we propose a novel incentive-rewarding mechanism called EMOTIVER that can assign rewards to users appropriately. The proposed mechanism uses an external evaluator and interactive learning agents. We also investigate a way of appropriately controlling rewards based on the system service's quality and managing policy.

In wireless local area networks (WLANs), the necessity of quality-of-service (QoS) control for uplink flows is increasing because interactive applications are becoming more popular. Fairness between flows transmitted by stations with different physical transmission rates must be ensured in QoS control for link-adaptive WLANs, which are widely used nowadays. We propose a novel distributed access scheme called QC-DCA to satisfy these requirements. QC-DCA adaptively controls the parameters of carrier sense multiple access with collision avoidance (CSMA/CA). QC-DCA has two QoS control functions: guarantee and classification. QC-DCA guarantees target throughputs and packet delays by quickly adjusting CSMA/CA parameters. In QoS classification, the difference of throughputs and packet delays between different QoS classes is maintained. These two functions allow QC-DCA to suppress the unfairness caused by differences of transmission rates in the physical layer. We evaluated the throughput and delay performances of our scheme using computer simulations. The results show the viability of our scheme.

One of the features of a software-defined network (SDN) is a logically centralized control plane hosting one or more SDN controllers. As SDN controller placement can impact network performance, it is widely studied as the controller placement problem (CPP). For a cost-effective network design, network providers need to minimize the number of SDN controllers used in the network since each SDN controller incurs installation and maintenance costs. Moreover, the network providers need to deal with the failure of SDN controllers. Existing studies that consider SDN controller failures use the scheme of connecting each SDN switch to one Master controller and one or more Slave controllers. The problem with this scheme is that the computing capacity of each SDN controller cannot be used efficiently since one SDN controller handles the load of all SDN switches connected to it. The number of SDN controllers required can be reduced by distributing the load of each SDN switch among multiple SDN controllers. This paper proposes a controller placement model that allows the distribution against SDN controller failures. The proposed model determines the ratios of computing capacity demanded by each SDN switch on the SDN controllers connected to it. The proposed model also determines the number and placement of SDN controllers and the assignment of each SDN switch to SDN controllers. Controller placement is determined so that a network provider can continue to manage all SDN switches if no more than a certain number of SDN controller failures occur. We develop two load distribution methods: split and even-split. We formulate the proposed model with each method as integer linear programming problems. Numerical results show that the proposed model reduces the number of SDN controllers compared to a benchmark model; the maximum reduction ratio is 38.8% when the system latency requirement between an SDN switch and an SDN controller is 100[ms], the computing capacity of each SDN controller is 6 × 106[packets/s], and the maximum number of SDN controllers that can fail at the same time is one.

Simulating the mobility of mobile devices has always been an important issue as far as wireless networks are concerned because mobility needs to be taken into account in various situations in wireless networks. Researchers have been trying, for many years, to improve the accuracy and flexibility of mobility models. Although recent progress of designing mobility models based on social graph have enhanced the performance of mobility models and made them more convenient to use, we believe the accuracy and flexibility of mobility models could be further improved by taking a more integrated structure as the input. In this paper, we propose a new way of designing mobility models on the basis of relational graph [1] which is a graph depicting the relation among objects, e.g. relation between people and people, and also people and places. Moreover, some novel mobility features were introduced in the proposed model to provide social, spatial and temporal properties in order to produce results similar to real mobility data. It was demonstrated by simulation that these measures could generate results similar to real mobility data.

Predictive spatial-monitoring, which predicts spatial information such as road traffic, has attracted much attention in the context of smart cities. Machine learning enables predictive spatial-monitoring by using a large amount of aggregated sensor data. Since the capacity of mobile networks is strictly limited, serious transmission delays occur when loads of communication traffic are heavy. If some of the data used for predictive spatial-monitoring do not arrive on time, prediction accuracy degrades because the prediction has to be done using only the received data, which implies that data for prediction are ‘delay-sensitive’. A utility-based allocation technique has suggested modeling of temporal characteristics of such delay-sensitive data for prioritized transmission. However, no study has addressed temporal model for prioritized transmission in predictive spatial-monitoring. Therefore, this paper proposes a scheme that enables the creation of a temporal model for predictive spatial-monitoring. The scheme is roughly composed of two steps: the first involves creating training data from original time-series data and a machine learning model that can use the data, while the second step involves modeling a temporal model using feature selection in the learning model. Feature selection enables the estimation of the importance of data in terms of how much the data contribute to prediction accuracy from the machine learning model. This paper considers road-traffic prediction as a scenario and shows that the temporal models created with the proposed scheme can handle real spatial datasets. A numerical study demonstrated how our temporal model works effectively in prioritized transmission for predictive spatial-monitoring in terms of prediction accuracy.

Our prior papers proposed a traffic engineering scheme to further localize traffic in peer-assisted content delivery networks (CDNs). This scheme periodically combines the content files and allows them to obtain the combined content files while keeping the price unchanged from the single-content price in order to induce altruistic clients to download content files that are most likely to contribute to localizing network traffic. However, the selection algorithm in our prior work determined which and when content files should be combined according to the cache states of all clients, which is a kind of unrealistic assumption in terms of computational complexity. This paper proposes a new concept of virtual local server to reduce the computational complexity. We could say that the source server in our mechanism has a virtual caching network inside that reflects the cache states of all clients in the ‘actual’ caching network and combines content files based on the virtual caching network. In this paper, without determining virtual caching network according to the cache states of all clients, we approximately estimated the virtual caching network from the cache states of the virtual local server of the local domain, which is the aggregated cache state of only altruistic clients in a local domain. Furthermore, we proposed a content selection algorithm based on a virtual caching network. In this paper, we used news life-cycle model as a content model that had the severe changes in cache states, which was a striking instance of dynamic content models. Computer simulations confirmed that our proposed algorithm successfully localized network traffic.

The mobile cloud computing (MCC) paradigm is aimed at integrating mobile devices with cloud computing. In the client-server architecture of MCC, mobile devices offload tasks to the cloud to utilize the computation and storage resources of data centers. However, due to the rapid increase in the traffic demand and complexity of mobile applications, service providers have to continuously upgrade their infrastructures at great expense. At the same time, modern mobile devices have greater resources (communication, computation, and sensing), and these resources are not always fully utilized by device users. Therefore, mobile devices, from time to time, encounter other devices that could provide resources to them. Because the amount of such resources has increased with the number of mobile devices, researchers have begun to consider making use of these resources, located at the “edge” of mobile networks, to increase the scalability of future information networks. This has led to a cooperation based architecture of MCC. This paper reports the concept and design of an resource sharing mechanism that utilize resources in mobile devices through opportunistic contacts between them. Theoretical models and formal definitions of problems are presented. The efficiency of the proposed mechanism is validated through formal proofs and extensive simulation.

Streaming systems that can maintain Quality of Experience (QoE) for users have attracted much attention because they can be applied in various fields, such as emergency response training and medical surgery. Dynamic Adaptive Streaming over HTTP (DASH) is a typical protocol for streaming system. In order to improve QoE in DASH, a multi-server system has been presented by pseudo-increasing bandwidth through multiple servers. This multi-server system is designed to share streaming content efficiently in addition to having redundant server resources for each streaming content, which is excellent for fault tolerance. Assigning DASH server to users in these multi-servers environment is important to maintain QoE, thus a method of server assignment of users (user allocation method) for multi-servers is presented by using cooperative game theory. However, this conventional user allocation method does not take into account the size of the server bandwidth, thus users are concentrated on a particular server at the start of playback. Although the average required bit rate of video usually fluctuates, bit rate fluctuations are not taken into account. These phenomena may decrease QoE. In this paper, we propose a novel user allocation method using coalition structure generation in cooperative game theory to improve the QoE of all users in an immediate and stable manner in DASH environment. Our proposed method can avoid user concentration, since the bandwidth used by the overall system is taken into account. Moreover, our proposed method can be performed every time the average required bit rate changes. We demonstrate the effectiveness of our method through simulations using Network Simulator 3 (NS3).

Wireless content sharing where peers share content and services via wireless access networks requires user contributions, as in fixed P2P content sharing. However, in wireless access environments, since the resources of mobile terminals are strictly limited, mobile users are not as likely to contribute as ones in fixed environments. Therefore, incentives to encourage user contributions are more significant in wireless access environments. Although an incentive service differentiation architecture where the content transfer rate is adjusted according to the contributions of each downloading user has been already proposed for fixed P2P, it may not work well in wireless access environments because several factors effect wireless throughput. In this paper, we propose a novel architecture for contribution-based transfer-rate differentiation using wireless quality of service (QoS) techniques that motivates users to contribute their resources for wireless content sharing. We also propose a radio resource assignment method for our architecture. Computer simulations and game-theoretic calculations validate our architecture.

Despite the increasing use of mobile computing, exploiting its full potential is difficult due to its inherent characteristics such as error-prone transmission channels, diverse node capabilities, frequent disconnections and mobility. Mobile Cloud Computing (MCC) is a paradigm that is aimed at overcoming previous problems through integrating mobile devices with cloud computing. Mobile devices, in the traditional client-server architecture of MCC, offload their tasks to the cloud to utilize the computation and storage resources of data centers. However, along with the development of hardware and software technologies in mobile devices, researchers have begun to take into consideration local resource sharing among mobile devices themselves. This is defined as the cooperation based architecture of MCC. Analogous to the conventional terminology, the resource platforms that are comprised of surrounding surrogate mobile devices are called local resource clouds. Some researchers have recently verified the feasibility and benefits of this strategy. However, existing work has neglected an important issue with this approach, i.e., how to construct local resource clouds in dynamic mobile wireless networks. This paper presents the concept and design of a local resource cloud that is both energy and time efficient. Along with theoretical models and formal definitions of problems, an efficient heuristic algorithm with low computational complexity is also presented. The results from simulations demonstrate the effectiveness of the proposed models and method.

In content services where people purchase and download large-volume contents, minimizing network traffic is crucial for the service provider and the network operator since they want to lower the cost charged for bandwidth and the cost for network infrastructure, respectively. Traffic localization is an effective way of reducing network traffic. Network traffic is localized when a client can obtain the requested content files from other a near-by altruistic client instead of the source servers. The concept of the peer-assisted content distribution network (CDN) can reduce the overall traffic with this mechanism and enable service providers to minimize traffic without deploying or borrowing distributed storage. To localize traffic effectively, content files that are likely to be requested by many clients should be cached locally. This paper presents a novel traffic engineering scheme for peer-assisted CDN models. Its key idea is to control the behavior of clients by using content-oriented incentive mechanism. This approach enables us to optimize traffic flows by letting altruistic clients download content files that are most likely contributed to localizing traffic among clients. In order to let altruistic clients request the desired files, we combine content files while keeping the price equal to the one for a single content. This paper presents a solution for optimizing the selection of content files to be combined so that cross traffic in a network is minimized. We also give a model for analyzing the upper-bound performance and the numerical results.

In this paper, we propose a new resource management scheme for multiple video stream transmission in a wireless environment. The proposed scheme adaptively determines transmission parameters such as the number of assigned time slots, modulation format, and forward error correction (FEC) code rate according to the required bit rate and error sensitivity of the video stream as well as the channel state. The computer simulation results show that the proposed scheme drastically improves the image quality degradation due to channel errors.

This paper proposes an adaptive transmission scheme for web prefetching in wireless communication systems. The proposed adaptive transmission scheme controls the modulation format and the error control scheme according to the access probability of the web document being transmitted. In the proposed system, the actually requested documents and the documents which have high access probability are transmitted with a reliable transmission format, while the pages whose access probabilities are lower than a certain threshold are transmitted with a bandwidth efficient transmission format. The computer simulation results show that the proposed scheme drastically improves the latency performance.

When the number of users in a service area increases in mobile multimedia services, no individual user can obtain satisfactory radio resources such as bandwidth and signal power because the resources are limited and shared. A solution for such a problem is user-position control. In the user-position control, the operator informs users of better communication areas (or spots) and navigates them to these positions. However, because of subjective costs caused by subjects moving from their original to a new position, they do not always attempt to move. To motivate users to contribute their resources in network services that require resource contributions for users, incentive-rewarding mechanisms have been proposed. However, there are no mechanisms that distribute rewards appropriately according to various subjective factors involving users. Furthermore, since the conventional mechanisms limit how rewards are paid, they are applicable only for the network service they targeted. In this paper, we propose a novel incentive-rewarding mechanism to solve these problems, using an external evaluator and interactive learning agents. We also investigated ways of appropriately controlling rewards based on user contributions and system service quality. We applied the proposed mechanism and reward control to the user-position control, and demonstrated its validity.