Mobile traffic is currently the most important traffic on the Internet, both domestically and internationally. This is predominantly attributable to widespread cloud computing-based services on mobile networks. Fifth generation (5G) mobile networks are expected to comfortably accommodate this type of traffic by supporting 1,000 times faster speeds than conventional 4G. However, commercial implementation of 5G mobile is targeted for the year 2020. Therefore, interim accommodation approaches are needed. In essence, 5G mobile networks are an evolution of 4G in which a licensed spectrum that generates revenue from user data transfer is being considered. Consequently, more cost-effective methods that utilize the unlicensed spectrum are also desired. Meanwhile, concomitant with pursuit of miniaturization and reduction in weight, the number and types of network interfaces in recent mobile devices are increasing. We propose a method for carrier aggregation of multiple heterogeneous wireless links based on software-defined networking (SDN) that controls traffic and manages the wireless interfaces of mobile devices effectively when multiple radio access technologies are available. Evaluations conducted of the proposed method on an experimental testbed developed using the OpenStack cloud computing platform with aggregated multiple radio access technology environments indicate that it is feasible and provides higher data rate.

Mobile cloud service is the most important traffic generator today, and high data rate services in this area are increasing. The Virtual Desktop Infrastructure (VDI) is a circuit-like service that is widely deployed owing to its security merits and the resource constraints of mobile devices. However, VDI requires a high and guaranteed virtually constant wireless data rate. Thus, we focus on the problems that have to be resolved in order for IEEE802.21 Media Independent Handover (MIH) to support a guaranteed wireless data rate and also enable it to offer optimized and maximized data rate support for mobile cloud services. We also consider a virtual machine (VM) migration scheme that is tightly coupled to mobile networks and can minimize the user's service delay and reduce the bandwidth requirements of the wired network. We then present a consistent control framework by extending the Global Environment for Network Innovations (GENI) control framework to provide a single integrated control framework for cloud computing and Future Internet compatibility. Finally, we develop an experimental testbed using a mobile cloud computing environment and evaluate the performance of the proposed scheme. We show that the proposed method can enhance the Quality of Experience (QoE) of mobile cloud computing services with increased data rate support and a single consistent control framework that is compatible with the GENI-based Future Internet architecture. The results of evaluations conducted indicate that our proposed method provides 24%–41% better data rate compared to conventional methods.

In this paper, we focus on a scheme that supports mobility for groups of sensor networks. Mobility in wireless sensor networks (WSNs) is one of the most important WSN technologies for applications such as healthcare, vehicular communication systems, intelligent transport systems, and logistics applications. This paper proposes a new mobility management architecture for WSNs that is based on the ID/LOC separation concept for ID-based communications with location-based routing. The proposed architecture supports energy-efficient lightweight mobility control for a large number of WSNs by distributed management manner. Furthermore, the discover-before-forward concept is proposed for route optimization. Performance results show that the proposed ID/LOC separation-based mobility architecture for supporting 6LoWPAN is more efficient and lighter than the existing HIP scheme in terms of energy consumption, total signaling cost and packet delivery cost ratio.

Pricing is an effective approach for spectrum access control in cognitive radio (CR) networks. In this paper, we study the pricing effect on the equilibrium behaviors of selfish secondary users' (SUs') data packets which are served by a CR base station (BS). From the SUs' point of view, a spectrum access decision on whether to join the queue of the BS or not is characterized through an individual optimal strategy that is joining the queue with a joining probability. This strategy also requires each SU to know the average queueing delay, which is a non-trivial problem. Toward this end, we provide queueing delay analysis by using the M/G/1 queue with breakdown. From the BS's point of view, we consider a duopoly market based on the two paradigms: the opportunistic dynamic spectrum access (O-DSA) and the mixed O-DSA & dedicated dynamic spectrum access (D-DSA). In the first paradigm, two co-located opportunistic-spectrum BSs utilize freely spectrum-holes to serve SUs. Then, we show the advantages of the cooperative scenario due to the unique solution that can be obtained in a distributed manner by using the dual decomposition algorithms. For the second paradigm, there are one opportunistic-spectrum BS and one dedicated-spectrum BS. We study a price competition between two BSs as a Stackelberg game. The cooperative behavior between two BSs is modeled as a bargaining game. In both paradigms, bargain revenues of the cooperation are always higher than those due to competition in both cases. Extensive numerical analysis is used to validate our derivation.

This paper studies price-based spectrum access control in cognitive radio networks, which characterizes network operators' service provisions to delay-sensitive secondary users (SUs) via pricing strategies. Based on the two paradigms of shared-use and exclusive-use dynamic spectrum access (DSA), we examine three network scenarios corresponding to three types of secondary markets. In the first monopoly market with one operator using opportunistic shared-use DSA, we study the operator's pricing effect on the equilibrium behaviors of self-optimizing SUs in a queueing system. We provide a queueing delay analysis with the general distributions of the SU service time and PU traffic using the renewal theory. In terms of SUs, we show that there exists a unique Nash equilibrium in a non-cooperative game where SUs are players employing individual optimal strategies. We also provide a sufficient condition and iteraIntive algorithms for equilibrium convergence. In terms of operators, two pricing mechanisms are proposed with different goals: revenue maximization and social welfare maximization. In the second monopoly market, an operator exploiting exclusive-use DSA has many channels that will be allocated separately to each entering SU. We also analyze the pricing effect on the equilibrium behaviors of the SUs and the revenue-optimal and socially-optimal pricing strategies of the operator in this market. In the third duopoly market, we study a price competition between two operators employing shared-use and exclusive-use DSA, respectively, as a two-stage Stackelberg game. Using a backward induction method, we show that there exists a unique equilibrium for this game and investigate the equilibrium convergence.

We study the cross-layer design of congestion control and power allocation with outage constraint in an interference-limited multihop wireless networks. Using a complete-convexification method, we first propose a message-passing distributed algorithm that can attain the global optimal source rate and link power allocation. Despite the attractiveness of its optimality, this algorithm requires larger message size than that of the conventional scheme, which increases network overheads. Using the bounds on outage probability, we map the outage constraint to an SIR constraint and continue developing a practical near-optimal distributed algorithm requiring only local SIR measurement at link receivers to limit the size of the message. Due to the complicated complete-convexification method, however the congestion control of both algorithms no longer preserves the existing TCP stack. To take into account the TCP stack preserving property, we propose the third algorithm using a successive convex approximation method to iteratively transform the original nonconvex problem into approximated convex problems, then the global optimal solution can converge distributively with message-passing. Thanks to the tightness of the bounds and successive approximations, numerical results show that the gap between three algorithms is almost indistinguishable. Despite the same type of the complete-convexification method, the numerical comparison shows that the second near-optimal scheme has a faster convergence rate than that of the first optimal one, which make the near-optimal scheme more favorable and applicable in practice. Meanwhile, the third optimal scheme also has a faster convergence rate than that of a previous work using logarithm successive approximation method.

In this paper, we investigate the cross-layer design for congestion, contention, and power control in multi-hop cognitive radio ad-hoc networks (CRAHNs). In particular, we develop a unified optimization framework achieving flexible tradeoff between energy efficiency and network utility maximization where we design two novel cross-layer cognitive algorithms comprising efficient powered-controlled MAC protocols for CRAHNs based on the concepts of social welfare and net revenue in economics. The proposed framework can balance interference, collision, and congestion among cognitive users (CUs) including cognitive sources and cognitive links while utilizing stochastic spectrum holes vacated by licensed users (LUs). The former allows both cognitive sources and cognitive links to simultaneously adjust their transmission parameters (i.e., transmit power, persistence probability, and rate) following the law of diminishing returns whereas the latter forces cognitive links to control the persistence probability and transmit power in order to asymptotically balance the offered load regulated by cognitive sources. Our proposed protocols are then validated and their performance is compared with the existing MAC schemes in the literature via numerical studies.

The IEEE 802.11 [1] provides multiple channels for wireless communications at the Physical Layer, but the Medium Access Control (MAC) protocol is only designed for a single channel. If the multiple channels can be exploited by multi-channel MAC protocol, there can be multiple transmissions on different channels. Besides that, the power control algorithm can improve the spatial reuse of wireless channels. In this paper, we combine the multi-channel MAC protocol and the power control algorithm together to exploit multiple channels and improve frequency reuse. The main idea of our proposal is to use IEEE 802.11 Power Saving Scheme (PSM) with different transmission power levels in the ATIM window and the data window. All nodes transmit ATIM/ATIM-ACK/ATIM-RES messages with the maximum power while contending the data channel during the ATIM window, and use the minimum required transmission power in the data window on their negotiated channels. The simulation results show that the proposed E-MMAC improve the performance of the network: aggregate throughput, average delay and energy efficiency.

Efficient and fair power allocation associated with congestion control in orthogonal frequency division multiplexing (OFDM)-based multi-hop cognitive radio networks (CRNs) is a challenging and complicated problem. In this paper, we consider their mutual relationship through a cross-layer optimization design that addresses both aggregate utility maximization and energy consumption minimization. By introducing the unique outage constraint of primary user (PU) protection, the joint congestion control and power control (JCPC) formulation is shown to be a nonlinear non-convex optimization problem. Using dual decomposition approach, we first propose a distributed algorithm that can attain the optimal solution via message passing while maintaining the architectural modularity between the layers. Next, we develop a suboptimal algorithm using a new heuristic method to alleviate the overhead burden of the first solution. Finally, the numerical results confirm that the OFDM-based multi-hop CRNs can optimally exploit the spectrum opportunity if the PU outage probability is kept below the target.

In this paper, we focus on a scheme that supports mobility for IPv6 over Low power Wireless Personal Area Network (6LoWPAN) sensor nodes. We define a protocol for 6LoWPAN mobile sensor node, named 6LoMSN, based on Proxy Mobile IPv6 (PMIPv6). The conventional PMIPv6 standard supports only single-hop networks and cannot be applied to multihop-based 6LoWPAN. It does not support the mobility of 6LoMSNs and 6LoWPAN gateways, named 6LoGW, cannot detect the PAN attachment of the 6LoMSN. Therefore, we define the movement notification of a 6LoMSN in order to support its mobility in multihop-based 6LoWPAN environments. The attachment of 6LoMSNs reduces signaling costs over the wireless link by using router solicitation (RS) and router advertisement (RA) messages. Performance results show that our proposed scheme can minimize the total signaling costs and handoff latency. Additionally, we present the design and implementation of the 6LoMSN mobility based on PMIPv6 for a healthcare system. According to the experimental results, the 6LoMSN of the proposed PMIPv6-based 6LoWPAN can be expected to use more of the battery lifetime. We also verify that the 6LoMSN can maintain connectivity, even though it has the freedom of being able to move between PANs without a mobility protocol stack.