Human mobility modeling has increasingly drawn the attention of researchers working on wireless mobile networks such as delay tolerant networks (DTNs) in the last few years. So far, a number of human mobility models have been proposed to reproduce people’s social relationships, which strongly affect people’s daily life movement behaviors. However, most of them are based on the granularity of community. This paper presents interest-oriented human contacts (IHC) mobility model, which can reproduce social relationships on a pairwise granularity. As well, IHC provides two methods to generate input parameters (interest vectors) based on the social interaction matrix of target scenarios. By comparing synthetic data generated by IHC with three different real traces, we validate our model as a good approximation for human mobility. Exhaustive experiments are also conducted to show that IHC can predict well the performance of routing protocols.

Mobile cloud computing (MCC) enables the mobile devices to offload their applications to the cloud and thus greatly enriches the types of applications on mobile devices and enhances the quality of service of the applications. Under various circumstances, researchers have put forward several MCC architectures. However, how to reduce the response latency while efficiently utilizing the idle service capacities of the mobile devices still remains a challenge. In this paper, we firstly give a definition of MCC and divide the recently proposed architectures into four categories. Secondly, we present a Hybrid Local Mobile Cloud Model (HLMCM) by extending the Cloudlet architecture. Then, after formulating the application scheduling problems in HLMCM and bringing forward the Hybrid Ant Colony algorithm based Application Scheduling (HACAS) algorithm, we finally validate the efficiency of the HACAS algorithm by simulation experiments.

With the continued evolution of wireless communication technology, relaying is one of the features proposed for the 4G LTE Advanced (LTE-A) system. The aim of relaying is to enhance both coverage and capacity. The idea of relays is not new, but relaying is being considered to ensure that the optimum performance is achieved to enable the expectations or good quality of service (QoS) of the users to be met while still keeping capital expenditure (CAPEX) within the budgeted bounds of operators. In this paper, we try to stand for an operator to propose a solution that determines where and how many relays should be deployed in the planning stages to minimize the development cost. In the planning stages, we not only derive a multicast tree routing algorithm to both determine and fulfill the QoS requirements to enhance throughput, but we also utilize the Lagrangian relaxation (LR) method in conjunction with optimization-based heuristics and conduct computational experiments to evaluate the performance. Our contribution is utilizing the LR method to propose an optimal solution to minimize the CAPEX of operators to build up a relay network with more efficiency and effectiveness and the QoS can be guaranteed by service level agreement.

6LoWPAN technology has attracted extensive attention recently. It is because 6LoWPAN is one of Internet of Things standard and it adapts to IPv6 protocol stack over low-rate wireless personal area network, such as IEEE 802.15.4. One view is that IP architecture is not suitable for low-rate wireless personal area network. It is a challenge to implement the IPv6 protocol stack into IEEE 802.15.4 devices due to that the size of IPv6 packet is much larger than the maximum packet size of IEEE 802.15.4 in data link layer. In order to solve this problem, 6LoWPAN provides header compression to reduce the transmission overhead for IP packets. In addition, two selected routing schemes, mesh-under and route-over routing schemes, are also proposed in 6LoWPAN to forward IP fragmentations under IEEE 802.15.4 radio link. The distinction is based on which layer of the 6LoWPAN protocol stack is in charge of routing decisions. In route-over routing scheme, the routing distinction is taken at the network layer and, in mesh-under, is taken by the adaptation layer. Thus, the goal of this research is to understand the performance of two routing schemes in 6LoWPAN under error-prone channel condition.

To achieve high accuracy in wireless positioning systems, both accurate measurements and good geometric relationship between the mobile device and the measurement units are required. Geometric dilution of precision (GDOP) is widely used as a criterion for selecting measurement units, since it represents the geometric effect on the relationship between measurement error and positioning determination error. In the calculation of GDOP value, the maximum volume method does not necessarily guarantee the selection of the optimal four measurement units with minimum GDOP. The conventional matrix inversion method for GDOP calculation demands a large amount of operation and causes high power consumption. To select the subset of the most appropriate location measurement units which give the minimum positioning error, we need to consider not only the GDOP effect but also the error statistics property. In this paper, we employ the weighted GDOP (WGDOP), instead of GDOP, to select measurement units so as to improve the accuracy of location. The handheld global positioning system (GPS) devices and mobile phones with GPS chips can merely provide limited calculation ability and power capacity. Therefore, it is very imperative to obtain WGDOP accurately and efficiently. This paper proposed two formations of WGDOP with less computation when four measurements are available for location purposes. The proposed formulae can reduce the computational complexity required for computing the matrix inversion. The simpler WGDOP formulae for both the 2D and the 3D location estimation, without inverting a matrix, can be applied not only to GPS but also to wireless sensor networks (WSN) and cellular communication systems. Furthermore, the proposed formulae are able to provide precise solution of WGDOP calculation without incurring any approximation error.

With more and more mobile device users, an increasingly important and critical issue is how to efficiently evaluate mobile network survivability. In this paper, a novel metric called Average Degree of Disconnectivity (Average DOD) is proposed, in which the concept of probability is calculated by the contest success function. The DOD metric is used to evaluate the damage degree of the network, where the larger the value of the Average DOD, the more the damage degree of the network. A multiround network attack-defense scenario as a mathematical model is used to support network operators to predict all the strategies both cyber attacker and network defender would likely take. In addition, the Average DOD would be used to evaluate the damage degree of the network. In each round, the attacker could use the attack resources to launch attacks on the nodes of the target network. Meanwhile, the network defender could reallocate its existing resources to recover compromised nodes and allocate defense resources to protect the survival nodes of the network. In the approach to solving this problem, the “gradient method” and “game theory” are adopted to find the optimal resource allocation strategies for both the cyber attacker and mobile network defender.

Mean consensus problem is studied using a class of discrete time multiagent systems in which information exchange is subjected to some network-induced constraints. These constraints include package dropout, time delay, and package disorder. Using Markov jump system method, the necessary and sufficient condition of mean square consensus is obtained and a design procedure is presented such that multiagent systems reach mean square consensus.

Location estimation for object tracking is one of the important topics in the research of wireless sensor networks (WSNs). Recently, many location estimation or position schemes in WSN have been proposed. In this paper, we will propose the procedure and modeling of location estimation for object tracking in WSN. The designed modeling is a simple scheme without complex processing. We will use Matlab to conduct the simulation and numerical analyses to find the optimal modeling variables. The analyses with different variables will include object moving model, sensing radius, model weighting value α, and power-level increasing ratio k of neighboring sensor nodes. For practical consideration, we will also carry out the shadowing model for analysis.

When machine-type communication (MTC) devices perform the long-term evolution (LTE) attach procedure without bit rate limitations, they may produce congestion in the core network. To prevent this congestion, the LTE standard suggests using group-based policing to regulate the maximum bit rate of all traffic generated by a group of MTC devices. However, previous studies on the access point name-aggregate maximum bit rate based on group-based policing are relatively limited. This study proposes a multistage control (MSC) mechanism to process the operations of maximum bit rate allocation based on resource-use information. For performance evaluation, this study uses a Markov chain with $M/G/k/k$ to analyze MTC application in a 3GPP network. Traffic flow simulations in an LTE system indicate that the MSC mechanism is an effective bandwidth allocation method in an LTE system with MTC devices. Experimental results show that the MSC mechanism achieves a throughput 22.5% higher than that of the LTE standard model using the group-based policing, and it achieves a lower delay time and greater long-term fairness as well.

Many real-world problems can be formulated as numerical optimization with certain objective functions. However, these objective functions often contain numerous local optima, which could trap an algorithm from moving toward the desired global solution. To improve the search efficiency of traditional genetic algorithms, this paper presents a mutual-evaluation genetic algorithm (MEGA). A novel mutual-evaluation approach is employed so that the merit of selected genes in a chromosome can be determined by comparing the fitness changes before and after interchanging with those in the mating chromosome. According to the determined genome merit, a therapy crossover can generate effective schemata to explore the solution space efficiently. The computational experiments for twelve numerical problems show that the MEGA can find near optimal solutions in all test benchmarks and achieve solutions with higher accuracy than those obtained by eight existing algorithms. This study also uses the MEGA to find optimal flow-allocation strategies for multipath-routing problems. Experiments on quality-of-service routing scenarios show that the MEGA can deal with these constrained routing problems effectively and efficiently. Therefore, the MEGA not only can reduce the effort of function analysis but also can deal with a wide spectrum of real-world problems.

Interference control (IC) between the secondary system and the primary system is an important issue for underlay cognitive radio network (CRN). The secondary system should limit the interference power to primary system by adjusting its transmission power. Many relevant works have been done based on the assumption of the quasistatic channel which is not suitable for the fast time-varying fading channel; the performance of IC in underlay CRN will become worse when the channel varies fast. This paper studies the IC issue in high mobility environment. By considering the channel state information (CSI) outdatedness, a short frame structure scheme and a mean interference power constraint scheme are proposed to reduce the influence of CSI outdatedness on IC performance. Furthermore, by considering the channel estimation error, a spherical error region model based robust IC scheme is designed as well. The proposed IC schemes of the secondary system are converted to the power allocation problems, and then they are formulated to optimization problem whose objects are to maximize the capacity of the secondary system with the interference constraints. The above optimization problems are solved by the water-filling style method. The simulation results show that the proposed IC schemes can effectively control the interference power to the primary system.

Multicast routing is an effective way to transmit messages to multiple hosts in a network. However, it is vulnerable to intermittent connectivity property in mobile ad hoc network (MANET) especially for multimedia applications, which have some quality of service (QoS) requirements. The goal of QoS provisioning is to well organize network resources to satisfy the QoS requirement and achieve good network delivery services. However, there remains a challenge to provide QoS solutions and maintain end-to-end QoS with user mobility. In this paper, a novel penalty adjustment method based on the rough set theory is proposed to deal with path-delay constraints for multicast routing problems in MANETs. We formulate the problem as a constrained optimization problem, where the objective function is to minimize the total cost of the multicast tree subject to QoS constraints. The RPGA is evaluated on three multicast scenarios and compared with two state-of-the-art methods in terms of cost, success rate, and time complexity. The performance analyses show that this approach is a self-adaptive method for penalty adjustment. Remarkably, the method can address a variety of constrained multicast routing problems even though the initial routes do not satisfy all QoS requirements.

Virtualization plays an important role in the recent trend of cloud computing. It allows the administrator to manage and allocate hardware resources flexibly. However, it also causes some security issues. This is a critical problem for service providers, who simultaneously strive to defend against malicious attackers while providing legitimate users with high quality service. In this paper, the attack-defense scenario is formulated as a mathematical model where the defender applies both proactive and reactive defense mechanisms against attackers with different attack strategies. In order to simulate real-world conditions, the attackers are assumed to have incomplete information and imperfect knowledge of the target network. This raises the difficulty of solving the model greatly, by turning the problem nondeterministic. After examining the experiment results, effective proactive and reactive defense strategies are proposed. This paper finds that a proactive defense strategy is suitable for dealing with aggressive attackers under “winner takes all” circumstances, while a reactive defense strategy works better in defending against less aggressive attackers under “fight to win or die” circumstances.

Periodic broadcasting is an effective approach for delivering popular videos. In general, this approach does not provide interactive (i.e., VCR) functions, and thus a client can tolerate playback latency from a video server. The concept behind the approach is partitioning a video into multiple segments, which are then broadcast across individual communication channels in terms of IP multicast. The method improves system throughput by allowing numerous clients to share the channels. For many broadcasting schemes, client receiving bandwidth must equal server broadcasting bandwidth. This limitation causes these schemes to be infeasible in mobile networks because increasing receiving bandwidth at all client sites is expensive, as well as difficult. To alleviate this problem, the fibonacci broadcasting (FiB) scheme allows a client with only two-channel bandwidth to receive video segments. In comparison with other similar schemes, FiB yields smallest waiting time. Extending FiB, this work proposes a new scheme (called FiB+) to achieve smaller client buffering space and the same waiting time under two-channel receiving bandwidth. Extensive analysis shows that FiB+ can yield 34.5% smaller client buffer size than that of FiB. Further simulation results also indicate that FiB+ requires lower client buffering space than several previous schemes.

Due to the advancement of network technology, video-on-demand (VoD) services are growing in popularity. However, individual stream allocation for client requests easily causes a VoD system overload; when its network and disk bandwidth cannot match client growth. This study thus presents a fundamentally different approach by focusing solely on a class of applications identified as latency tolerant applications. Because video broadcasting does not provide interactive (i.e., VCR) functions, a client is able to tolerate playback latency from a video server. One efficient broadcasting method is periodic broadcasting, which divides a video into smaller segments and broadcasts these segments periodically on multiple channels. However, numerous practical systems, such as digital video broadcasting-handheld (DVB-H), do not allow clients to download video data from multiple channels because clients usually only have one tuner. To resolve this problem in multiple-channel broadcasting, this study proposes a novel single-channel broadcasting scheme, which leverages segment-broadcasting capability further for more efficient video delivery. The comparison results show that, with the same settings of broadcasting bandwidth, the proposed scheme outperforms the alternative broadcasting scheme, the hopping insertion scheme, SingBroad, PAS, and the reverse-order scheduling scheme for the maximal waiting time.