Shengling Wang

Routing in pocket switched networks

Pocket switched networks (PSNs) provide a new networking paradigm that takes advantage of human mobility to distribute data. Due to the frequent and long-duration disruptions of network links, routing in PSNs is nontrivial. In this article, we first outline the challenges of PSN routing. After that, we summarize the behavioral traits of human beings employed by existing PSN routing schemes and give a brief survey on the state-of-the- art PSN routing techniques. Finally, we analyze the characteristics of existing PSN routing protocols and present some open problems that may foster future research on PSN routing.

AP Association for Proportional Fairness in Multirate WLANs

In this paper, we investigate the problem of achieving proportional fairness via access point (AP) association in multirate WLANs. This problem is formulated as a nonlinear programming with an objective function of maximizing the total user bandwidth utilities in the whole network. Such a formulation jointly considers fairness and AP selection. We first propose a centralized algorithm Non-Linear Approximation Optimization for Proportional Fairness (NLAO-PF) to derive the user-AP association via relaxation. Since the relaxation may cause a large integrality gap, a compensation function is introduced to ensure that our algorithm can achieve at least half of the optimal in the worst case. This algorithm is assumed to be adopted periodically for resource management. To handle the case of dynamic user membership, we propose a distributed heuristic Best Performance First (BPF) based on a novel performance revenue function, which provides an AP selection criterion for newcomers. When an existing user leaves the network, the transmission times of other users associated with the same AP can be redistributed easily based on NLAO-PF. Extensive simulation study has been performed to validate our design and to compare the performance of our algorithms to those of the state of the art.

Opportunistic Routing in Intermittently Connected Mobile P2P Networks

Mobile P2P networking is an enabling technology for mobile devices to self-organize in an unstructured style and communicate in a peer-to-peer fashion. Due to user mobility and/or the unrestricted switching on/off of the mobile devices, links are intermittently connected and end-to-end paths may not exist, causing routing a very challenging problem. Moreover, the limited wireless spectrum and device resources together with the rapidly growing number of portable devices and amount of transmitted data make routing even harder. To tackle these challenges, the routing algorithms must be scalable, distributed, and light-weighted. Nevertheless, existing approaches usually cannot simultaneously satisfy all these three requirements. In this paper, we propose two opportunistic routing algorithms for intermittently connected mobile P2P networks, which exploit the spatial locality, spatial regularity, and activity heterogeneity of human mobility to select relays. The first algorithm employs a depth-search approach to diffuse the data towards the destination. The second one adopts a depth-width-search approach in a sense that it diffuses the data not only towards the destination but also to other directions determined by the actively moving nodes (activists) to find better relays. We perform both theoretical analysis as well as a comparison based simulation study. Our results obtained from both the synthetic data and the real world traces reveal that the proposed algorithms outperform the state-of-the-art in terms of delivery latency and delivery ratio.

Approximate optimization for proportional fair AP association in multi-rate WLANs

In this study, we investigate the problem of achieving proportional fairness via Access Point (AP) association in multi-rate WLANs. This problem is formulated as a non-linear program with an objective function of maximizing the total user bandwidth utilities in the whole network. It is NP-hard, and therefore effort in this paper is made to seek approximate solutions. We propose a centralized algorithm to derive the user-AP association via relaxation. Such a relaxation may cause a large integrality gap. Therefore a compensation function is introduced to guarantee that our algorithm can achieve at least half of the optimal solution in the worst-case scenario theoretically. Extensive simulation study has been reported to validate and compare the performances of our algorithms with those of the state-of-the-art.

The Tempo-Spatial Information Dissemination Properties of Mobile Opportunistic Networks with Levy Mobility

Mobile opportunistic networks make use of a new networking paradigm that takes advantage of node mobility to distribute information. Studying their inherent properties of information dissemination can provide a straightforward explanation on the potentials of mobile opportunistic networks to support emerging applications such as mobile commerce, emergency services, and so on. In this paper, we investigate the inherent properties of information dissemination using the Lévy mobility model to characterize the movement pattern of the nodes. Because Lévy mobility can closely mimic human walk, the analysis model we adopt is practical. Our analyses are taken from the perspectives of small- and large-scales. From the perspective of small-scale, the distribution of the minimum time needed by the information to spread to a given region is investigated, from the perspective of large-scale, the bounds of the probability of the earliest time at which the information arrives in a region that is sufficiently farther away are obtained. We also provide the rate that such probability approaches zero as the distance to the region increases to infinity. Finally, our main results are validated by the numerical simulations.

Mobility-Assisted Routing in Intermittently Connected Mobile Cognitive Radio Networks

In mobile ad-hoc cognitive radio networks (CRNs), end-to-end paths with available spectrum bands for secondary users may exist temporarily, or may never exist, due to the dynamism of the primary user activities. Traditional CRN routing algorithms, which typically ignore the intermittent connectivity of network topology, and traditional mobility-assisted routing algorithms, which generally overlook the spectrum availability, are obviously unsuitable. To tackle this challenge, we propose a Mobility-Assisted Routing algorithm with Spectrum Awareness (MARSA) to select relays based on not only the probability that a node meets the destination but also the chance at which there exists at least one available channel when they meet. To the best of our knowledge, this paper is the first to bring the idea of mobility-assisted routing to deal with the intermittently connected attribute of mobile ad-hoc CRNs, and the first to enhance the mobility-assisted routing by considering the temporal, spatial, and spectrum domains at the same time. Our simulation results demonstrate the superiority of MARSA over traditional algorithms in intermittently connected mobile CRNs.

Virtual track: applications and challenges of the RFID system on roads

The RFID System on Roads (RSR), which includes RFID tags deployed on roads and RFID readers installed on vehicles, is an essential platform for future transportation systems. It can provide unique features that are missing from the current systems, including lane level position, road traffic control information, vehicle distance estimation, real time driving behavior analysis, and so on. Based on these features, several novel vehicular applications can be implemented, which can significantly improve the transportation safety and efficiency. Specifically, the proposed applications on RSR include Assisted Navigation Systems, Electrical Traffic Control, Unmanned Patrol Systems, Vehicle Distance Estimation, Parking Assistant System, Route Tracing and Access Control, Unmanned Ground Vehicles. We also investigate the corresponding engineering/system and research challenges for implementing RSR and its applications in this article.

Mobility in IPv6: Whether and How to Hierarchize the Network?

Mobile IPv6 (MIPv6) offers a basic solution to support mobility in IPv6 networks. Although Hierarchical MIPv6 (HMIPv6) has been designed to enhance the performance of MIPv6 by hierarchizing the network, it does not always outperform MIPv6. In fact, two solutions have different application scopes. Existing work studies the impact of various parameters on the performance of MIPv6 and HMIPv6, but without analyzing their application scopes. In this paper, we propose a model to analyze the application scopes of MIPv6 and HMIPv6, through which an Optimal Choice of Mobility Management (OCMM) scheme is designed. Different from the existing work that either propose new mobility management schemes or enhance existing mobility management schemes, OCMM chooses the better alternative between MIPv6 and HMIPv6 according to the mobility and service characteristics of users, addressing whether to hierarchize the network. Besides that, OCMM chooses the best mobility anchor point and regional size when HMIPv6 is adopted, addressing how to hierarchize the network. Simulation results demonstrate the impact of key parameters on the application scopes of MIPv6 and HMIPv6 as well as the optimal regional size of HMIPv6. Finally, we show that OCMM outperforms MIPv6 and HMIPv6 in terms of total cost including average registration and packet delivery costs.

Analyzing the potential of mobile opportunistic networks for big data applications

The advantages brought by opportunistic data delivery make mobile opportunistic networking a promising technology for big data computing. Thus, it is important to study the potential of mobile opportunistic networks in supporting big data applications by analyzing their fundamental data dissemination properties. However, such an analysis is nontrivial as a large dimension of elements may affect the data spreading behavior in mobile opportunistic networks. In this article, we first outline the challenges of analyzing the potential of mobile opportunistic networks for big data applications. Then we survey the state-of-the-art analytical results on data dissemination properties in mobile opportunistic networks. Finally, we summarize our analytical results and present a few open research issues that may foster future research endeavors on mobile opportunistic networks to support big data applications.

Coverage adjustment for load balancing with an AP service availability guarantee in WLANs

In wireless local area networks, adjusting the coverage of access points (APs) may force the clients near the coverage boundaries of congested APs to associate with lightly-loaded ones, thus realizing load-balancing. Such an approach has the advantage of requiring no modification on the client software/hardware compared to other load-balancing techniques. However, its applicability is undermined by the problems of AP service cheating and AP service loophole resulted from coverage adjustment, which significantly affect the AP service availability. Nevertheless, these two problems are largely ignored by the existent research. To tackle this challenge, a variable polyhedron genetic algorithm (GA) is proposed, which not only provides an AP service availability guarantee but also yields a near-optimal beacon range for each AP when the number of evolutions is large enough. Simulation study indicates that our algorithm is superior over the default 802.11 AP association model in terms of load-balancing and network throughput enhancement. In addition, the variable polyhedron GA outperforms the traditional GA in terms of fitness value and convergence speed.